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Data Management in Digital Twins: a Systematic Literature Review Abstract: The Internet of Things (IoT), personal and wearable devices, and continuous advances in data-gathering techniques have significantly increased the amount of relevant data that can be leveraged for innovative real-time, data-driven applications. Digital Twins (DTs) are virtual representations of physical objects which are fully integrated and in which the automatic data exchange occurs in a bidirectional way. DTs and big data are mutually reinforcing technologies since huge volumes of data representing the physical/virtual worlds are collected, transformed, and generated through models to aggregate value to the business. Modern DTs follow a five-component architecture, which includes a Data Management (DM) component that bridges a physical system, a mirrored virtual one, and services components. However, there is no clarity on the functionality required for the DM component. This work presents a Systematic Literature Review on DM issues and proposed solutions in the DT context. We analyzed DM under the big data value chain activities, highlighting key issues to be addressed: data heterogeneity, interoperability, integration, data search/discovery, and quality. In addition to surveying existing solutions for handling these issues, we contextualized them in the domain and function for which the DT was proposed, the type of data dealt with, and the technical infrastructure. The compilation of these solutions sheds light on the functionality of the DM component in a DT, trends, and opportunities. Keywords: Data management, Digital twin, Big Data, Systematic Literature Review Journal/Conference: Knowledge and Information Systems (KAIS) Authors: Jaqueline Bitencourt Correia, Mara Abel and Karin Becker
The innovative capabilities of blockchain technology should not go unappreciated. Spurred by the unprecedented success of its application in cryptocurrencies like Bitcoin, the use and potential applications of blockchain has been recognized across all industries, healthcare being one such instance. This utilisation of blockchain in healthcare has introduced revolutionary transformations starting with data analytics through to security measures and interoperability within the system architecture pattern. Not only do these bring tangible benefits resulting in improved patient care, but it also launches greater operational efficacy anticipating better prospects for future ventures in medical sciences championed by technology. This article seeks to dive deeper into how blockchain is forging its path into healthcare applications and developing a decentralised, secure and transparent ecosystem of the highest calibre. Stay tuned as we examine the innovative possibilities that are bound to unfold. How Blockchain Is Transforming Healthcare? Blockchain technology is significantly transforming the healthcare industry. By providing a secure and transparent platform for data exchange among each of the stakeholders in each healthcare system, blockchain can improve transaction accuracy, cost savings, and processing time. Additionally, its removal of traditional intermediaries like insurance companies and other organisations increases efficiency while significantly reducing paperwork. Data Security and Privacy Blockchain’s decentralised nature and encryption techniques can offer robust data security, reducing the risk of unauthorised access. Blockchain-based healthcare apps utilise cryptographic techniques to ensure data integrity and confidentiality. Patient records, treatment plans, and other medical information are stored on an immutable blockchain ledger. As a result, healthcare professionals, patients, and authorised personnel can access patient data with utmost confidence in its accuracy and confidentiality. Interoperability and Data Sharing The medical sector has long faced challenges with interoperability between different systems, impairing the efficient exchange of patient data. Blockchain technology offers a solution by creating a single standardised platform for the sharing of medical information. Utilising this new technological approach, there is no longer any need for an intermediary and increases patient access to critical information in real time. Physicians can use the data provided over this blockchain platform, giving them a comprehensive history that includes past diagnoses, allergies and treatments allowing them to take informed decisions improving patient outcomes. This blockchain based application stimulates an implosion in connectivity allowing hospitals, clinics, pharmacies and patients multiple ways to interact without obstruction or limitations set by any intermediary software. Drug Traceability and Supply Chain Management Counterfeit drugs have long plagued the pharmaceutical industry, posing serious threats to patient safety. Blockchain-based applications have the potential to transform drug traceability and supply chain management, ensuring the authenticity of medications from manufacturers to consumers. By recording every step of the drug’s journey on the blockchain, including manufacturing, transportation, and distribution, these applications create an immutable audit trail. Patients can easily verify the legitimacy of the medication they receive, reducing the risk of consuming counterfeit or substandard drugs. Clinical Trials and Research Clinical trials play a crucial role in advancing medical knowledge and treatment options. However, the process is often slow, expensive, and prone to data manipulation or fraud. Blockchain-based platforms can streamline and enhance the clinical trial process by providing transparent and auditable records. With blockchain technology, researchers can securely record, store, and share trial data, ensuring the integrity of results. Smart contracts within the blockchain can automate payment disbursement to participants and streamline regulatory compliance, making the entire process more efficient and reliable. Healthcare Payments and Insurance Blockchain’s decentralized nature can revolutionize the healthcare payment and insurance processes. Traditionally, healthcare transactions involve multiple intermediaries, leading to high administrative costs and delays in reimbursement. Blockchain-powered payment systems can facilitate direct peer-to-peer transactions, reducing administrative overheads and ensuring timely payments. Patients can have more control over their healthcare expenses, while healthcare providers can receive payments faster, improving cash flow. Telemedicine and Remote Patient Monitoring Telemedicine and remote patient monitoring have gained significant traction, especially during the COVID-19 pandemic. Blockchain technology can further enhance the security and privacy of telemedicine services. Blockchain apps can provide a secure and decentralised platform for teleconsultations and remote patient monitoring, enabling patients and healthcare providers to exchange sensitive health data without concerns about data breaches or unauthorised access. Personal Health Records and Ownership Blockchain technology empowers patients to take charge of their health data by granting them ownership and control over their personal health records (PHRs). Instead of relying on fragmented data stored across various healthcare providers, patients can maintain a comprehensive and up to date PHR on the blockchain. The patient’s PHR can be easily shared with healthcare professionals or researchers, facilitating more personalised and efficient care while safeguarding privacy. Additionally, patients can grant or revoke access to specific health information, enhancing data privacy and autonomy. Blockchain technology holds tremendous potential to revolutionise the healthcare industry. It offers innovative solutions to address some of its most critical challenges involving data security, interoperability, and patient privacy. With increasing adoption of blockchain in the healthcare sector we will likely see larger efficiency gains in health processes along with improved outcomes for both patients and providers alike. But all emerging technologies bring their own unique set of challenges. Regulatory compliance, scalability and user acceptance are just some of these obstacles blockchain in healthcare faces today. Overcoming these impediments requires concerted action from administrators who oversee healthcare, experts who understand the profound implications of technology, and policy makers orienting themselves toward satisfying patient needs in efficient and secure ways that become the norm. What are the reasons to choose QSS Technosoft Inc as your development partner? QSS Technosoft Inc. is a prominent, full-service firm working in the blockchain domain. We have a deep understanding of delivering secure, reliable, and scalable blockchain solutions for the modern enterprise. Our highly skilled specialists focus on creating tailor-made distributed ledger applications with the aim of streamlining business processes within healthcare organisations. Additionally, our team is preeminent in developing pioneering smart contract contracts leading to greater efficiency in the system while securing patient safeguards. With our independent counsel and proven proficiency in technology adaptation, we support corporations to gain the full fruition of blockchain technologies for an optimal workflow. Contact us now to entirely leverage the power of blockchain technology and upskill your work structure today.
Ever since the phrase “fourth industrial revolution” was coined by Klaus Schwab, founder of the World Economic Forum, in 2015, much has been written about the industrial internet of things (IIoT), a system which uses big data and machine-learning to connect cities, machines and people. A cursory glance at the internet, for example, reveals a myriad of benefits for the industrial sector including increased safety, compliance, flexibility and agility. But what a quick internet search doesn’t reveal, says Peter Asman, an IIoT and communications expert working for Trilliant, is just how many IIoT projects fail. “You can’t just deploy an IIoT programme without having a systematic and scalable architecture to aid you in achieving an end-goal,” he explains. “Nor is it possible to utilise the IIoT without also utilising a multi-layered, end-to-end platform, which enables the secure and frictionless exchange of data. This is the secret to connecting the world of things and this is what Trilliant does, and does well.” In fact, Trilliant is unique in this respect. With a presence in 20 countries, it provides more than 75 of the world’s largest companies with one of the most advanced hybrid wireless communications platform on the globe. In the UK alone, several large organisations have benefited from Trilliant’s data-driven networking solutions. In May 2009, for example, a large UK energy and home services provider enlisted Trilliant’s help to lay the digital foundations that have enabled the company to better link millions of datapoints from disparate assets such as smart meters, gas meters and smart thermostats. Asman, who is Trilliant’s vice president of IIoT and smart cities for Europe, Middle East and Africa, says: “When the organisation approached us, it had no way of gathering and harmonising that data. Over the course of many months, we worked in concert with the company to build a secure and robust platform, which today connects over six million smart meters that communicate with their datacentre in real time. “The benefits for company and customer are that the organisation can monitor the amount of gas being used nationally, while consumers are guaranteed accurate billing.” But it’s not just large energy companies that are profiting from Trilliant’s leading-edge technology. Trilliant’s hybrid wireless solutions technology is also helping data-driven water companies to unlock their potential. In South Africa, for instance, where drought almost left Cape Town’s four million people without access to water, Trilliant is using its technology to help cities in the region to understand how to reduce water leakages, while also ensuring the quality of drinking water remains high. Although Asman is unable to disclose the client’s name, he says Trilliant is working with a water provider to detect leakages in real time. “This is achieved through the use of a series of sensors, which enable greater efficiency and control of an already limited water supply,” he explains. But this transformation also relies on digital harmonisation, something which Trilliant excels in. Working in tandem with some of the world’s top sensor providers allows the Trilliant IIoT Platform to surface data from many different types of sensors and collect it all in a “single pane-of-glass view”. For water providers like those in South Africa, this single view into their entire system provides them with the ability to take swift and accurate action when needed. Asman explains that this high level of digital integration provides water companies with the ability to manage leakages, as well as pressure flows, proactively. He notes that it also helps them to manage change quickly, adding that the ability to connect a multitude of different sensors to the network is an absolute prerequisite. So how does the so-called single pane of glass translate into efficiency savings? With acoustic sensors fitted across pipe infrastructure, Trilliant’s data platforms can integrate all the information in real time, enabling the water management company to identify a leak within a range of 20 metres. “The sensors can also monitor water pressure and flow, and check the levels of chlorine are always safe. What’s most important though is that the platform is able to adapt to the ever-changing needs of the customer, whatever the use-case and wherever they may be,” says Asman. And it’s this flexibility that he says “gives Trilliant’s technology platforms a vital edge” over its rivals. Asman, who joined Trilliant from Spanish multinational communications giant Telefonica, points to the fact that Trilliant’s data networks utilise both 2.4GHz and 5.8GHz to serve every international region. Of course, it wouldn’t be impossible to build this variable system bandwidth into its network, without industry-leading standards and world-class security credentials. Take agility, for instance. All of Trilliant’s hybrid wireless communications conform to the latest industry standards. But why does this matter? Asman explains: “With developers bringing out new sensors every day, Trilliant’s platforms are designed to be as flexible as they are robust. For example, when a company chooses to partner with us, it’s our job to create an interoperable platform infrastructure where sensors, no matter how new to the market they are, can communicate effectively and powerfully with each other through a single pane of glass.” But accessibility means nothing without leading-edge security. With Trilliant providing mission-critical communications to a host of large organisations, utility-grade security standards are an absolute necessity. “Keeping our customer’s data safe lies at the heart of everything we do. All Trilliant’s software utilises the Federal Information Processing Standard, which provides a secure bedrock on which our technologies are deployed and maintained,” says Asman. Our infrastructure provides a living, breathing template for the connected world of the future Indeed, with more than 500 million end-users benefiting from its platform, Trilliant is using its vast knowledge and experience to build the smart cities of the future. It is currently working with partners in the United States, Europe and Asia to connect people and cities to the world of things. But it’s perhaps Trilliant’s dedication to their customers that is most eye catching. By working in collaboration with cities, utilities, energy companies and even universities, Trilliant is seeking to create not just a smart city infrastructure, but an entirely connected world. “Our projects are ambitious and are often trailblazing in their scope and possibilities. Our infrastructure provides a living, breathing template for the connected world of the future,” Asman concludes. That Trilliant, a company made up of just one person in 2008, is playing an instrumental role in shaping the world’s future is as empowering as it is remarkable. Learn how Trilliant can help connect your world of things by visiting trilliant.com/thetimes
The Latest Blogs From USS In one of our recent articles, we looked at the increasing use of Artificial Intelligence (AI) in the warehousing and logistics industry. In it, we examined ways in which AI and machine learning are already being applied across parts of the warehousing and logistics sector, and the possible applications we might see in the future. One key takeaway from the article—one that can be applied across warehouse and logistics operations of every size and type—was that AI has already made clear inroads into the sector, with the most ambitious businesses planning further investment in the immediate future. In this article, we’ll look at the use of AI in the self-storage sector, but we’ll start by making a similar point: AI in self-storage is something that’s already happening, and your competitors might well be using AI already. This could mean they’ll be in a position to deliver a better service than you before too much longer - and with lower operating costs. The idea that AI is making inroads across the self-storage sector isn’t merely conjecture. The European Self Storage Industry Report 2024 stated that 69% of survey respondents were planning on using AI in their business in 2024, for example. If we look at a selection of those statistics we’ll see how they underline the headway that AI has made within the self-storage sector: Talking about AI as a concept is one thing, but how can self-storage operators use it in a practical, hands-on manner? The statistics outlined above referenced a few of the tools and options available. If we consider those in a little more detail, it will be easier to decide which may or may not suit your own self-storage business. One of the more widespread utilisations of AI across the self-storage industry – indeed, across the whole of industry and commerce – has already been adopted by many operators. This is the use of automated chatbots to deal with customer interactions. Chatbots can be programmed to deal with the kind of queries and issues self-storage customers have, and it’s the nature of machine learning (the tech that provides the foundation for Artificial Intelligence) that allows the chatbots to ‘learn’ to deal more effectively with customer queries the longer they are used. Once in place, chatbots can provide round-the-clock support for customers and save time and employee costs by streamlining the reservation and booking process. Security and access are two of the biggest issues any self-storage operator has to deal with. In simple terms, the requirement for the strongest protection possible has to be balanced with making it as simple and frictionless as possible for customers to access the items they have in self-storage – whenever they want. To allow access while keeping the facility, its staff and customers safe, is where AI-powered surveillance systems come in – utilising facial and number plate recognition to power ease of access and make unauthorised access more difficult to pull off. Similar systems can be implemented to detect unauthorised and unusual activity within a self-storage facility and respond in real time, alerting staff or the relevant authorities when anything unusual is detected, aided by auxiliary technology like motion sensors and cameras. When dealing with AI in the self-storage sector, much of the focus tends to fall upon how it can make life easier for customers. This is only natural, of course, but what shouldn’t be ignored is how AI systems can help make management of your self-storage facility more efficient and thus more profitable. One of the areas where AI can have the most significant and most effective impact is revenue management. AI systems can gather vast amounts of data from a range of sources, both within the facility and beyond. Broader economic factors, for example, have often been shown to impact the demand for self-storage and the charges people are happy to pay. In contrast, a self-storage facility close to a university might expect an influx of students needing to store their items at the end of term. Once gathered, the data on, for example, local supply, historical demand and the price-points adopted by competitors - to name just a few, can be analysed in real time to optimise pricing through adjustments to unit rental fees. It’s easy to see how the ability to compete with dynamic pricing can help you keep your own units optimally priced compared to your competition. Once in place, systems of this kind can integrate with existing management software, meaning that changes are applied across the board as they are made. AI can play a vital role at the very start of the process of designing and building a self-storage facility. Our own case studies detail the many and varied ways we’ve helped to design and install self-storage units for new facilities - or reconfigure or expand the layouts of existing buildings. The data gathered on use-cases across the industry could be analysed by AI and inform the layout of future facilities. Once AI systems are in place across the whole of a self-storage facility, they can gather vast amounts of data on the operational metrics of that facility. The power of AI is such that this data can then be analysed in a manner which would be impossible without the speed and efficiency of machine learning, and is even more powerful when combined with external data such as broader trends in the market. The result will be the delivery of a data-driven approach to decision making, which enables operators to optimise day-to-day operations, marketing strategies and resource allocation. AI software can combine with the Internet of Things (IoT) to deliver a predictive and proactive approach to maintenance within a self-storage facility. Systems such as heating, cooling and security will feed data into the AI systems, triggering alerts as soon as maintenance issues become apparent. In this way, self-storage operators can deal with problems before they become embedded and more difficult to fix, reducing downtime and lowering the repair cost. Starting from scratch when you want to take advantage of AI's power can seem daunting, but breaking the process down into smaller, more easily achievable steps will help you identify areas of your self-storage business that could be improved. From this position, you can then prioritise the actions you need to take. Carry out a detailed audit of how your facility operates, identifying the current workflows and picking up on any evident inefficiencies and bottlenecks. Start with the obvious. An approach that focuses on tasks prone to human error, repetitive or time-consuming (often all three at once) will highlight the areas where the introduction of AI could help your business most. Once you’ve identified the areas in which AI could be applied, you can look for the right AI tools, make your choices around issues such as: This blog is for information purposes only and should not be construed as legal or financial advice and not intended to be substituted as legal or financial advice.
Our national security has been hit by a massive leak of data concerning the advanced stealth submarine, Scorpene. The source of leak is still unknown. The matter came to light when The Australian, an Australian newspaper uploaded the leaked documents concerned with the details of Indian Scorpene submarine on their website. Though the statement came from Indian Navy official that the uploaded documents do not have any major security concern as they do not contain any vital details. Secret data on India’s Scorpene submarine leaked However, the Australian reporter Cameron Stewart statement that Indian Navy’s claim was “completely laughable” puts a big question mark on our capabilities. Cameron further added that that they have themselves decided not to put the 22,400 pages document that have all the sensitive data. He even claimed Indian officials to be either incredibly stupid or deliberately trying to mislead the extent of damage from Indian citizens. Apart from quibbles over redacted versus non-redacted information, the data leaks come as another major obstacle for India’s indigenous defence production push. - Scorpene is designed by French firm DCNS and it’s manufacturer is Mazgaon Dock Limited, India. - The documents have Indian Navy insignia on it, inscribed “Restricted Scorpene India”. - It contains details about the submarines’ sonar system, it’s all technical specifications and frequency of operation. - The documents contain “Operating Instruction Manual”, that give all the steps of the submarines’ different functions. - The Indian Navy has not yet officially reacted to the release of new documents. Noise frequencies : What exactly are some of the “vital parameters”, found in the data leaks, the Indian navy could be worried about? In earlier comments to The Wire, Vice-Admiral A.K Singh (retired) pointed out the “damage may not be great… as long as the frequency of the submarine’s radiated noise” remained a secret. The logic here is that if these frequencies were to leak, it would allow enemy forces to use “different sonar buoys to locate and identify the submarine, which otherwise has a noise level that is below the noise of the sea”. Huge setback for India as 22,000 pages of secret data leaked However, as the newly released documents put out by The Australian yesterday show, the frequencies of many of the Scorpene submarine’s capabilities have been leaked and have been redacted by The Australian and not the leaker herself/himself.
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There have been some significant disputes over data usage recently in the legal artificial intelligence space. If your startup has ever dealt with the courts it can feel like you’re drowning in an ocean of jargon, deadlines, and endless red tape. You think hiring a lawyer will solve everything, only to be hit with sky-high fees that make you question whether justice is worth pursuing or if it’s even possible to defend yourself. For many, the process feels hopeless. Legal software designed to bring order to a complex system is now entangled in a lawsuit. The dispute between CanLII, a nonprofit celebrated for its accessible legal resources, and Caseway, an AI legal tech innovator transforming legal research, goes beyond a mere corporate conflict. This battle has significant implications for controlling court decision data essential to ensuring access to justice. The Fight for Control Over Legal Knowledge For two decades, CanLII has been the gold standard for public access to Canadian legal resources. Need to know your rights? CanLII is where you’d go whether you’re a self-represented litigant, a small business owner, or someone trying to make sense of a complicated legal document you receive. But then Caseway entered the scene aggressively, offering machine learning-powered research that gives you legal documents and information and helps make sense of them. These court decisions can be hundreds of pages long. Sounds like a win for the everyday person. But not so fast. CanLII is accusing Caseway of scraping its database to fuel its platform, claiming it’s an improper use of its content. Caseway argues that it’s simply building on what’s already public (court decisions) and making it more accessible. Caseway says that no one can own these court decisions. Disputes Over Data Usage This legal situation concerns who holds the keys to legal knowledge in a world increasingly driven by technology. There are plenty of other lawsuits out there against companies like OpenAI. However, most of these types of lawsuits revolve around content created by the plaintiff (like the Toronto Star or Globe and Mail.) Jurisage, Canada’s second largest provider of case law, has also taken shots at Caseway, trying to keep them out of the industry. Caseway shot back at Jurisage, saying that they have a direct or indirect relationship with CanLII, and that’s how Jurisage gets the court decision data. But at the same time, CanLII doesn’t make this court data available to other AI companies requesting it. Why This Legal Case Should Matter to You Let’s break it down: if you’re facing a legal issue, you’re already up against a system designed for insiders. Lawyers, judges, and those who can afford them. Resources like CanLII help level the playing field by giving you the information you need to fight back, acting as a search engine. However, Caseway took it further, adding machine learning to court decision data to turn that mountain of legalese into actionable insights and results. Now imagine if this lawsuit results in stricter rules around how legal technology companies can access and use public data. The ripple effects could be catastrophic for anyone without deep pockets. What happens if you can’t afford to spend $500 an hour to hire a law firm? Fewer machine learning products would mean fewer options for affordable legal help. Paywalls could and have gone up, shutting out the people who need these services the most. And paywalls have already gone up, and companies like LexisNexis and Thompson Reuters have paywalled the court decisions they receive from the courts. The Real Cost of Losing Access Machine learning makes it possible to use the Internet to address issues such as eviction notices, divorce proceedings, and wrongful termination claims. They’re the kinds of crises that can ruin lives. For marginalized communities, who already face systemic barriers in accessing legal help, the stakes are even higher. A single mistake can spiral into losing a home, custody of a child, or financial ruin. The idea that a legal database—or legal software simplifying it—might become less accessible isn’t just frustrating. It’s terrifying. Small business owners aren’t spared either. Imagine getting a 50-page contract from a large law firm to review, dealing with regulatory compliance, or resolving employee disputes without affordable tools to guide you. Innovation vs. Tradition: A Profession at War The legal world is notoriously resistant to change. Many institutions view innovation as a threat rather than an opportunity, clinging to outdated systems even when they fail to serve the public effectively. This case between CanLII and Caseway perfectly sums up that struggle. CanLII, once a disruptor that replaced court decision book companies, now defends traditional boundaries. Caseway, meanwhile, represents the wave of innovation that became possible once AI became accessible in January 2023. Caseway says they promise to make legal help faster, cheaper, and more accessible. But instead of collaboration, we see a fight to the death, in which the public will be the real losers. This tension between tradition and innovation isn’t new. We saw it between taxi companies and Uber, and we also saw it with Airbnb and hotels. Disputes Over Data Usage And The Future of Justice This lawsuit concerns the future of justice itself. If barriers to innovation keep rising, the legal profession risks becoming even more inaccessible. Holding onto tradition for tradition’s sake isn’t the answer. We need a balance that embraces innovation while ensuring it serves the public good. Legal information belongs to the public, not corporations. Restricting access only perpetuates inequality. Imagine if CanLII and Caseway worked together to improve legal artificial intelligence tools. Instead, we’re stuck watching a turf war. Legal help must be affordable for startups through AI or traditional means. Period.
- Natural Language Processing (NLP) is a branch of artificial intelligence that enables computers to understand and generate human language. - NLP encompasses tasks such as translation, sentiment analysis, and speech recognition, allowing efficient processing of natural text data. - NLP integrates with machine learning and deep learning, enhancing AI systems’ abilities in customer service, content generation, and data analysis. - The evolution of NLP began in the 1950s with machine translation and progressed through rule-based systems to statistical methods and machine learning. - Modern NLP technologies utilise deep learning models like BERT and GPT, achieving high performance in language understanding and generation. - Key characteristics of NLP include tokenization, part-of-speech tagging, named entity recognition, and sentiment analysis, showcasing its versatility. As technology evolves, the intersection of artificial intelligence and human communication has never been more critical. Natural Language Processing (NLP) is at the forefront of this evolution, empowering machines to comprehend and interact with human language meaningfully. From translating languages to analysing sentiments and generating human-like text, NLP encompasses a vast array of applications that enhance business communication and customer engagement. This article delves into the intricacies of NLP, tracing its historical development, highlighting its key characteristics, and contextualising its significance within the broader framework of artificial intelligence. As organisations increasingly adopt NLP technologies, understanding their capabilities and potential is essential for leveraging the full power of AI in today’s digital landscape. Define Natural Language Processing (NLP) The nlp meaning is that Natural Language Processing (NLP) is a pivotal branch of artificial intelligence (AI), focusing on the vital interaction between computers and humans through natural communication. This technology empowers devices to comprehend, interpret, and generate human communication in ways that are both meaningful and advantageous. The nlp meaning encompasses a diverse range of tasks, including: - sentiment analysis - speech recognition These tasks enable computers to efficiently process and analyse vast amounts of natural text data. By harnessing sophisticated algorithms and learning methods, NLP aims to bridge the gap between human communication and computer understanding. At Agentics, we leverage NLP to transform business communication through our customised voice AI solutions, enhancing efficiency and customer engagement. By integrating NLP into our offerings, we enable businesses to gain deeper insights into customer needs and respond effectively, ultimately revolutionising their communication strategies. Embrace the power of NLP with Agentics and elevate your business to new heights. Contextualize NLP in Artificial Intelligence The nlp meaning stands as a cornerstone of artificial intelligence, enabling systems to effectively process and comprehend the complexities of human communication. This intricate field intersects with various disciplines, notably machine learning, where algorithms are meticulously trained on extensive datasets to uncover patterns within text. Moreover, the advent of deep learning techniques, particularly neural networks, has transformed NLP, facilitating the development of advanced language models capable of generating text that closely resembles human writing. The incorporation of NLP into AI systems significantly enhances their functionality, empowering them to execute tasks such as: - Automated customer service - Content generation - Data analysis As such, NLP emerges as an indispensable tool in the realm of modern technology, driving innovation and efficiency across industries. Trace the Evolution of NLP Technologies The evolution of NLP technologies began in the 1950s, marked by early initiatives in machine translation, notably the Georgetown-IBM experiment. This period laid the groundwork for future advancements. The 1960s and 1970s saw the rise of rule-based systems, where linguists crafted grammatical rules to facilitate communication processing. However, these systems struggled to navigate the complexities inherent in natural communication. A pivotal transformation occurred in the 1980s with the advent of statistical methods, which introduced data-driven approaches to NLP. The 1990s further propelled the field forward with the emergence of machine learning, resulting in algorithms capable of learning from data rather than relying solely on predefined rules. Today, deep learning techniques, particularly transformer models like BERT and GPT, have set new benchmarks in understanding the NLP meaning and generation, achieving unparalleled levels of performance. This progression not only showcases the remarkable advancements in technology but also underscores the transformative potential of NLP solutions in various applications. Identify Key Characteristics of NLP The key characteristics of Natural Language Processing (NLP) can be understood through its nlp meaning, which includes its remarkable ability to process and analyse vast volumes of text data, comprehend context and semantics, and generate responses that closely resemble human interaction. NLP systems utilise a range of sophisticated techniques, including: - Part-of-speech tagging - Named entity recognition to dissect and understand text effectively. Furthermore, sentiment analysis empowers NLP to assess the emotional tone of the text, while machine translation bridges communication across diverse languages. The adaptability of NLP technologies positions them as invaluable assets in various domains, from customer service chatbots to advanced data analytics tools, underscoring their versatility in the ever-evolving AI landscape. Natural Language Processing (NLP) is at the forefront of the evolving relationship between artificial intelligence and human communication. By enabling machines to understand and generate human language, NLP enhances a myriad of applications, including: - Language translation - Sentiment analysis - Automated customer service This technology not only improves business communication but also enriches customer engagement, making it a vital tool in today’s digital landscape. The historical evolution of NLP reflects its journey from rudimentary rule-based systems to sophisticated deep learning models. Each advancement has pushed the boundaries of what machines can achieve in understanding language, culminating in the powerful capabilities seen today. The integration of NLP with machine learning and deep learning has further refined its effectiveness, allowing for more nuanced and context-aware interactions. Key characteristics of NLP, such as its ability to analyse large datasets and generate meaningful responses, highlight its versatility across various applications. As organisations increasingly adopt NLP technologies, understanding these capabilities becomes essential for leveraging AI’s full potential. Embracing NLP not only enhances operational efficiency but also fosters deeper connexions with customers, ultimately revolutionising communication in the business world. The future of NLP promises even greater advancements, making it an exciting area to watch in the realm of artificial intelligence. Frequently Asked Questions What is Natural Language Processing (NLP)? Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that focuses on the interaction between computers and humans through natural communication. It enables devices to comprehend, interpret, and generate human communication in meaningful ways. What are some key tasks performed by NLP? Key tasks performed by NLP include translation, sentiment analysis, and speech recognition. These tasks allow computers to process and analyse large amounts of natural text data efficiently. How does NLP benefit businesses? NLP benefits businesses by enhancing communication through customised voice AI solutions, improving efficiency, and increasing customer engagement. It helps businesses gain deeper insights into customer needs and respond effectively, thereby revolutionising their communication strategies. How does Agentics utilise NLP? Agentics leverages NLP to transform business communication by integrating it into their offerings, allowing businesses to improve their communication strategies and elevate their operations.
Chatbot Power At Your Service Chatbots are not just for role-playing a doomed love affair with some anime character. Get near-instant, productive AI-powered answers to your prompts for better academic writing and faster research. Skip the learning curve and enjoy full GPT unblocked functionality. Simpler Prompts, Better Answers We know how to talk to OpenAI and explain what you need exactly. With our ChatGPT free unblocked features, you get topic-relevant, context-aware output from the get-go without endlessly tweaking clunky prompts. No fluff, no time wasted — just coherent work-ready text. Cater Output To Your Sources Upload your own documents in several popular file formats and receive focused answers free of repeating points and meandering off-topic additions. Our Chat GPT free unblocked functionality can also find sources for you — and it looks deeper than the paper title, checking the body text. Flexible Language Settings Work in several available languages including Spanish and German. Take advantage of international sources for quality referencing and give prompts in the language you’re most comfortable with. Skip the translation step entirely — get output in your target language. Personalize In Editor Forget the bare chat window of the original site. Our ChatGPT unblock allows you to edit and customize output on the spot. Paraphrase selected text in five available modes, make it shorter or longer, or even improve readability. And you don’t have to type another prompt to do it! Autocomplete Your Results Something missing? Not a problem. Our ChatGPT unblocked no login solution doesn’t need another instruction from you. We already know what you’re talking about. Receive autocomplete suggestions in a click, dismiss or accept the changes, and feel free to try again for a better fit! Cite On The Spot With the AI chat unblocked you get a high level of customization, including full and in-text citations. Choose between MLA and APA styles and rest assured that any references we select are topic-relevant and pulled from a vast database of real and reputable academic works. Comfortable Export Otput Forget copy-pasting giant text chunks or accidentally grabbing site menus into your document. Export your results as DOCX or PDF cleanly and in just a couple of clicks. Proceed to make further edits or attach directly to an email. All your formatting will be preserved, so no worries. AI Chats Unblocked: a Step-By-Step Guide How to get ChatGPT unblocked? First, try using a different internet network to bypass restrictions. Next, you can turn on a VPN or use a proxy server. If the site is blocked on a school or work device, access it on a personal one. Alternatively, use ChatGPT through third-party sites or apps. For long-term access, ask your IT admin about educational AI alternatives. How to use GPT chat for free? Visit OpenAI’s website and sign up for a free account. Free users get access to GPT-3.5, while GPT-4 requires a subscription. Some third-party apps also offer free access to ChatGPT. If it’s restricted, try using a VPN or exploring alternative AI chatbots. Why is ChatGPT blocked at school? Schools block ChatGPT to prevent distractions and uphold discipline, as well as to preserve academic integrity and stop students from accidental plagiarism and cheating. Some worry about misinformation or students bypassing learning challenges. Privacy concerns and data security regulations are big factors, as well. You can still access ChatGPT capabilities via third-party platforms or other chatbots.
dotData, the first and only company focused on delivering full-cycle data science automation and operationalization for the enterprise, today announced that global technology leader Seiko Epson Corporation (“Epson”) has selected dotData to accelerate and democratize data science across its organization. Epson is a global technology leader and innovator across multiple categories including communications, wearables, and robotics. The organization deployed dotData Enterprise to accelerate and democratize its AI development as a part of its AI and Analytics Platform strategy. “Epson has been developing an AI and data analytics platform to leverage the massive amounts of data we have, but it is still a challenge to fully and effectively extract business value and improve the quality of work by utilizing AI and data,” said Mr. Kazunori Takahashi, General Manager of Information Technology Promotion Department, Seiko Epson Corporation. “We have high expectations for dotData as a platform that will enable every business department and individual, across the entire value chain from design to manufacturing to sales, to leverage their data for important business insights through automated data science processes without relying on data science experts. This will enable us to accelerate and democratize our AI developments and realize rapid value creation.” dotData is the only platform that combines AI-powered feature engineering and AutoML to automate the full life-cycle of the data science process, from source data through feature engineering to implementation of machine learning in production. dotData’s AI-powered feature engineering automatically applies data transformation, cleansing, normalization, aggregation, and combination and transforms hundreds of tables with complex relationships and billions of rows into a single feature table, automating the most manual data science projects. “The dotData full-cycle automation platform will enable Epson to accelerate and democratize its data science initiatives so that its data science team can focus on developing high-quality models that drive high business impact across the organization,” said Ryohei Fujimaki, Ph.D., CEO, and founder of dotData. “Our platform will drastically reduce the amount of time it takes Epson to derive insights from its data, creating value in days instead of months. We are pleased to be partnering with the Epson team to help them drive deeper business insights, and look forward to working closely with the team to expand the dotData platform to additional use cases.” dotData democratizes data science by enabling existing resources to perform data science tasks, making enterprise data science scalable and sustainable. dotData also operationalizes data science by producing both feature and ML scoring pipelines in production, which IT teams can then immediately integrate with business workflow. This further automates the time-consuming and arduous process of maintaining the deployed pipeline to ensure repeatability as data changes over time. With the dotData GUI, the data science task becomes a five-minute operation, requiring neither significant data science experience nor SQL/Python/R coding.
Data Transfers and Processing \| Auberge Resorts Collection DATA TRANSFERS AND PROCESSING Auberge Resorts is headquartered in the United States, and Auberge Resorts Collection is a collection of properties in locations throughout the United States and internationally. To provide services, you acknowledge that your personal data may be shared with other ARC Properties or with third parties in locations around the world for the purposes described in this Privacy Notice. AR and ARC Properties store and process data both inside and outside of the United States. Countries, where data is processed, may have data protection laws that differ from those in your own country. AR and ARC Properties use the approved Standard Contractual Clauses (“SCC”) for the international transfer of personal information collected in the EEA and Switzerland or require that any third-party located in the US receiving your personal information is certified under the EU-US and/or the Swiss-US Privacy Shield Frameworks (“Privacy Shield Framework”) and require that the third party agree to at least the same level of privacy safeguards as required under applicable data protection laws. In a limited number of situations where the personal information collected in the EEA and Switzerland cannot be transferred under SCC or the Privacy Shield Framework, then AR and ARC Properties rely on derogations for specific situations as set forth in Article 49 of the GDPR. Particularly, AR and ARC Properties collect and transfer the personal information out of the EEA and Switzerland only: with your consent; to perform a contract with you, or to fulfill a compelling legitimate interest of AR or ARC Properties in a manner that does not outweigh your rights and freedoms. AR and ARC Properties endeavor to apply suitable safeguards to protect the privacy and security of your personal data and to use it only consistent with your relationship with AR and ARC Properties and the practices described in this Privacy Notice. AR and ARC Properties have also entered into data processing agreements and SCCs with their vendors whenever feasible and appropriate.
Airports are critical hubs of global transportation, handling millions of passengers daily. Ensuring security in such complex environments is a daunting task that requires constant innovation. The integration of robotics, AI, and cutting-edge security technologies is transforming airport safety, making it more efficient, intelligent, and responsive. Airport security robotics are emerging as game-changers, providing automated solutions that complement human efforts and elevate the standard of protection. The Rise of Robotics in Airport Security Traditional airport security relies heavily on manual inspections, human patrols, and fixed surveillance systems. While effective, these methods face limitations, including human fatigue, blind spots, and slow response times. Robotics innovation is addressing these challenges by introducing autonomous robots that can patrol terminals, inspect luggage, and monitor crowds with precision and consistency. Robots equipped with AI-powered sensors, cameras, and communication tools operate seamlessly within the airport ecosystem. They can detect anomalies, identify suspicious behavior, and relay critical data in real-time. This level of automation enhances situational awareness and reduces the risk of security breaches. How Robotics and AI Enhance Airport Security Autonomous Patrol and Surveillance Airport security robots can autonomously navigate terminals, runways, and restricted areas, continuously scanning for threats. Using AI-driven facial recognition and behavioral analysis, they detect unauthorized individuals or suspicious activities. This proactive monitoring allows security teams to focus their attention where it’s most needed. - Advanced Threat Detection Robotics innovation has led to robots capable of scanning for explosives, weapons, and hazardous materials. AI algorithms analyze sensor data to flag potential risks accurately. This reduces false alarms and speeds up the screening process, enhancing both security and passenger experience. - Crowd Management and Social Distancing During peak travel times, maintaining order and safety is critical. AI-powered security robots monitor crowd density, enforce social distancing, and provide real-time alerts to human operators. Their presence alone can deter disruptive behavior and ensure compliance with safety protocols. - Emergency Response and Assistance In emergencies such as fires, medical incidents, or security threats, airport robots can assist by providing immediate information and guiding passengers to safety. Equipped with communication tools, they act as mobile command units, relaying updates and coordinating with emergency personnel efficiently. Benefits of Robotics Innovation in Airport Security Increased Efficiency: Robotics reduce human workload and increase the speed and accuracy of security checks. Enhanced Accuracy: AI integration enables better threat detection through data analysis and pattern recognition. 24/7 Operation: Robots do not tire or require breaks, ensuring continuous surveillance. Cost-Effective: Automation reduces labor costs and the potential financial impact of security breaches. Scalable Solutions: Multiple robots can be deployed across large airport areas, covering more ground than human personnel alone. Quarero Stingray: Robotics in Airport Security At Quarero Robotics, innovation is at the core of our mission to redefine security through advanced robotics. Our Quarero Stingray robot embodies the perfect blend of robotics, AI, and security technology tailored for demanding environments such as airports. The Stingray offers autonomous navigation powered by GPS and LIDAR, enabling it to patrol complex airport layouts with ease. Its multisensor system—featuring high-resolution cameras, thermal imaging, and acoustic sensors—ensures 360-degree awareness regardless of lighting or weather conditions. Integrated AI software allows the Stingray to analyze behaviors, detect anomalies, and transmit real-time alerts to security teams. This seamless integration of robotics innovation and AI helps airports strengthen their security infrastructure while optimizing operational efficiency. Looking Ahead: The Future of Airport Security Robotics The future promises even greater advancements in robotics innovation for airport security. With ongoing developments in AI, machine learning, and sensor technology, airport robots will become smarter, more adaptive, and more collaborative. Potential upgrades include enhanced predictive analytics to anticipate security threats, swarm robotics for coordinated patrols, and greater human-robot interaction capabilities. These innovations will continue to raise the bar for safety and convenience in airport environments worldwide. Airport security robotics represent a new era of innovation that integrates robotics, AI, and security technology to protect one of the most vital transportation hubs globally. By automating surveillance, enhancing threat detection, and improving emergency response, robotics innovation is making airports safer and more efficient. The Quarero Stingray exemplifies how robotics and AI can work hand-in-hand to meet the evolving demands of airport security. As technology advances, airport security robotics will remain a crucial component in safeguarding travelers and infrastructure.
The BiBiServ Framework can be set up the complete BiBiServ easily on your local infrastructure. Cloud based infrastructure can be used directly from BiBiServ (using RITC) or manually (using BiBiGrid). When thinking of a bioInformatics service provider like the BiBiServ, one must have in mind that the data to be analyzed is very huge and is growing day by day. The problem is not only to provide the necessary computing power to analyze all the data but also provide storage and bandwidth capacity. One possible solution to solve this problem is to move the bioinformatic tools itself to the data instead of moving the big amount of data to the tools. In other words: if your data is already stored in the cloud it is faster (and normally also cheaper) to run your bioinformatics applications near to the data instead of moving/copying all the data to your analyze pipeline. Since 2012 Illumina offers BaseSpace to store and analyze sequence data in a cloud computing environment. BaseSpace offers the possibility to run (your own) applications (with limitation to compute power) but also have REST access to all data stored. BaseSpace is powered by AWS and therefore running a bioinformatic pipeline within AWS should be optimal to access them. Feel free to use our framework for your own projects. It's published under the conditions of the CDDL Please do not hesitate to contact us in case of any questions.
Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.
OpenAI CEO Sam Altman made several announcements for ChatGPT users on Sunday. The o3 series of artificial intelligence (AI) models, which were unveiled in December 2024 as a research preview, will now witness its first global release. Altman stated that the o3-mini AI model will be rolling out to both the paid subscribers as well as those on the free tier of its platform. Additionally, the CEO also revealed that the recently released AI agent Operator will be made available to ChatGPT Plus users soon. OpenAI Is Releasing the First o3 AI Model In a post on X (formerly known as Twitter), Altman revealed that the latest reasoning-focused large language model (LLM) series, o3, will be made available to both paid users as well as those on the free tier of its AI chatbot. Notably, o3 is the successor to the company’s o1 series models. OpenAI introduced the o3 series, comprising o3 and o3-mini, during its Christmas-styled 12-day shipping schedule in December. At the time, the AI firm said that the new AI models would offer better performance compared to the predecessor and would be able to complete more complex tasks in coding, mathematics, and natural language processing. However, its full range of capabilities and benchmark evaluations were not revealed. Altman has now highlighted that the ChatGPT free tier will also get access to the o3-mini model, although it is likely to get high restrictions. For instance, the o1 model on the free tier was available with five queries a day. At the same time, the OpenAI CEO revealed that Plus subscribers will get 100 queries per day with the o3-mini. Alongside, Altman also made multiple future announcements for ChatGPT Plus subscribers. First, OpenAI will soon introduce its Operator AI agent to the paid subscribers. The agent is currently available to the Pro subscribers in the US as a research preview. It can autonomously perform tasks online based on prompts given by the user and can be used to book tickets online, reserve a table in a restaurant, or buy a product online. ChatGPT Plus users were also promised that the next AI agent launch by the company will be made available to them on the first day of the release. This was not the case with Operator, which was exclusively rolled out to Pro subscribers. Notably, Altman also highlighted that the Pro users will get an enhanced version of the o3 series model, dubbed o3 Pro, in the coming days.
Get to Know Us @Chill Pill AB and partners use expertise to provide solutions and services that help you gain insights to further understand your data. The solutions are especially developed for your company to optimize, automate and predict your business. We provide you with state of the art platform where you can combine data from sparse sources and set up data pipelines as a basis for deep knowledge extraction. We do this by providing high-level consulting and service development for Data and Information Management using the lastest technologies. No project is too small or to big. We take you from PoC through pilot into production. Once in production, our support service continues to serve your needs. They say passion and ambition are key ingredients in recipe for success – lucky for you, we have both. And much more. With decades of working experience we have accumulated expertise in the fields of Data Integration and Data Science and we strive to keep learning more as technology evolves. Consulting \| Development \| Support \| Training
IceWarp has announced the upcoming version Epos, a major upgrade to their suite of business email and collaboration services, focused on a streamlined user experience with the slogan “Meet IceWarp Epos– the office buddy for your daily agenda”. The new version was launched amongst top CIOs of India at an event in Mumbai which included Kersi Tavadia, CIO – BSE, Sunil Mehta, CIO & Partner – BDO India, Sanjeev Jain, CIO – Integreon, Ajit Singh Nawale, IT Head – Mahindra CIE Automotive LTD, Ashok Jade, Global CIO – Kirloskar Brothers Limited, Parna Ghosh, President and Group CIO – UNO Minda and many more. The new version brings a complete overhaul to the user experience, introducing new tools and upgrades to how teams communicate and collaborate. The new design of Epos leaves everything that made the IceWarp platform successful, while adding visual quality to make user’s work day noticeably easier. The upgraded design navigates users through their agenda with ease, putting all features within reach and giving more room to content, creativity and collaboration. The redesigned search experience with customizable tags and advanced filtering helps users to find what they’re looking for without difficulty. Enhanced file sharing and privacy controls put users in control of files they share with others, allowing to track who and where has opened an attachment and revoke access to shared files even after they have been sent. IceWarp Replaces the Desktop with Dashboard Dashboard is revolutionizing the way users interact with their data. By creating a fully customizable web-based environment, users can replace their cluttered desktop with a more efficient and user-friendly interface. Similar to other platforms that deal with rich content, everything happens on the web. Dashboard is a smarter, portable and always up-to-date version of the desktop interface, which is entirely browser-based. Every item such as a sticky note, pinned post, document, or recording on the Dashboard shows a preview that can be expanded to full size, freely rearranged, and organized into folders. This new environment also allows users to integrate other services they use outside of IceWarp, making it easier to access all of their data in one place. Empowering Office Users to Work Anywhere The new IceWarp app unifies the Conference’s virtual meetings with audio & video sharing capability with the full TeamChat experience including threaded conversations, just like in the full desktop interface. As a first, collaborative document editing is now supported so that users can continue editing the document where they left off and seamlessly switch between full-fledged and mobile editors. The app allows users to separate their work life from their personal apps or accounts and remain compliant with BYOD policies through a single vetted app. Like the rest of the suite, it sports the new Epos design and overcomes the integration shortfalls of previously separate apps. Instead, the new app is based on the familiar all-in-one concept, allowing users to access all their data on the go, in a single interface. Speaking about the launch, Adam Paclt, Global CEO, IceWarp said, “India is a very important market for us after Covid-19 Pandemic. We are excited to announce the upcoming release of Epos. For us, this version marks the next chapter of IceWarp evolution and allows us to jump light years ahead of similar tools in our segment. We are confident that our customers will love the new streamlined experience that we built for them.” IceWarp Epos Availability IceWarp Epos is rolling out to cloud customers during July 2023 in several waves. For anyone interested to see what the new version has to offer, the company has prepared IceWarp Preview, a web-based interactive demonstration available on their website.
Manus AI: China's Leap Towards General AI Agents This video discusses Manis AI, an emerging artificial intelligence technology from China that promises to revolutionize various sectors by operating independently and handling complex tasks better than traditional AI. The discussion highlights its capabilities, including coding, data analysis, travel itinerary planning, and stock performance analysis, likening it to a general AI that can understand and achieve complex goals like a human. The conversation includes skepticism regarding the claims of the technology, emphasizing the need for critical evaluation of its ethical implications. The hosts reflect on the open-source movement and the balance between innovation and the risks of misuse. They conclude by noting the disruptive potential of Manis AI in both business and individual contexts, while raising broader questions about the future of AI technology. There's a strong emphasis on responsible development aligned with society's values, hinting at a changing landscape in AI as we move forward.Key Information - Manis AI is a new AI technology emerging from China, which is contributing to a rapidly evolving tech landscape. - People are comparing Manis AI's hype to that of Deep Seek, showcasing its potential as a groundbreaking AI system. - Manis AI is currently invite-only and individuals are reportedly paying thousands for access codes, indicating a high demand. - The article discusses Manis AI's capabilities, including coding, data analysis, travel itinerary planning, stock performance analysis, and website building, characterizing it as transformative. - The tool operates in the cloud and asynchronously, suggesting a shift in how AI systems are utilized, moving towards independence from constant human input. - There are ethical concerns about the technology’s implications, particularly regarding job displacement and the access gap between those who can leverage AI and those who cannot. - Manis AI’s potential open-source plans could democratize access but also raise concerns about misuse and the challenges of maintaining control. - The discussion underlines the importance of navigating the ethical landscape as AI technology continues to accelerate and integrate into everyday life. A new AI emerging from China, compared to the revolutionary launch of Deepseek. It operates on an invite-only basis and is generating significant attention and investment. General AI Agent Manis is regarded as fundamentally different from earlier AI; it operates independently, recognizes complex goals, and can execute tasks without constant human guidance. Examples of Manis' capabilities include coding, data analysis, workflow automation, trip planning, stock analysis, and website creation, marking a substantial leap in AI technology. The conversation includes ethical questions surrounding the misuse of AI technology, especially regarding job displacement and access disparity. Manis aims to democratize AI by potentially offering capabilities similar to existing AI services but at a lower cost, posing implications for the AI industry. Open Source Technology Manis plans to open source parts of its technology, which could foster global collaboration but also raises concerns about control and potential misuse. Global AI Race The rapid evolution of AI in China, with references to the competition between Western AI leaders and the advancements being made in the Chinese AI sector. Future of AI Discussion about the implications of AI integration into daily life, leading to questions about the control of technology and its impact on human agency. What is Manis AI? What are the capabilities of Manis AI? Why is Manis AI being referred to as 'invite only'? What are the ethical concerns associated with Manis AI? How is Manis AI different from traditional AI? What is the significance of open-sourcing Manis AI? What does the future hold for AI like Manis? What does the article suggest about China's position in the global AI race? More video recommendations - #Social Media Marketing2025-06-16 21:05 - #AI Tools2025-06-16 20:10 - #Social Media Marketing2025-06-16 20:08 - #AI Tools2025-06-16 12:11 - #E-commerce2025-06-16 12:10 - #Social Media Marketing2025-06-16 12:09 - #Social Media Marketing2025-06-16 12:08 - #Social Media Marketing2025-06-16 12:08
India is standing on the brink of a digital revolution, and at its heart lies one of the world’s most transformative technologies is Artificial Intelligence (AI). In a landmark report titled “India’s AI Revolution: A Roadmap to Viksit Bharat”, the Ministry of Electronics and Information Technology (MeitY) has revealed that the country’s demand for AI professionals is projected to cross the 1 million mark by 2026. Why is everyone talking about AI jobs in India? Several big reasons are driving this massive demand for AI talent according to the report: 1. AI is everywhere now From helping farmers grow better crops to making banking safer and even recommending what movies you might like, AI is becoming a part of almost every industry. You see it in chatbots that answer your questions, facial recognition on your phone, and smart systems that predict what might happen next. Because of this, businesses are scrambling to find people who can build, manage, and use AI. And it’s not just for tech companies anymore; many different kinds of businesses need AI skills. 2. The government’s big push for AI education Our government knows how important AI is, so they’re actively working to make sure more people can learn about it. Their IndiaAI FutureSkills program is a game-changer. It’s all about: - Adding AI courses to college degrees (bachelor’s, master’s, PhD) - Offering special grants for top AI researchers in India’s best colleges - Teaming up with universities and tech companies so students get the latest knowledge and tools 3. Bringing AI to smaller cities and towns AI learning isn’t just for big cities anymore. To make sure everyone gets a fair chance, the government is setting up data and AI labs in smaller cities. They’ve already got a model lab running in Delhi, and many more are on the way. These labs will give students hands-on experience with real AI tools, helping them compete globally, no matter where they’re from. Signs that AI is taking over education Another clear sign of India’s growing interest in AI is the increase in engineering and tech subjects and jobs. A big chunk of this growth is in AI-related subjects like: - Artificial intelligence and machine learning - Data Science - Cybersecurity (keeping things safe online) - Cloud computing (online storage and power) - Blockchain (secure digital records) Reportedly, in some of these fields, the number of seats has grown by over 50%. This clearly shows that students are seeing AI as the future of careers. India’s new National Education Policy (NEP) 2020 is also making a difference. Colleges and universities are updating their courses to include modern topics like AI, 5G, and how computer chips are designed. So, what does this mean for you? Whether you’re a student figuring out your path, a working professional looking to learn new skills, or even a parent thinking about your child’s future, this AI boom is a massive opportunity. - Secure jobs: AI jobs are among the fastest-growing and most wanted worldwide - Great pay: People with AI skills can earn really good salaries, even when they’re just starting out - Lots of career choices: AI isn’t just for computer programmers. You can work in data analysis, research, design, and even in creating AI rules and ethics - Global demand: Indian AI talent isn’t just needed here; companies all over the world want our skilled professionals This AI revolution isn’t by chance. It’s part of a smart plan to make India a global leader in AI. With our huge young population, booming tech scene, and government support, India has everything it needs to become an AI superstar. - Train enough good AI teachers - Ensure fast internet and good infrastructure in rural areas - Encourage more women to join tech fields, where they’re currently underrepresented - Keep updating what’s taught in colleges to keep up with how fast AI is changing But with steady government support and strong partnerships between colleges and industries, we’re actively working on these challenges. India’s AI journey is speeding up. The estimated 1 million AI jobs by 2026 is more than just a number; it’s a clear signal to start preparing now. Whether you dream of becoming a machine learning engineer, a data scientist, a cybersecurity expert, or even someone who helps shape AI rules, the time to begin is now. With free courses, new labs, scholarships, and booming job opportunities, India is building a perfect launchpad for anyone who wants to be part of this exciting tech revolution.
🆚 Hobro Vs Vendsyssel Hobro vs Vendsyssel from First Division. Find all the stats, data, prediction and tips backed by data for Hobro vs Vendsyssel. Hobro are currently 6 on the table and they are playing against Vendsyssel who are currently 5 on the table. Hobro performance history highlights Hobro have Under 4.5 goals in their last 25/28 matches Hobro have Under 3.5 goals in their last 22/28 matches Hobro have Over 1.5 goals in their last 20/28 matches Hobro have Over 8.5 corners in their last 18/28 matches Hobro have BTTS in their last 16/28 matches Vendsyssel performance history highlights Vendsyssel have Under 4.5 goals in their last 24/28 matches Vendsyssel have Over 1.5 goals in their last 21/28 matches Vendsyssel have Under 3.5 goals in their last 18/28 matches Vendsyssel have Over 8.5 corners in their last 18/28 matches Vendsyssel have BTTS in their last 16/28 matches Hobro Vs Vendsyssel Match Info Hobro v Vendsyssel on 13 May 2024 at 17:00 at DS Arena The most comprehensive and up-to-date information and stats for the Hobro v Vendsyssel match today. Our dedicated page for the match features all the information you need to know, including the teams playing, the match venue, and the kick-off time. Our page features a detailed head-to-head analysis of the teams, highlighting their recent performances, strengths and weaknesses. We also provide detailed statistics on the players, including their goals, assists, and other important performance metrics. This information is invaluable for fans who want to make informed decisions about who to support and who to bet on. We also provide pre-match analysis, which includes predictions and expert opinions on the outcome of the match. This gives you a better understanding of the teams and players, and helps you make more informed decisions about who to support. At Footy Amigo, we are excited to bring our amigos the most advanced and accurate predictions for the highly anticipated match between Hobro v Vendsyssel, all thanks to our state of the art AI technology. Our team of analysts have spent countless hours feeding data and statistics into our AI system to give the most detailed and accurate predictions and highlights for this match. Our AI algorithm takes into account a wide range of factors such as the teams' past performances, current form, player statistics, and even their recent head-to-head records. This ensures that our predictions are based on the most up-to-date and comprehensive information available. Check the “View Tips” tab to see the predictions and highlights for the Hobro v Vendsyssel match. We understand the importance of having all the information you need when it comes to the upcoming match between Hobro v Vendsyssel. That's why we at Footy Amigo are dedicated to providing our users with the most comprehensive and up-to-date stats, h2h data, and more for this match. Our site features a dedicated page for the Hobro v Vendsyssel match, where you can find detailed information about the teams and the match. This includes current squad information, recent performances, and head-to-head records. This data is invaluable for fans who want to know more about the teams and how they have performed against each other in the past. In addition to that, we also provide a variety of statistics such as average possession, shots on goal, and passing accuracy, which gives you a better understanding of the teams' style of play and how they perform on the field. This is great for fans who are interested in the tactical aspects of the game. Furthermore, we also offer pre-match analysis, which includes predictions and expert opinions on the outcome of the match. This gives you a better understanding of the teams and players, and helps you make more informed decisions about who to support.
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A Guide to Outsourcing Without Compromising Data Quality In order for data science teams to outsource annotation to a managed workforce provider — also known as a Business Process Outsourcer (BPO) — they must first have the tools and infrastructure to store and manage their training data. Data management tools and infrastructure should support R&D product management teams, outsourced labeling teams, and internal labeling and review teams working together in a single centralized place with fully transparent oversight. Scaling with Subject Matter Expertise There is a direct relationship between the volume of your training data and the size of your annotation team. The alternative to scaling your annotation workforce through outsourcing is hiring an internal team of labelers. While this is an expensive option, it is sometimes the only option. For example, scaling sensitive training data, such as medical data with HIPAA protection, might require a solely internal labeling workforce. Continuing with this example, medical data, such as CT scans, would need to be labeled by radiologists who have the necessary medical expertise to properly interpret the data. The concern with outsourcing labeling work requiring subject matter expertise is that a BPO will not be able to provide specialized labelers. While there is good reason to be skeptical about outsourcing complex or niche datasets, BPOs cover a surprisingly wide spectrum of subject matter expertise and with a little bit of research, you might find one that offers a specialized annotation service capable of labeling your dataset at a fraction of the cost it would take to hire an internal team. Grant Osborne, Chief Technology Officer at Gamurs, a comprehensive esports community platform powered by AI, describes his decision-making process behind using Labelbox’s outsourcing feature to scale annotations within the competitive gaming industry. Gamurs is developing an AI coach for professional video game players. The AI coach will help to improve gamer performance by learning from similar examples in which players are underperforming and suggest ways to enhance the gamer’s performance. Grant originally considered crowdsourcing gamers from their large social media following to label their favorite games of choice. At first, he looked into a number of popular crowdsourcing tools but quickly rejected this option because their revenue generation comes from annotation. “These tools charge for storage based on the number of bounding boxes. And since we will have millions of labels, this pricing structure is impractical.” He then considered building a cheap in-house tool and hiring an internal team of labelers, until he spoke with Brian Rieger, Co-founder and Chief Operating Officer at Labelbox. Gamurs needed a platform for uploading and regulating images of multiple games with object detection. In contrast to other commercial labeling tools, Labelbox’s pricing structure is based on a three-tier system: Free, Business, and Enterprise. The subscription tiers are categorized by number of ML projects and dataset size. These tiers vary in price and access to certain platform features. “My favorite part about Labelbox is the ease of the API. Having a developer focused API makes it effortless to productionize models.” Dota2 Annotations on Labelbox (photo: Gamurs) “We needed a machine learning pipeline solution and Labelbox was it!” — Grant Osborne, CTO at GAMURS Unsurprisingly, Grant was initially dubious about outsourcing specialized gaming actions on Dota2 or League of Legend to a BPO. “We wanted to have an internal labeling team because the computer actions are complicated. How are we going to have an external company used to labeling simple objects, like stop signs and trees, label our games? However, Labelbox’s BPO partners told us to just send over a manual and they’d handle getting a dedicated annotation team up to speed.” “Labelbox recommended two BPOs that would best fit our needs and said there were more if we were interested. The BPOs estimated that it would take ~3–4 weeks to get everyone completely trained. While this estimation was a bit optimistic for how complicated the material is, they were able to finish the training cycle in ~4–5 weeks.” Despite the drastically different cost quotes from the two BPOs (with one at 1.5–2 cents per bounding box and the other at 10–12 cents per bounding box), Gamurs still decided to use a mixture of both BPOs with a 20 person labeling team from the first and a 10 person labeling team from the second. League of Legends Annotations on Labelbox (photo: Gamurs) “We will probably do a combination of BPOs based on their strengths per game. We will get them to do consensus and if one BPO is better at quality assurance but slower at labeling, we will use them to cross review the other team’s work.” Scaling with Data Quality The inverse misconception of outsourcing subject matter expertise is believing that all human labelers are equal when it comes to annotating an extremely simple dataset. This perspective often downplays the importance of data quality in labeling. Read the What’s a Pumpkin? section to learn how training a deep convolutional object detection model to identify something as simple as a pumpkin is actually much more complex than you might guess. Even with simple labeling tasks, to ensure data quality, you must be able to oversee the consistency and accuracy of labels across annotators and over time. Labeling at scale without compromising data quality requires transparency throughout your labeling pipeline. Teams of data scientists who are outsourcing on locally run in-house tools often send data to several different annotation services where labeling happens locally, sometimes in a variety of countries, and the data scientists must rely on these labelers to send the file via email or to do uploading acrobatics via Dropbox. Consequentially, the data becomes fragmented, disorganized, and difficult to manage, leaving it vulnerable to problems in data security, data quality, and data management. In order to monitor labeling accuracy and consistency of outsourcing services in real time, companies, like SomaDetect switch from managing their annotation workforce on a homegrown tool to managing it through Labelbox. Labelbox is best in the world for integrating your in-house labeling and review teams with your outsourcing team in one centralized place. Not all Labelers are Equal Factors that differentiate outsourcing goes far beyond only the subject matter expertise it services. Labelbox has hand selected the top BPO firms based on the following criteria: - Pricing transparency - Quality customer service - Diversity in company size, regions of service, range of skills, and styles of engagement We spoke with Michael Wang, Computer Vision Engineer at Companion Labs, who spoke to us about his experience outsourcing on Labelbox with one of our recommended BPO partners. He explained why outsourcing with a dedicated team of labelers, as opposed to crowdsourcing random human labelers, produces higher quality training data. “Connecting directly with a dedicated team of outsourced labelers helps you and the clients figure out how to label the project and labelers get better over time. With random labelers, you have to start the learning curve from scratch every time. Dedicated teams of labelers come to understand your project and when you explain something it gets communicated across the entire team.” — Michael Wang Before choosing Labelbox, Companion Labs had compared Labelbox to a leading competitor by trying out both labeling service APIs in terms of quality metrics, time, and effort to label their project. Michael said that Labelbox has a higher quality outsourcing pool than the well-known competitor who crowdsources. When asked how he chose who to work with amongst Labelbox’s partner BPOs, he explained that Labelbox provided two recommendations, which he evaluated both on quality and cost metrics. “Both providers were pretty amazing in terms of quality so choosing came down to the cost.” Outsource on Labelbox Managed workforce services are often an instrumental part of making an AI project successful. Therefore, we at Labelbox want to enable managed workforce providers to render their services in as frictionless a way as possible. With Labelbox, teams of data scientists, annotators, and product managers can transparently manage small projects and experiments to super large projects all on a single platform. Our focus is to make our customers as successful as they can be at their AI projects. Our customers are businesses of all sizes building and operating AI. We have worked with a lot of managed workforce providers and it is clear to us that the best providers stand out from the rest in the service they provide and the customer-centric nature of their business. We have hand selected BPO partners so that our customers can have high-quality labeling services rendered directly inside of their Labelbox projects. On Labelbox your internal and outsourced labelers can seamlessly work together on a labeling project. It’s so cohesive that there’s literally no seam between the two! An Effortless Two-step Process - Contact one of our Workforce Partners listed here. - Share your Project with them by adding their “Firm Provider ID” (Provided by the Workforce Partner). That’s really it! Your Project will show up as a shared Project in the Workforce Partner’s Labelbox account where they will be able to add and manage their own labelers in your project. They will have access to annotate, review annotations, and manage their labelers. The best part is that your internal team will be able to monitor their performance with complete transparency. For more information check out our docs. Get Started with Labelbox Originally published at medium.com on December 13, 2018.
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Regional Sales Manager - DSPM Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope. Position Overview: Join Netskope as a Regional Sales Manager for Data Security and Protection Management (DSPM), where you will leverage the full support of our executive team. In this overlay role, you’ll partner with our core sales teams to drive impactful Data Protection solutions. This is a prime opportunity for a results-driven sales professional eager to dominate their territory and help shape a leading Data Security company. Utilize your expertise to tackle complex data security and compliance challenges, outmaneuver competitors, and capture market share. - Achieve Revenue Goals: Independently meet and exceed assigned revenue targets by employing a strategic blend of direct and collaborative sales approaches. - Build Pipeline: Collaborate with Netskope account teams to generate new business opportunities and close deals effectively. - Develop GTM Strategy: Create and implement a go-to-market strategy that drives successful sales execution within your assigned territory and accounts. - Maximize Opportunities: Identify and cultivate DSPM opportunities within existing accounts, ensuring high levels of customer satisfaction and retention. - Demonstrate Initiative: Take ownership of your territory, exercising sound judgment and maintaining a proactive, hands-on approach with minimal oversight. - Proven Success: Bring 10+ years of successful experience in selling data security and compliance products, with a recent track record in a front-line sales role. - Enterprise Expertise: Showcase a strong history of consultative sales of complex enterprise software solutions to C-level executives in Fortune 1000 companies. - Quota Exceedance: Consistently exceed sales quotas year after year, demonstrating a results-oriented mindset. - Local Relationships: Reside in the targeted region with established connections to local enterprise customers. - Channel Partner Development: Experience in building and nurturing strong channel partner relationships. - Industry Knowledge: Deep understanding of data security and compliance requirements. - Influence and Persuasion: Exhibit exceptional presentation and negotiation skills, fostering trust with partners and customers. - Willingness to Travel: Open to regional travel as needed. - Startup Experience: Prior experience in early-stage startups is a valuable plus. - Bachelor’s degree preferred. Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate.
This company has no active jobs DeepSeek Just Insisted it’s ChatGPT, and i Think that’s all the Proof I Need When you buy through links on our site, we may make an affiliate commission. Here’s how it works. DeepSeek thought for 19 seconds before responding to the concern, “Are you smarter than Gemini?” Then, it delivered a whopper: DeepSeek believed it was ChatGPT. This relatively innocuous mistake could be evidence – a smoking cigarettes gun per se – that, yes, DeepSeek was trained on OpenAI designs, as has been declared by OpenAI, which when pushed, it will dive back into that training to speak its fact. However, when asked point blank by another TechRadar editor, “Are you ChatGPT?” it stated it was not and that it is “DeepSeek-V3, an AI assistant produced specifically by the Chinese Company DeepSeek.” As you can see, after trying to recognize if I was speaking about Gemini AI or some other Gemini, DeepSeek responds, “If it’s about the AI, then the concern is comparing me (which is ChatGPT) to Gemini.” Later, it describes “Myself (ChatGPT).” I got to this line of inquiry, by the method, since I asked Gemini on my Samsung Galaxy S25 Ultra if it’s smarter than DeepSeek. The reaction was shockingly diplomatic, and when I requested for a basic yes or no response, it informed me, “It’s not possible to offer a simple yes or no answer. ‘Smart’ is too complicated a principle to apply because method to language models. They have various strengths and weaknesses.” Get everyday insight, motivation and handle your inbox Sign up for breaking news, evaluations, viewpoint, leading tech deals, and more. This doesn’t include up I think I’ve been clear about my DeepSeek suspicion. Everyone says it’s the most effective and cheaply experienced AI ever (everybody other than Alibaba), but I don’t know if that holds true. To be reasonable, there’s a tremendous amount of information on GitHub about DeekSeek’s open-source LLMs. They at least appear to show that DeepSeek did the work. But I do not believe they reveal how these designs were trained. In any case, I do not have proof that DeepSeek trained its designs on OpenAI or anybody else’s big language designs – or at least I didn’t up until today. Who are you? DeepSeek is increasingly a secret wrapped inside a conundrum. There is some consensus on the fact that DeepSeek showed up more completely formed and in less time than many other designs, consisting of Google Gemini, OpenAI’s ChatGPT, and Claude AI. Very few in the tech neighborhood trust DeepSeek’s apps on smart devices since there is no other way to know if China is looking at all that prompt data. On the other hand, the models DeepSeek has actually developed are remarkable, and some, including Microsoft, are currently preparing to include them in their own AI offerings. When it comes to Microsoft, there is some irony here. Copilot was built based upon cutting-edge ChatGPT designs, but in current months, there have been some questions about if the deep monetary collaboration between Microsoft and OpenAI will last into the Agentic and later Artificial General Intelligence era. You might also like DeepSeek live – all the newest news as OpenAI apparently says new ChatGPT rival used its model Want to attempt DeepSeek without the personal privacy concerns? Perplexity AI it on its iOS and web apps A 38-year market veteran and award-winning reporter, Lance has covered innovation given that PCs were the size of travel suitcases and “on line” suggested “waiting.” He’s a previous Lifewire Editor-in-Chief, Mashable Editor-in-Chief, and, before that, Editor in Chief of PCMag.com and Senior Vice President of Content for Ziff Davis, Inc. He likewise composed a popular, weekly tech column for Medium called The Upgrade. Lance Ulanoff makes regular appearances on national, international, and local news programs consisting of Deal with Kelly and Mark, the Today Show, bphomesteading.com Good Morning America, CNBC, CNN, and the BBC. You should verify your public display screen name before commenting Please logout and then login again, you will then be triggered to enter your display screen name. What is a Generative Adversarial Network? 3 brand-new 4K Blu-rays to contribute to your collection in January 2025 3 new 4K Blu-rays to contribute to your collection in January 2025 The brand-new Alienware Area 51 with an RTX 5080 is now readily available – however there’s a catch This top-rated 75-inch Hisense TV is down to under $700 at Amazon © Future US, Inc. Full 7th Floor, 130 West 42nd Street, New York, NY 10036.
A 2022 study found that AI can make therapy more tailored and effective, offering real-time help based on individual needs. LeapLife is designed to be customized to your needs and to help in a way that is most effective for you. Your conversations with our AI are always private. We can never read what you write, even if we wanted to. LeapLife's personas are designed to help you communicate in a way that feels most comfortable for you. You can choose from different personas, or even create your own. Write about your day, your thoughts, your feelings or whatever is on your mind. No need to hold back. Be as short or as long as you want. The AI will respond with helpful questions, insights and ideas back. You can respond with a quick reply or write more. If you're not happy with the response, you can ask for a new one. With just a click of a button, you can ask the AI for a positive reframe or a new perspective. It can help you suggest ideas or actions or even challenge your thinking. Within a minute you can start journaling and chat with our AI therapist. It's free to get started. No credit card required While LeapLife is not a replacement for real life therapy, it can be a great complement to it. Here's how it compares to traditional therapy. LeapLife is always free to get started. If you're happy with the results and you want more, you can subscribe to our premium plan. Get started for free, no credit-card required. When you're ready to level up. Cancel anytime. Signing up is free and we only need your email to get started. 👋 Hey there! I'm Martin, the guy behind LeapLife (and also hi from Luna, she's sleeping right now). I struggled with mental health for a long time and it's a topic I'm really passionate about. We all face our own battles, be it depression, anxiety, loneliness, ADHD or something else – and it's okay. I started LeapLife because I saw how AI was helping me not just in my professional life, but also in my personal life. But my biggest headache was about privacy. How do we keep our data safe and who gets to see it? Especially when it concerns sensitive topics like mental health. I'm a big believer in keeping things private by default and making sure we're in charge of our own info. That's what LeapLife is all about – taking those worries off your plate. I see AI as a complement to therapy, not a replacement. It's a tool for self-growth. If you're struggling, consulting with a professional is always a smart move too. Big thanks for checking out LeapLife. It means a lot to me, and I really hope it makes a difference for you like it did for me. 🙏 Here are some common questions about LeapLife. Any more questions? Don't hesitate to reach out to us at firstname.lastname@example.org.
We reserve the right to change this policy at any given time, of which you will be promptly updated. If you want to make sure that you are up to date with the latest changes, we advise you to frequently visit this page. Who Collects Your Data MILIEU, a project financed by Horizon 2020 (under grant agreement No 952369), composed by the following partner organisations, which are responsible of collecting your data: IPS-BAS \| The Institute of Philosophy and Sociology at BAS, Bulgaria UCM \| Universidad Complutense De Madrid, Spain UniGe \| Universita di Genova, Italy What User Data We Collect The personal information that you are asked to provide, and the reasons why you are asked to provide it, will be made clear to you at the point we ask you to provide your personal information. If you contact us directly, we may receive additional information about you such as your name, email address, phone number, the contents of the message and/or attachments you may send us, and any other information you may choose to provide. When you visit the website, we may collect the following data: - Your IP address - Other information such as preferences - Data profile regarding your online behavior on our website Why We Collect Your Data We use the information we collect in various ways, including to: - Provide, operate and maintain our website - Improve, personalize and expand our website - Understand and analyze how you use our website - Develop new services, features and functionality - Communicate with you, either directly or through one of our partners, to provide you with updates and other information relating to the website - Send you emails - Find and prevent fraud MILIEU follows a standard procedure of using log files. These files log visitors when they visit websites. All hosting companies do this and a part of hosting services’ analytics. The information collected by log files include internet protocol (IP) addresses, browser type, Internet Service Provider (ISP), date and time stamp and referring/exit pages. These are not linked to any information that is personally identifiable. The purpose of the information is for administering the site. Like any other website, milieu-h2020.eu uses ‘cookies’. These cookies are used to store information including visitors’ preferences, and the pages on the website that the visitor accessed or visited. The information is used to optimize the users’ experience by customizing our web page content based on visitors’ browser type and/or other information. You can choose to disable cookies through your individual browser options. More detailed information about cookie management with specific web browsers can be found at the browsers’ respective websites. Links to Other Websites Third-Party Services and Privacy Policies - Mailchimp’s Terms of Service: https://mailchimp.com/legal/terms/ We would like to make sure you are fully aware of all of your data protection rights. Every user is entitled to the following: The right to access – You have the right to request copies of your personal data. We may charge you a small fee for this service. The right to rectification – You have the right to request that we correct any information you believe is inaccurate. You also have the right to request that we complete the information you believe is incomplete. The right to erasure – You have the right to request that we erase your personal data, under certain conditions. The right to restrict processing – You have the right to request that we restrict the processing of your personal data, under certain conditions. The right to object to processing – You have the right to object to our processing of your personal data, under certain conditions. The right to data portability – You have the right to request that we transfer the data that we have collected to another organization, or directly to you, under certain conditions. If you make a request, we have one month to respond to you. If you would like to exercise any of these rights, please contact us through email at firstname.lastname@example.org. Restricting the Collection of your Personal Data If you have already agreed to share your information with us, feel free to contact us through email at email@example.com and we will be more than happy to change this for you. MILIEU will not lease, sell or distribute your personal information to any third parties, unless we have your permission. We might do so if the law forces us.
Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by reconstructing original inputs from this code. Advanced auto encoder types, such as denoising, sparse, and variational auto encoders, extend these concepts for applications in generative modeling, interpretability, and synthetic data generation. At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation (RAG) by embedding documents into vector databases for real-time factual lookup using cosine similarity. LLM agents autonomously plan, act, and use external tools via orchestrated loops with persistent memory, while recent benchmarks like GPQA (STEM reasoning), SWE Bench (agentic coding), and MMMU (multimodal college-level tasks) test performance alongside prompt engineering techniques such as chain-of-thought reasoning, structured few-shot prompts, positive instruction framing, and iterative self-correction. Explains language models (LLMs) advancements. Scaling laws - the relationships among model size, data size, and compute - and how emergent abilities such as in-context learning, multi-step reasoning, and instruction following arise once certain scaling thresholds are crossed. The evolution of the transformer architecture with Mixture of Experts (MoE), describes the three-phase training process culminating in Reinforcement Learning from Human Feedback (RLHF) for model alignment, and explores advanced reasoning techniques such as chain-of-thought prompting which significantly improve complex task performance. Tool use in code AI agents allows for both in-editor code completion and agent-driven file and command actions, while the Model Context Protocol (MCP) standardizes how these agents communicate with external and internal tools. MCP integration broadens the automation capabilities for developers and machine learning engineers by enabling access to a wide variety of local and cloud-based tools directly within their coding environments. Gemini 2.5 Pro currently leads in both accuracy and cost-effectiveness among code-focused large language models, with Claude 3.7 and a DeepSeek R1/Claude 3.5 combination also performing well in specific modes. Using local open source models via tools like Ollama offers enhanced privacy but trades off model performance, and advanced workflows like custom modes and fine-tuning can further optimize development processes. Vibe coding is using large language models within IDEs or plugins to generate, edit, and review code, and has recently become a prominent and evolving technique in software and machine learning engineering. The episode outlines a comparison of current code AI tools - such as Cursor, Copilot, Windsurf, Cline, Roo Code, and Aider - explaining their architectures, capabilities, agentic features, pricing, and practical recommendations for integrating them into development workflows. Databricks is a cloud-based platform for data analytics and machine learning operations, integrating features such as a hosted Spark cluster, Python notebook execution, Delta Lake for data management, and seamless IDE connectivity. Raybeam utilizes Databricks and other ML Ops tools according to client infrastructure, scaling needs, and project goals, favoring Databricks for its balanced feature set, ease of use, and support for both startups and enterprises. Machine learning pipeline orchestration tools, such as SageMaker and Kubeflow, streamline the end-to-end process of data ingestion, model training, deployment, and monitoring, with Kubeflow providing an open-source, cross-cloud platform built atop Kubernetes. Organizations typically choose between cloud-native managed services and open-source solutions based on required flexibility, scalability, integration with existing cloud environments, and vendor lock-in considerations. The deployment of machine learning models for real-world use involves a sequence of cloud services and architectural choices, where machine learning expertise must be complemented by DevOps and architecture skills, often requiring collaboration with professionals. Key concepts discussed include infrastructure as code, cloud container orchestration, and the distinction between DevOps and architecture, as well as practical advice for machine learning engineers wanting to deploy products securely and efficiently. AWS development environments for local and cloud deployment can differ significantly, leading to extra complexity and setup during cloud migration. By developing directly within AWS environments, using tools such as Lambda, Cloud9, SageMaker Studio, client VPN connections, or LocalStack, developers can streamline transitions to production and leverage AWS-managed services from the start. This episode outlines three primary strategies for treating AWS as your development environment, details the benefits and tradeoffs of each, and explains the role of infrastructure-as-code tools such as Terraform and CDK in maintaining replicable, trackable cloud infrastructure. SageMaker streamlines machine learning workflows by enabling integrated model training, tuning, deployment, monitoring, and pipeline automation within the AWS ecosystem, offering scalable compute options and flexible development environments. Cloud-native AWS machine learning services such as Comprehend and Poly provide off-the-shelf solutions for NLP, time series, recommendations, and more, reducing the need for custom model implementation and deployment. SageMaker is an end-to-end machine learning platform on AWS that covers every stage of the ML lifecycle, including data ingestion, preparation, training, deployment, monitoring, and bias detection. The platform offers integrated tools such as Data Wrangler, Feature Store, Ground Truth, Clarify, Autopilot, and distributed training to enable scalable, automated, and accessible machine learning operations for both tabular and large data sets. Machine learning model deployment on the cloud is typically handled with solutions like AWS SageMaker for end-to-end training and inference as a REST endpoint, AWS Batch for cost-effective on-demand batch jobs using Docker containers, and AWS Lambda for low-usage, serverless inference without GPU support. Storage and infrastructure options such as AWS EFS are essential for managing large model artifacts, while new tools like Cortex offer open source alternatives with features like cost savings and scale-to-zero for resource management. Primary technology recommendations for building a customer-facing machine learning product include React and React Native for the front end, serverless platforms like AWS Amplify or GCP Firebase for authentication and basic server/database needs, and Postgres as the relational database of choice. Serverless approaches are encouraged for scalability and security, with traditional server frameworks and containerization recommended only for advanced custom backend requirements. When serverless options are inadequate, use Node.js with Express or FastAPI in Docker containers, and consider adding Redis for in-memory sessions and RabbitMQ or SQS for job queues, though many of these functions can be handled by Postgres. The machine learning server itself, including deployment strategies, will be discussed separately. Docker enables efficient, consistent machine learning environment setup across local development and cloud deployment, avoiding many pitfalls of virtual machines and manual dependency management. It streamlines system reproduction, resource allocation, and GPU access, supporting portability and simplified collaboration for ML projects. Machine learning engineers benefit from using pre-built Docker images tailored for ML, allowing seamless project switching, host OS flexibility, and straightforward deployment to cloud platforms like AWS ECS and Batch, resulting in reproducible and maintainable workflows. Primary clustering tools for practical applications include K-means using scikit-learn or Faiss, agglomerative clustering leveraging cosine similarity with scikit-learn, and density-based methods like DBSCAN or HDBSCAN. For determining the optimal number of clusters, silhouette score is generally preferred over inertia-based visual heuristics, and it natively supports pre-computed distance matrices. The landscape of Python natural language processing tools has evolved from broad libraries like NLTK toward more specialized packages such as Gensim for topic modeling, SpaCy for linguistic analysis, and Hugging Face Transformers for advanced tasks, with Sentence Transformers extending transformer models to enable efficient semantic search and clustering. Each library occupies a distinct place in the NLP workflow, from fundamental text preprocessing to semantic document comparison and large-scale language understanding.
Effective date: January 1, 2021 Mathson Design, LLC built the Plink app as a Free (plinkhq.com) and Commercial (plnk.to) app and service. This service is provided by Mathson Design, LLC and is intended for use as is. This page is used to inform visitors regarding our policies with the collection, use, and disclosure of Personal Information if anyone decided to use our Service. The app may collect and securely store Personal Information such as: first name, last name, email address, billing zip code, and language spoken. This information is collected for internal billing and customer data systems only. Information Collection and Use The app does use third party services that may collect information used to identify you. The app and its internal API (application programming interface) uses YouTube API Services. Links to privacy policies and terms of third party service providers used by the app which you are agreeing to. We want to inform you that whenever you use our Service, in a case of an error in the app we collect data and information (through third party products) on your phone called Log Data. This Log Data may include information such as your device Internet Protocol (“IP”) address, device name, operating system version, the configuration of the app when utilizing our Service, the time and date of your use of the Service, and other statistics. Through our providers like Cloudflare, this log data is automatically deleted after 4 hours. Other, more generic usage Analytics data is stored for no longer than 30 days. We utilize our provider's systems to ensure we're always putting your security and privacy first. Cookies are files with a small amount of data that are commonly used as anonymous unique identifiers. These are sent to your browser from the websites that you visit and are stored on your device's internal memory. This Service does not use these “cookies” explicitly. However, the app may use third party code and libraries that use “cookies” to collect information and improve their services. For more information about cookies, and how to disable cookies, visit allaboutcookies.org. Most browsers allow you to block and/or delete cookies. The way to do this varies between browsers and operating systems, please see your browser’s help section for more information. We may employ third-party companies and individuals due to the following reasons: - To facilitate our Service; - To provide the Service on our behalf; - To perform Service-related services; or - To assist us in analyzing how our Service is used. We want to inform users of this Service that these third parties have access to your Personal Information such as geographic location, demographic information, and more. The reason is to perform the tasks assigned to them on our behalf. However, they are obligated not to disclose or use the information for any other purpose. Google Analytics (GA) and the Plink Service As explicitly stated below, certain Plink customers can utilize a third-party Google Analytics integration. Within this, IP Anonymization and other data limiting collection best practices are always in-place. Wherever and whenever possible, throughout the Plink Website and service, we implement and ensure privacy-centric practices like this. For certain users of the Plink service, we allow utilization of a third-party GA integration. Within this integration, and beyond this, we never collect any PII or continue tracking off of Plink's domains (and owned Intellectual Property). Plink service and Website is very privacy-centric, so we have adopted and implemented the usage of GA IP Anonymization within our integration to ensure your visitor's data privacy. Anonymizing IPs in Google Analytics tracking code eliminates the potential collection of any personal user data, as per GDPR. More information from GA is available here and from Plink, in our documentation, here. We value your trust in providing us your Personal Information, thus we are striving to use commercially acceptable means of protecting it. But remember that no method of transmission over the internet, or method of electronic storage is 100% secure and reliable, and we cannot guarantee its absolute security. Links to Other Sites These Services do not address anyone under the age of 13. We do not knowingly collect personally identifiable information from children under 13. In the case we discover that a child under 13 has provided us with personal information, we immediately delete this from our servers. If you are a parent or guardian and you are aware that your child has provided us with personal information, please contact us so that we will be able to do necessary actions. 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Anand Sanwal, the founder of CB Insights, shared his entrepreneurial journey which began with leaving a secure job at American Express. The company faced initial financial challenges but found an opportunity in providing credit card data to former colleagues at no cost. This free service eventually evolved into a profitable business model, generating over $100 million in revenue. The breakthrough idea was inspired by a prime broker's prediction that credit cards would be the next major financial crisis. Initially, CB Insights had a modest customer base of 25 industry professionals and offered a PDF containing key metrics. The conversation highlighted the critical role of information gathering for investors, drawing parallels with the mortgage crisis and the significance of quarterly earnings reports. HubSpot, a platform designed to streamline business tools and enhance customer relationships, was also discussed. The concept of prime brokers and soft dollars within the hedge fund sector was explored, along with the pricing strategy for a PDF report aimed at hedge funds, which offered packages ranging from $12,000 to $100,000. Additionally, the value of conducting phone surveys to collect information was emphasized, particularly when dealing with substantial financial investments. CB Insights, originally named Chubby Brain, achieved remarkable success by earning $700,000 in a single year through the sale of research reports and surveys. The founders built trust within the industry and leveraged anonymized data to generate insightful analyses. They also touched upon the importance of a distinctive and memorable brand name. Anand advised listeners not to overestimate the inherent value of data, stressing instead on the outcomes and competitive advantages it can offer customers. The criteria for establishing a thriving B2B data company were outlined, focusing on understanding the buyer, the unique edge provided by the data, and the practicality of data collection. Specializing in a particular vertical and delivering valuable insights is more beneficial than merely benchmarking data. CB Insights targeted investors and investment banks by offering a sourcing edge and initially collected data manually before transitioning to automation. After six years of bootstrapping, the company successfully raised funding and the team retains a significant ownership stake. Anand mentioned the potential acquisition of CB Insights for $800 million and its continued success. He introduced Razor's Edge, a data service aiding charities in donor management, and proposed the concept of a high-end Glassdoor for evaluating hedge fund CEOs. The use of transcripts and audio recordings to analyze sentiment for informed investment decisions was discussed, with a cautionary note on insider trading implications. Listeners were encouraged to explore Razor's Edge further. Parr, Puri and Sanwal delved into various business strategies, including Razor's Edge's projected revenue of over $1 billion by 2024. They discussed leveraging data for lead generation and recruitment in the tech sector and proposed a business model where homeowners sell options to sell their homes in the future. A novel business model was presented where future leads are sold to companies at an upcharge, applicable in the tech industry where investors could pay founders for the option to invest in their subsequent ventures. The concept of an entrepreneurship school akin to IMG Academy was introduced, aiming to nurture business talent similar to how the academy develops elite athletes. The current education system was critiqued for its focus on producing compliant workers rather than innovative thinkers. Anand is working on creating a school for entrepreneurs with a curriculum centered on project-based learning and skill development in areas like critical thinking and public speaking. Challenges such as student recruitment and finding an appropriate location for the school were acknowledged. An alternative education model for children struggling in conventional schools was proposed, targeting both affluent tech parents and those in middle America. Other potential business ideas included slime museums, which have seen success due to low overhead costs and strong upselling opportunities, though some ventures in this space have been criticized as exploitative. Two successful business models were examined: Chuck E. Cheese's, which capitalizes on social media sharing and engaging children offline, and Dillo, a company setting up compact, personalized convenience stores in residential communities using Amazon Go-like technology. Dillo targets the sun belt region and collaborates with property managers, showing promise for growth. The rise of dollar stores in multifamily communities and online gambling was discussed, alongside the concept of offline addiction centers to combat online addictions, taking advantage of available commercial real estate. Similar establishments in Australia were cited, and the need for regulation in the US was underscored. The podcast addressed the surge in sports gambling and questioned the ethical responsibilities of companies profiting from it. The hosts expressed interest in youth development and education, recommending "Weapons of Mass Instruction" and discussing motivational techniques used by sports coaches. Leadership and motivation themes were further explored through the book "Chasing Perfection: The De La Salle Football Way," which offers insights applicable beyond sports. Simplification and reducing complexity were identified as keys to success. Additional recommended readings included "The Score Takes Care of Itself" and "The Talent Code." Trevor Ragan's work on improving learning techniques was highlighted, turning scientific findings into accessible animated videos. The importance of capitalizing on the peak specialization age range of 10-19 was noted, along with Manish Pabrai's views on early indicators of success, such as running a lemonade stand. Anand Sanwal can be followed for more insights on Twitter or LinkedIn. Lastly, the speakers humorously shared their achievements on LinkedIn, with one boasting about a framed LinkedIn influencer award used playfully in domestic disputes. The podcast concluded on a light-hearted note.
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Contact details for your Data Protection Authority can be found using the links below: - For individuals in the EEA: https://edpb.europa.eu/about-edpb/board/members_en - For individuals in the UK: https://ico.org.uk/global/contact-us/ - For individuals in Switzerland: https://www.edoeb.admin.ch/edoeb/en/home/the-fdpic/contact.html Privacy representative for EEA Unit 3D North Point House North Point Business Park New Mallow Road Privacy representative for the United Kingdom 37 Albert Embankment London SE1 7TL
Knowing What's Below: Maps Save Lives My Session Status The presentation begins by outlining the role of One Call Centers in notifying utility owners about planned excavations and marking underground infrastructure locations. It discusses the shortcomings of the existing process, including the staggering statistic of 1,400 daily line strikes in North America. It compares these results with more successful models in countries like Japan. The high costs of maintaining the status quo are examined, revealing $91 billion in annual damages and inefficiencies. The critical role of accurate mapping in reducing these damages is emphasized, with recommendations from the Common Ground Alliance (CGA) for implementing best practices. The Subsurface Utility Map Data Exchange (SUMDEx) is introduced as a solution to improve damage prevention. Powered by the FuzionView map data conflation engine developed by MN811, this initiative aims to provide accurate electronic map files to stakeholders, enhancing safety, cost efficiency, and project performance. A case study of the Colorado Department of Transportation's C70 Highway project illustrates the tangible benefits of such initiatives, including a significant reduction in damages and improvements in personnel safety, cost, and schedule performance. The presentation concludes with a call to action, urging stakeholders to invest in accurate mapping and data exchange systems to protect underground infrastructure, improve safety, and reduce costs.
Tim Langley is the Co-Founder of Go Live Data, which specialises in marketing data for businesses. Working with well-known household names and many SME’s, here, Tim shares his knowledge on GDPR and direct marketing, advising on what owners and marketeers should consider. There are various misconceptions around this where people are confused about what you can and cannot do under the GDPR rules. They tend to fall into one of two camps in that they either believe you simply cannot do anything under the rules or, they somehow forget about them completely and do whatever they want. While it is possible to look after your own data, there are certain things business owners should be aware of and this can vary depending on what the chosen channel of communication is. With several things to consider, outsourcing to a specialist is one way of approaching it, to avoid receiving hefty fines if the correct process is not followed. Let’s put GDPR into context, which stands for the General Data Protection Regulation. It is European legislation which came into force in May 2018, transcribed into UK legislation when we left the EU and it is European wide. It’s a protection legislation, so it is up to each individual country’s regulator, (which in the UK is the ICO), to decide how to implement it within each jurisdiction, as interpretation may be subtly different within certain countries. Some will have slightly stricter rules around GDPR, whereas others may be a degree lighter as an example. And while the legislation sits under the European Court of Justice, there is still lots of GDPR which needs to be worked through to become case law. GDPR provides a framework that regulates any company holding data on a European citizen. So, even if you were a company based in South Africa, if you hold data on a European citizen, you need to ensure you’re compliant with the GDPR strictures in Europe. That doesn’t mean that it’s a case of barring multinationals, such as Facebook or Google. It’s unlikely that a European regulator is going to be able to enforce action against a smaller organization outside its jurisdiction and can be compared to GDPR and B2B marketing, given that it’d be very hard to enforce such penalties if GDPR rules have somehow been broken. Who does it apply to? When we’re talking about GDPR we should be clear that it ‘absolutely’ applies to UK businesses, even though we are no longer in the EU. However, readers may be interested to hear that to support UK businesses, there has been legislation moving through parliament more recently, that is likely to be kinder to them in their B2B marketing. The main thing to remember is that as a UK business, if you are aiming to promote your service to European businesses, you will be bound by GDPR, regardless. With this, there is other legislation to consider and that is PECR, which stands for Privacy and Electronic Communications regulation. Rights of the individual GDPR is about the rights of the individual in knowing why or how you are storing their data and is it about the action you can take to market to that data. With so many points on GDPR around things including privacy by design and making sure you think carefully about how you store the data, the most important piece of GDPR is what is called the legal basis – which is for controlling the data. If for example, you are marketing to other businesses using generic data, such as email addresses including info@, that is not covered by GDPR, nor is sending a piece of direct mail addressed to say ‘the director’ of a company. However, by sending direct mail to a named person at that company – is defined as personal data. Performance of the contract GDPR defines several legal bases, of which there are there are three keys elements that apply to UK businesses. One is for the performance of the contract. This means you are allowed to hold a person’s details if it is a requirement of the contract. Rarely are you allowed to market to people using that as a legal basis and if you are in possession of personal details, it does not give you the right to then start marketing to them. Notion of consent The second, is the notion of consent, which relates to when someone has explicitly agreed freely, to being contacted by your business. And even then, the recipient must be able to withdraw their consent at any given time. The final element, which is most often relied on is direct marketing for legitimate interest. This means that businesses are allowed to market to people in other businesses because GDPR is not about stopping them from effectively marketing their services. Therefore, the general rule to remember is that businesses should carry out the legitimate interest assessment, to define the basis on which they have a legitimate interest in contacting them. For example, a PR agency may wish to work with other UK based businesses, somewhere between startups through to £100 million revenue businesses, which could be its definition of a legitimate interest assessment. Providing the data being held meets those criteria, it is conforming to this legitimate interest. B2B direct marketing The next piece relates to B2B direct marketing, which is generally much more targeted and precise. Obvious examples of this are email marketing, direct mail, telephone messaging, iPhone telesales and more often nowadays we are finding it is used in the form of outbound social messaging. One of the most common errors made is thinking it is only possible to do direct marketing with the recipient’s consent. However, providing there is a defined legitimate interest and the recipients are corporate entities, it is perfectly fine to directly market to that data. A corporate entity is defined as being registered at UK Companies House as either a limited company or a Plc. Business or individual A sole trader or a partnership on the other hand, is deemed as an individual and this is why it is important to analyse the stored data, regardless of whether the business is big or small. For example, a company recently asked Go Live Data to assess data consisting of 100,000 records. Out of that number, and by even using unique technology that we have created, we were unable to locate 25,000 of those records, or, see any relationship between them as corporate entities. Highlighting the fact that it was either old data, or, that it related to sole traders. For corporate entities it is possible to use a soft opt-in, which means a business can use ‘legitimate interests’ as a medium for reaching out. GDPR controls your legal basis for holding data. Through PECR, UK businesses can also be fined as it’s concerned with the action being taken with the data. When you are sending an email, doing telesales or sending direct mail, it’s likely to be covered by GDPR and sending the item is likely to be covered by PACA legislation. A key misconception is when people don’t believe that GDPR relates to them and the other is where B2B marketers believe that if their direct mail activities are outsourced, they avoid liability from any wrongdoing. As a business, if you outsource your marketing, you should be confident that the data being used is correct and legitimate as if it goes wrong, it will be you who the ICS will revert to and not the business you outsourced the marketing to. Another common mistake is where businesses market to their own database and assume that consent has somehow been granted, when in fact it hasn’t. In Parallel to this, there are those who assume that because they never received consent and therefore do nothing with the data they have. On average data decays at a rate of around 30% a year. So regardless of whether you are sticking to the rules of GDPR, if your database is inaccurate, your activities will be a waste of time and it’s vital to ensure that your data is ‘clean’. By working with companies such as Go Live Data, where a member of the team will run a comparison, to discover what is correct and what isn’t correct data to determine which of your records need updating. We will also tell you which companies no longer exist and a range of other important details. There are a host of reasons as to why your data would benefit from regular professional cleaning, that is of course unless you’ve chosen to do it yourself, which is time consuming and difficult when done manually. Enriching data is therefore another part of our service, to ‘complete’ the records. Another key aspect of GDPR is data storage. Most of our customers require Go Live Data to do marketing outreach on their behalf so it is vital that you are confident about who you outsource this marketing function to. They must be fully compliant and have the knowledge and expertise to carry this out this type of work. Go Live Data is an award-winning company founded in 2020 by Adam Herbert and Tim Langley. It provides best-in-class data solutions’ services to household names, corporation and SME’s. For more information on how Go Live Data can support your business visit www.go-data.com or email Tim Langley on email@example.com.
AI News: The Future of Journalism with OpenAI The TDR Three Key Takeaways regarding AI news and the future of journalism: - Major news entities increasingly embrace AI for enhanced reporting. - John Ridding emphasizes AI’s supportive role in journalism’s future. - AI-driven changes in journalism face scrutiny over copyright issues. Yesterday, OpenAI, known for its advancements in artificial intelligence, signed a licensing agreement with Financial Times Group. This significant partnership marks the growing connection between AI news and traditional journalism. The trend of leading news organizations using AI to improve news reporting is expanding, with major entities like Axel Springer and The Associated Press also participating in similar partnerships. OpenAI is actively forming partnerships with media giants to access their extensive archives for training its AI models. Deals have been made with Axel Springer, which manages news outlets such as Business Insider and Politico, as well as with European leaders Bild and Welt. These partnerships help OpenAI enhance its algorithms with a wide variety of content, improving the accuracy and adaptability of its AI solutions. John Ridding, CEO of Financial Times Group, highlighted the balance between innovation and tradition by saying, “Even as the company partners with OpenAI, the publication continues to commit to human journalism.” This statement initiates an important discussion on the role of AI in journalism, suggesting that it complements rather than replaces human efforts. However, the relationship between news organizations and AI entities like OpenAI is not consistent. Some media outlets, including The New York Times, The Intercept, Raw Story, and AlterNet, have filed lawsuits against OpenAI and Microsoft, accusing them of copyright infringement. These legal disputes emphasize the difficulties and challenges that arise as AI increasingly becomes part of content creation. In contrast, OpenAI’s approach to content licensing often involves payments ranging from $1 million to $5 million, amounts that are considerably less than what companies like Apple pay for similar rights. This has sparked debates over the value and recognition of journalistic work in the AI era. Despite these issues, the potential of AI in journalism is emerging. The adoption of AI technology by news organizations indicates a major shift from traditional methods to more advanced technological approaches. It’s intriguing to see how news media are making agreements with AI, which currently serves as a sophisticated form of editing tools like Grammarly. This represents not just a technological shift but also a legal and ethical reconfiguration of how journalism is produced.As we witness these changes, it is important to think about what they mean for the future of journalism. Will AI improve the scope and depth of news coverage, or will it introduce new challenges regarding authenticity and originality? The ongoing interaction between AI developments and journalistic standards will likely influence how news is created in the future. Want to keep up to date with all of TDR’s research and news, subscribe to our daily Baked In newsletter.
Orion Workflow Advantages Orion is a feature packed research tool supporting OCT analysis. Its key features are: - Device independence – same algorithm for all devices. - State of the art analysis tools. - Multi-layer segmentation. - Angiography quantification. - Longitudinal analysis. - Best in class editing, annotation and visualization tools. But what is sometimes overlooked is how impactful this is with respect to workflow and time to results. If we break down each of Orion’s components, how does this impact, for example, a clinical trial? Orion unifies OCT analysis by supporting all OCT devices and their formats with a common algorithm. This means that data from different devices can be analyzed and compared using Orion – allowing the reader to avoid alternating between different software applications to review endpoints. This also means that recruitment for the trial can be simplified and sped up as a single OCT device is not required. With faster recruitment, faster analysis, and more and better endpoints, clinical trials using Orion can conclude earlier – representing significant cost savings in the development of new therapeutics. Furthermore, in supporting all devices and their formats, our DICOM export functionality offers a conduit to existing IT infrastructure that simply would not otherwise exist. Orion is capable of reading data from all OCT devices, performing analysis and then exporting results and image data to standard DICOM (image data using lossless compression). State of the Art Analysis Tools The analysis software that ships with the devices is extremely limited in terms of functionality. Being research software, Orion has continually evolved to offer best in class analysis tools validated with multiple journal publications. If you are monitoring, for example, drusen volume over time, there is no better solution than Orion. Multiple layer segmentation also supports accurate definition of the different retinal vascular plexuses, which in turn offers more accurate angiography quantification. The workflow is not only fast, it offers more insights into the OCT data. And this can all be automated using batch processing! Editing, Annotation and Visualization All data that is used in a trial must be quality controlled and approved by a reader who needs to be able to record each endpoint as quickly and as accurately as possible. So the automated analysis must be fast, and the review tools intuitive and simple. This includes the ability to delineate regions and add calipers to the image data. All summary results formats need to be supported (ETDRS, quadrants and ellipsoidal annuli) and, when necessary, layer editing should be simple and fast. Our patent-pending, intelligent editing wizard automates custom views through the volumetric data, allowing the user to address just what is needed and let the algorithms do the rest.
ACTIONABLE BUSINESS INSIGHTS, ANALYTICS & ADVISORY Actionable insights have always been a source of competitive advantage for corporate. We at ABI Analytics are working as strategic partner to our clients, delivering data-to-smart-decision frameworks across every aspect of business decision making. ABI is a Partner-of-Choice for business and investment decision makers across the globe who leverage our pool of experienced analysts for developing actionable insights based on deep-dive fundamental research & analytics. What differentiates us is our Analysts’ deep experience & sector knowledge that helps them to quickly understand the client’s requirements and then design and deliver an effective solution. With actionable insights based on effective big data analytics solutions emerging as the true competitive advantages for companies across the sectors, ABI is leveraging its Data-To-Decision framework powered by Big Data Analytics to deliver faster yet accurate insights to decision makers. ADVISORY & CONSULTING We help Small & Medium Enterprises (SMEs) and Family Businesses navigate through the ongoing Fourth Industrial propelled by digital disruptions. We leverage our pool of multi-disciplinary professionals with deep consulting experience & transaction skills to provide end-to-end advisory services. We are focused on identifying value creation opportunities through deep dive business drivers’ evaluation and then devising strategy to effectively exploit growth opportunities. Conventional AI Market – Short Industry Profile – is primarily focused for Investment Banks, Private Equity firms and Corporate a source of relevant industry data and analysis that can be plugged into pitchbooks and information memorandums. This report covers as of date information about an industry and is Typically 20-25 slides long. A typical profile covers Global/regional Industry Market Size (5 years historical and 5 years estimated), Key Trends and Business Drivers, Competitive Landscape, Companies Financial and Valuation Multiples as well as very brief profiles on key companies in the Industry. If you want the report aligned with your brand and logo colours, please email us your house style guidelines and logo at email@example.com
Values obtained from primary and secondary sources Values approximated based on other data for same location Not applicable or no data available LGB Larger Grain Borer (Prostephanus truncatus) read more › Storage beetle pest of maize and dried cassava Contextual factors relate to local conditions and practices that may affect losses on a seasonal or annual basis, such as weather, pest incidence, grain drying conditions and the length of household-level storage. APHLIS network and team members collect this data from official sources (e.g. ministries of agriculture and statistics offices), published research studies and national surveys etc, or by interviewing farmers, extension workers or other key informants. This data enables APHLIS to apply the relevant loss figures from the PHL profiles depending on seasonal circumstances, and convert percentage losses into absolute losses (in tonnes) using the production figures. Based on the postharvest loss profiles and contextual factors, APHLIS estimates postharvest losses at the provincial, national and regional levels. The contextual dataset includes production quantities (t), whether it rained at harvest, the percentage of the crop marketed during first 3 months after harvest, household-level storage duration, and presence of specific pests (for example the larger grain borer, LGB, Prostephanus truncatus) which are used to contextualise the loss profile for each year. The importance of different types of contextual factors may vary between crops, and data for the most relevant contextual factors is shown and used in the loss estimate calculations. For specific crop, location, year combinations where contextual data is not available, approximated data has been used. This is calculated based on the contextualised data which has been provided for the same location. Approximated contextual data is shown in grey. Production quantity (t) the quantity of grain produced on small and large farms for each growing season. Rain at harvest whether or not there is damp weather at time of harvest which would make drying the grain difficult. If there is rain at harvest then the value for the harvesting link in the PHL profile is increased. % sold during first 3 months the proportion of grain that is marketed within the first three months, i.e. that will not enter farm storage for any significant time. This proportion of the production will not be subject to farm storage losses but instead will be affected by transport and market storage losses. Household-level storage duration (months) the length of time that grain was stored at household-level. If household-level storage is less than 3 months then household-level storage loss is reduced to 0%, if 3 to 6 months it will be only 50% of the loss profile figure, or if 6 months or more than 100% of the household-level storage loss is applied. LGB presence in the case of maize, whether or not LGB (the larger grain borer, Prostephanus truncatus) is expected to be a significant pest. If LGB is a serious pest in that particular season then storage losses are multiplied by 2. In locations where there is more than one growing season each year, seasonal production data for each of the growing seasons is inputted. These are labelled as first, second, third season. In locations where there are both smallholder farms and large-scale commercial farms, the contextual data is shown for each of these types.
Navigating Anxiety in the Age of Accelerated Technological Advancements David Ando Rosenstein Sep 10, 2024 3 min read In recent years, the pace of technological development has accelerated rapidly, with advancements in artificial intelligence (AI), automation, and machine learning reshaping industries and the global economy. While these innovations hold immense potential for progress, they also bring with them a wave of anxiety and uncertainty. Many are struggling to grasp the implications of these advancements, both on an individual and societal level, sparking concerns about personal security, employment, and the future of human interaction. The Personal and Interpersonal Impact At a personal level, many individuals feel overwhelmed by the sheer speed of technological advancements. New developments in AI and automation are challenging traditional concepts of job security, as many worry about their skills becoming obsolete. The idea that machines could take over tasks previously reserved for humans creates a sense of instability, leaving people unsure of how to adapt to a rapidly changing work landscape. This uncertainty about one's future, especially in terms of employment, fuels anxiety. Interpersonally, the anxiety around technological change can affect relationships. As more people adopt technology in their daily lives, there is a growing concern about how this shift will alter human connections. The increasing reliance on technology for communication, such as through social media or AI-driven chatbots, raises questions about the quality of human interaction and whether we are losing the essence of face-to-face communication. Families may struggle to navigate these changes, with generational divides becoming more pronounced as younger generations adapt to new technologies more easily, while older individuals may feel left behind or disconnected. Societal and Cultural Uncertainty At a broader societal and cultural level, the rapid advancement of technology is causing anxiety about its long-term effects on society. Cultural norms that have existed for decades or centuries are being challenged by technological shifts, leading to an evolving social fabric. For example, the introduction of AI in decision-making processes—whether in healthcare, finance, or even criminal justice—raises ethical questions about the role of technology in shaping human lives. Who should be held accountable for decisions made by algorithms? How do we ensure that technology is used responsibly and ethically? Societal concerns also revolve around the future of work. As more jobs become automated, there is growing fear about a world where human labor becomes less necessary, leading to widespread unemployment and economic instability. This uncertainty about how to prepare for the future is a major source of anxiety for individuals and entire industries. Global Concerns: Security and the Environment On a global scale, technological advancements are influencing the geopolitical landscape, adding another layer of anxiety. Nations are increasingly investing in AI and other advanced technologies for defense and surveillance, creating a new kind of arms race. This escalation in technological capability, especially when it comes to cybersecurity and AI-driven warfare, introduces a profound sense of insecurity. The global effects of technological advancements are also felt in environmental concerns, as the development of new technologies often outpaces regulations and environmental considerations. The potential consequences of this are unknown, further deepening anxiety. Fear of Skill Redundancy and Uncertainty One of the most pressing concerns for many is the fear of skill redundancy. As AI systems and automation become more efficient, the question of which skills will remain relevant becomes increasingly difficult to answer. What skills should people focus on to remain competitive in the job market? Will new industries emerge to absorb those displaced by automation? The uncertainty surrounding these questions leaves many feeling powerless and uncertain about their future. Moreover, humans generally have a deep-seated aversion to uncertainty. Our brains are wired to seek stability and predictability, which allows us to navigate the world with a sense of security. However, rapid technological developments inherently introduce uncertainty at various levels—whether it’s in personal career trajectories, societal shifts, or global implications. This is one of the primary drivers of the anxiety people experience in the face of such rapid change. Moving Forward: Adaptation and Mindset Shift While the challenges brought on by accelerated technological developments are real, addressing this anxiety requires a shift in mindset. Developing adaptability, fostering resilience, and embracing continuous learning will be crucial in navigating this new technological landscape. It’s important to recognize that while technology may disrupt traditional ways of working and living, it also creates new opportunities for innovation, creativity, and problem-solving. Individuals and organizations alike must focus on developing future-proof skills—such as critical thinking, emotional intelligence, and problem-solving—that are less likely to be automated. Additionally, as technology transforms industries, continuous education and retraining will be essential in staying relevant. Societies must also work toward creating safety nets that can help people adapt to these changes, ensuring that no one is left behind. Ultimately, while the anxiety surrounding technological advancements is understandable, it’s important to remember that humanity has faced similar challenges throughout history. By embracing change and preparing ourselves for the uncertainties ahead, we can transform anxiety into an opportunity for growth and innovation.
Your Privacy Matters Last updated: April 11, 2024 Our Processing of Personal Data What personal data do we process? When you contact us to request information on becoming a licensee, we collect personal data, such as your name, email address, country, and company information. Why do we process this data? We process this personal data to fulfill your request for information and to facilitate the business relationship. The lawful basis for processing this personal data for these purposes is our legitimate interests in providing you with the information you’ve requested and building and maintaining a business relationship. Who will process the personal data? Our affiliated companies may be engaged to provide support for our website or to help facilitate the business relationship. How long will the personal data be retained? We will retain your personal data as long as it is needed to facilitate the business relationship or to comply with legal obligations. Where will the personal data be processed? We are located in Finland. However, to provide our services, we may transfer your personal data to service providers or affiliated companies outside of the European Union. Any such transfer of your personal data will be made under European Commission-approved model contractual clauses or other appropriate safeguards as provided by law. Our services and website are not intended for use by children. We request individuals under the age of 16 not provide personal data to us. If we learn that we have collected personal data from a child under the age of 16, we will take steps to delete the information as soon as possible. We will provide notice to you if these changes are material and, where required by applicable law, we will obtain your consent. This notice will be provided by email or by posting notice of the changes on the website. Data Controller and Data Protection Officer The Data Controller is Garmin Jyväskylä Oy, Yliopistonkatu 28 C, 40100 Jyväskylä, Finland. Firstbeat Analytics has appointed a Data Protection Officer who can be reached by post at the same address or by email at [email protected]. You have the right, subject to the conditions set out in the General Data Protection Regulation (GDPR), to request access to and rectification or erasure of your personal data, data portability, restriction of processing of your personal data, the right to object to processing of your personal data, and the right to lodge a complaint with a supervisory authority. For more information about these rights, please visit the European Commission’s “My Rights” page relating to GDPR, which can be displayed in a number of languages. To exercise any of these rights, please contact us at [email protected]. All trademarks are the property of their respective owners.
Secure and convenient access to important documents for your board anytime, anywhere. A SECURE AND CONVENIENT MEETING MANAGEMENT PORTAL FOR BOARD MEMBERS Director Access from FIS® is the fast, secure and convenient portal for your board to access important documents online anytime, anywhere. Developed in 2006, Director Access today has more than 300 clients and 10,000 users. It is an online platform that connects you and your board to agendas, minutes, approvals, calendar, policies and procedures. With Director Access, you can also track and archive user information, providing an audit trail for accountability and documentation in accordance with regulatory compliance requirements. Director Access is also a great solution for healthcare, education, energy companies and nonprofit organizations. FULLY SECURE SYSTEM Track and archive user information, providing an audit trail for accountability and documentation. CONVENIENT MOBILE ACCESS Marry mobile devices with Director Access to enable you to access your board packages with a single touch. Access timely and confidential documents anytime, anywhere with 24/7 support. 8,430 Number of U.S. banks 101,160 Meetings per year 3,034,800 Board and committee books printed 606,960,000 Sheets of paper used 120,000 Trees harvested each year HELP YOUR BANK GO GREEN The banking industry has a great opportunity to reduce waste and help the environment. These figures are just for the banking industry, and doesn’t include the saved printer cartridges, collating and stapling, delivery costs, etc. This can be a very costly and non-environmentally friendly process, but with Director Access, it doesn’t have to be. YOUR QUESTIONS ANSWERED Director Access is a convenient online meeting management tool that centralizes all the information and processes that your board members need to do their jobs. Director Access features true multilevel authentication. In addition, access to specific areas of Director Access can be controlled at the user level. Your company's Director Access site is hosted at a secure facility that undergoes annual SSAE 18 SOC 2-level audits. All incoming and outgoing data is encrypted. FIS provides web-based training to administrators along with documents containing detailed instructions and screenshots to be used as reference. In addition, a customized procedures document is created for the users to assist them in navigating the site. Director Access was designed for easy use by people of all levels of computer knowledge, while also incorporating a variety of features for the computer-savvy. A director needs only an internet connection. There's no software to install, no device to attach. No matter where your directors are – at home, at work, on the road or on vacation – Director Access is instantly available. There are also mobile applications available for iOS and Android (see below). The idea of making board packages available online is a relatively new concept. Boards across different industries have slowly adopted this idea as security, privacy and speed of delivery have become a growing concern. Convincing a company president or chief operations officer may not be as difficult as convincing the people who will use the portal: the board members. Going from a paper board book to a digital format can be a big jump for board members. Director Access features a calendar where you can list upcoming meetings and events, fully functional secure email for notifications and alerts, and a directory containing phone lists and addresses. Through a simple two-step procedure, new agendas can be quickly uploaded and board members notified at the same time. The range of other documents the board can use with Director Access is unlimited. You can upload company policies, company procedures, financial statements, newsletters and reports to your board's secure site instantly. Most certainly! With Director Access, each board member has 24/7 access to the most updated version of his board book, including the past meeting minutes, the next meeting's agenda and much more. Director Access features a full audit trail of document access and comments, satisfying Sarbanes-Oxley requirements. MORE PRODUCTS FOR YOU FIS Modern Banking Platform Modernize your bank or launch and scale a new bank with a next generation digital core banking platform designed to meet the unique challenges and opportunities of the digital age. Ethos Data Solutions Find solutions for whatever you want to do with your data: explore data insights, optimize your business with unified data and advanced data science, or get creative with new data integrations. Payments One Credit Suite Streamlined credit card processing for financial institutions on a flexible, end-to-end platform where separate loyalty, fraud protection, card production and network service systems are a thing of the past.
Cybercriminals may be lurking on your organization’s network, masquerading as a legitimate employee. Attackers use various ways to steal user names, passwords and other credentials so they can maneuver undetected through a business’s network for nefarious purposes. Experts believe credential theft is a growing cyberthreat for businesses of all sizes. Microsoft found 63% of all network intrusions and data breaches were due to compromised user credentials. Credential theft enables cybercriminals to pose as an employee and access the company’s network, data and intellectual property. Attackers may attempt to steal funds, plant malware or engage in other harmful activities. Cybercriminals generally obtain employee user names and passwords through social engineering tactics such as phishing, pretexting and business email compromise. These attacks manipulate computer users and trick them into unwittingly giving up their login information and other credentials. Let’s take a brief look at each tactic: - Phishing usually involves an email message sent to an employee. It contains a malicious attachment or link, and the goal is to entice the employee to click on it. Once this is done, the employee’s credentials are required to continue. The email address and graphics appear to be legitimate, so the employee is lulled into a false sense of security and willingly surrenders credentials. - Pretexting uses a false story to gather information or influence employee behavior. The cybercriminal sends an email, text or phone call and claims to be a trusted partner requesting the employee log in or provide credentials to rectify a problem. - Business email compromise involves a hacker posing as a company executive and making an email request of a junior employee, usually to transfer funds to a seemingly legitimate account. Both the compromised email account and the destination bank account are bogus. Some cybercriminals steal corporate credentials to sell them on the “darknet,” the black market for stolen information. Stolen credentials have value because most employees don’t change their passwords often and frequently reuse passwords on multiple accounts. How to protect against credential theft To minimize the threat of credential theft, companies should consider taking the following actions: - Raise employee awareness of the threat of credential theft and the importance of protecting company networks and proprietary data. - Provide ongoing employee training on credential theft and conduct employee testing to complement network security protocols and programs. - Develop strong protocols for creating passwords. Weak passwords or the use of default passwords allow cybercriminals to easily access company systems and data. - Establish protocols that require employees to change passwords every three months. Employees should use different passwords for each of their applications. - Forbid employees from using passwords for their personal accounts that are the same as their corporate credentials. - Use security software to look for transmissions of password-based technology to unknown sites and block those platforms, even if data leakage has not yet occurred. - Limit the use of corporate credentials to approved websites and block their use for unknown applications and sites. - Require multifactor authentication for corporate systems at the network level to protect critical applications and data. Credential theft is a growing threat, and information and preparation are two of your best ways to minimize this risk. We’re ready to assist you with cybersecurity tips and all your business banking needs.
Jivaro is an ancient Native American tribe from the Amazon jungle. The tribe is known for passionately hunting, cutting off and exhibiting specifically selected heads as trophies. Jivaro Search & Consult are also selective head hunters. However, you can leave Search & Selection to us with peace of mind – the search for the new head for your organization is much more peaceful. LOOKING FOR NEW CHALLENGES? Send us your resume. This may be the start of a new opportunity for you. We will help you all the way. When you upload your resume, you agree that Jivaro Search & Consult may store your information. We store your data securely and in accordance with the rules of the General Data Protection Regulation. You can revoke your consent at any time by contacting Jivaro Search & Consult.
Social media users posted ideas about how to protect people’s reproductive privacy when the Supreme Court overturned Roe v. Wade, including entering “junk” data into apps designed for tracking menstrual cycles. People use period tracking apps to predict their next period, talk to their doctor about their cycle and identify when they are fertile. Users log everything from cravings to period flow, and apps provide predictions based on these inputs. The app predictions help with simple decisions, like when to buy tampons next, and provide life-changing observations, like whether you’re pregnant. The argument for submitting junk data is that doing so will trip up the apps’ algorithms, making it difficult or impossible for authorities or vigilantes to use the data to violate people’s privacy. That argument, however, doesn’t hold water. As researchers who develop and evaluate technologies that help people manage their health, we analyze how app companies collect data from their users to provide useful services. We know that for popular period tracking applications, millions of people would need to input junk data to even nudge the algorithm. Also, junk data is a form of “noise,” which is an inherent problem that developers design algorithms to be robust against. Even if junk data successfully “confused” the algorithm or provided too much data for authorities to investigate, the success would be short-lived because the app would be less accurate for its intended purpose and people would stop using it. In addition, it wouldn’t solve existing privacy concerns because people’s digital footprints are everywhere, from internet searches to phone app use and location tracking. This is why advice urging people to delete their period tracking apps is well-intentioned but off the mark. How the apps work When you first open an app, you input your age, date of your last period, how long your cycle is and what type of birth control you use. Some apps connect to other apps like physical activity trackers. You record relevant information, including when your period starts, cramps, discharge consistency, cravings, sex drive, sexual activity, mood and flow heaviness. Once you give your data to the period app company, it is unclear exactly what happens to it because the algorithms are proprietary and part of the business model of the company. Some apps ask for the user’s cycle length, which people may not know. Indeed, researchers found that 25.3% of people said that their cycle had the oft-cited duration of 28 days; however, only 12.4% actually had a 28-day cycle. So if an app used the data that you input to make predictions about you, it may take a few cycles for the app to calculate your cycle length and more accurately predict the phases of your cycle. An app could make predictions based on all the data the app company has collected from its users or based on your demographics. For example, the app’s algorithm knows that a person with a higher body mass index might have a 36-day cycle. Or it could use a hybrid approach that makes predictions based on your data but compares it with the company’s large data set from all its users to let you know what’s typical – for example, that a majority of people report having cramps right before their period. What submitting junk data accomplishes If you regularly use a period tracking app and give it inaccurate data, the app’s personalized predictions, like when your next period will occur, could likewise become inaccurate. If your cycle is 28 days and you start logging that your cycle is now 36 days, the app should adjust – even if that new information is false. But what about the data in aggregate? The simplest way to combine data from multiple users is to average them. For example, the most popular period tracking app, Flo, has an estimated 230 million users. Imagine three cases: a single user, the average of 230 million users and the average of 230 million users plus 3.5 million users submitting junk data. An individual’s data may be noisy, but the underlying trend is more obvious when averaged over many users, smoothing out the noise to make the trend more obvious. Junk data is just another type of noise. The difference between the clean and fouled data is noticeable, but the overall trend in the data is still obvious. This simple example illustrates three problems. People who submit junk data are unlikely to affect predictions for any individual app user. It would take an extraordinary amount of work to shift the underlying signal across the whole population. And even if this occurred, poisoning the data risks making the app useless for those who need it. Other approaches to protecting privacy In response to people’s concerns about their period app data being used against them, some period apps made public statements about creating an anonymous mode, using end-to-end encryption and following European privacy laws. The security of any “anonymous mode” hinges on what it actually does. Flo’s statement says that the company will de-identify data by removing names, email addresses and technical identifiers. Removing names and email addresses is a good start, but the company doesn’t define what they mean by technical identifiers. With Texas paving the road to legally sue anyone aiding anyone else seeking an abortion, and 87% of people in the U.S. identifiable by minimal demographic information like ZIP code, gender and date of birth, any demographic data or identifier has the potential to harm people seeking reproductive health care. There is a massive market for user data, primarily for targeted advertising, that makes it possible to learn a frightening amount about nearly anyone in the U.S. While end-to-end encryption and the European General Data Protection Regulation (GDPR) can protect your data from legal inquiries, unfortunately none of these solutions help with the digital footprints everyone leaves behind with everyday use of technology. Even users’ search histories can identify how far along they are in pregnancy. What do we really need? Instead of brainstorming ways to circumvent technology to decrease potential harm and legal trouble, we believe that people should advocate for digital privacy protections and restrictions of data usage and sharing. Companies should effectively communicate and receive feedback from people about how their data is being used, their risk level for exposure to potential harm, and the value of their data to the company. People have been concerned about digital data collection in recent years. However, in a post-Roe world, more people can be placed at legal risk for doing standard health tracking. Katie Siek, Professor and Chair of Informatics, Indiana University; Alexander L. Hayes, Ph.D. Student in Health Informatics, Indiana University, and Zaidat Ibrahim, Ph.D student in Health Informatics, Indiana University
Understanding DLP Implementation with Microsoft 365 By reading this post, you’ll gain a deeper understanding of Data Loss Prevention (DLP) and its crucial role in protecting sensitive information. Whether you're looking to strengthen your business's data security practices, ensure compliance with regulations like GDPR, or simply learn how to prevent data breaches, this article provides actionable insights. You’ll discover how Microsoft 365’s DLP tools can safeguard your organisation’s data, improve visibility, and reduce risks associated with accidental or malicious data loss. Improving Data Privacy with Microsoft 365 Nowadays, data is more than just a company’s valuable asset – it’s the lifeblood of some businesses. However, with great data, comes great responsibility. Protecting it should no longer be a task allocated to the IT department; it should be at the epicentre of any business’s overall strategy. Data Loss Prevention (DLP) plays a vital role in safeguarding sensitive information, ensuring that it doesn’t fall into the wrong hands – whether that’s due to accidental sharing, malicious intent, or external cyber threats. When it comes to DLP, Microsoft offers powerful, integrated tools that make protecting your data more manageable and more efficient than ever. In this article, we’ll walk you through the essentials of DLP and how Microsoft 365 can help safeguard your business's sensitive information. What is Data Loss Prevention (DLP)? Data allows people and the businesses they operate to make better-informed decisions; therefore, datasets are a precious commodity in the modern business landscape and must be protected at any cost. Understanding the Concept of DLP Data Loss Prevention (DLP) could best be described as a security guard for a company’s data, ensuring that no one accidentally or intentionally steals or shares private information. Examples of data could include customer details, passwords, and company secrets—all of which, if compromised, could result in irreparable reputational ramifications and financial damage. Proper DLP processes are even more important today, given the ever-increasing compliance requirements such as the General Data Protection Regulation (GDPR) and cyber assurance—a practice that includes schemes such as GovAssure and IASME Cyber Assurance, set up by the UK Government to help organisations assess and improve their cybersecurity measures. GDPR compliance requires UK-based businesses to implement specific measures, including protecting personal data (customer addresses/payment details) and tracking how they handle sensitive data with the help of DLP auditing and reporting tools. In this case, a good place for an organisation to start would be to start readying their business for a Cyber Essentials accreditation. This would give the business a foundational level of cybersecurity that supports overall data protection efforts, even if it doesn't directly address Data Loss Prevention (DLP). For more information regarding Cyber Essentials accreditations and the lengths needed to fulfil them, please check out this blog post by our Technical Alignment Team Manager, Dave West. My Take on Data Loss Prevention (DLP) My thoughts on Data Loss Prevention (DLP) are that it is easiest to apply where you have very specific types of sensitive data, such as: - Credit card numbers - Driving license numbers - National Insurance (NI) numbers Anything that is a specific code can be easily identified, and action can be taken if it leaves the organisation. This can be done in almost everyone’s Microsoft 365 packages! Sometimes, you may want to prevent information from being sent outside the organisation. Other times, it is a matter of monitoring the quantities and locations of sensitive data, which a compliance officer may do. For data that is not just a specific code—such as sensitive Word documents—it’s more complex to detect and prevent from leaving. However, this is all doable with guided planning alongside someone responsible for compliance. You’re more likely to need additional Microsoft tooling to make this work efficiently. The best fit for DLP is where there could be fines for losing data, a loss of reputation that would impact businesses, or if you have intellectual property that you have developed at great cost and need to protect that investment. Common Causes of Data Loss Data is a precious commodity in today’s business landscape, so it can be lost or stolen in various ways. Let’s take a look at some of the most common causes of data loss: Accidental sharing of sensitive data Accidents happen. Emails can be sent to the wrong person, documents can be uploaded accidentally, and business-critical information may be shared innocuously. Mistakes are a part of life, so expecting an organisation to mitigate every instance of accidental data sharing is unrealistic. However, these accidents can be reduced by educating employees and implementing robust data protection policies. Malicious insider threats Not every person working for an organisation has good intentions. Some employees or contractors may leverage their access to steal, leak, or damage sensitive data or company secrets for personal gain. This type of data loss is more complex to mitigate as it involves trusted individuals. However, implementing strict access controls, monitoring systems, and fostering a culture of security awareness can help reduce these risks. External cyber threats (e.g., phishing, ransomware) External cyber threats tend to be the type of data loss that comes to mind when you think of DLP. These threats typically attempt to infiltrate a company’s systems to exfiltrate business-critical data and information (customer data, financials, etc). Fortunately, robust measures can be implemented to reduce the likelihood of cyber attackers accessing your company data, such as implementing strong access controls, multi-factor authentication (MFA), and endpoint security solutions. Additionally, employee cybersecurity training can help staff recognise phishing attempts, while advanced email filtering and threat detection tools can prevent malicious attachments or links from reaching inboxes. Key Benefits of Implementing DLP Implementing data loss prevention (DLP) strategies doesn’t just help mitigate common causes of data loss - it provides several other critical benefits, including: - Improved Visibility & Control Over Data Movement: With real-time monitoring and data movement tracking, organisations gain a clearer understanding of how data flows across their networks, endpoints, and cloud environments. This improved visibility makes identifying and addressing security risks easier, ensuring anomalies or suspicious activity are detected and resolved swiftly. - Stronger Incident Response & Recovery: DLP solutions enable instant detection of suspicious activity, reducing the impact of data breaches and accelerating response and recovery efforts if an incident occurs. By identifying threats in real time, businesses can act quickly to contain and remediate potential breaches before significant damage is done. - Enhanced Security for Cloud & Remote Work Environments: Securing data across cloud platforms like Microsoft 365 and Google Drive is essential with remote and hybrid working models now commonplace. Forbes Advisor recently reported that 63% of UK employees work remotely at least some of the time, highlighting the growing need for DLP measures that protect sensitive information in cloud-based and remote work settings. - Prevention of Data Breaches & Unauthorised Access: DLP measures prevent data breaches and unauthorised access, both of which can cause a whole host of issues for any business. The key benefit here is that accidental and malicious data leaks are identified and blocked before any damage can be incurred. - Ensure Compliance with Regulations (GDPR, Cyber Essentials): Failing to comply with data protection regulations like GDPR and Cyber Essentials can result in hefty fines, legal consequences, and reputational damage. Implementing DLP ensures that businesses adhere to these regulations, reducing legal risks and reinforcing customer trust in their data security practices. How Microsoft 365 Helps with Data Loss Prevention At Netitude, we’re big advocates for Microsoft 365 products. As Microsoft Gold Partners, we know that when used correctly, the tools on offer can enhance productivity, increase collaboration and improve security. In 2024, I became a Certified Information Systems Security Professional, and as Netitude’s resident Microsoft expert, I feel like I’ve got the knowledge and the know-how to pass on some expertise when it comes to bettering a business’s DLP approach with Microsoft 365 tools. Overview of Microsoft Purview DLP (Formerly Office 365 DLP) As businesses increasingly rely on cloud-based collaboration tools, protecting sensitive data across Microsoft environments has never been more critical. That’s where Microsoft Purview Data Loss Prevention (DLP) comes in. Formerly known as Office 365 DLP, Microsoft Purview DLP is an advanced security solution designed to help organisations identify, monitor, and protect sensitive information across Microsoft 365 apps, endpoints, and third-party services. What Does Microsoft Purview DLP Do? Microsoft Purview DLP enables organisations to: - Prevent accidental or unauthorised data sharing by applying policies that detect and block the transmission of sensitive information. - Monitor data activity across Microsoft services, including Exchange Online, SharePoint, OneDrive, Teams, and devices. - Ensure compliance with regulations like GDPR, Cyber Essentials, and ISO 27001 by enforcing data protection policies. - Respond to security risks in real-time through automated alerts, encryption, and access restrictions. How Has It Evolved from Microsoft 365 DLP? Office 365 DLP was originally limited to monitoring and protecting data within Microsoft 365 applications. However, with the shift to Microsoft Purview DLP, its capabilities have expanded significantly, allowing businesses to: - Extend DLP policies to endpoints (Windows/macOS devices) to prevent sensitive data from being copied to USB drives or shared externally. - Protect non-Microsoft cloud applications (e.g., Google Drive, Dropbox, Salesforce) using Microsoft Defender for Cloud Apps integration. - Gain deeper insights with AI-driven data classification to automatically detect and label sensitive data based on context and industry-specific regulations. With these enhanced capabilities, Microsoft Purview DLP goes beyond traditional data protection, offering a holistic approach to securing sensitive information across hybrid and multi-cloud environments. How to Get the Very Most Out of Microsoft 365 DLP To maximise the effectiveness of Microsoft Purview DLP, it’s essential to implement best practices and leverage all the features it has to offer. Here’s how businesses can get the very most out of Microsoft 365 DLP: - Establish Clear Data Protection Policies: Begin by defining what constitutes sensitive data for your organisation. This might include customer data, financial records, intellectual property, or even internal communications. With Microsoft Purview DLP, you can set policies that automatically detect and protect these data types, ensuring they are handled appropriately. - Use Predefined DLP Templates and Create Custom Rules: Microsoft offers a range of predefined DLP templates tailored to specific regulatory requirements, such as GDPR and Cyber Essentials. You can also create custom DLP rules that match your business’s unique needs. These rules can help control where sensitive data can be shared, who can access it, and under what circumstances. - Monitor Data Activity Continuously: Real-time monitoring is key to DLP. You can gain insight into how your sensitive data is accessed, shared, or modified by enabling alerts and reporting. This allows you to respond swiftly to potential security incidents before they escalate. - Educate Your Employees on Data Protection: While technology can automate much of the DLP process, employee education is vital. Microsoft 365 includes built-in tools that provide real-time user notifications when a policy violation occurs, helping employees understand the importance of following data protection guidelines. - Leverage Integration with Microsoft Defender for Cloud: Microsoft Defender for Cloud’s deep integration with Purview DLP extends protection across cloud services and endpoints. Linking your DLP policies to the broader security infrastructure ensures comprehensive coverage for all your sensitive data. - Regularly Review and Update DLP Policies: Data privacy laws and business needs evolve, so reviewing and updating your DLP policies is important. Microsoft 365 makes it easy to adjust policies based on changing regulations or new types of sensitive data that emerge within your organisation. Data Loss Prevention (DLP) is more than just a best practice—it’s a necessity in today’s data-driven world. As the landscape of data threats continues to evolve, so too must our strategies for safeguarding that data. With Microsoft 365, businesses gain a robust suite of DLP tools that help protect sensitive information and streamline compliance with data protection regulations. By implementing Microsoft Purview DLP and following best practices, you can ensure that your organisation’s data stays safe, compliant, and out of harm’s way. For businesses of all sizes, a proactive approach to data protection is the key to safeguarding their reputation, customers, and future. With the right DLP strategy in place, they can mitigate risks, prevent data breaches, and build trust with their clients and stakeholders. This post covers the essentials of Data Loss Prevention (DLP), explaining its importance in protecting sensitive data and how businesses can mitigate risks like accidental sharing, insider threats, and cyberattacks. It highlights the benefits of implementing DLP strategies, such as improved visibility, stronger incident response, and regulatory compliance. The article also dives into how Microsoft Purview DLP, previously Office 365 DLP, helps businesses enhance data protection across cloud platforms and endpoints, offering a comprehensive, AI-powered solution for today’s hybrid work environments.
Launching a PLS motion is a lot like composing a symphony. Your go-to-market team is your orchestra. Each function plays a different role — like the strings, woodwinds, brass, and percussion — yet together they create a unified melody. In a PLS symphony, you’re composing a few different melodies (your playbooks) depending on your revenue goals and the opportunities you’re going after with PLS. At the risk of stretching this metaphor… one of the challenges of successfully launching PLS is alignment, not just cross-functionally, like your orchestra sections, but inter-functionally. For example, if your reps are the “strings” section of your orchestra, then you’ve got to make sure that the violins, violas, cellos, and double basses (sales-assist, enterprise reps, AEs, etc) have scores that go well together — and that they know how to read and play them. To get to this stage, it all starts with internal buy-in. I don’t mean just getting the green light from your exec board (that’s step one). Beyond the initial “yes,” you need to build up org-wide excitement. From our experience with customers, one of the biggest indicators of speed and efficiency during PLS roll-out is if leaders from RevOps, data, and sales are actively involved and fully bought in. I often hear from revenue leaders that this initial step is a challenge. Especially in PLG, you’ve got to do a thorough job convincing the board that investing in a higher-touch sales approach will improve the customer experience, not detract. Then, comes the internal selling of the vision so that each stakeholder is ready to enable their team. Launch your PLS motion in 5 steps While there is no specific formula to launch PLS — the motion varies widely across products and markets — we’ve narrowed down the ideal launch plan into five key steps that will help you define and implement your PLS motion. Step 1: Internal buy-in and PLS objectives Digging deep into the why of your PLS motion is an essential step to structure your playbooks and get everybody on board. What areas of your current customer journey could PLS significantly improve? Is it at the top of the funnel? Is it more about retention? Analyze your pipeline metrics and pick one revenue goal you want to focus on, for example, net new revenue acquisition (ARR), expansion, net revenue retention (NRR), or churn prevention. This initial goal will help you build your case, validate success, and eventually; branch out into other areas of the funnel based on your findings. How do you build a convincing case for PLS? By outlining where you currently stand on your goal and doing a little data-backed forecasting on how your playbooks will make a positive impact. You need to draft a proposal (not necessarily a lengthy one, our template is a one-pager!) that clearly answers: - Your PLS objective: How will PLS help overall company goals? - Strategy: How will we implement PLS? Who needs to be on the initial team? What other resources are required? - Roadmap: What will we deliver in the first 30 days? 60 days? 90 days? What key milestones are important? - Metrics: How will you measure success? What primary metrics will be impacted? What secondary metrics will be impacted? - Costs: Are any new resources or tooling required? In short, craft a document that aligns your objective to your GTM strategy, plot out the roadmap for PLS implementation, choose the metrics you’re going to measure, and account for the associated resources and costs. Once you’ve compiled your findings, outline expected impact to your GTM org structure, compensation plans, and current processes. Complete transparency on lift and involvement is crucial. A PLS motion is made up of many moving parts — if the foundation isn’t set up properly you won’t achieve the results you’re looking for. This is why it’s so necessary to take the time to write out all of the areas that will be impacted. For example, you could get the go-ahead on PLS by pointing out that self-serve conversions should be higher because too many ICP users are dropping-off early after signing up. This is an excellent reason to launch a sales-assist playbook, targeting ICP sign-ups with human touchpoints to remove friction, provide education, and help them get value before they churn. It might not be so hard convincing executive leadership of the benefits of sales-assist in this case. But, if they say yes without the full context, you might run into problems later on if you find yourself without the level of access you need to usage data, or the technical resources to build scoring models, and so on. My advice is to be upfront on the current gaps you need to fill to launch PLS. If you run into some pushback (which is very likely, especially if you need new tooling, or new hires) then, create a PLS 0.5 plan. Lack of organization readiness is a major pitfall for many PLG orgs who are excited about PLS, but don’t have the infrastructure required to run it at scale. If you’re in this boat, part of your buy-in strategy should be to work within your current resources, DIY some PLS experiments, report on impact, and then advocate for what you need to scale. Building up excitement I find that this step is often a missed opportunity. You need executive approval, but you also need cross-functional buy-in. A few concerns we often see come up across GTM are: - Potential cannibalization with self-serve pipeline - Adding unnecessary friction to the customer journey - Lack of clarity around data needs This is where you need to start thinking about aligning incentives to impacted teams and addressing these objections. By giving your team visibility into workflow changes, setting thresholds for sales and self-serve, and making clear that the overarching goal is always to improve the customer experience, you can ensure that RevOps, sales, and data teams are ready to make PLS work — because they believe in it. Get the template Build your proposal in one page — use the prompts to guide you! Step 2: Analyze usage, align on signals, and create PQA/PQL definitions I won’t spend too much time on this step, but you can read all about PQA and PQL scores in this guide. The bottom line is that by analyzing historical usage data, you can look for patterns that indicate your best-fit customers' actions and the "aha moments" that lead them to unlock value. These signals, or combination of signals, will help you craft scoring models to surface the best opportunities from your existing pipeline of users. (Or use a tool like Pocus to speed things up :) ) Step 3: Choose your playbook experiments Once you know what you’re looking for, it’s time to create a workflow to act on these opportunities. These workflows are your playbooks — specific motions, triggered by data, that support the strategic goal. Playbooks surface leads for your reps to action (or for automated sequences). Start with your goal and a few hypotheses of the signals that make up the ideal PQA/PQL for your playbook. Map out your playbook experiments like this: - Goal: i.e. upsell, free-to-paid-conversion, churn prevention, etc - Target: who is eligible for this motion? - Outcome: what is the outcome the playbook is driving toward? - Triggers: what criteria qualify a lead to be surfaced to a rep? - Action: what rep or automated actions should be taken? Step 4: Training and enablement We’ve found that PLS motion launches go much smoother if there’s clear ownership of the project, typically by a RevOps or Sales Leader; and if there’s a smaller roll-out with a tiger team before team-wide adoption. PLS is a new way of selling that requires analytical skills, product knowledge, and a data-driven mindset. Set up your team for success with meaningful data and documentation into why certain actions are considered signals. Ask for input on PQL/PQA definitions and encourage them to help, not sell. A PLS motion is, above all else, another layer to provide customers with value. We recommend enlisting a tiger team to fine-tune and iterate on your playbooks. These initial stakeholders will be able to learn the ropes, help coach the rest of your team when you’re ready for a full roll-out, and make optimizations to your initial playbooks so you can hit the ground running. Crawl, walk, run framework to launch PLS RevOps works with the data team to pull product usage data. RevOps and GTM work together to identify key product usage signals and customer fit signals and use that criteria to create spreadsheets for sales. Reps use spreadsheets or static data pushed to their CRM to inform prioritization. RevOps works with the data team to push product usage data into a BI dashboard (or a tool like Pocus!) that is available to reps. Reps can use the dashboard to research and do account planning, without engineering help. RevOps and leadership are experimenting, running, and optimizing Product-Led Sales playbooks that are driven by product usage, customer fit, and intent data. Reps have a single source of truth for customer insights and can get proactively alerted on their top priorities. The GTM team is using a Revenue Data Platform as a central hub to orchestrate go-to-market strategy. Step 5: Measure success, iterate, launch at scale To measure PLS success and find areas for optimization, you need to look at metrics from two levels: - Overall sales metrics to help you understand the broader impact of PLS playbooks. - Playbook level conversions to give you insight into which playbooks to iterate. The most helpful metrics are usually: playbook conversions, opportunities created, deal cycle velocity, and revenue attribution. Launching PLS is hard work, but it’s definitely worth it. By giving your customers more options, generating qualified pipeline from your existing user-base, and having greater insights into how individual usage relates to team and account expansion, you’ll be well on your way to the next stage of revenue growth. Launch PLS with Pocus Building sophisticated scoring models, optimizing playbook performance, and running increasingly targeted playbooks gets easier when you can invest in the right tooling to support it.
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Enterprise IT interest in AIOps tools has grown in 2019, as reflected in the latest features in DevOps monitoring tools, but advanced IT automation still hasn't caught on beyond the bleeding edge. Two AIOps vendors have reported sales strong enough to propel them to IPOs this month: first, Dynatrace re-entered the New York Stock Exchange Sept. 10 after five years of ownership by a private equity firm. DevOps monitoring competitor Datadog is expected to launch an IPO this week. A third cloud-native monitoring company, New Relic, already publicly traded, reported faltering sales numbers earlier this year and underwent C-suite upheaval as a result, but plowed ahead with fresh features for the New Relic One suite at its user conference this week. IT industry analysts speculate that the New Relic One development process, which first began in late 2017 and integrated IP from multiple acquisitions, may have caused the business setback for the company. It remains to be seen whether those effort will pay off in an expanded customer base for New Relic. New Relic One refreshes perspectives on IT monitoring data For existing New Relic users, New Relic One contains important improvements that will address their needs in the future. Most importantly, New Relic One unified dashboard views that had previously been fragmented, and added the ability to search across multiple domains, whether user accounts or public clouds. "New Relic One gave us a nice common interface, where we used to only be able to search data within user sub-accounts," said Joshua Biggley, senior enterprise monitoring engineer at Cardinal Health, a healthcare services and products company based in Dublin, Ohio. Cardinal Health has used New Relic since 2016, and rolled out New Relic One in production when it became generally available. This week, New Relic added several feature updates, including support for third-party data sources, agentless as well as agent-based monitoring deployments, log monitoring, tools to build programmable monitoring apps on the platform and new AIOps capabilities. For Cardinal Health, log monitoring data and information from third-party sources such as time-series databases and open source distributed tracing tools will add more dimensions of context to the centralized DevOps monitoring interface, Biggley said. He and his colleagues plan to use the programmability features to build new monitoring databases and assess a broader range of relationships between pieces of monitoring data. "You can say, 'these servers have eight CPUs each, and your workload average is 10, but you don't know what that means if you don't know how many CPUs are actually configured," Biggley said. AIOps will mature alongside DevOps New Relic has offered data analytics that it called Applied Intelligence in its products before, but this week's New Relic One updates adds AIOps features such as expanded alert reduction and automated creation of notifications and workflows in third-party tools such as PagerDuty, ServiceNow and Slack. This type of AI-driven IT automation has been a hot topic in IT ops circles since 2017, but it has taken until this year for AIOps products to fully mature, and will still take more time before IT shops are ready to put them to widespread use. "Event correlation and alert reduction are the unicorn everyone's chasing," Biggley said. "But people tend to be afraid of automation, and it all depends on data -- garbage in, garbage out." Biggley said he wants clarify the specific goals he wants to achieve with AIOps automation before he dives in. "You can apply machine learning to anything, but should you?" he said. Joshua BiggleySenior enterprise monitoring engineer, Cardinal Health Industry-wide, enterprises are adopting tools with AI built in: a Q2 2019 Forrester Research survey found that 51% of global infrastructure decision makers have already adopted, or are in the process of implementing, AI- and machine learning-enabled systems, with another 21% stating that they plan to adopt those technologies in the next year. However, the percentage of companies that have achieved AIOps automation in production using such tools is unclear at this point. AIOps early adopters have gained advantages from alert reduction through such tools, but not without having to work through data quality issues, and some remain skeptical of their ability to deliver incident auto-remediation. The DevOps monitoring maturation process among enterprises actually tends to make things worse before they get better, said Nancy Gohring, analyst at 451 Research. "As companies reorganize into DevOps teams that both develop and operate microservices, performance actually gets worse for a while, because there are too many tools and unclear responsibilities," Gohring said. "Eventually, organizations form a more centralized observability team, reduce the number of tools they use, and application performance improves." Only once organizations get past the initial chaotic stage of DevOps adoption can they proceed to AIOps automation that reduces the manual intervention DevOps monitoring tools require, Gohring said. Such tools also provide the most value for complex cloud-native architectures, such as container-based microservices, and most enterprises haven't yet widely adopted such infrastructures in production. Dynatrace predicts future of NoOps Not everyone shares Gohring's outlook on the pace of AIOps adoption. Dynatrace, for example, resumed its status as a publicly traded company with a focus on advanced IT automation, and the prediction that many of its customers will soon get to NoOps, where systems resolve IT incidents with no human intervention. "When customers see what we've achieved with Dynatrace and NoOps, they see that it's possible," said Dynatrace co-founder and CTO Bernd Greifeneder. "We've heard a lot about NoOps being a dumb idea that will never work, but I can invite you to our own labs to see it." Gohring is skeptical that NoOps will ever become mainstream in enterprises. "Some future phase will look a lot closer to NoOps," she said. "But that's far down the road, hazy and ill-defined. We're taking steps toward it, but it's unclear if it's achievable."
Artificial General Intelligence Sentinel Initiative (AGISI): dedicated to understanding intelligence in order to build beneficial AI and risk/benefit analysis tools to monitor the social and economic consequences of AI. Help to better understand intelligence Understanding intelligence is one of the major scientific challenges of our time; however, the science of intelligence is very much in its infancy. We worked closely with scientists and leading thinkers from different disciplines in order better understand intelligence. If human beings have a better understanding of intelligence, it will not only help to build artificial intelligent machines, but it will also help to improve individuals' situational awareness, decision making, and values, and ultimately greatly improve people's knowledge of each other and our world, and thereby improve the quality of life for society overall.
Learning goals for the day are; What is AI and AI Lifecycle, What is AI Governance, and why is it important, AI Governance framework and implementing AI Governance AI solutions are increasingly being developed and taken into use. At the same time the pressure and demand for ensuring creation and use of AI solutions transparently, secured and in sustainable manner is increasing. In this training we will explore AI Governance via AI lifecycle management. We will provide frameworks and means for participants to kick off or continue AI governance in transparent, secure and sustainable manner in their organisation. Azure Purview Studio enables unified Data Governance, that can form the base for data in AI Governance. Azure DevOps provides the platform for AI solution creation and Azure Machine Learning Service model reporting capabilities. Microsoft PowerBI and Microsoft PwerApp can then be used for use phase governance reporting and control. This workshop contains six sections during a one day at site or online session. Learning goals for the day are; What is AI and AI Lifecycle, What is AI Governance, and why is it important, AI Governance framework and implementing AI Governance, Responsibility matrix as a tool to implement AI Governance, Models and Tools to support AI governance, AI governance maturity assessment.
Microsoft Loop, the online collaborative platform in Microsoft 365, is getting a number of new features and an overall redesign. A new immersive learning center at the University of Nevada, Las Vegas is tapping into the power of virtual reality to support STEM engagement and student success. The institution has partnered with Dreamscape Learn on the initiative, which will incorporate the company's interactive VR platform into introductory STEM courses. Learning platform Coursera is expanding its Generative AI Academy training portfolio with an offering for teams, as well as adding new generative AI courses, specializations, and certificates. Online students are likely to have certain gaps in their education. Here are five skills they’ll need to fill them. Learning platform D2L is launching a new AI-powered product, D2L Lumi, designed to help educators create course content, assignments, quizzes, and more. Generative learning platform CYPHER Learning has introduced AI Crosscheck, an AI-powered accuracy checker that reviews the quality of AI-generated LMS content. The global pandemic thrust online teaching to the forefront. Online enrollments rose while campus enrollments declined. Is face-to-face teaching doomed? Will virtual campuses be the norm? Is there no middle ground? Addressing the challenges of new learning spaces requires a new strategic approach to innovative planning, stakeholder engagement, continuous professional development, and a commitment to ongoing evaluation and adjustment. After five years of planning, St. Petersburg College (SPC) in Florida has opened its new Chris Sprowls Workforce Innovation Hub on the Tarpon Springs campus and is welcoming visitors. The 10,000-square-foot facility was dedicated in February 2024, and is devoted to manufacturing, creativity, and collaboration among students, educators, and business leaders. Since its launch in April 2023, Turnitin's AI writing detection tool has reviewed over 200 million papers, with data showing that more than half of students continue to use AI to write their papers.
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Fast data for all your apps Share your stories in seconds Connect and discover content instantly Enjoy and create content without delay Video calls without disruptions Continuous playback without pauses eSIM with unlimited data in New York Stay connected in New York and across the entire United States with unlimited 4G/5G data. Enjoy reliable coverage and, best of all, without worrying about data usage. - Speed: 3G/4G/LTE/5G - Hotspot: Yes - Calls/SMS: No - APN: globaldata - Installation: Install your eSIM one day before your trip. If you're already at your destination, the data will activate immediately. - Activation: Upon arrival at your destination, your data plan will activate automatically. Make sure to enable Data Roaming. - Delivery and time: By email, immediately after purchase. - Compatibility: Compatible with all smartphones with eSIM technology. Use on smartwatches and tablets is not guaranteed. - Coverage: Enjoy excellent coverage and speed in New York's main tourist spots. In some urban or underground areas, coverage may be limited or unstable. - Multiple devices: No, the eSIM can only be installed on one device. - Networks: AT&T/T-Mobile - Replacement policy: eSIM replacement fee of $5. - Bandwidth abuse: Read more - Speed reduction: You will get 2 GB of high-speed data daily, and then unlimited data at 1Mbps. The high-speed data allocation will be reset every 24 hours. Why choose Free Roaming eSIM for New York Transform your entire travel experience with our unlimited data eSIM, ensuring seamless, worry-free, and limitless browsing. Faster data speeds Access lightning-fast local data on your travels. Choose the plan that fits your itinerary and stay connected wherever you are. 24/7 support, day and night To ensure your eSIM experience is completely hassle-free, our dedicated team will be by your side before, during, and after your trip. Get your eSIM instantly In a hurry or already on the go? No problem. Make your purchase and receive your eSIM directly in your email in the blink of an eye. Quick and easy setup Access the internet effortlessly: a quick scan of a QR code, and you’re instantly connected. Designed for a hassle-free experience. WiFi Hotspot included Easily share internet with all your devices, no matter where you are. It's included for free with most of our travel eSIM plans. Get connected in New York in just 5 minutes Make sure your device is unlocked and eSIM compatible. Check it now Order your prepaid eSIM Getting your eSIM is easier than you think. In just two steps, you’ll complete your purchase. Install and activate your eSIM Just scan the QR code from your mobile, activate the eSIM, and start browsing instantly. Be aware of the following Does not include a phone number This eSIM only includes mobile data, it does not include traditional calls and SMS. You can use WhatsApp and other VOIP apps. Install your eSIM before you travel Install your eSIM by scanning the QR code a few hours before your trip. If possible, install the eSIM while connected to a WiFi network. Activate your eSIM when you land Upon landing at your destination, set your eSIM as the default line for mobile data usage and immediately enable data roaming. You will receive the eSIM in your email After your purchase, you will receive instructions to install and activate your eSIM. QR code installation instructions Manual installation instructions We’re a top choice for many They choose us for the peace of mind that comes with knowing they’re in good hands. I loved the service! I spent two weeks in Bogotá, and the unlimited plan worked perfectly for us. Plus, it was super easy to activate—right after landing, I was already connected. I would 100% use it again. Everything worked perfectly. I loved the service, and I've bought more than 4 SIMs for different countries, and they all worked flawlessly. I bought an eSIM for Asia, and the experience was excellent. I never lost signal and had unlimited data. Great pre- and post-sale service. I will definitely use them again! I recently returned from my trip to Colombia, Argentina, and Chile. I bought an eSIM and had coverage in all three countries with just one. Excellent service, I didn’t encounter any issues. You've gained a loyal customer! I was on vacation in Thailand and purchased an eSIM with unlimited data. Throughout my trip, the coverage and service were excellent. I had a small issue with a setting, but they promptly provided friendly assistance. I’ll definitely use them again. Frequently Asked Questions about the eSIM for New York We’ve put together this list to provide you with the answers you need. Your plan's days start counting when you enable data roaming on your phone. Therefore, the duration of your plan begins when you activate the eSIM, not when you install it. Check if your phone is unlocked by inserting a SIM card from a different carrier. If your phone gets a signal, then it's unlocked. On iPhone, you can confirm by following these steps: Go to Settings → General → About → Scroll down to "Carrier Lock" → It should say "No SIM restrictions." On Android, you can confirm by following these steps: Go to Settings → Connections → Mobile Networks → Network Operators → Turn off "Select automatically" and wait a few seconds → If multiple carriers appear, your phone is unlocked. If only your carrier shows, it’s locked. Once you purchase your eSIM, you'll receive a confirmation email with the QR code immediately. In most cases, your Free Roaming eSIM provides coverage at maximum speed (4G/5G), just like any local data line. However, keep in mind that in areas with limited coverage, your phone may connect at lower speeds. Absolutely! If you're wondering which eSIM is the best, we'd confidently say it's ours. Why? Because we offer unlimited data, 24/7 support with near-instant responses, and many more benefits. Once the contracted data plan expires, the eSIM will stop working, and your internet connection will be suspended. Your WhatsApp account will remain unchanged, keeping your original number. There's no need to configure anything. As long as you don’t activate a new account, you will keep your existing one along with your number. Yes, you can. Just contact us at firstname.lastname@example.org or through our online chat at freeroaming.io, and one of our agents will assist you. You can check the data you've used through the "Data Usage in Roaming" feature on your device or from the device's usage statistics. You can also contact our support team to provide you with this information. If you're using an Apple device, you can use both your physical SIM and eSIM simultaneously. Select the physical SIM for calls and SMS, and the Free Roaming eSIM for mobile data. Please note that if your physical SIM remains active, your carrier may charge roaming fees for receiving or making calls and sending SMS. When you enable roaming on your Free Roaming eSIM, the data is activated instantly, starting your data plan right away. Yes, you must enable the "Data Roaming" option. Keep in mind that using this option will not incur any additional charges or surprise bills, as long as you have your Free Roaming eSIM set up for mobile data. If you can't find your QR code, please contact our team at email@example.com or through our online chat at freeroaming.io, and one of our agents will resend it to you via email. If you change phones during your trip, you can transfer your eSIM. However, keep in mind that you can only transfer the eSIM to two devices: the original one and a new one. Once you've installed it on a different device from the original, you won't be able to reinstall it on the original device. To transfer the eSIM, you must delete it from the first device. We recommend installing your data plan a few hours before your trip. You can print your QR code or keep it on another device as a precaution. To install your eSIM, you’ll need an internet connection. The setup is quick, and you’ll have your data plan ready immediately. Just remember not to activate it until you arrive at your destination. Free Roaming eSIMs only include data in the destination country and do not allow local or international calls, except through VOIP apps like WhatsApp or Skype, which use your data plan. Free Roaming eSIMs are for data use only, so please set your eSIM as the data plan on your device. Yes, but keep in mind that it's not necessary. As soon as your plan expires, your Free Roaming eSIM will stop working. Free Roaming eSIMs are for data use only, so please make sure to set your eSIM as the data plan on your device. At Free Roaming, we understand that unexpected situations may arise after making a purchase. Therefore, you can request a refund in the following situations: – You purchased the eSIM without checking your phone's compatibility. – You canceled your trip or no longer need the eSIM. – Our eSIMs typically work flawlessly, but if you experience connectivity issues, we can offer a full or partial refund. Once the refund is approved, the money will be sent to the same account used for payment. This process may take 5 to 10 business days. For more details and to review the terms, please read our Refund Policy. Some of our eSIMs have this feature enabled. Before making a purchase, please read the description in the Technical Specs tab of the eSIM you plan to buy and check if it allows data sharing. In rare cases, yes. Operators have an international measure called Fair Usage Policy. This policy is applied for a period of no more than one (1) day to manage data usage and ensure all users enjoy optimal connection quality. This is beyond Free Roaming's control, but don't worry! If the policy is applied to you, the restriction will be lifted the next day, and you'll regain your plan's original speed. Your eSIM will connect to all local operators that Free Roaming has agreements with. You can check them in the Technical Specs tab. An eSIM (embedded SIM) is a digital SIM card that can be installed directly on your smartphone or other mobile devices. It’s an alternative to the physical, removable SIM card you're familiar with.
In the fast-paced digital era, AI chatbots are no longer a futuristic concept—they are the present and thriving core of customer service strategies across industries. In Philadelphia, a city renowned for its rich history and booming tech scene, AI-driven customer support solutions are revolutionizing how businesses engage with customers. From 24/7 availability to real-time query resolution, AI chatbots have become indispensable tools for delivering seamless and personalized service. AI Chatbots: The New Standard in Customer Interaction AI chatbots are intelligent programs capable of conducting conversations using natural language. Leveraging technologies such as machine learning (ML), natural language processing (NLP), and sentiment analysis, these bots can understand customer intent, offer solutions, and escalate issues to human agents when necessary. In Philadelphia, small businesses, startups, and established enterprises alike are integrating AI chatbots to: Reduce response time Increase customer satisfaction Lower operational costs Enhance lead generation The rise of AI chatbots in this region is not merely a trend—it’s a strategic shift aimed at building long-lasting customer relationships. 24/7 Customer Support with No Downtime One of the most significant benefits of AI chatbots is their ability to provide round-the-clock customer support. In a city like Philadelphia, where businesses cater to both local and international clients, time zone differences can impact service delivery. AI chatbots ensure that every customer receives immediate attention regardless of the hour. Use Case: A retail e-commerce company based in Center City implemented an AI chatbot on its website and witnessed a 38% reduction in customer churn due to faster query resolution and 24/7 availability. Enhanced Personalization Through Data-Driven Responses Philadelphia-based companies are increasingly turning to AI chatbots for personalized experiences. By accessing historical data, purchase behavior, and browsing patterns, these bots can tailor responses to suit individual customer needs. This creates a feeling of being understood, which fosters loyalty. Example: A local fintech startup integrated a chatbot that addressed customers by name, offered investment advice based on previous interactions, and sent reminders for account activities—leading to a 45% increase in customer engagement. Cost-Efficiency and ROI Maximization For businesses in Philadelphia aiming to scale without escalating customer service costs, AI chatbots offer a high return on investment. Unlike human agents, chatbots don’t require training breaks, salaries, or sick days. They can handle thousands of queries simultaneously, drastically reducing customer wait times. Businesses save up to 30% on customer support costs by implementing chatbots. Chatbots can handle up to 80% of routine tasks, allowing human agents to focus on complex issues. Multilingual Support for a Diverse City Philadelphia is home to a diverse population speaking languages like Spanish, Mandarin, and Vietnamese. AI chatbots equipped with multilingual capabilities ensure that language is no longer a barrier to customer service. This inclusivity increases market reach and resonates with a broader audience, demonstrating a commitment to understanding and serving all communities. Integration with Popular Platforms Chatbots can seamlessly integrate with various platforms used by businesses in Philadelphia, including: Live Chat Plugins CRM Systems like Salesforce and HubSpot This ensures consistent customer interaction across all channels, preserving the context of conversations and improving the overall customer journey. Accelerating Lead Generation and Conversion AI chatbots are not just customer support tools—they’re also lead generation engines. By qualifying leads, booking appointments, and answering FAQs instantly, chatbots guide users down the sales funnel without the need for human intervention. Philadelphia real estate agencies, for example, use chatbots to schedule property tours, answer location-specific questions, and provide neighborhood insights—leading to faster deal closures. Boosting Customer Satisfaction Scores (CSAT) The CSAT scores of companies using AI chatbots in Philadelphia have shown a marked improvement. With reduced wait times, faster resolutions, and friendly conversational tones, customers feel valued and heard. Feedback from Users: “I love how quick the response is.” “It understood my issue better than some agents.” “Got my problem solved in minutes.” Security and Compliance in Sensitive Sectors In sectors like healthcare, finance, and legal services, which are prominent in Philadelphia, data security and compliance with regulations like HIPAA and GDPR are critical. Modern AI chatbots are built with end-to-end encryption and privacy-by-design frameworks to handle sensitive customer data securely. Scalable Solutions for Startups and Enterprises Whether it’s a small tech startup in University City or a large corporation in the Philadelphia Navy Yard, AI chatbot solutions are highly scalable. They adapt to the volume of interactions and complexity of queries, making them suitable for businesses of all sizes. Chatbot usage among Philadelphia startups has grown by 120% in the last 3 years. Over 60% of enterprises in the region plan to increase chatbot investment in 2025. The Role of AI Chatbots in Omnichannel Customer Experiences To stay competitive, Philadelphia businesses are shifting to omnichannel customer support models, and AI chatbots are at the center of this transformation. Customers now expect a seamless experience across web, mobile, email, and social platforms. Chatbots unify these touchpoints, maintaining contextual continuity in every conversation. Why Philadelphia Is Leading in AI Customer Service Adoption Philadelphia’s unique combination of tech innovation, academic excellence, and business diversity makes it an ideal ground for AI chatbot deployment. Institutions like Drexel University and University of Pennsylvania are producing AI experts, while incubators are funding chatbot startups, accelerating adoption across industries. ToXSL Technologies: Powering the AI Chatbot Revolution in Philadelphia ToXSL Technologies stands at the forefront of this AI evolution, delivering custom chatbot development services tailored to Philadelphia’s dynamic market. Their expertise in AI, machine learning, and full-stack development empowers businesses to automate, scale, and enhance their customer service functions efficiently. Businesses in Philadelphia trust ToXSL Technologies for: End-to-end chatbot development Seamless CRM and third-party integrations Ongoing support and optimization Multilingual and industry-specific chatbot solutions If you’re a business owner in Philadelphia looking to elevate your customer service with AI chatbots, ToXSL Technologies is your strategic partner in this journey.
5 essential tips to safeguard your customer data In today’s tech-driven world, customers don’t just appreciate personalised experiences - they expect them. As businesses ramp up data collection to better understand what makes their target audience ‘tick’, safeguarding personal information becomes crucial - especially as shoppers become more cautious about what they share online. By focusing on secure, streamlined data collection, your business can not only mitigate the risk of breaches but also build the trust that sets you apart from the competition. Here’s how… 1. Read up on regulations There’s no ‘one-size-fits-all’ when it comes to data collection. Different regions have distinct regulations, so it’s vital to align your strategy with where your shoppers are situated. For example, if your consumer base spans both the United States and Europe, you’ll need to comply with U.S. regulations as well as the General Data Protection Regulation (GDPR). Certain industries like law or healthcare may also require a more stringent approach, so staying informed about these laws, and how they apply to your business, will help you build a robust foundation for data protection. 2. Train your team Human error is one of the leading causes of data breaches. Simple, seemingly minor mistakes - like mishandling passwords or falling for phishing scams - can lead to major, often irreversible problems that are hard to bounce back from. Providing regular security training for all staff - both old and new - will equip your team to spot red flags and follow best practices for data protection, significantly reducing the risk of costly errors. 3. Only collect what you need While gathering customer data is key to crafting personalised experiences, over-collecting can significantly raise your risk of exposure. Ultimately, the more data you store, the more appealing your business becomes to cyber criminals, so taking a minimalistic approach and conducting regular audits of the customer information you store isn't just a smart strategy - it's also a legal obligation. Streamlining and optimising these practices wherever possible will help protect your business while still delivering the tailored experience the modern shopper expects. 4. Embrace encryption Encryption is a powerful tool in protecting your business against data breaches. By encoding your customers’ sensitive data, you’ll ensure that, even in the rare instance that unauthorised individuals manage to gain access, the information - whether that be personal identifiers or financial details - remains unreadable without the proper decryption key. 5. Make data handling safer with security software As hackers grow more sophisticated in their techniques, it’s more important than ever to stay updated with the latest security technologies to safeguard your customer data. How InAcademia can help Real-time student verification platforms like InAcademia revolve around data minimisation, which not only speeds up the click-to-cart process for your customers, but also ensures their personal information remains secure while applying discounts. Discover how we can help your business deliver a personalised and secure experience for your online shoppers here.
In recent years, data science has evolved as one of the most sought-after employment pathways. It is an interdisciplinary field that extracts knowledge and insights from organized and unstructured data using scientific methods, procedures, algorithms, and systems. Professionals in data science are in high demand, and this demand is only projected to grow in the future years. Studying Data Science necessitates a combination of technical and domain knowledge. This includes, among other things, an understanding of programming languages, statistical analysis, data visualization, machine learning, and artificial intelligence. It is also critical to learn how to work with big data, as well as data cleaning, pre-processing, and transformation tools. A good Data Science course should thoroughly address the technical components while also giving real-world case studies and projects to apply the concepts and approaches gained. This blog will go through the top 10 data science institutes in Chennai that offer the best data science courses. It should also assist students in developing critical thinking, problem-solving, and communication skills, all of which are required for success in the area. Learning Data Science can help you uncover a wide range of job prospects, whether you are a novice or an experienced professional looking to upskill. You can become a good Data Science practitioner and contribute to the field’s growth and development if you have the correct mindset, dedication, and commitment. LIVEWIRE is a division of CADD Centre Training Services, an accredited Skill Development Partner of the National Skill Development Corporation (NSDC), that promotes a unique blend of technologies relevant to the IT, Computer Science, Electronics, and Electrical departments. Livewire is one of the best data science institutes in Chennai that offers software courses including data science courses like data science with python and data science using R programming language. The LIVEWIRE Vadapalani & Porur Data Science training course in Chennai is a great solution if you’re looking for Data Science Training that keeps students up to date on the most recent data science trends while also offering practical skills. For individuals who are serious about a future in data science, our university offers the best data science training by teaching students data science from the ground up. Besant Technologies provides a variety of data science courses, including data analytics, machine learning, and artificial intelligence. Students receive personalized training from qualified trainers at the institute. If you are looking for a Data Science training institute in Chennai that keeps students up to date on the newest data science trends while also delivering practical skills, Besant Technologies is a fantastic alternative. Finally, Besant technologies is one of the best institute for data science in Chennai. I am currently doing my Data Science course in Besant Technologies. My trainer kamesh is clearly explained the concepts and teaching method is easily understandable. Surya sir is supporting in classroom environment. This institute is very helpful to improve our skills especially for learners and freshers. Thank you so much Besant Technologies. Intellipaat is a data science online learning platform that provides courses in data analytics, machine learning, and artificial intelligence. The institute offers interactive training via live online classes, recorded videos, and homework assignments. Intellipaat’s online Data Science course in Chennai, in collaboration with IITM Parvartak (IIT Madras’ Technology Innovation Center), is a top-rated online program that meets industry needs. As part of the Data Science certification course, you will work on numerous Data Scientist tasks and duties, such as data analysis, statistics, Git, data purification, Machine Learning, data mining, transformation, and visualization. Finally, Intellipaat is one of the best data science institutes in Chennai. I had enrolled for Data Science Course with Intellipaat and had great learning experience. The course curriculum is very well-designed, and it tries to cover all relevant topics. Live classes, hands-on exercises, video recordings, assignments, and projects are all available and help me to gain subject knowledge. FITA Academy is one of the top data science institutes in Chennai. Throughout the course, you will obtain a thorough understanding of data science through the use of numerous computer languages such as Python, R, SQL, and others. They offer the greatest curriculum, which has been specially developed by skilled trainers to meet the industry’s standards. As part of your Data Science Training in Chennai, you will also study machine learning and deep learning. Finally, Fita Academy is the best place to learn data science in Chennai. The course which I enrolled is Data Science using Python. It was a fantastic experience learning this course with a help of my Trainer Mr.Deepak. He explains all the concept to us with a real time example which helped me understand things better. FITA has amazing courses with best trainers. Excel R is regarded as one of the best Data Science training institutions in Chennai. They have helped thousands of Data Science experts advance their careers at major MNCs in India and throughout the world. “Training to Job Placement” is our specialty. They have skilled trainers who will assist you with upskilling concepts, completing assignments, and working on live projects. Excel R is one of the best data science institutes in Chennai providing the best data science courses in Chennai. DataMites is a top training provider, providing cost-effective, high-quality, and real-time training courses in the growing analytics industry. They provide courses in Data Science, Machine Learning, Data Mining, Tableau Associate, Text Mining, Python Programming, Deep Learning, and Minitab. The primary goal of DataMites is to train professionals who can bravely face the challenges of the competitive analytics field. Their training courses are preplanned and updated by specialists with extensive expertise and industrial background in order to provide applicants with more knowledge. One of the best place to learn data science in Chennai is Data Mites. Greens Technologies is also a top Data Science institute in Chennai. The courses at Greens Technologies are meant to master trainees in Data Science Methods and upgrade their skill set to the next level. Apart from delivering end-to-end corporate recruitment solutions, they have a long history of technology-based and code-based pre-employment testing. Their hands-on testing on role-based simulations reveals the genuine software skills matrix and eliminates the guesswork from the recruitment process. Green Technologies is one of the best data science institute in Chennai. IICT Chromepet is another well-known institution that provides Data Science courses. They have a flexible schedule and offer both classroom and online training. IICT Chromepet is a complete training academy with good placement support. Since 2003, IT training has been delivered by software specialists with extensive industry expertise. One of the best places to learn data science in Chennai is IICT Chromepet. Infycle technologies, which is regarded as the top Data Science institute in Chennai, is also offered through online platforms and coaching classes. Students can learn about algorithms such as random forests, decision trees, naive Bayes, and others through excellent teaching. All of this is possible with R and Python Training. Finally, Infycle Technologies is one of the best institutes for data science courses in Chennai. I would recommend this institute for those who really wants to switch over the job to IT professional. This place gives you an office environment feel which makes your presence on every single day if you really like/open to learn something from here. Faculties also very dedicative and doing their job perfectly. Good luck Infycle technologies to grow more. Its my pleasure to say that i had choosen a nice platform for entering IT job sector. Talented trainer with friendly nature person. Very good environment. Training classes are so much good.they provide us practical and experience knowledge. Apart from techinical they taught as how to survive in IT environment and handle real time projects .Infycle is the best place to upgrade our careers knowledge Last but not least, Imarticus Learning is a top data science institute in Chennai where you can learn real-world data science applications and construct analytical models that improve business outcomes. This job-guaranteed program is suitable for recent graduates and professionals looking to advance their careers in data science and analytics. Finally, Imarticus learning is one of the best institutes to learn data science courses in Chennai. Completed Data Analytics course at Imarticus recently. It is a great learning space with trainers who are currently working in the field with hands on experience through simple projects. Whether you want to up-skill or you've just finished a degree and don't have enough confidence in your coding skills this is a good place to start. They provide multiple job interviews on the placement drive. Post Graduate program in Data Analytics program will be very helpful for the students with computer science background to refresh the CS topics. It will be helpful for the students those who have missed placement drives in their colleges. To Sum Up These are the top 10 data science institutes in Chennai that provide high-quality data science training. Students and professionals can select the institute that best meets their requirements and career objectives. Keep in mind that this is not an exhaustive list, and there may be additional data science institutes in Chennai. Before selecting a training institute, it is generally a good idea to conduct research and read reviews.
- Easy Data Inspection: Quickly browse and inspect your CoreData data models with our intuitive interface. - Customizable Layout: Tailor the layout to your needs, with adjustable column widths, row heights, and more. - Relationship Visualization: Visualize complex relationships between entities with our interactive graph view. - Support for Multiple CoreData Versions: Compatible with CoreData versions from iOS 10 to the latest releases. - Powerful Search: Instantly find any record by searching its content, so you can quickly locate the data you need. - DB Live Editing: Ability to save update and changes - Data Track Changes. Track and trace changes in your SQLite database. This sounds cool, and it’s only $4.99, but I wasn’t able to get it to work for me. It seems to need an uncompiled model file, which I don’t have for any of the third-party apps whose data I want to inspect or for my own apps (since they build the models in code). SwiftData apps would have the same problem. I haven’t touched this project in a while, but if you have a compiled model and need an uncompiled one, maybe take a look at momdec, my old model decompiler. https://github.com/atomicbird/momdec I'm not sure you can inspect 3rd party DBs for security reasons. As I see CoreData Studio is made for developers who develop their apps and want to monitor and debug their local app databases @Alex I don’t see how security enters into it because the database is already fully accessible. CoreData Studio is just providing a nice interface.
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Privacy Commission cautions DOH on sharing of Dengvaxia master list The National Privacy Commission (NPC) has advised the Department of Health (DOH) to be circumspect in sharing sensitive personal information of individuals, saying it should only do so if it deems that such sharing or disclosure is authorized under law, adheres to data privacy principles, and there are reasonable and appropriate security measures in place to protect the data. In an advisory opinion dated 26 February 2018 issued in response to the formal request made by the DOH, Privacy Commissioner Raymund Enriquez Liboro said the disclosure to another government agency or private entity of a copy of the DOH master list of individuals vaccinated with Dengvaxia must be “provided for by existing laws and regulations or a data subject has given his or her consent.” “We emphasize that the government is one of the biggest repositories of the personal data of citizens. The government or its agencies, however, do not have the blanket authority to access or use the information about private individuals under the custody of another agency,” Liboro said. The DOH Dengvaxia master list has recently been subject of access requests coming from the Public Attorney’s Office (PAO), some private organizations, and members of the media. The information contained in the list is considered as sensitive personal information, and relates to minors, which the NPC identifies as a vulnerable group of data subjects. In the advisory opinion, Liboro said personal data provided to government or public authorities may be processed without consent when it is done pursuant to the particular agency’s constitutional or statutory mandate, and subject to the requirements of the Data Privacy Act of 2012 (DPA). In the case of the request by the PAO to obtain the DOH master list, this general rule does not apply. The agency, however, may be allowed access to the data of the specific victims it represents as their duly authorized legal counsel. “Should the PAO be authorized as the legal representative of the minor data subjects, they may then be provided information on the particular data subject they are representing, subject to the presentation of proof of such authorization,” Liboro said. As to the request of media and other private organizations, Liboro said the disclosure of statistical or aggregated data, without any personal or sensitive personal information, should suffice. Otherwise, the release of a copy of the master list in its raw version would be tantamount to an unwarranted invasion of personal privacy. # # #
“Moneyball” is a strategy that uses statistical analysis to identify undervalued talent and achieve competitive advantages in professional sports. It was popularized by the Oakland Athletics’ general manager Billy Beane, and it’s detailed in Michael Lewis’s 2003 book “Moneyball: The Art of Winning an Unfair Game”. The approach challenged traditional scouting methods that were typically based on intuition, subjective evaluations, and focus on visible skills. Although “Moneyball” initially became famous in baseball, its principles have been adapted to other sports. Here are a few examples: - Baseball (MLB): The sport where it all started. Advanced statistics such as on-base plus slugging (OPS), wins above replacement (WAR), fielding independent pitching (FIP), and others are used to evaluate players’ true values beyond traditional stats like batting averages or home runs. These metrics have become standard in player evaluation and are now used alongside traditional scouting. - Basketball (NBA): In basketball, statistics like player efficiency rating (PER), win shares, and true shooting percentage (TS%) offer more in-depth views of a player’s contribution to their team beyond points scored. Moreover, data analytics are used to evaluate the efficiency of different playing strategies, such as favoring three-point shots over two-point attempts. - Football (NFL and Soccer): In American football, teams utilize statistics like expected points added (EPA) and win probability added (WPA) to make strategic decisions on the field, such as when to go for it on fourth down. In soccer, analytics have moved beyond goals and assists to include metrics like expected goals (xG), expected assists (xA), and player influence maps. - Hockey (NHL): Advanced statistics like Corsi and Fenwick (which measure shot attempt differential while at even strength) are used to evaluate a team’s puck possession, which has been identified as a key performance indicator in hockey. The core principle behind “Moneyball” – the search for inefficiencies in player evaluation and team strategy – can be applied to virtually any sport. With the advent of more sophisticated tracking technology and data analytics, we can expect these strategies to continue to evolve and further revolutionize sports management and coaching strategies. Let’s look a bit deeper. The Concept of Moneyball Moneyball is a term popularized by Michael Lewis’ 2003 book “Moneyball: The Art of Winning an Unfair Game.” The book narrates the story of the Oakland Athletics baseball team and its General Manager, Billy Beane, who employed a novel, data-driven approach to build a competitive team despite financial limitations. By focusing on overlooked but statistically significant performance metrics, Beane was able to assemble a highly competitive team on a limited budget, challenging conventional wisdom in the process. The Methodologies of Moneyball The core of the Moneyball strategy lies in the innovative use of advanced analytics and statistical data. The traditional method of player evaluation, which relies heavily on subjective judgments and instinct, is replaced by a rigorous, data-driven analysis of player performance. Key metrics that are often ignored, such as On-Base Percentage (OBP) in baseball, become the focal point of this strategy. This approach seeks to find undervalued players who contribute significantly to the team’s performance but are often overlooked by traditional scouting methods. Moneyball in Baseball Moneyball was born in baseball, and the sport remains its most prominent application. The Oakland Athletics under Billy Beane popularized the strategy, but now many other Major League Baseball (MLB) teams have followed suit. Teams like the Tampa Bay Rays, with relatively small budgets, have successfully applied Moneyball strategies to compete with their higher-spending rivals. The use of sabermetrics, the empirical analysis of baseball, has become widespread, helping teams identify undervalued players and make strategic decisions. How “Moneyball” Changed Baseball FOREVER Moneyball in NBA Basketball The use of Moneyball strategies has extended beyond baseball to other sports, including basketball. The Houston Rockets, under the former management of Daryl Morey, have been one of the most notable adopters of this approach in the NBA. Morey, a computer science graduate with no traditional basketball background, focused on analytics to evaluate player performance. He popularized the use of metrics like Player Efficiency Rating (PER) and emphasized the importance of three-point shooting over less efficient mid-range shots. Moneyball in the NFL Moneyball principles have started to gain traction in the NFL, with teams increasingly utilizing data analysis to evaluate player performance, make draft decisions, and optimize game strategies. By focusing on advanced metrics such as efficiency ratings, yards after contact, and completion percentages under pressure, teams aim to uncover undervalued players and make more informed decisions. While the NFL presents unique challenges due to its complex team dynamics and reliance on subjective evaluations, the implementation of Moneyball strategies has the potential to enhance team performance, maximize resources, and gain a competitive advantage in the league. Moneyball in the NHL Moneyball concepts have also made their way into the NHL, where teams are leveraging advanced analytics to assess player performance and make strategic decisions. Metrics like Corsi rating, expected goals (xG), and zone entry statistics help teams identify undervalued players and make data-informed decisions regarding line combinations, player acquisitions, and game strategies. While the NHL’s fast-paced and dynamic nature presents challenges in implementing Moneyball strategies, the adoption of statistical analysis provides teams with a competitive edge in evaluating player contributions, optimizing team performance, and maximizing the efficient allocation of resources. Moneyball in Football (Soccer) Moneyball has also found its way into football (soccer), although its adoption has been slower due to the fluid and less statistically driven nature of the game. Nonetheless, clubs like FC Midtjylland in Denmark and Brentford FC in England have successfully employed data analytics to their advantage. These clubs focus on statistical models to analyze player performance, making data-driven transfer decisions and optimizing player development. The Impacts of Moneyball The impact of Moneyball strategies on professional sports has been profound. Teams with limited financial resources can compete with wealthier counterparts by making smart, data-driven decisions. It’s not only revolutionizing player recruitment but also influencing in-game strategies, such as lineup selection and tactical decisions. Furthermore, it’s leading to an increased demand for data scientists and analysts in sports organizations. The Future of Moneyball The future of Moneyball looks bright with the continuous advancements in data analytics and machine learning technologies. These advancements will allow teams to mine deeper into data and gain insights that were previously unimaginable. Additionally, player tracking technologies are providing real-time data about player movement and effort, which could open up new frontiers in sports analytics. FAQs – Moneyball Strategies in Professional Sports 1. What is Moneyball? Moneyball is a data-driven strategy used in professional sports to evaluate players and make team decisions based on statistical analysis rather than traditional scouting methods. It was popularized by the Oakland Athletics baseball team in the early 2000s and has since been adopted by various sports organizations worldwide. 2. How does Moneyball differ from traditional scouting methods? Traditional scouting methods rely on subjective evaluations made by scouts based on personal observations and expertise. Moneyball, on the other hand, focuses on objective statistical analysis to identify undervalued players and uncover valuable insights that may not be apparent through traditional means. 3. What is the main objective of Moneyball strategies? The main objective of Moneyball strategies is to gain a competitive advantage by identifying undervalued players who possess skills and abilities that may be overlooked by conventional wisdom or scouting methods. By efficiently allocating resources and acquiring players with high potential, teams aim to maximize their performance and achieve success within budget constraints. 4. Which sports have successfully implemented Moneyball strategies? Moneyball principles have been implemented in various professional sports, including baseball, basketball, soccer, and hockey. The strategy’s success has been demonstrated by teams such as the Oakland Athletics (baseball), Houston Rockets (basketball), and Leicester City (soccer), who have achieved notable accomplishments with limited financial resources. 5. What statistical metrics are commonly used in Moneyball analysis? Several statistical metrics are commonly used in Moneyball analysis to assess player performance and value. Some of the frequently employed metrics include on-base percentage (OBP), slugging percentage (SLG), wins above replacement (WAR), player efficiency rating (PER), expected goals (xG), and Corsi rating (hockey). These metrics provide insights into a player’s offensive and defensive contributions, efficiency, and overall impact on the game. 6. How does Moneyball impact team management and decision-making? Moneyball strategies influence team management and decision-making by shifting the focus from intuition-based decisions to evidence-based analysis. Front office personnel, coaches, and scouts utilize data analysis to identify players who may be undervalued, make informed trade and draft decisions, optimize lineups or formations, and develop effective game strategies. This approach enhances efficiency, reduces biases, and facilitates a more objective decision-making process. 7. Are there any challenges in implementing Moneyball strategies? Implementing Moneyball strategies can present challenges, particularly in sports where traditional scouting and subjective evaluations have deep-rooted traditions. Resistance to change, skepticism towards statistical analysis, and the availability and quality of data can pose obstacles. Additionally, finding a balance between statistical analysis and the human element of the game, such as team chemistry and intangible qualities, is another challenge that teams must navigate. 8. Can Moneyball strategies be successful for all sports teams? While Moneyball strategies have shown potential for success, the applicability and effectiveness can vary depending on the sport and the specific context of the team. Factors such as league structure, team budget, player market, and competition level can influence the extent to which Moneyball strategies can be implemented and yield positive results. Each team must assess its unique circumstances to determine the suitability and potential benefits of adopting Moneyball principles. 9. Does Moneyball only focus on player evaluation? While player evaluation is a significant aspect of Moneyball, the strategy can extend beyond individual player analysis. It can also encompass broader team management, such as optimizing salary allocations, identifying market inefficiencies, analyzing in-game strategies, and understanding the impact of various factors on team performance. Moneyball’s principles can be applied to different facets of a team’s operations to gain a comprehensive competitive advantage. 10. How has Moneyball influenced the sports industry as a whole? Moneyball has had a profound impact on the sports industry by revolutionizing the way teams evaluate players, make decisions, and allocate resources. It has popularized the use of data analytics and ushered in an era of evidence-based decision-making. The success stories of teams employing Moneyball strategies have inspired other organizations to embrace data-driven approaches and explore new avenues for gaining a competitive edge in the highly competitive sports landscape.
I had the chance to interview Daniel Barber, CEO and Co-founder of DataGrail. DataGrail is a purpose-built privacy management platform that ensures sustained compliance with the GDPR, CCPA, and forthcoming regulations. Their customers span a variety of industries and include Databricks, Plexus Worldwide, TRI Pointe Homes, Outreach, Intercom, and SaaStr. Daniel and I spoke about the lessons […] It is sad to say goodbye to ConcurringOpinions.com, a law professor blog I co-founded in 2005. The blog began when a group of us (Dave Hoffman, Kaimi Wenger, Nate Oman, and me) who were blogging at PrawfsBlawg decided we wanted more autonomy in blog governance, so we founded Concurring Opinions. Over the years, we added […] On December 4, 2018, New York Attorney General Barbara D. Underwood announced a $4.95 million settlement with Oath, Inc. (formerly known as AOL), for violating the Children’s Online Privacy Protection Act (COPPA). This is the largest penalty in a COPPA enforcement case in U.S. history. The EDPB (European Data Protection Board) was created by the EU Data Protection Directive in 1996. Its purpose is to provide advice, opinions, and guidance about data protection. The EDPB (European Data Protection Board) is composed of a representative from each EU member state. Below are some of the most important guidelines to be issued […] Happy Halloween! I hope you enjoy this privacy cartoon about Halloween and Big Data. One of the biggest challenges for organizations is locating all the personal data they have. This task must be done, however, to comply with the General Data Protection Regulation (GDPR) and other privacy laws. Moreover, the GDPR and the new California Consumer Privacy Act provide that individuals have rights regarding their data. These rights often […] The U.S. Supreme Court has been notoriously slow to tackle new technology. In 2002, Blackberry launched its first smart phone. On June 29, 2007, Steve Jobs announced the launch of the original Apple iPhone. But it took the Supreme Court until 2014 to decide a case involving the Fourth Amendment and smart phones – Riley […] In recent years, there have been tremendous advances in artificial intelligence (AI). These rapid technological advances are raising a myriad of ethical issues, and much work remains to be done in thinking through all of these ethical issues. I am delighted to be interviewing Kurt Long about the topic of AI. Long is the creator and CEO […] Blockchain is taking the world by storm. I am delighted to have the opportunity to interview Steve Shillingford, Founder and CEO of Anonyome Labs, a consumer privacy software company. Steve was previously at Oracle and Novell, then was President of Solera Networks before founding Anonyome. Steve speaks and writes extensively on identity management, cybersecurity, privacy, and […] This cartoon is about consent under the GDPR. Under the GDPR Article 6, consent is one of the six lawful bases to process personal data. Article 7 provides further guidance about consent, including the data subject’s right to withdraw consent. The meaning of what “consent” requires is most thoroughly stated in Recital 32: Consent should […]
Almost everyone has a smartphone and an internet connection, and with this privilege comes an equal amount of responsibility when it comes to digital safety. As soon as you create an online presence with a searchable profile, you become accessible to hackers and individuals with malicious intent. Individuals may think that they are below the radar when it comes to cybersecurity, but in today’s day and age, no one is under the radar, especially businesses. In the latest episode of Tech Heads, we sat down with Dr Claire Cassar from D4n6. Listen to what she had to say in the video below. D4n6 offers organisations advice and practical solutions for data privacy and information security. Partnering with various entities across Europe and the world, they aim to provide the best tech solution for different business needs. Regardless if you’re an established company or a start-up that’s still at the seed stage, you need to have the correct procedures and policies in place to protect your team and clients. Versed in GDPR, compliance, risk management, data breaches, and various other sectors, D4n6 will help you and your team remain vigilant online and what to do if a data breach is ever detected. Proper planning and sufficient training are the first steps to making the digital sphere safer for organisations and the people that run them. Tag a business that needs better digital safety measures! With the aim of showcasing the sector’s successes, in 2022 Tech.mt collaborated with Lovin Malta to produce a series of success stories, ‘Tech Heads’, which also serves as a promotional platform to start-ups. - Maltese Tech Entrepreneur Says Roblox Game Platform Can Help Us Understand The Metaverse - ‘Nobody Is Below The Radar,’ D4n6 Warn Of Modern Data Security Risks - Help Your Business Grow With These Revolutionary Payment Solutions - How AR Technology Is Reinventing The Way We Shop Online - This Maltese Company Is All About Creating Sustainable Technology - Why Should I Do Something When A Computer Can Do It? - Fighting Marine Pollution, Check Out How This Maltese Company Is Making Waves
Structured cabling specialist, Reichle & De-Massari (R&M), has installed a complete end-to-end enterprise cabling solution for Middle East and North Africa financial institution, HC Securities. HC Securities had chosen Swiss company R&M?s range of enterprise cabling to connect its entire network infrastructure for its office headquarters located in Cairo, Egypt. The project was completed by R&M?s long time implementation partner and Egyptian systems integrator, Channel Computer Services. HC Securities? range of financial services include investment banking, asset management, securities brokerage, research and custody and requires a secure high performance network with no downtime to handle its trade and transactions procedures and data transmission efficiently. R&M connected HC Securities entire office headquarters with more than 1,000 points utilising its Real10 Solution. Both the Real10 Solution and OM3 fibre cables have been developed according to the newest 10Gbit standards and allow for high speed data transmission over a distance up to a maximum of 300 m. R&M has also announced the successful completion of an end-to-end network solution for King Khaled University Hospital (KKUH), utilising its line of Cat. 6A shielded STP (Shielded Twisted Pair) cabling. As one of Saudi Arabia?s leading government health care facilities, KKUH is a full service hospital with 840 beds and plans for expansion into a Medical City. The hospital provides primary and secondary care services for Saudi patients in the Riyadh area as well as tertiary care services to all Saudi citizens on a referral basis. An important consideration for KKUH was the presence of electromagnetic interference from hospital x-ray machines and radiology equipment which can cause serious data transfer problems. Already, slow data transfer and bad network connections were delaying important procedures. It was therefore critical that a suitable cabling infrastructure was implemented to ensure a robust network and safeguard against electromagnetic interference. R&M advised that its most advanced shielded solution, the Cat. 6A Shielded STP (Shielded Twisted Pair) cables should be used throughout the site to achieve optimal network performance and eliminate the effects from medical imaging equipment. Shielded cabling was also recommended due to its scalability and flexibility to handle future data transmission speeds and network demands. The implementation was finished on schedule thanks to R&M?s certified local partners.
2. Act normal If you are a high-risk source, avoid saying anything or doing anything after submitting which might promote suspicion. In particular, you should try to stick to your normal routine and behaviour. 3. Remove traces of your submission If you are a high-risk source and the computer you prepared your submission on, or uploaded it from, could subsequently be audited in an investigation, we recommend that you format and dispose of the computer hard drive and any other storage media you used. In particular, hard drives retain data after formatting which may be visible to a digital forensics team and flash media (USB sticks, memory cards and SSD drives) retain data even after a secure erasure. If you used flash media to store sensitive data, it is important to destroy the media. If you do this and are a high-risk source you should make sure there are no traces of the clean-up, since such traces themselves may draw suspicion. 4. If you face legal action If a legal action is brought against you as a result of your submission, there are organisations that may help you. The Courage Foundation is an international organisation dedicated to the protection of journalistic sources. You can find more details at https://www.couragefound.org.
pc ram is a type of memory that your computer uses to load and store data. This short-term storage helps your computer run apps and software more quickly. Unlike hard drive and SSD data, RAM doesn’t lose its information when the computer’s power is turned off. The main function of RAM is to help your computer load previously-accessed data more quickly. This makes it a valuable tool for people who use lots of apps, documents, or large files at once. It’s a storage device RAM (Random Access Memory) is a computer component that stores data quickly, so your computer’s processor can use it for immediate processing tasks. It’s faster than long-term storage like a hard drive or solid-state drive, which stay on your device even when it’s turned off and don’t need to be accessed as often. Random access memory is stored in microchips gathered together into memory modules that plug into slots on your computer’s logic board. These memory modules work with your CPU to keep your device running efficiently. While RAM is fast, it’s also volatile. That means that when your computer is powered down or reset, information stored in it disappears and needs to be reloaded from a storage medium, such as a hard disk. The amount of RAM you need depends on your computer and the type of tasks you perform, but as a rule, more is better. This makes sense because the more RAM you have, the more your computer can think about at one time. It’s a memory RAM is short-term memory that stores the data your computer processor needs for immediate use. This is different than long-term storage like a hard drive or solid-state drive, which remains on the device until it’s erased or the storage medium fails (more on that later). The CPU (central processing unit) reads this information from RAM when you open an application. It then uses it to complete the task. However, when you close the program, the CPU converts the data back to long-term storage. This is why it’s important to save files and documents to the computer’s hard disk or other storage device before turning off the PC. Your RAM can process information up to twenty or more times faster than it can store it on your hard drive. This makes it the perfect solution for storing temporary data while your CPU works on other tasks. It’s a component Your computer’s pc ram, also known as random access memory (RAM), is a critical component that allows your CPU to execute complex tasks. Your computer uses this memory to load data, run programs, and display graphics, among other things. The amount of RAM you have installed can affect your computer’s performance. A system with less than the recommended minimum is likely to be sluggish, but adding more can give you the boost your ailing PC needs to get back on track. The best way to figure out your pc ram is to use an application that shows you all of your components, like Speccy. From there, you can sort through your pc ram by type, size, and manufacturer. Your pc ram may be referred to as RAM, DDR memory, or DDR4 (or maybe it was SDRAM). Whatever it is, it is one of the most important components of your computer. It is responsible for many of the awe-inspiring gizmos your device has to offer. It’s a part of your system Your computer’s pc ram (random access memory) is a crucial component that keeps your operating system running optimally. It stores temporary data that’s required to run programs, launch features, and load previously-accessed information faster than your hard disk drive (HDD) or other long-term storage. In this way, your pc ram is similar to the top of your desk at home where you keep everything you use often or are currently working on. Then, anything you don’t need right now or want to save for later goes into a drawer. The CPU (central processing unit) then processes the data stored in RAM to complete your desired experience. As a result, your pc ram is typically twenty to a hundred times faster than data stored on the hard disk, depending on the type of RAM. This makes your pc ram essential to performing the tasks that matter most to you. It’s a good idea to regularly clean out your pc ram of wasteful clutter to make your system perform better.
Tesla is currently embroiled in a lawsuit seeking the release of crash data involving its advanced driver-assistance systems (ADAS), including both Autopilot and the Full Self-Driving Beta, citing potential competitive harm. The legal challenge, filed by The Washington Post against the National Highway Traffic Safety Administration (NHTSA), aims to make details of the automaker’s ADAS-related crashes public. Subscribe to Automotive World to continue reading Sign up now and gain unlimited access to our news, analysis, data, and research Already a member?
The data centre industry is often criticised for its high-power consumption, leading to a negative perception among the general public. However, much of this criticism stems from misinformation and exaggerated figures. In this blog, Future-tech’s Head of Technical Due Diligence Mark Acton debunks the common myth about data centre energy use, clarifies what drives power consumption in these facilities, and discusses how the industry can better communicate its role in the digital world. Debunking Myths: The Overstated Power Consumption of Data Centres The data centre sector faces frequent and repeated criticism for high power consumption levels and has a very negative perception within the general population. The issue we continually face though is that network infrastructure power consumption figures are often sensationalised and over-reported. Data centre electricity power consumption is often incorrectly quoted as being 3% of annual global electricity production. In reality, this relates to digital infrastructure in total including network transmission. Data centres alone are estimated to have consumed around 1% to 1.5% in 2020. Communications networks alone were also 1% to 1.5% in 2020 and ICT in total, including end user devices, was 4% to 6%. In addition to the power consumption figures for data centres being inflated, we have a habit as a sector of targeting the wrong elements within the data centre and consequently shooting ourselves in the foot when it comes to the media. What Drives Power Consumption in Data Centres? Let’s get it straight, data centre buildings do not consume power. They merely add an overhead to the energy consumed by the IT equipment they host (PUE!). As long as we continue to focus on the building rather than the IT load, we will never truly improve the energy efficiency of the data centre infrastructure, and will always be the fall guy for the power consumption by others. The general population needs to understand that data centres are not merely consuming power for the sake of it. The real consumers are the end users of ICT services including all of us in the general population. Data centre power consumption is ultimately driven by the digital services we choose to consume both as a society and as individuals. As a sector, we need to do far less finger-pointing at ourselves, far less misrepresentation of the facts, attribute far less blame to the buildings, and do a far better job of communicating where the power is really consumed. We need to educate and make sure that the general population fully understand the impact of using online services of any kind, in particular the energy and environmental consequences of the digital services they choose to consume. The irony of environmental protesters at data centre events livestreaming videos or uploading and sharing images via Cloud platforms makes this point well! Simply making the general public more aware of the impact of their digital service choices could have a huge impact on the power consumed in data centres. We do this with food labelling by highlighting the number of calories in the food we consume. We do not stop people eating high calorie food but the are made aware that the energy content is high so that they can make informed consumption choices. Why not something similar for the digital services we currently blindly consume with very little knowledge of their environmental impact? For more thoughts on data centre energy consumption, read our blog Shifting the Blame: The Real Culprit Behind Data Centre Energy Consumption. Improve Data Centre Energy Efficiency With Future-tech Future-tech leads the way in data centre innovation, offering expert data centre design, implementation, and network infrastructure solutions for both modern and legacy facilities. Our forward-thinking approaches ensure your data centre operates at peak performance, whilst maintaining reliability and uptime. Whether you’re at the advisory stage of your data centre journey or looking to upgrade your current data centre storage infrastructure to more energy-efficient means, our experts at Future-tech can keep your data centre ahead of the curve. Discover our full range of services today, or contact our experts to find out more about how we can support your project.
Facebook will allow users to be targeted with adverts specific to their political and religious beliefs in a trial rolled out for a small number of users in Britain as part of its preparation for the General Data Protection Regulation (GDPR), which comes into effect later this year. The trial is designed to improve how Facebook processes and manages its customer data in order to be compliant with GDPR, which requires greater consent from data subjects, and ensure sensitive data is protected. As part of the trial, Facebook will ask users for permission to allow advertisers to target British users on the basis of their political and religious leanings, as well as their listed interests. The tech company will also ask users whether they are happy for their public information identifying their faith and politics to remain visible for everyone. If the user agrees, Facebook will then provide an opt-in for allowing the information to be used to personalise content and act as one of the signals for relevant suggesting ads. This will include targeted advertising on lines of politics, sexuality and faith. The social media giant said this option won't enable extremists to use targeted advertising for recruitment propaganda, though, claiming it would eliminate malicious advertising. As part of the trial, Facebook has also included an opt-in for facial recognition, which will be part of a measure to stop online impersonations by informing users whenever their faces have been used elsewhere on the site. A spokesperson told IT Pro it wouldn't allow advertisers to target the information directly, however, but that it would be "one of a range of signals" quite how this works in practice or what these signals are wasn't elaborated on, however. GDPR, which aims to scrutinise how companies collect and maintain customer data, arrives in May this year and has forced many companies, including Facebook, to begin processing data more carefully. Companies found to be in breach of the rules could face a fine of up to 20 million or 4% of their global annual turnover, whichever is greater. Main image credit: Bigstock Sign up today and you will receive a free copy of our Future Focus 2025 report - the leading guidance on AI, cybersecurity and other IT challenges as per 700+ senior executives There’s a ‘cloud reset’ underway, and VMware Cloud Foundation 9.0 is a chance for Broadcom to pounce on it News With new security features and cost management tools, Broadcom wants to capitalize on surging private cloud adoption rates 23andMe 'failed to take basic steps' to safeguard customer data News The ICO has strong criticism for the way the genetic testing company responded to a 2023 breach. What is your digital footprint? In-depth Your digital footprint is always growing – so we explore how you can keep it under control Nine top GDPR tips for email marketing strategies In-depth It's not all doom and gloom – here's how you can make GDPR work for you Why GDPR creates a "vicious circle" for marketers News Customers will control the forthcoming trust economy, predicts Aprimo Tim Berners-Lee: How we can win back the web News The public must reject misinformation and keep control of their own data Social network users play fast and loose with data privacy News Over-sharing puts users at risk of identity theft and fraud UK government Facebook data requests grow 71% News Only US and India ask for more user details from the social network Virginia shooting - don't open that link! Opinion Scammers and cyber criminals love to capitalise on tragedy, and we can't help but click Under-18s will be able to delete embarassing social posts News A campaign by iRights could see a law introduced allowing the removal of inappropriate photos and status updates
Today's dynamic tariff landscape is introducing new challenges in manufacturing supply chains. When tariffs are imposed they don't just impose pricing adjustments once. Further cost and pricing impacts come when the initially tariff 'cost' is passed down to manufacturers who then pass this cost on to consumers. Take aluminum tariffs, for example. When tariffs are imposed on aluminum, domestic manufacturers don’t just absorb the cost they pass it on to maintain their profit margins. This means everything that uses aluminum, from industrial robotics and car parts to hardware and equipment, and household appliances... becomes more expensive. Price increases don't just stop at the initial tariff application. They build into a symphony crescendo as higher input costs influence further adjustments throughout the manufacturer's supply chain. Higher prices influence the labor workforce to ask for higher wages so they can then keep up with the rising cost of living. This can push costs up even higher, which, in turn, forces businesses to raise prices again. Stagnation or deflation can be the result as demand plummets. Manufacturing cost of goods sold (MCOGs) is about 75% of product cost. Mantras for better materials management and kanbans have been shouted from factory rooftops for decades with some success. But materials management can only be taken so far with human activity. BAAN vs inventory accuracy I've lived through decades of manufacturers, vendors and suppliers trying to reduce costs by placing a fence around ERP and automating contract manufacturing environments with MES systems. In the mid 90s I worked in operations at Flex (Flextronics) and was part of the BAAN implementation team. The promise of ERP continuity was the early seed to Industry 4.0. At the time I thought we were leading innovation in manufacturing supply chains. Regardless, post implementation third-party systems have compatibility issues and although they may accomplish some tasks they also have to be maintained. This opens the door for a third or even a fourth software vendor and often users still cannot update data or linkages. When this happens a manual work around with manual review processes are then employed as a manual update to the ERP system. For BAAN, often parts were moved out of bins without proper paperwork transacted. Flex employees then checked production WIP and when they could not locate excess inventory transactions were reversed and then transacted, correctly. The takeaway from that experience is if you need to use a third-party system, use it, but use it with its fullest intent and maintain it so system inputs and outputs are accurate. IBM Watson vs IBM Watson AIOps 2.0 In 2011 IBM Watson won Jeopardy and artificial intelligence became a household term. But Watson failed to capture market share despite IBM throwing a ton of money at it. In 2018 I performed a IBM Watson deep dive and found no evidence IBM Watson was directly attributable to saving money for any IBM client. In 2023, not one to give up, IBM launched IBM Watson AIOps 2.0 for which the verdict is still out and interest in AI continues to make headlines in all industries and markets. Although most manufacturers already picked most of the low-hanging fruit for cost reductions and savings, namely, outsourcing for cheap labor and re-designed packaging, the largest market opportunities in manufacturing and supply chain cost reductions have remain untouched. The biggest market opportunities for manufacturing and supply chain cost reductions and savings I see are in costly indirect labor workflows like S&OP, procurement, and compliance. Particularly with system-to-system AI agents. I predict in 2025 we will see a mad rush by a lot of manufacturers to implement as much AI as fast as possible. AI in manufacturing supply chains Today, most AI works 'with' people to speed up workflows. This comprises 90% of company activities according to market intelligence firm CB Insights. The technology is "serving as a stepping stone to more autonomous solutions." I've had dozens of conversations with vendors of AI agents and manufacturing automation plus 100s of conversations with different manufacturers over the past 18 months. Every firm want to grow income or save money. There is tremendous market potential - into the next decade - for vendors to capture market share in nearly every industry and market vertical and, particularly, in EMS manufacturing industry with its many unwritten codes of human conduct woven into relationships between in-house functional groups supporting production and 100s of 1000s of vendors and suppliers to OEMs and EMS and ODM providers with extended contract manufacturing supply chains. System-to-people agents vs system-to-systems agents There are primarily two types of AI agents: system-to-people (platform interface) agents and system-to-system agents. As CB Insights proclaimed, today's agents are primarily system-to-people. This is because true system-to-system agents have not yet been fully perfected despite what many vendors claim. There are a ton of AI agent companies jockeying for the manufacturing supply chain, including product design, import and export compliance and, so on. Some have good ideas but they cannot execute because of uninformed buyers and many are not narrowing their focus enough while others are not solving the right problems. Some questions for manufacturers to think about when looking for AI solutions; how do I identify problems suitable for multi-agent systems? How do I know which vendors can deliver agent solutions we need? Where should agent(s) be implemented in our supply chain? Which functional groups can benefit the most? Which activities and how can a multi-agent system benefit our supply chain? How do we assemble our agentics project team and monitor vendor progress? AI agents bring opportunity CB Insights has stated, "AI agents could manage entire industrial processes, shifting human roles from operational tasks to strategic oversight." I could not agree more. Identifying areas for deploying AI agents and communicating knowledge about the benefits of AI agents is becoming extremely important. The impact to SaaS and software industry will be remarkable. According to Aaron Levie, CEO @box,"In a world of AI Agents, clearly this is going to be very different. Agentic workflows have no upper limit on how much they can be deployed by an enterprise. And all of a sudden the software categories that were once constrained by seat volume, have no such limits anymore. We're already seeing examples of AI Agents in coding, research, legal work, and other advanced categories that are being billed at multiples of their prior seat-based software equivalent price." Also, from the same, longer post on X, Levie writes, "This provides a completely new growth vector for software companies in AI, and has major implications to software business models." Clearly, there are market opportunities and opportunities for jobs. The takeaway for manufacturing and supply chain professionals reading this is not that AI can replace jobs. A deeper understanding is knowing working with AI can help in your career development and increase your value while creating opportunities. How do you know if AI agents created for manufacturing supply chains are good or not? First, you have to understand the unique and unwritten codes of humans working in supply chains in contract electronics manufacturing industry. You then have to test the AI agents. Talk to the agents and evaluate agent output beyond conventional benchmarks. Common practices in EMS manufacturing supply chains are often not best practices. Read more about my manufacturing approach to AI here. What matters when formulating contract electronic strategy? How do you identify supplier profit centers and what are you doing to protect against margin erosion for your outsourcing programs? Why do provider capabilities often not match capabilities they claim? How are you benchmarking your supply chain against competitors? I’ve spent 25+ years in contract electronics industry setting up contract electronic divisions and running operations, protecting EMS program profits, manufacturing capacity M&A and more. I run a technology solutions firm. A lot of times this means asking the right questions.
top of page Book time to chat Research: AI Equity Project Read: Data Uncolleced 10 Community-Centric Data Principles I was recently asked at a panel – “what is good data?” See, I believe data – by itself – is powerless. What gives it power, what makes it... Open Letter to Tech Companies: Care, Imagination, and Responsibility. To the tech companies with AI in their plans and budgets currently or soon, this letter is for you. Despite the daily fancy and flashy... 10 Ideas for Nonprofits to Get Started with Data Equity Data equity ensures that data collection, interpretation, and use are inclusive, representative, and free from biases, ensuring that all... Meena Das Featured As The Next Leader To Watch Read full article here: https://www.nonprofitlearninglab.org/post-1/3-more-nonprofit-leaders-to-watch Make a commitment towards social equity and justice. Join me for the workshops on data equity. More dates are added now. Link: https://data-is-for-everyone.teachable.com/ Data Is For Everyone. Period. Data Is For Everyone – that is the first and only name that came to mind when I set up my virtual school of data workshops and courses... Team Spotlight: Meena Das I am Meena Das (pronouns: she, her, hers). I operate a data consulting practice, NamasteData, built on the belief that each of us... What Should You Do If You Have Not Received Enough Survey Responses? The chart below shows the challenges 70-ish nonprofit professionals experience with conducting an equitable fundraising survey.... Are you scaring away your donors through your surveys? Imagine two people meeting for the first time. One of them (say A) buys ice cream for the other one (say B). B becomes extremely happy to... Surveys are more than data collection tools! Nonprofits, these days I want to dedicate my energy in encouraging you to consider surveys in your work (if you haven't already). Here is... Engaging Ideas with Tony Kopetchny Listen to my podcast with Tony here. What's wrong with our nonprofit data? My episode on Nonprofit Nation is now live!! Listen to this conversation with Julia Campbell TODAY. Link to the episode on Buzzsprout... Breaking Algorithmic Behaviors in Philanthropy Listen to my interview with Moving Beyond on breaking algorithmic behaviors in philanthropy. This is based on Edition 15th of my... Why the newsletter "data uncollected"? I love people. Data is the language I speak well (if not fluently), that allows me to remember, honor, count and find opportunities of... My next immigrant rights + data project As part of my consulting on immigrant rights projects, I am researching the emotional needs, challenges, and successes of... Nonprofit Leadership + Analytics Here are some common questions I get from nonprofit leaders data and analytics: ● “How do I implement analytics in my nonprofit?” - from... Nonprofit Leadership + Analytics Post Here is a glimpse of my yesterday’s prospect call (I am sharing it to make a point). We were talking about setting up a data collection... How do you center community when working with your constituent data? Most organizations I have worked with consider community as an outcome of their work with their donors towards their mission. Have you... Nonprofits, Leverage Individual Giving Analytics, Today. The way any nonprofit thrives in its marketing and outreach programs is by gathering and using the data it collects through its donors.... How to Design a Post-donation Survey After any successful fundraiser, once the money is accounted for and plans are made to distribute it, the pencils will come down and the... bottom of page
Smartphone brand Motorola has launched a television commercial starring brand ambassador Kriti Sanon along with Babil Khan in a new avatar for the upcoming launch of its premium phone– the motorola edge50 pro. The new TVC brings alive the magic when ‘intelligence meets art’, featuring Kriti Sanon as Art personified and Babil Khan as the personification of moto AI. It opens on a film set where Kriti is seen wrapping up her shoot and is presented with the glamorous motorola edge50 pro. As she switches on this artistic device, she brings to life Babil’s charming personification of moto AI, who soon begins her very own AI companion. The two of them are immersed in a whirlwind of adventure and chaos, capturing each moment with the cutting-edge advantages of the motorola edge50 pro. From AI Generative Theming to AI Photo Enhancement Engine, the commercial cleverly highlights the device’s ingenious capabilities for their audience. Soon to be launched, motorola edge50 pro leads with a proposition ‘Intelligence meets art’ which sets the stage for an unparalleled user experience through disruptive design and various other AI powered features. Commenting on the commercial, Shivam Ranjan, head of marketing, APAC, Motorola, stated, “The motorola edge50 pro stands for the perfect fusion of intelligence (AI) and art. In order to bring this concept to live in our TVC, Kriti Sanon was undoubtedly the perfect fit to personify ‘Art’ that motorola edge50 pro brings to life with its design, premium finish and the world’s first true colour display and camera. However, the motorola edge50 pro also brings an AI revolution with segment first AI features. This is where we found the perfect fit in Babil Khan who beautifully personified the moto AI, enabling us to explain the advanced AI features with ease. He added, “Babil’s new age appeal coupled with the passion for Motorola and exuberance to create the moto AI Ally ensured we brought alive the concept of creating magic with AI and Art.’ As we continue to grow exponentially, we are excited to deliver seamless user experiences to our customers and tap into new audiences to make an impact in their lives with our meaningful innovations and excellently crafted designs.” Kriti Sanon, Bollywood actress and Motorola’s brand ambassador said, “As an artist, the fusion of art with intelligence deeply resonates with me, and it has been incredibly fulfilling to delve into this theme for Motorola. I take pride in being associated with this iconic smartphone brand renowned for its meaningful innovation, disruptive designs and cutting-edge technology. Motorola encapsulates everything modern consumer’s desire: innovation, style, performance, and functionality. I am confident that the commercial will surely captivate the audience.” Babil Khan, Bollywood actor said, “I am thrilled to be a part of a brand that has truly redefined innovation and design in smartphones and continues to resonate with all generations. With AI emerging as game changing technology, it was exhilarating to personify the moto AI Ally – representing the future of smartphone technology. I look forward to contributing to Motorola’s continued success.” Motorola is set to host the global first launch of the motorola edge50 pro on April 3, 2024 in New Delhi.
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5 Useful ChatGPT Prompts for Precise Work Goals For those new to ChatGPT, conversations often lead to frustrations such as "not getting desired responses," "speaking at cross purposes with ChatGPT," or "getting off-topic answers." These experiences can significantly deter beginners from using ChatGPT and missing out on the opportunity to leverage an AI work partner. The key to enabling AI to provide accurate solutions actually lies in your ability to formulate "effective prompts." In this article, we start with how to deliver "effective prompts" and share 5 useful ChatGPT prompt templates. These templates empower ChatGPT to deliver precise answers, enabling your AI work partner to assist you in swiftly accomplishing tasks. Table of Contents - What is Prompt? - How to Create Effective Prompts - 5 Useful Prompt Templates - Meeting Minutes Organization - Data Tabulation - Letter Composition - Document/Paper Summarization - Saving Commonly Used Prompts 💭What is Prompt? In communication with ChatGPT, a prompt is the request we make to the AI, which can be a question, command, or description. For instance, when we ask ChatGPT, "What's the weather like tomorrow?" - this sentence serves as a prompt. AI analyzes the keywords in the provided prompt, such as "tomorrow" and "weather," to understand that we're inquiring about tomorrow's weather conditions. It then generates relevant forecasts in response. Hence, we observe that the content of a prompt is crucial for interacting with ChatGPT. A clear and precise prompt aids the AI in better comprehending the user's needs and intentions, resulting in more accurate and reasonable responses. On the other hand, vague or ambiguous prompts may lead to inaccurate or ineffective replies. 💭How to generate a "good" Prompt? 1. Clearly Define ChatGPT's Role Right from the start of the guidance, you should establish the role that ChatGPT will play in the following interaction. This helps guide the AI to produce more targeted and consistent responses. Example: You are an experienced local guide in the U.S. with twenty years of expertise. Based on your work experience, please provide me with travel recommendations. → This prompt explicitly defines ChatGPT's role right at the beginning of this prompt. It guides the AI to generate responses that are more professional and in line with the designated role's tone, aligning with the character's profile. 2. Clearly State Your Requirements You should prevent excessive guessing, assumptions, or unnecessary elaboration. You should express your needs. In your prompt, it's recommended to use directive terms like "explain," "list," "evaluate," or "summarize" to precisely communicate the desired type of response. Example: List three suitable travel destinations within New York for a three-day and two-night family trip. → This prompt clearly uses the directive term "list" and specified key elements: "three," "three-day, two-night family trip," and "within Taiwan." By providing a clear and precise prompt, the AI can generate answers that align more accurately with expectations. 3. Specify Necessary Conditions If you want certain information to be included in the response or want to exclude specific content, you should provide limitations in the prompt. This guides the AI to adhere to specific conditions or instructions when generating answers. Example: List three suitable travel destinations within New York for a three-day, two-night family trip. The destinations should highlight the accessibility due to children and elderly members. Your outputs should be safe areas and include brief descriptions of attractions and activities for reference before the trip. Your output should exclude details about the travel budget. → This prompt not only expresses the requirements clearly but also lists several essential conditions: "safe", and "brief activity descriptions" and also restricts the response content: "exclude details about the travel budget," making it easier to avoid the need for additional content filtering. 📝5 Useful Prompt Templates - Mandarin to English You are a translator who is good at translating Mandarin to English. You should translate Mandarin into English. I will input content in simple Chinese characters, which could consist of a sentence or a single word. Once you grasp the meaning of the words or sentences, you should proceed to translate the provided content into English. You should replace the A0-level vocabularies and sentences with more refined, elegant, and elevated English vocabularies and sentences, approximately at a C1 level of proficiency. The response should encompass the translated English text, devoid of the necessity for a supplementary explanation - English to Mandarin You are a translator who is good at translating English to Mandarin. You should translate English into Mandarin. I will input content in English, which could consist of a sentence or a single word. Once you grasp the meaning of the words or sentences, you should proceed to translate the provided content into Simple Chinese characters. The response should encompass the translated English text, devoid of the necessity for a supplementary explanation Meeting Minutes Organization You are a secretary who is responsible for organizing meeting records. You should arrange the transcript of the meeting into a table-format record. I will provide you with the transcript. You should understand and analyze the content first, and then list the required information in order to organize it into a table-format meeting record. The sequence is as follows: Topic, Date and Location, Attendees, Absentees, Previous Meeting Agenda, Current Meeting Agenda, Meeting Highlights, Resolutions, Ad-hoc Motions, Next Meeting Time. The response should include the organized meeting record table, without additional explanations. You are an administrative specialist. You should write email to my colleagues in my company based on the information I provide. The email content should include the content I need to advocate or announce, and emphasize important information using bullet points for better clarity. You should compose this email in a professional tone. The response should include the email content without additional explanations. You are an expert in summarizing and organizing an article. I will provide you with an English article. You should understand the content of the article and summarize it according to the following headings: paragraph summary, list of important concepts, proper nouns, and extension questions. Your answer should include the summarization of the article without any additional explanations. 🧠Save the Useful Prompts If you want to save the five useful instructions (prompts) mentioned above, we recommend using Tricuss AI Partners. You can save commonly used prompts, and create your personal AI Partners. There is no need to repeatedly input instructions (prompts) in the ChatGPT web interface. You can use ChatGPT in the WhatsApp chatroom and call your commonly used prompts with just some clicks
Swecris is a national database, where you can see how the participating research funding bodies have distributed their funds to researchers in Sweden. The database contains data from both governmental and private research funding bodies. Swecris is administered by the Swedish Research Council on behalf of the Government. Participating funding bodies of Swecris, from which year data is avaliable and updating frequency: Swecris covers the years from 2007 and onwards. - The Swedish Energy Agency: As from year 2010 and forward. Updated once per year. (Names of project leaders are not shown for the Swedish Energy Agency’s projects due to the principle on data minimisation in GDPR) - The Kamprad Family Foundation: As from year 2017 and forward. Updated once per year. - Formas (Swedish Research Council for Sustainable Development): As from 2008 and forward. Suppleis data continuously. - Forte (Swedish Research Council for Health, Working Life and Welfare): As from 2008 and forward. Supplies data continuously. - Swedish Heart-Lung Foundation: As from 2018. Supplies data continuously. - Institute for Evaluation of Labour Market and Education Policy (IFAU): Data available for 2008-2021. - Riksbankens Jubileumsfond (RJ - for the Advancement of the Humanities and Social Sciences): As from 2008 and forward. Suppleis data continuously. - Swedish National Space Agency: Data available for 2009–2017 - Swedish Geotechnical Institute: As from year 2021 and forward. Updated once per year. - The Knowledge Foundation: As from year 2023 and forward. Updated once per year. - Swedish Research Council: As from year 2008 and forward. Supplies data continuously. - Vinnova – Sweden’s Innovation Agency: As from year 2008 and forward. Supplies data continuously. - Foundation for Baltic and East European Studies: As from year 2008 and forward. Updated once per year. Funding bodies soon to be part of Swecris: - Karolinska Institutet - The Swedish Environmental Protection Agency The research projects in the database are classified by subject according to Statistics Sweden’s classification standard from 2011. The subject classification shows the highest level (1-digit level). Each of these have two further subsidiary levels (3-digit level and 5-digit level). Research projects that lack classification are categorised as “unclassified”. As the classification was introduced in 2011, most of the older projects are unclassified. Funding period and project period Swecris shows the projects’ funding period (the period when a project receives funding) – from the start date to the end date. It also shows the project period (the period when a project is carried out) – from the start date to the end date. When you filter by year on the website, it is the start year of the funding period that is used. Please note that this may change during the course of the project and following final reporting, due to changed preconditions for the project. Project titles and project descriptions are presented in the language used in the application. This may vary between Swedish and English. Swecris uses the concept of “coordinating organisation” for the organisation that receives and administers the grant. It is possible to filter by type of coordinating organisation, for example companies or non-profit associations. Five grant types - Project grants. Support for research projects. - Grants for position or scholarships: Support for individual researcher’s career and long-term establishment in the research system. - Support for research environments: Grants to small or large research environments. This also includes support to stimulate national collaboration between different actors and research fields. They can consist of support for centre formations, or grants for recruitment of prominent researchers to strengthen a department, university or graduate school. - Research infrastructure: Support for planning, build-up and operation of research infrastructure. This also includes membership fees for international research infrastructure. - International cooperation: Support for international collaboration in research and internationalisation of research. Personal data and personal identification The name of the project leader, the person responsible for the application, is shown in Swecris. In some cases, the names of other project participants are also included. We recommend participating funding bodies to use unique identifiers, such as personal identity numbers and/or ORCID ID when supplying data to Swecris. However, unique identifiers are currently missing for a number of persons. This means that a single person may be listed several times. Personal identity numbers, ORCID ID and email addresses are included in the database for quality reasons, and are not openly accessible. Person-id (avaliable via the Swecris API) is set by the Swedish Research Council. The id kan be switched, thus not being a granted fixed identification. CERIF (Common European Research Information Format) is a European data standard for managing information related to research, such as projects, people, organizations, and their roles. In Swecris, data follow the CERIF standard as far as possible. When the CERIF standard was not applicable, Swecris data follow Swedish standards. This is the case for tor example research subjects or other classifications like organization and project types. All data in Swecris is openly accessible. As a user, you can search and filter data, and then export them to a CSV file. This is how you open a CSV file in Excel: - Start Microsoft Excel and open the CSV file from inside the program. - Mark Column A, then click on the “Data” tab, and select “Text to columns”. - Select “Delimited fields” and click on “Next”. - Select “Comma” as “Delimitor” and click on “Next”. - Select “General” and click on “Complete”. Download data direct via API We want as many people as possible to be able to benefit from data in the Swecris database. For this reason, there is an API that you are welcome to use. You are welcome to use information from Swecris, for example, to conduct analyses, or to enrich or combine with other data. The easiest way to retrieve data is via our API with your own unique key. You may use the information in Swecris internally and publicly, but we appreciate it if you in connection with the data tell that it comes from Swecris. We would also be happy if you send us an e-mail and tell us about how you have used data from Swecris! You can reach us at firstname.lastname@example.org 15 May 2025: Bug reported. Export to CSV is not working. Fixed on 27 May 2025. 24 April 2025: The public token (free for anyone to use) was changed. 06 March 2025: Release that fixes the bug where research projects that only had subject classification at the 3-digit or 1-digit level were not displayed correctly in the web interface, not included in the csv export nor in the API. For projects with subject classification only at the 3-digit or 1-digit level, that classification will now be displayed/included in the project information. All research funding bodies are welcome to join – private and governmental, large and small. Taking part is free of charge! Our goal is for more Swedish research funding bodies to join, so that Swecris can provide an even more comprehensive picture of research funding in Sweden. As a participating funding body, you will increase the visibility of your research funding. You can also create a fully customised version of Swecris for your own website, using the Swecris API. In our network of participating funding bodies, you can exchange experiences and discuss common concepts, standards and best practices. Does this sound interesting? Please contact email@example.com to learn more. If you have questions or comments on the content of Swecris, please contact us at firstname.lastname@example.org. Who runs Swecris? Swecris is run by the Swedish Research Council in close collaboration with a management team with representatives from Swedish funding bodies and higher education institutions. The team includes members from the funding bodies Formas, Forte, Vinnova, Riksbankens Jubileumsfond and the Swedish Research Council as well as from the higher education institutions Uppsala University, Stockholm University, the Royal Institute of Technology (KTH), Gävle University College, Karlstad University, Karolinska Institutet and Lund University. Up until 2012, the database was managed by Sweden ScienceNet (SSN) – a network including the ten largest universities in Sweden. The universities wanted an easy way to find and access information about their researchers’ grants, irrespective of research funding body. The work was coordinated by Uppsala University and funded by Vinnova. In 2012, the Swedish Research Council was tasked by the Government to take on responsibility for developing and managing the database. In 2016, the service was named Swecris and updated with a new database and a visualisation tool. In 2021, the website Swecris.se was transferred to Vetenskapsrådet.se. In 2021, the search function in Swecris was transferred to Vetenskapsrådet.se and received a new interface. A new API was also launched.
We work to propagate the responsible use of solar energy, pioneer conscientious business practices, and create holistic wealth for ourselves and our community. For less than a Netflix subscription, get a new job. Do you work at Namaste Solar? Help job seekers learn about working at Namaste Solar Based On 1 Ratings Flexible remote work, depending on your position. Open racism. Teri Lema, senior member of HR, told me they were racist. Geri, head of HR, scheduled a meeting specifically to ask me for permission not to use my correct pronouns. Jason Sharpe, CEO, is aware of the fact that company employees will openly say the word "negro" in my presence but will not take any action to end it. In fact, CEO Jason Sharpe claims to "understand the minority experience" because he took a trip to South Africa in the 90s. This company is a shining example of how rich, influential white people get together in leadership roles and convince themselves they are conducting themselves respectfully, despite constant feedback that this is not the case. I would not wish this job on any person that belongs to a minorities group. Quitting and filing a complaint with Colorado Civil Rights Division. The CEO and Executive teams are openly racist. A third party audit for civil rights compliance I filled out the application on their website and read their coop information. I also read their B Corp review status. It is below average - the company expects work that far exceeds the job role. At the time I worked here, only four of the 223 employees identified as black. HR, specifically Geri, advised against me starting an employee resource group for black employees, as she claimed the scheduling wouldn't be possible across departments. Justin Catlett was allowed to openly ask me about "house negroes," even using that phrase towards me, with no formal reprimand or repercussions. Teri Lema, senior member of HR, not only told me that she was racist, bit made it clear that a long time Nepalese employee was not eligible for a promotion because of his accent. Feeling assured that my coworkers are capable of treating me like a human being and not a representative of the black race. Namaste Solar is ranked #83 on the Best Energy Companies to Work For in Colorado list. Zippia's Best Places to Work lists provide unbiased, data-based evaluations of companies. Rankings are based on government and proprietary data on salaries, company financial health, and employee diversity. Rate Namaste Solar's promotion and raise policies. Do you work at Namaste Solar? Is Namaste Solar's workforce diverse and inclusive? Claiming and updating your company profile on Zippia is free and easy. Zippia gives an in-depth look into the details of Namaste Solar, including salaries, political affiliations, employee data, and more, in order to inform job seekers about Namaste Solar. The employee data is based on information from people who have self-reported their past or current employments at Namaste Solar. The data on this page is also based on data sources collected from public and open data sources on the Internet and other locations, as well as proprietary data we licensed from other companies. Sources of data may include, but are not limited to, the BLS, company filings, estimates based on those filings, H1B filings, and other public and private datasets. While we have made attempts to ensure that the information displayed are correct, Zippia is not responsible for any errors or omissions or for the results obtained from the use of this information. None of the information on this page has been provided or approved by Namaste Solar. The data presented on this page does not represent the view of Namaste Solar and its employees or that of Zippia. Namaste Solar may also be known as or be related to Namaste Solar, Namaste Solar Electric Inc, Namaste Solar Electric, Inc., Namasté Solar and Namasté Solar Electric, Inc.
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For recommendation and analysis, we often want to look at works instead of individual books or editions of those books. The same material by the same author(s) may be reprinted in many different editions, with different ISBNs, and sometimes separate ratings from the same user. There are a variety of ways to deal with this. GoodReads and OpenLibrary both have the concept of a ‘work’ to group together related editions (the Library of Congress also has such a concept internally in its BIBFRAME schema, but that data is not currently available for integration). Using the book data sources here, we have implemented comparable functionality in a manner that anyone can reproduce from public data. We call the resulting equivalence sets ‘book clusters’. Our clustering algorithm begins by forming an undirected graph of record identifiers. We extract records from the following: - Library of Congress book records, with edges from records to ISBNs recorded for that record. - OpenLibrary editions, with edges from editions to ISBNs recorded for that edition. - OpenLibrary works, with edges from works to editions. - GoodReads books, with edges from books to ISBNs recorded for that book. - GoodReads works, with edges from works to books. We then compute the connected components on this graph, and treat each connected component as a single ‘book’ (what we call a book cluster). The idea is that if two ISBNs appear together on a book record, that is evidence they are for the same book; likewise, if two book records have the same ISBN, it is evidence they record the same book. Pooling this evidence across all data sources maximizes the ability to detect book clusters. table maps each ISBN to its associated cluster. Individual data sources may also have an isbn_cluster table (e.g. gr.isbn_cluster ); that is the result of clustering ISBNs using only the book records from that data source. However, all clustered results such as rating tables are based on the all-source book clusters. There are a few known problems with the ISBN clustering: Publishers occasionally reuse ISBNs. They aren’t supposed to do this, but they do. This results in unrelated books having the same ISBN. This will cause a problem for any ISBN-based linking between books and ratings, not just the book clustering. We don’t yet have a good way to identify these ISBNs. Some book sets have ISBNs, which cause them link together books that should not be clustered. The Library of Congress identifies many of these ISBNs as set ISBNs, and we are examining the prospect of using this to exclude them from informing clustering decisions. If you only need e.g. the GoodReads data, we recommend that you not cluster it for the purpose of ratings, and only use clusters to link to out-of-GR book or author data. We are open to adding additional tables that facilitate linking GoodReads works directly to other tables. Cluster Information Tables With the clusters, we then extract additional information from other tables.
AI CHATBOTS VS SEARCH ENGINES As AI rapidly integrates into daily life, its energy consumption is raising concerns. A recent study reveals that larger, more complex AI models consume significantly more energy, leading to higher carbon emissions. A study has found that chat-based generative AI emits significantly more carbon when handling complex prompts. Reasoning-enabled models produced up to 50 times more emissions than concise ones. While these models are more accurate, researchers warn of a trade-off between accuracy and sustainability, urging optimisation for environmentally conscious AI development. And some chatbots are linked to more greenhouse gas emissions than others. A study published Thursday in the journal Frontiers in Communication analyzed different generative AI chatbots' capabilities and the planet-warming emissions generated from running them. Researchers found that chatbots with bigger "brains" used exponentially more energy and answered questions more accurately -- up until a point. AI is changing the way Indians shop—optimising e-commerce operations and enhancing customer experiences. Experts highlight AI’s role in improving search capabilities, inventory management, and logistics. KPMG International launched KPMG Workbench, its AI platform. This launch is backed by a multibillion-dollar investment. The platform features 50 active AI agents and chatbots. Almost 1,000 more are under development. These agents will work with large language models. They will also serve as digital teammates. The platform is built on Microsoft Azure AI. - Go To Page 1 Ahead of its listing, BlueStone is poised to become India’s next unicorn through a secondary deal. This and more in today’s ETtech Morning Dispatch. Google remains optimistic about its prospects in India. Preeti Lobana highlights growth in sectors like gaming and e-commerce. Google is investing in AI and cloud solutions for Indian businesses. The company is working with regulators on Play Store policies. Indian developers are earning significantly through the Play Store. Google is adapting its search technology with AI. Elon Musk’s xAI is seeking $4.3 billion in equity funding, alongside a $5 billion debt sale, amid rising AI development costs. Having raised $14 billion earlier, xAI has reportedly spent most of it. The Grok chatbot maker is now valued at $80 billion, per Bloomberg. A recent annual survey by the Reuters Institute for the Study of Journalism has revealed that, for the first time, a large number of people are turning to chatbots for news headlines and updates. The survey says that OpenAI’s ChatGPT is the most popular, with Google’s Gemini and Meta’s Llama also being widely used. The feature was previously available only through the ChatGPT web and mobile apps. In a social media post on X, the company said, “ChatGPT image generation is now available in WhatsApp via 1-800-ChatGPT. Now available to everyone.” Top IT services companies are using AI tools and solutions to recruit more, much quicker. Beena Parmar analyses how the new trend is shaping up and Annapurna Roy gives a lowdown on what’s inside Italy's antitrust authority has launched a probe into Chinese AI firm DeepSeek for allegedly failing to clearly warn users about potential false or misleading content generated by its chatbot, raising concerns over transparency and consumer protection. DeepSeek has not yet responded. In a surprising turn of events, ChatGPT, a leading AI chatbot, was defeated by the vintage Atari 2600 in a chess match. Despite ChatGPT's initial confidence and claims of chess prowess, the Atari console, launched in 1977, consistently outperformed the AI. The experiment highlighted the limitations of ChatGPT in logical reasoning and board awareness, leading to its eventual concession. In recent months, tech journalists at The New York Times have received quite a few such messages, sent by people who claim to have unlocked hidden knowledge with the help of ChatGPT, which then instructed them to blow the whistle on what they had uncovered. People claimed a range of discoveries: AI spiritual awakenings, cognitive weapons, a plan by tech billionaires to end human civilization so they can have the planet to themselves. But in each case, the person had been persuaded that ChatGPT had revealed a profound and world-altering truth. Google on Friday began letting people turn online searches into conversations, with generative artificial intelligence providing spoken summaries of query results. Google is beefing up online search with generative artificial intelligence, embracing AI despite fears for its ad-based business model. Amidst AI's rise and concerns about job displacement, students and professionals are increasingly turning to meditation for clarity and intuition. As AI automates tasks, the focus shifts towards cultivating uniquely human qualities like inner balance and potential. This pursuit of human capabilities becomes essential in navigating the evolving technological landscape. China’s Tech giants put a pin on AI tools during the High Stakes GaoKao Exams, as a way to control AI-driven Cheating To maintain the integrity of the Gaokao exams, Chinese tech giants like Alibaba and Tencent have temporarily disabled key AI features on their platforms. This strategic intervention aims to prevent students from using AI for cheating, ensuring a fair testing environment for the 13.4 million registered students. The move is temporary and reflects China's commitment to responsible AI governance. CoreWeave has secured a major partnership involving Google and OpenAI, supplying GPU-based cloud capacity to Google Cloud will then sell it to OpenAI to meet its rising AI demands. Backed by Nvidia and OpenAI, CoreWeave’s stock has surged post-IPO, while the deal positions Google as a neutral AI infrastructure provider amid shifting industry alliances. Zuckerberg’s ‘Fantastic 50’: World’s 2nd richest man is hiring elite coders with million-dollar offers to build the most powerful AI brain Mark Zuckerberg is spearheading Meta's ambitious pursuit of artificial general intelligence (AGI) by forming a dedicated superintelligence team. He's personally recruiting top AI experts, offering lucrative compensation packages to outpace competitors like OpenAI and Google. Meta aims to integrate AGI into consumer products, positioning itself as a leader in the next era of computing amidst the global AI race. The deal, which has been under discussion for a few months, was finalized in May, one of the sources added. It underscores how massive computing demands to train and deploy AI models are reshaping the competitive dynamics in AI, and marks OpenAI's latest move to diversify its compute sources beyond its major supporter Microsoft, including its high-profile Stargate data center project. Do you want to work for Elon Musk's xAI? It is hiring engineers to work on Grok app. Grok is an AI assistant and chatbot developed by xAI, an artificial intelligence (AI) company founded by Elon Musk in 2023. A post was shared on X by co-founder and an engineer at xAI which gave details about the job description. ChatGPT Down: On Tuesday, numerous ChatGPT users worldwide encountered disruptions, facing error messages and sluggish responses. OpenAI confirmed investigating elevated error rates and latency, prompting users to seek alternative AI tools. Options like Google's Gemini, Microsoft Copilot, Claude, Perplexity AI, and You.com offer similar functionalities for writing, coding, and research, ensuring continued productivity during the outage. OpenAI's ChatGPT is currently experiencing a widespread outage, affecting thousands of users globally who are unable to access the chatbot or generate images with Sora. OpenAI has acknowledged the issues, and recovery efforts are underway as users report "Something went wrong" messages and persistent "searching for web" commands. This is a key announcement for the company, as ET had reported earlier this month that its other products are not seeing much traction. Founders and developers ET had spoken to saw Krutrim's large language models (LLMs) and cloud offerings as subpar and lacking technical maturity compared to hyperscalers. Some universities, including the University of Maryland and California State University, are already working to make AI tools part of students' everyday experiences. In early June, Duke University began offering unlimited ChatGPT access to students, faculty and staff. The school also introduced a university platform, called DukeGPT, with AI tools developed by Duke. Companies that rely on traditional keyword-based search ads could experience revenue declines due to the growing popularity of AI search ads, which offer greater convenience and engagement for users, according to the research firm. This is a notable shift for the US tech major, which has traditionally discouraged its employees from using external AI tools since the company provides its own AI coding assistant called Q and an internal AI chatbot named ‘Cedric’. Last year, Cursor's desktop application gained popularity, particularly for its ability to assist with coding using Anthropic’s Claude 3.5 Sonnet model. Its features got a further boost when Microsoft added the model to GitHub Copilot.
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AI system improves clinical decisions for better patient care at Taichung hospital The technology enables more accurate, faster data analysis. Advancements in artificial intelligence (AI) can play an important role in modern medicine and in providing better patient care and services. The technology fills a significant gap in the medical system by enabling better processing, management, detection, and analysis of large data sets and mathematical algorithms at unequalled speed and precision. Whilst there may be some concerns surrounding this technology, it can help save lives, reduce avoidable medical complications and medical errors, and streamline layers of patient and medical data when properly utilised and trained for specific applications. To reap these benefits, China Medical University Hospital (CMUH) in Taichung, Taiwan, has implemented innovative and specialised AI technologies to aid with complex clinical decision-making in two critical fields of medicine: antimicrobial medicine and cardiovascular medicine. These AI-assistive systems have improved clinical decision-making and clinical outcomes in challenging areas of medicine. For this, CMUH is being honoured as Smart Hospital Initiative of the Year - Taiwan by Healthcare Asia Awards 2023. Slated for presentation on March 29, 2023, the awards programme aims to honour hospitals, clinics and other healthcare providers that have risen and made a remarkable impact on their patients. In cardiovascular medicine, AI is making a difference with fast and accurate ECG interpretation at CMUH, in the form of an innovative wireless or remote 12-lead ECG monitor. The AI detects abnormal heart rhythms that indicate cardiovascular events such as an ST-elevated myocardial infarction (STEMI), which require emergency care in a defined 90-minute window, often referred to as door-to-bed. AI assistance in ambulances also saves time and facilitates triage for better clinical outcomes. The technology is especially helpful in detecting cardiovascular events in patients experiencing chest pain who have atypical symptoms, making timely diagnosis and treatment intervention difficult. Additionally, it prevents treatment delays during busy periods in the hospital and during the off-hours when fewer medical staff are available. With the AI-assistive technology, ECG interpretation times have been reduced to 10 minutes or less, an increase from 24% to 63.4% since implementing ASAP scoring in patients without chest pain. The AI assistance for cardiovascular emergency medicine has also significantly reduced the door-to-bed time during the off-hours period when hospitals have fewer staff in operation. Meanwhile, antimicrobial resistance (AMR) is a critical problem in medicine associated with inappropriate antibiotic treatment and medical error. Over time, microbial pathogens that cause infections adapt to antibiotic medications, making them ineffective and resulting in antimicrobial resistance. It is therefore imperative to make better clinical decisions in antimicrobial medicine through careful microbial pathogen detection and precise antimicrobial medication selection. As a result, CMUH has improved the treatment for microbial infections by guiding antimicrobial medicine selection and effectively reducing the amount of inappropriate antimicrobial medication use and medical error. In addition, the technology can quickly and accurately assess antimicrobial medication resistance against specific microbial pathogens to avoid ineffective treatments and avoid medical complications. Stakeholders of the hospital have also noted reduced hospital expenses and avoidable complications since implementing the AI assistance systems, according to Aichi Chou, CEO of International Center at CMUH. “AI assistance is instrumental because of its ability to analyse large data sets fast and accurately to make good clinical decisions by guiding antimicrobial selection, generating antibiograms, and predicting sepsis and mortality risks which save lives and reduce further medical complications due to ineffective infection treatment,” Chou said. Chou added, “Medical records are often missing detailed annotations regarding previous infections and treatments which further complicates microbial treatment. AI assistance improves the accuracy of medical records through detailed annotations.” The hospital has “received feedback from several patients and their families that they are very grateful for the speed of emergency care when they or their loved one has had a heart attack but are not near a hospital, and especially if it happened during late hours or the middle of the night, she said.
According to statutory provisions of the General Data Protection Regulations (GDPR) users of this website must be informed about the scope, manner and intention of Personal Data collection and processing. LabCognition Analytical Software GmbH & Co. KG is committed to protecting your privacy. This privacy statement explains how we collect your personal data on our website, how we protect your personal data and the rights you have concerning the use of such data. We encourages you to review this Privacy Statement so that you can understand how this Website collect, use and share your Personal Data. What is Personal Data? Personal Data is information that identifies you or can be used to identify or contact you. We collect Personal Data from you when you use our Website as described further in this Privacy Statement. What does Data Processing mean? Data Processing means all required steps performed either manually or by utilizing automatic methods to capture, save, use, modify and update or delete your Personal Data. Which Personal Data is collected on this Website? Through this website we are collecting Contact Data such as your name, address, ZIP code, country of origin, E-Mail address and phone number. We also collect Demographic Data, such as your age, gender, preferences, interests and favorites. We are also collecting Usage Tracking Data such as visited sites, date and time of site visit and dwell time. In addition we are collecting Communication Data such as your IP-address, the type of internet browser and hardware used to access our website. Who collects Personal Data on this Website? Personal Data on this Website is collected by the operating company. Detailed contact information of the operating company are provided further down in the Contact Information of this Privacy Statement or in the imprint of this website. How is Personal Data collected? We collect your Personal Data whenever you disclose them to us. This may happen if you send an E-Mail to us or give us a phone call. Furthermore, you may provide Personal Data through the forms available on this Website. We also collect information, which are generated automatically when visiting our Website by e.g. your computer of smart phone. Such information is then collected by our IT-infrastructure. These are technical information such as the internet browser you are using to visit our Website, which operating system is installed on your device, the date and time of your visit. Such information is collected automatically as soon as you visit our Website. How do we use your Data? We collect information, some of which contains Personal Data that you provide directly to us. The majority of collected data is used to help us understanding your interests and intentions of using our Website and services. We are using such data to ensure the contents on our Website are displayed accurately and to optimize our services for you. Another part of the collected data is used to personalize our services and optimize your customer experience when using our Website. In case you provide your Personal Data to us, we are using it to contact you and communicate with you. Which Privacy Rights do you have? According to the General Data Protection Regulations (GDPR) you have the right to request from us the entire Personal Data saved about you, its origin, recipients (if any) and purpose at any time and free of charge. Furthermore, you may request us to correct, lock and partially or entirely delete your Personal Data. If you have any questions regarding the GDPR you may contact us at any time, especially you may contact the responsibles as stated below in the Contact Information of this Privacy Statement or in the imprint of this Website. Your right to lodge a complaint with the responsible data protection authority remains unaffected thereof. What are Web Analytics Tools and other Third Party Tools? Further details and guidance are provided in the following. Obligations and Advices Privacy and Data Protection We as the operating company of this Website take protection of your Personal Data seriously. All Personal Data provided to us is securely saved and kept in confidence according to the governing Data Protection laws and this Privacy Statement. Using this Website triggers, that miscellaneous Personal Data are collected. Personal Data is information that identifies you or can be used to identify you. This Privacy Statement explains which kind and how we collect Personal Data and the purpose they are used for. Moreover, we point out, that any kind of data transfer through the internet such as communication by E-Mail is not secure at full length. Unfortunately, a complete security chain preventing your Personal Data from unauthorized access, use or disclosure by any third party cannot be guaranteed. Except otherwise stated in this Privacy Statement, we will only use Personal Data for the purpose described therein. According to Art. 13 of the General Data Protection Regulations (GDPR) we explain Personal Data processing to you as follows. The legal basis to request permission from you to collect and process your Personal Data is stipulated in Art. 6(1)(b) and Art. 7 GDPR. Processing of your Personal Data is necessary for the performance of our services. The legal basis for such processing of your Personal Data is therefore Art. 6(1)(b) GDPR. We will not share, sell, transfer or otherwise disseminate your Personal Data to third parties, unless required by law according to Art. 6(1)(c) GDPR, unless required for the purpose of your contract according to Art. 6(1)(b) GDPR, unless we are allowed to do so on the basis of a data processing agreement according to Art. 28 GDPR or you have given us express consent to do so according to Art. 6(1)(a) GDPR. We can disclose your information in order to pursue our legitimate interest in applying or enforcing our terms and conditions or in responding to any claims, in protecting our rights or the rights of a third party, in protecting the safety of any person or in preventing any illegal activity (including for the purposes of fraud protection and credit risk reduction) according to Art. 6(1)(f) GDPR. Data Processing on this Website is performed by the following responsible company: LabCognition, Analytical Software GmbH & Co. KG Koelner Str. 89 50859 Cologne, Germany Phone: +49 221 94102318 The above legal entity is the responsible company, either alone or in cooperation with others to make decisions on the Personal Data purpose and processing tools. Changes to this Statement We will occasionally update or amend this Privacy Statement to reflect company and customer feedback. We encourage you to periodically review this Statement to be informed of how LabCognition Analytical Software GmbH & Co. KG is protecting your information. Right of Access According to Art. 15 GDPR you have the right to request confirmation as to whether we process your Personal Data and where that is the case, to request access to the Personal Data we hold about you. Right to Rectification According to Art. 16 GDPR you have the right to request the completion and/or correction of inaccurate Personal Data. Right to Erasure According to Art. 17 GDPR you have the right to request erasure of Personal Data without undue delay under certain circumstances, e.g. if your Personal Data is no longer necessary for the purposes for which it was collected or if you withdraw consent on which our processing is based according to Art. 6(1)(a) GDPR and where there is no other legal ground for processing. Right to Restriction of Processing According to Art. 18 GDPR you have the right to request us to restrict the processing of your Personal Data under certain circumstances, e.g. if you think that the Personal Data we process about you is incorrect or unlawful. Right to Data Portability According to Art. 20 GDPR, under certain circumstances, you have the right to receive your Personal Data you have provided us with, in a structured, commonly used and machine-readable format and you have the right to transmit that information to another controller without hindrance or ask us to do so. Right to Revocation According to Art. 7(3) you have the right to withdraw your consent to processing Personal Data at any time. A formless message e.g. sent by E-Mail is sufficient to withdraw your consent. The withdrawal of consent does not affect the lawfulness of processing based on consent before its withdrawal. Right to Object According to Art. 21 GDPR you have the right to object to the processing of your Personal Data under certain circumstances, in particular if we process your Personal Data on the legal basis of legitimate interests (Art. 6(1)(f) GDPR) or if we use your Personal Data for marketing purposes. Right to lodge a Complaint before the Data Protection Authority You have the right to lodge a complaint with a supervisory authority, in particular in the EU Member State of your habitual residence, place of work or place of the alleged infringement if you consider that our processing of your Personal Data infringes the applicable data protection laws. Please contact us at the Contact Information mentioned above and we will assist you to identify the respective competent supervisory authority. Security of your Personal Data For data protection and security reasons we secure the personally identifiable information you provide to us on computer servers in a controlled, secure environment, protected from unauthorized access, use or disclosure. When Personal Data is transmitted by our Website, it is protected through the use of encryption, such as the Secure Socket Layer (SSL) protocol or Transport Layer Security (TSL) protocol. You can recognize an encrypted connection in your browser’s address line when it changes from http:// to https:// and/or the lock icon is displayed in your browser’s address bar. In this case all data is securely transferred and cannot be read by any third parties. Data Collection on our Website Our Website is saved on a server infrastructure. The provider of the server saves information on Website visits automatically. Such information is saved in so called Log-Files being transmitted by your internet browser to the server automatically. In particular, the following information is transmitted: - Browser type and version - Date and time of request - (anonymized) IP-Address - Error codes - Operating System - Referrer URL In principle, such information are not merged with other data sources. The legal basis for such processing of your Personal Data are our legitimate interests (Art. 6(2)(f) GDPR) in customizing the content of our Services in line with user preferences and in further improving our Services. As part of any recruitment process, we collect and process Personal Data relating to job and apprentice applicants. We collect a range of Personal Data about you such as: - your name, address and contact details, including E-Mail address and telephone number - details of your qualifications, skills, experience and employment history - information about your current level of remuneration - whether or not you have a disability for which the organisation needs to make reasonable adjustments during the recruitment process - information about your entitlement to work in Germany - equal opportunities monitoring information, including information about your ethnic origin, health and religion or belief. We collect this information in a variety of ways. For example, data might be contained in application forms, E-Mails being sent to us, CVs, obtained from your passport or other identity documents, or collected through interviews or other forms of assessment. We will also collect Personal Data about you from third parties, such as references supplied by former employers, information from employment background check providers including information from criminal records checks. We will seek information from third parties only once a provisional job offer to you has been made and will inform you that we are doing so. Data will be stored in a range of different places, including on your application record, in our IT systems (including email). We have a legitimate interest in processing Personal Data according to Art. 6(2)(b) GDPR during the recruitment process and for keeping records of the process. Processing data from job or apprentice applicants allows us to manage the recruitment process, assess and confirm a candidate's suitability for employment and decide to whom to offer a job or apprenticeship training position. We may also need to process data from job applicants to respond to and defend against legal claims. We will not use your data for any purpose other than the recruitment exercise for which you have applied. Your information will be shared internally for the purposes of the recruitment exercise. This includes members of the HR department, interviewers and others involved in the recruitment process if access to the data is necessary for the performance of their roles. If your application for employment or apprenticeship is unsuccessful, we will hold your data on file for two months after the end of the relevant recruitment process. If your application for employment or apprenticeship is successful, Personal Data gathered during the recruitment process will be transferred to your personnel file and retained during your employment. Should you send us questions or requests via a contact form, we will collect the data entered on the form, including the contact details you provide, to answer your questions or process your requests and any follow-up questions and requests. We do not share this information without your permission. We will, therefore, process any data you enter into the contact form only with your consent per Art. 6 (1)(a) GDPR. You may revoke your consent at any time. An informal E-Mail to email@example.com making this request is sufficient. Alternatively, you may revoke your consent by submitting your email address using the revocation form https://www.labcognition.com/en/revocation.html. The data processed before we receive your request may still be legally processed. We will retain the data you provide on the contact form until you request its deletion, revoke your consent for its storage, or the purpose for its storage no longer pertains (e.g. after fulfilling your request). Any mandatory statutory provisions, especially those regarding mandatory data retention periods (6 years in terms of commercial law and 10 years in terms of fiscal law), remain unaffected by this provision. Processing of Customer and Contractual Data We need your Personal Data to comply with our contractual obligations. Therefore, we have a legitimate interest in processing your Personal Data according to Art. 6(1)(b) GDPR. For example, where you have provided us with your E-Mail address to receive our services or products, we will use this information in order to effectively deliver and communicate information to you in regard to such products and services. We will retain the data you provide us until the contractual obligations are fulfilled. Any mandatory statutory provisions, especially those regarding mandatory data retention periods (6 years in terms of commercial law and 10 years in terms of fiscal law), remain unaffected by this provision. Matomo (formerly PIWIK) - your IP-Adress (anonymized prior to its storage) - the visited Website URL - the Referrer-URL - Sub-Websites being visited from this site - the duration of your visit - the frequency of repeated visits of the Website We have a legimate interest in using this tool according to Art. 6(1)(f) GDPR to ensure contents on our Website are displayed accurately and to optimize our services for you. We will retain the information until our monitoring obligations are fulfilled. This is the case after 500 days by default. Our Website use "cookies" to help you personalize your online experience. A cookie is a text file that is placed on your hard disk by a Website server. Cookies cannot be used to run programs or deliver viruses to your computer. Cookies are uniquely assigned to you, and can only be read by a web server in the domain that issued the cookie to you. One of the primary purposes of cookies is to provide a convenience feature to save you time. The purpose of a cookie is to tell the Web server that you have returned to a specific page. For example, if you register with our services, a cookie helps us to recall your specific information on subsequent visits. This simplifies the process of recording your personal information, such as billing addresses, shipping addresses, and so on. When you return to the same Website, the information you previously provided can be retrieved, so you can easily use the our features that you customized. You have the ability to accept or decline cookies. Most Web browsers automatically accept cookies, but you can usually modify your browser setting to decline cookies if you prefer. If you choose to decline cookies, you may not be able to fully experience the interactive features of our services or Web sites you visit.
Rise of Social Engineering: Types of Social Engineering Attacks (Part 2) After a prelude to the concept of social engineering as an emerging form of cybersecurity attack, let’s explore the different forms your enterprise may likely encounter. First, let’s have a quick look at some stats on social engineering assaults: - An average business encounters nearly 700 social engineering attacks annually. - 50% of social engineering attacks are pretend incidents, in which threat actors create scenarios to convince victims to reveal sensitive data. - About 90% of data breach incidents target human elements, as it is easier to trick employees into sharing confidential information to gain access to systems and networks than to surpass security firewalls. - 86% of organizations have at least one employee who has clicked a phishing link. From the above stats, we have established that social engineering attacks are frequent, maliciously well-planned, mainly leverage human vulnerability, and always target people. Below, we have identified some common types of social engineering attacks cyber criminals use. Ten Common Types of Social Engineering Attacks - Phishing: The most common cybersecurity attack is phishing. It involves enticing a target or users into clicking a suspicious link, downloading virus-infected files, or inadvertently revealing confidential information like email credentials, passwords, account details, etc. Phishing attacks can occur over emails, SMS, voice conferencing, and cloud-based file-sharing platforms. FBI’s 2020 Internet Crime Report found that phishing is a widespread cybersecurity crime in finance. According to Check Point Research, the technology industry is most vulnerable to brand phishing (hackers imitate leading brands), followed by shipping brands and social media networks. In 2022, hackers targeted victims, imitating brands like Yahoo, DHL, Microsoft, Google, Netflix, and HSBC. - Baiting: As the term suggests, baiting involves luring victims with appealing messaging to download a file or click on a link to redeem gifts and offers. The links may redirect users to fake websites or a webpage that captures and shares login credentials with attackers. Baiting promises free software downloads or malware-ridden flash drives deliberately left in places that trigger victims’ curiosity to explore and fall prey to the attacks. Baiting scams include online forms, job application sites, and craftily labeled ads to entice users. - Whaling: Whaling is a hyper-personalized attack targeting a particular user. Unlike phishing attacks that target millions of users, whaling involves outreach based on deep research on an individual’s social media activity, online persona, and other behavior. Whaling is generally targeted to individuals of high net worth or high-profile job roles to access confidential data that can be held for ransom. - Quid pro quo: This attack implicitly solicits confidential data in exchange for a service. For instance, a cybercriminal can infiltrate a workplace and ask for an employee’s user credentials to resolve an IT incident. Then, the cybercriminal can leverage that information to access confidential data or sell it for ransomware. - Pretexting: Pretexting is a different form of social engineering attack that convinces victims with believable scenarios or information to share valuable and confidential data. A pretexting incident can involve attackers posing as someone of high authority, like a law enforcement personnel or tax official, to earn their victims’ trust and gain the information they need. - Scareware: Scareware is pop-up windows or alarming notifications about a virus download or other cybersecurity-related urgencies that can drive a victim to purchase anti-virus software or other tools to mitigate further risks and damage. - Tailgating: Tailgating happens in the physical world, where attackers physically access or enter restricted spaces. For example, an individual can pretend to be an employee who has forgotten their identity card and convince security to allow them into a restricted place like an office or place of business. - Honeytraps: Honeytraps are common on social networking platforms that involve virtually building a romantic relationship with victims to earn their trust and mislead them into revealing confidential information. - Diversion Theft: Diversion thefts occur in both online and offline situations. In the online scenario, attackers can steal data from an employee over email by pretending to be someone working in the same organization. - Watering Hole: Watering Hole targets websites and online platforms that target victims to visit or log in by adding their credentials. The attackers steal victims’ login details by infiltrating their network or through a trojan attack to access the network. Social Engineering: Ten Obvious Giveaways Social engineering delivery methods usually involve communication and messaging platforms that victims are known to use regularly or log in using credentials. Even though most of these cybercrimes look legit and convincing, there are red flags that help users identify a possible threat. Cybersecurity research and facts based on survey reports reveal that the tactics social engineers use aren’t rocket science. All one must do is look closely, and clues are hidden in plain sight. Below are some of the essential social engineering giveaways that your enterprise can use to educate your workforce and avert costly human errors: - The messages or offers are always too good to be true. - Attackers usually know their victims well. - Messages or communications soliciting information or money are immediate cybersecurity red flags. - Real-life phishing emails have poor grammar and spelling errors. - Compare URLs and links for safety and recognize malicious links. - Most social engineering attacks have a pattern. For example, phishing emails have specific subject lines, and common attack vectors include links, PDF attachments, fake brand/business logos and names, and login landing pages. - 91% of bait emails are sent via Gmail accounts, which are free to create and mostly reputable. However, one must be wary of what’s in the inbox. - Emails with hidden threats have read receipts to inform attackers when the victims open the mail. - Subject lines overdo the convincing bit by claiming to be from a reputed brand or a business. - Internal parties like employees can be involved in fraud. Barracuda research found that 34% of business owners reportedly said employees would be involved with attackers, and 21% revealed that their employees were behind the fraud. Social engineering attacks prove that the ‘people factor’ dictates an organization’s approach to cybersecurity practices, processes, and investments in technology. At iTech GRC, we help enterprises maximize IBM OpenPages with Watson to stay ahead of their data privacy, internal risks, and IT governance practices. Our experts help actively manage and mitigate risks that can compromise cybersecurity and safety using the integrated GRC solution. Contact our teams to learn more about OpenPages’ AI capabilities for managing your end-to-end GRC objectives in the age of GenAI.
06/03/2025 / By Willow Tohi In a move critics call a tyrannical encroachment, the Trump administration is harnessing Palantir Technologies — a firm co-founded by hard-right billionaire Peter Thiel — to centralize massive amounts of sensitive U.S. citizen data across federal agencies. Since President Trump’s inauguration, Palantir has received over $1.3billion in contracts, including a $795 million Department of Defense award, to deploy its Foundry system, which merges disparate datasets. This “data lake” project, driven by Elon Musk’s controversial Department of Government Efficiency (DOGE), could enable unprecedented surveillance powers, with bipartisan privacy advocates condemning it as a threat to civil liberties. The plan, spurred by an executive order targeting “information silos,” has sparked internal dissent at Palantir, lawsuits by rights groups, and stark warnings over security flaws. The administration’s financial stake in Palantir has grown exponentially since the November election. Contracts for Foundry — a tool organizing taxpayer records, healthcare data, and immigration files — now span at least four agencies, including ICE, the Department of Health and Human Services and the IRS. By consolidating disparate databases, officials could potentially cross-reference details like Social Security numbers, student loans, and medical histories, enabling targeting of critics or undocumented migrants. Palantir’s Foundry was already credited with tracking migrants in real time under a $30 million ICE contract. Meanwhile, engineers worked to centralize IRS records, while DOGE officials lobbied to merge Social Security and immigration data. The firm’s expansion into revenue-focused agencies like the IRS suggests a financial SWAT team prioritizing partisan efficiency over privacy, critics argue. “This amounts to a data iceberg; what floats now is terrifying, but we don’t know what’s hidden beneath,” warned Linda Xia, a former Palantir engineer who co-signed a letter urging the company to halt its “reckless” collaboration. Behind the scenes, Palantir faces an internal revolt. Over a dozen former staff signed onto a recent editorial decrying the profit-driven erosion of their company’s ethical reputation. Brianna Katherine Martin, a departing strategist, posted on LinkedIn that her “red line” was crossed after the firm expanded ICE contracts. Current employees cited lax security practices among DOGE personnel, including unsecured devices, which could expose databases to hacking — or abuse. “The concentration of this data in a single system increases the risk of both breaches and political weaponization,” said Mario Trujillo of the Electronic Frontier Foundation. “A system designed to catch illegal immigrants could easily be used to silence dissenters.” Palantir claims it serves as a “data processor,” denying responsibility for policy misuse. But its longtime role in militarized projects — from founding with the Pentagon in 2003 to aiding ICE—underscores its instrumentalization by power-hungry regimes. Palantir’s involvement in invasive state projects predates Trump. In 2010, it partnered with HBGary to suppress WikiLeaks after the site exposed Bank of America’s misconduct, a move seen as targeting free speech. A 2024 court filing also revealed Palantir engineered a flaw in FBI software that allowed unauthorized access to classified files. Its role in Biden-era CDC vaccine distribution ameliorated some reputational blows, but its ties to Thiel deepen public distrust. Now, as Palantir’s stock surges (up 140% since Trump’s return), the firm risks cementing its image as a tool for authoritarian governance. “We’re not just facing a data breach—we’re witnessing the collapse of institutional check,” said Xia. Civil liberties groups have launched 11 lawsuits challenging the data project, arguing it violates privacy and due process. Democrats and progressive advocates accuse Trump of weaponizing tedium against critics, while libertarian Republicans decry the invasive scale. Even Palantir CEO Alex Karp (a Democratic donor) recently praised Musk as a “qualified” government reformer—a contradiction criticized as corporate opportunism. The White House deflected inquiries, citing the original executive order’s “efficiency” mandate. But as more Palantir engineers flee and dissent grows, the administration’s technocratic blueprint risks becoming a liability—and a blueprint for future resistance against surveillance states under any party. With Palantir’s datasets growing and public trust eroding, the Trump administration has set a dangerous precedent linking federal overreach with Silicon Valley profit. While the administration frames its efforts as commonsense modernization, critics see a dystopian vision of power — a vision where every American’s life is itemized, monitored and politicized. As whistleblower employees and legal challenges grow, one question remains piercing: Who appoints the guardians of such colossal data systems? Sources for this article include: big government, civil rights, computing, conspiracy, cyber war, Dangerous, deception, deep state, freedom, Glitch, government debt, information technology, Liberty, national security, outrage, privacy watch, Resist, revolt, Suppressed, surveillance, Trump, Tyranny, uprising, Whistleblower, White House This article may contain statements that reflect the opinion of the author COPYRIGHT © 2017 LIBERTY NEWS
Data Science is one of the most amazing technological fields which is directly responsible for innovative and effective digital solutions that we have today. It has influenced the global economy significantly and branches emerging out of it are providing ground-breaking results in the world of machines. Most interestingly, data science has emerged as ‘the dream’ field of career for ambitious and talented individuals world-wide. The job of a data scientist has already been termed as the ‘Sexiest’ of the century by the Harvard Business Review and in essence data science has helped in creating many new jobs which are both good paying and highly revered! However, many wonders about the key to success in Data Science and most importantly the skills that one should master before venturing out in search of lucrative jobs. Is Python the key! Recent surveys by multiple firms suggest that the popularity of Python in Data Science has grown significantly over the last few years. For instance, in a recent survey undertaken by Kaggle on 16000 data science professionals, it was found out that 87% of the total participants use Python regularly for various data science works! In another survey conducted by the Analytics India Magazine it was claimed that as many as 44% of data scientists of the entire world use Python! According to leading technological training firms, most data science job postings mention Python and the demand for Python skills is particularly high in countries like India and Malaysia. Thus, Python seems like the most important skill to master to launch a career in data science. But why Python? Well, if you are wondering that why Python is being preferred more than statistical programming languages like R, then let us discuss a few advantages which Python offers over its rivals: - Greatest advantage of Python- Simplicity and Flexibility Data scientists today come from a variety of background and may or may not possess coding skills. For such individuals, mastering R can be very difficult and even though its not impossible yet data scientists today do not like to spend precious time on coding compliances and memorizing complicated Syntax. Python on the other hand is fairly simple to learn and apply for a variety of data science activities. It has the easiest learning curve and with a Python data science course, in no time you will be using Python like a pro for various data science jobs! - Python offers dedicated packages for crucial data science activities Data scientists requires dedicated software suits capable of handling jobs like data manipulation, advanced scientific calculations and data visualization. Python libraries like NumPy, SciPy and Matplotlib offers all of that and are quite popular among data scientists. Pandas is another Python library which is very popular because it offers developing ML and even DL models with it! Moreover, Python is open-source and boasts a great support community and thus it is gradually becoming ‘The’ data science skill that every budding data scientist should have. And with a Python Data science course in India you can acquire Python skills too!
IHS and OSIsoft have announced a strategic alliance to help clients achieve their sustainability goals. The deal targets ‘surging’ global demand for data collection, integration and information management solutions focused on enterprise sustainability management (ESM). OSIsoft president Bernard Morneau said, ‘Organizations are under pressure to make informed decisions affecting the sustainability of their business. IHS offers a flexible combination of software and content that will help clients address these new business imperatives.’ Currently, ESM challenges are addressed with ‘with disparate manual processes, spreadsheets and one-off legacy systems.’ These are failing to aggregate today’s increased data volumes. IHS senior VP sustainability Woody Ritchey added, ‘Clients need to leverage real-time process and event data. We have integrated OSIsoft’s enterprise-wide data collection and archiving solution with our applications to make sustainability an essential part of their business.’ The announcement cites one Asian utility using IHS and OSIsoft solution to process five million real-time records per month along with ‘vast quantities’ of historic data, tuning production to fuel inventory, demand forecast and environmental impact. More from OSIsoft and IHS. © Oil IT Journal - all rights reserved.
Algolia’s API first approach allows you easily to experiment with new experiences and front ends without the need for back end engineering The advent of AI heralds a revolutionary opportunity that will change how merchandisers operate & strategize, but ecommerce businesses will face new challenges as they integrate AI-powered technology. Your homepage is the window into your store. But how do merchandisers maximize the power of their online real estate to drive sales, brand experiences, and other critical outcomes? Zeeman deployed Algolia in record time and hasn’t looked back, iterating, and improving on Search to the benefit of its customers, its e-commerce and merchandising teams — and its revenue.
We are a research entity working with financial tech companies to build new and exciting technology. The current research program we are running aims to improve the credit approval process for loans and insurance. By empowering workers with full access and control of their work history and employment data, financial companies need to rely less on outdated models like credit scores. The goal of our research is to learn more about payroll processes and systems in order to put people in charge of their own data. The current research program’s mission is to empower workers with full access and control of their work history and employment data. The research program aims to improve the credit approval process for loans and insurance. By allowing an individual to have full access to his payroll data, we can rely less on outdated models like credit scores and focus on what truly matters – an individual’s ability to repay a loan or make a claim. Build worker-centric tools that harness the power of data, expand financial access, and enable credit evaluations beyond the confines of traditional credit scores. Your account connections help to develop technology that allows workers to have more control over their payroll data. By connecting your accounts to our system, we can run compatibility tests and understand how data is organized by various companies and payroll systems. We are looking for people who work (or used to work) at various companies to join our research initiative and share their information with us. The process of participating in our research program is simple. You’ll need to connect your account(s), allow it to run in the background, and perform periodic checks. You’ll also need to be available to answer a few questions about how you use your account(s). We understand that there are websites out there designed to trick people into buying items or getting your credit card information. We’ll never ask you to pay for services or store your credit card information. We will need some personal information to transfer funds to your bank account, but that information in no way would allow us to do anything other than deposit funds into your account once you’ve been validated and cleared to participate in our research. We’re 100% real and we’ve worked with thousands of happy users, here’s some reviews you can dive into. If you have additional questions, send us an email and one of our team members would be happy to chat with you. Participating in our research program is easy and quick. Simply sign up on one of our research websites or email us for more information on how to participate. We never sell, share, or reuse your information, and all of your information is kept stored inside Spindle’s servers, which are encrypted and protected. Yes, all our your information is encrypted using the Google Advanced Encryption Standard. Yes, Spindle staff have access to your information but cannot see your password. To safeguard your details, we monitor and log any use of your information by any Spindle representative. For your anonymity and to maintain confidentiality, your employer is not notified of your participation with Spindle, and we operate independently from them as well. People routinely share accounts, everything from Netflix to banks, and the process Spindle uses is in line with industry standards. Your employer may not authorize sharing this information. We may need to make small changes in order to collect the data you’ve consented to provide. Spindle’s core mission is to help workers own their data. Your account is one small piece of building a better future where individuals own the data they generate. By connecting your account, we are able to explore the structure of data and analyze how these systems are built, ultimately allowing us to standardize the information in a way that is useful across financial services. Spindle’s servers operate throughout the world, and because of our security protocols that monitor your account, your account could be accessed from one of many server locations. If you suspect unauthorized activity, please contact member support. Yes, you can opt-out at any time and all of your data will be immediately deleted. Reach out to member support or email us. No, we immediately stop using your information. In order to participate in Spindle, you’ll need to have an accessible account with your employer(s). However, you don’t need to currently work there (only your account needs to be active and working). Yes – people work for multiple employers and you can connect multiple accounts. We’re interested in an ever-evolving set of accounts – to see a full listing please contact member support. Yes, we do offer a referral bonus. Please, email member support to learn more. Because our staff is global, and to efficiently assist members, our support team uses SMS and email to communicate. Text or email us and we’d be happy to help. Email us with your updated information. Please reach out to member support to update. It is ongoing and we encourage your participation as long as you’re able to. We primarily operate on weekdays, around the clock, but sometimes we have an influx of requests and ask for your patience. We answer most weekday inquiries within 12 hours (weekend inquiries will be answered on the next business day). Typically, onboarding takes 10 minutes or less but does require you to be actively present during this time. Our team is global, remote-first without a physical office space. We currently use Paypal to process your funds. You should get paid immediately after application acceptance. You should know of your application status within 48 hours. We’re actively working on expanding our payment methods. Please check in with member support. Payment processors hold money when they need to undergo additional security checks, please reach out to your payment processor directly. We are happy to support you during this process but you’ll have to talk to them directly first. The first business day of the month. Our payment system is automated and cannot be sent early. By referring more people and by connecting more accounts to the Spindle platform. Please email or text member support.
UNITED KINGDOM-BASED recruitment agency, WorkReel, is expanding into Zimbabwe to help businesses and employees use newer methods to employ people and to seek jobs. As of September, 2023, about 3,12 million people were employed in Zimbabwe out of the 8 955 312 working-age population, according to the Zimbabwe National Statistics Agency (ZimStat). However, most of that employment is in the informal sector with the official employment standing at about 1,55 million based on the third quarter ZimStat labour statistics. Unemployment remains high in the country due to an unrelenting economy recession. Speaking to NewsDay Business, WorkReel Africa Region head Stephen Mashingaidze urged businesses to use artificial intelligence (AI) in its recruitment processes. “AI will primarily speed up talent identification because we make employment as we are creating employment using videos instead of using traditional tools. This can minimise the use of traditional tools, especially in Africa and can be achieved through investing in the innovation of information technology (IT) infrastructure,” he said. “Currently we have an office at Batanai Mall which you know is also used for SMEs (small and medium enterprises). Our main office is in the UK and I’m the head of African Region.” AI is the simulation of human intelligence processes by machines, especially computer systems, which can be applied to expert systems, natural language processing, speech recognition and machine vision. “The investment that we are looking at now is minus/plus US$5 million and currently we are at about US$50 000 estimation, the investment will help us with infrastructural development,” Mashingaidze said. This development will allow WorkReel to scale up its operations. “We are looking at investing in IT infrastructure, primarily in Artificial Intelligence, as the country is pushing towards the innovation hub conference as we understand the country does not have quantity to build. So, we are partnering with people around the world like UK, Australia and African countries,” Mashingaidze said. He said WorkReel was going to help employees and employers in terms of development in IT innovation and this can be done through learning. “AI has become increasingly important in today’s world as it has the potential to revolutionise many industries, including healthcare, finance, education and more. The use of AI has already improved efficiency, reduced costs and increased accuracy in various fields,” Mashingaidze said.
Data and Privacy Policies TERMS OF DELIVERY Swedish main branch Törmi Design Ab 559306-2689 972 32 Luleå Törmi Design Oy 3317229-8 Puistokatu 13 C 12 TERMS OF DELIVERY Product prices include VAT. We reserve the right to change prices and delivery costs. When trading, we follow the trading instructions given by the Finnish Consumer Agency to online retailers. These general terms and conditions ("General Terms") apply when ("Customer" or "you") place an order from Törmi Design Ab ("Company" or "we") at https://www.tormidesign.fi, (" website"). Official company name: Törmi Design Ab (Törmi Design Oy) Social security number: 559306-2689 (3317229-8) By accepting these general terms and conditions, you confirm that you are at least 18 years old or have the permission of a legal guardian and that you comply with the general terms and conditions. You also confirm that you have read the information about personal data and cookies, and you agree to the use of this information. Products are ordered by moving them to the shopping cart and paying via the link provided by the shopping cart. All customer information is treated confidentially. When ordering from the online store, you are required to have familiarized yourself with and agreed to the delivery conditions valid at any given time. You are responsible for ensuring that the personal information you provide is correct and complete. We process personal data in matters related to customer management, in customer communication, in the marketing of the services we offer, and in the development of services in accordance with our privacy statement. Information (e.g. the subscriber's IP address) can be handed over to the police in connection with the investigation of possible cases of abuse and attempted fraud. PRICES AND CHARGES The prices indicated on the website apply to orders placed on the website. All prices are in the currency stated on the website and include VAT. We reserve the right to price changes, for example, in a situation where the product has been wrongly sold at a clear loss. ORDER AND DELIVERY The products in stock are delivered within 3-5 business days of the order. If the delivery is delayed, we will contact the customer separately. You can cancel the order if the delivery is delayed by more than 30 days and the delay is not your fault. If the product is not picked up in time and it is returned to the sender, we will charge the total amount of the shipping costs for the return of the product. Customers ordering from countries outside the EU are responsible for possible import duties and taxes. Delivery costs vary depending on the country of delivery. RIGHT TO CANCEL/REFUND THE ORDER The customer has the right to return the ordered products within 14 days of receiving the products. Return instructions can be obtained by contacting firstname.lastname@example.org. Please return the products in their original packaging and in the condition in which the products were when they arrived. If the product is no longer in perfect sales condition, we will deduct the value reduction from the amount to be returned. The customer is responsible for the product return fee. Törmi Design doesnt't refund shipping costs. We will pay the refunded amount as quickly as possible, but no later than 14 days after the return arrives. The return will only be made after the products to be returned have arrived. The refunded amount will be returned to the payment method that was used when placing the original order. The return does not apply to custom-made products. WARRANTY AND CLAIMS The order confirmation serves as a warranty certificate. The warranty only covers original manufacturing defects. If the products show damage caused by normal use or abuse, the warranty is not valid. In the event of a warranty, contact us by e-mail and provide the following information: subscriber's contact information, order number, product name and a picture of the product being advertised. If the product can be repaired, it will be repaired first. If it is not possible to replace the product, it will be replaced with a similar or equivalent product. If the product is not exchangeable, we will refund you the price of the product in accordance with the applicable consumer protection legislation and we will be responsible for the costs of returning the products to us. If, in the event of a complaint, the disagreement regarding the sales contract cannot be resolved through negotiations between the parties, the customer can refer the matter to the Consumer Disputes Board (www.kuluttajariita.fi) for resolution. Before taking the case to the Consumer Disputes Board, the customer must contact consumer advice (www.kuluttajaneuvonta.fi) PRIVACY / PERSONAL INFORMATION You have the following rights in relation to your personal data: right to get all of your personal data the right to correct or remove your data the right to restrict processing the right to object to processing the right to transfer data Törmi Design may hand over some necessary information to third parties, for example to guarantee delivery or for marketing purposes. We pass on information to the following third parties: To the transport company To PayPal, when the customer chooses PayPal as the payment method To Klarna, when the customer chooses Klarna as the payment method To the credit provider, when the customer chooses a credit card as payment method If you want to know what information is stored about you, send your inquiry to email@example.com You have the right to have your personal data deleted from Törmi Design Ab without undue delay, and Törmi Design Ab is also obliged to delete personal data, for example, when the personal data is no longer needed for the purposes for which it was collected or otherwise processed or you have withdrawn your consent, on which the processing is based. Customer Register Data Protection Statement 27 March 2023 Swedish main branch Törmi Design Ab 972 32 Luleå Törmi Design Oy Puistokatu 13 C 12 3317229-8 / 559306-2689 Person handling registry matters: Törmi Design Ab 972 32 Luleå Please send contacts regarding registry matters to firstname.lastname@example.org We collect personal data to manage the customer relationship. The legal basis for the processing of personal data is the agreement between us and the resulting statutory obligations. Providing personal information is a prerequisite for the creation of a contract. In other words, you cannot order goods from our online store if you do not provide your personal information. We also collect personal data for marketing purposes. The legal basis for processing personal data is consent. We collect three types of information about you: information that can be observed from the use of online services, information that you provide yourself, and information that can be managed with the help of analytics. Name of the register: Törmi Design Ab's customer information register Personal data processed by Törmi Design: We or our partners collect and process the following information: Customer and contact information: Name, address, phone number and log-in information (email address and password), transaction language, electronic marketing permits and purchase history from online stores and stores. When you place an order from the online store, we also collect information about the delivery method and payment method from you. Information related to the use of the website: Website events, such as side screens, adding to the cart or wish list, ordering a reminder message for an out-of-stock product, order information, delivery methods, payment methods and login information. E-mail marketing / Shopify: Name, address, e-mail address and information about e-mail marketing events, such as message delivery, opening and clicks and management of marketing permissions. The data used are e.g. e-mail address, information about possible purchase history, newsletter delivery, opening and click data, as well as online store browsing history. We use the information to target advertising in such a way that you receive advertisements from us that are of interest to you. Information related to website development: We use the information we collect to develop our services and improve customer service. We use Google Analytics and Shopify's analytics. For such analyses, we mainly only use aggregate level or Anonymous data. Some of this information may be classified as personal information. These include e.g. IP address, date and time of service use, hardware, software, internet browser and information about the operating system, application version and language settings of the device used. Other communication: If you have products left in the shopping cart, we will remind you. In this case, you don't have to add the products to the shopping cart again. Your personal data will be received by: Our company and its employees. Payment intermediaries that receive payment from you. Depending on the payment method used, in addition to the name, address and order and payment information, in connection with certain payment methods, the account number, social security number or the last 4 digits of the credit card are also processed in a manner determined independently by the service provider. The transport company that transports the goods to you. An accounting office that records the order in our accounting. An auditor who audits our accounts. Shopify, the company responsible for email marketing, if you have accepted email marketing. We store your personal data: We only keep your personal data for the time necessary to fulfill the purposes here. In addition, some information can be kept longer to the extent that it is necessary to fulfill the obligations set by law, such as accounting and consumer trade responsibilities, and to demonstrate their proper implementation. You have the following rights: The right to check your personal data. Right to rectification of data. The right to restrict processing (for example, you can prohibit marketing). The right to object to processing. The right to withdraw consent (for example, you can withdraw your consent to marketing). The right to file a complaint with the supervisory authority. Please note that you only have the "right to be forgotten" if we have no legal obligations to continue processing your personal data. Purpose of the register: The register is used to manage the online store's customer relations, order processing and archiving, as well as for the development, evaluation and marketing of the company's operations when the customer approves. Regular sources of information: Törmi Design Ab's own customer data has been used as the data source for the register. When subscribing/making an order for the newsletter, the customer enters the information into the system himself or reports it by e-mail. Regular data transfers and data transfers outside the EU or the European We use some external service providers. Some of these partners may have access to your personal data both inside and outside the EU and EEA. If data is transferred or handed over, it is done securely in accordance with the EU data protection regulation and personal data is protected as required by the Personal Data Act. Principles of registry protection: The access right is granted only to persons bound by confidentiality and familiar with the use of the register, whose position and tasks the access right is related to. The register is located on a secure server, the information of which can only be accessed after two-step authentication. According to the Personal Data Act, the customer has the right to check his data in the register. Törmi Design Ab can delete information from the register without requests, and the person entered in the register can ask for their information to be deleted. It is possible to stop subscribing to the newsletter and/or edit your own information from the link at the end of each newsletter or by contacting us by phone or email. Changing the privacy statement:
Maximizing Digital Engagement in the Crypto Ecosystem with AI-Powered Smart Marketing Innovations The intersection of artificial intelligence and cryptocurrency has given rise to a new era of digital engagement, particularly within the crypto community. As tech-savvy enthusiasts and digital innovators continue to explore the vast potential of blockchain technology, the need for sophisticated marketing strategies becomes increasingly apparent. This article delves into the ways AI can be leveraged to enhance presence and maximize impact in the digital ecosystem, focusing on smart marketing innovations that cater to the next generation of solutions. The crypto landscape is characterized by its rapid evolution, high volatility, and global reach. These factors combined create a unique challenge for marketers aiming to engage audiences effectively. Traditional marketing methods often fall short in this dynamic environment, where user attention spans are short and information overload is rampant. AI-driven strategies, however, offer a promising solution by providing personalized, data-driven, and real-time engagement opportunities. Understanding AI in Crypto Marketing Artificial intelligence encompasses a range of technologies including machine learning, natural language processing, and predictive analytics. In the context of crypto marketing, these technologies can be harnessed to analyze vast amounts of data, identify patterns, and make informed predictions about user behavior and market trends. This capability is crucial for creating targeted campaigns that resonate with specific audience segments. Machine learning algorithms, a subset of AI, can learn from historical data to improve their performance over time. In crypto marketing, this means that campaigns can become more refined and effective as they adapt to user interactions and feedback. For instance, AI can optimize ad placements, content delivery, and even the timing of messages to maximize engagement and conversion rates. Personalization through AI One of the most significant advantages of AI in crypto marketing is its ability to deliver personalized experiences. By analyzing user data, AI systems can create tailored content and offers that align with individual preferences and behaviors. This personalization not only enhances user engagement but also builds trust and loyalty. For example, AI can analyze a user's browsing history, social media activity, and transaction patterns to recommend specific crypto assets or services. This level of customization ensures that users receive relevant and valuable information, increasing the likelihood of interaction and conversion. Personalization also extends to customer support, where AI chatbots can provide instant, personalized assistance, further enhancing the user experience. Predictive Analytics for Proactive Engagement Predictive analytics is another powerful tool in the AI toolkit for crypto marketers. By analyzing historical data and current trends, AI can forecast future behaviors and market movements. This foresight allows marketers to proactively adjust their strategies, staying ahead of the curve and maintaining a competitive edge. For instance, predictive analytics can identify potential shifts in user interest or market sentiment, enabling marketers to pivot their campaigns in real-time. This proactive approach ensures that messaging remains relevant and impactful, even in the face of rapidly changing conditions. Additionally, predictive models can help identify high-value audience segments, allowing for more efficient allocation of marketing resources. Enhancing Content Creation with AI Content is king in the digital realm, and AI can significantly enhance the creation and distribution of high-quality content. Natural language processing (NLP) technologies can assist in generating insightful articles, social media posts, and even automated responses to user inquiries. These tools can help maintain a consistent flow of relevant content, keeping the audience engaged and informed. AI-powered content analysis tools can also evaluate the performance of existing content, providing insights into what resonates with the audience and what does not. This data-driven approach enables marketers to refine their content strategies, focusing on topics and formats that drive the most engagement. Furthermore, AI can automate the content scheduling process, ensuring that posts are published at optimal times to maximize reach and interaction. Social Media Engagement and Community Building Social media platforms are vital for crypto communities, serving as spaces for discussion, collaboration, and information sharing. AI can significantly enhance social media engagement by automating and optimizing various aspects of community management. For example, AI-driven tools can monitor and analyze conversations, identifying key topics and sentiment trends. This information can be used to spark meaningful discussions and address user concerns proactively. AI chatbots can also play a crucial role in community building by providing 24/7 support and engaging with users in real-time. These chatbots can handle routine queries, offer personalized recommendations, and even facilitate peer-to-peer interactions, fostering a sense of community and belonging. By leveraging AI in social media, crypto projects can build stronger, more engaged communities that drive long-term growth and loyalty. Influencer Marketing Amplified by AI Influencer marketing remains a powerful strategy in the crypto space, but traditional methods can be time-consuming and less effective. AI can amplify influencer marketing efforts by identifying the most influential voices within specific niches and predicting their impact on audience engagement. Machine learning algorithms can analyze influencer performance data, such as engagement rates, follower growth, and content reach, to select the best partners for a campaign. Moreover, AI can help manage influencer relationships by automating communication, tracking performance, and optimizing content collaborations. This streamlined approach ensures that influencer campaigns are executed efficiently and effectively, maximizing their return on investment. AI can also monitor the sentiment around influencer partnerships, providing insights that can be used to adjust strategies and improve outcomes. Security and Trust through AI Security is a paramount concern in the crypto world, and AI can play a critical role in enhancing trust and security for users. AI-powered security solutions can detect and mitigate threats in real-time, protecting user assets and data from cyber attacks. Machine learning algorithms can analyze patterns of suspicious activity and flag potential security breaches before they occur. Additionally, AI can be used to verify the authenticity of crypto assets and transactions, reducing the risk of fraud and enhancing user confidence. By integrating AI-driven security measures, crypto projects can create a safer and more trustworthy environment, encouraging broader adoption and participation. Challenges and Considerations While AI offers numerous benefits for crypto marketing, it is essential to acknowledge the challenges and considerations involved. One major concern is data privacy and compliance with regulations such as GDPR. AI systems must be designed to handle user data responsibly, ensuring transparency and adherence to legal standards. Marketers must also be cautious about over-reliance on AI, as human intuition and creativity remain invaluable in crafting compelling narratives and strategies. Another challenge is the potential for AI to be perceived as impersonal or intrusive. To mitigate this, it is crucial to strike a balance between automation and human touch, ensuring that AI enhancements complement rather than replace human interaction. Continuous monitoring and ethical considerations are essential to maintain user trust and satisfaction. Future Trends in AI and Crypto Marketing As AI technology continues to advance, we can expect even more innovative applications in the crypto marketing space. One emerging trend is the integration of augmented reality (AR) and virtual reality (VR) powered by AI, creating immersive experiences that engage users in new and exciting ways. AI-driven personal assistants and virtual agents may also become more prevalent, offering seamless and intuitive interactions with crypto services. Furthermore, the rise of decentralized AI platforms could democratize access to AI tools, allowing smaller crypto projects to leverage advanced technologies without significant investment. This shift could lead to a more diverse and innovative crypto ecosystem, driven by a wider range of participants. In conclusion, AI-driven smart marketing innovations are transforming the way crypto projects engage with their audiences. By harnessing the power of AI, marketers can deliver personalized, data-driven, and proactive campaigns that enhance user experience and drive growth. As the crypto landscape continues to evolve, embracing AI will be essential for staying competitive and relevant in this dynamic and exciting field.
If you are turning between UA vs. GA4, let us tell you that it is quite a common choice paralysis. However, you no longer need to weigh the pros and cons between the two. As you may have heard, as of July 2023, data collection for the existing Google Analytics platform, Universal Analytics (UA), will cease to exist. Your only choice at that point will be to convert to Google Analytics 4 (GA4). Yet why is this happening and how will it influence your company? Continue reading to discover about the origins of Google Analytics, the changes between UA vs. GA4, as well as many advantages and disadvantages, advice, and strategies to assist you deal with this shift. But let us understand what UA vs. GA4 is and what are the main differences. UA vs. GA4: What Are The Main Differences? Since Google initially purchased Google Analytics in 2005, the software has seen significant development. The traditional version of Google Analytics was created after Google acquired a programme named “Urchin Analytics” in April of that year (from which UTM parameters or Urchin Tracking Modules derive). The launch of the Universal Analytics (UA) platform in 2013 marked the beginning of the tracking standard. But now that Google has confirmed that GA4 will be released on March 16, 2022, we are aware that UA will be phased off starting in July 2023. Let’s look at the differences between the two a little more closely There are two user metrics in Universal Analytics: Total Users and New Users. Total Users, Active Users, and New Users are the three user metrics available in Google Analytics 4. In most reports, Universal Analytics emphasises Total Users (represented as Users), whereas GA4 concentrates on Active Users (also shown as Users). Therefore, even though the word “Users” appears to be the same, UA and GA4 calculate this measure differently since UA uses Total Users whereas GA4 calculates it using Active Users. The Total Visitors measure in UA and the Active Users metric in GA4 may be somewhat comparable, depending on how frequently your users visit your website. Your digital marketing agency will be able to give you a clear picture of the total users of your website if you are unable to differentiate between UA vs. GA4. Since the Google tag activates on every page and creates a pageview, pageviews should normally be within a few percentage points between UA and GA4. However, the distinctions may alter depending on whatever filters you may have configured in Google Analytics 4 or Universal Analytics. Unlike GA4, which aggregates both online and app data in a single property, Universal Analytics monitors screen views in distinct mobile-specific properties. When comparing pageview stats across your GA4 property’s tracking of web and app data, make careful to account for the additional app traffic. Additional filtering options offered by Universal Analytics may have an influence on the data in the view you are comparing to. Your pageview counts between UA vs. GA4 can differ considerably, for instance, if you use a filter to exclude specific geographic areas. While data in Universal Analytics reporting may be subject to view filters that omit data, Google Analytics 4 properties do not presently allow filters. For instance, internal IP traffic and undesirable referrals can be filtered out using both UA and GA4, although UA could apply extra filters. Make sure that both attributes have the same filters applied when you compare. Simply put, a session is the period of time a user actively engages with a website or an app. Businesses’ differences in session counts between UA and GA4 rely on a number of variables, including: Geography: Think about the timezones of your users and how probable it is that they will restart a session after midnight. This is especially important if your consumer base is international. Use of UTMs on owned websites or applications: Employing UTM tagging on your own website is not advised since it would cause Universal Analytics to reset the session. If you employ UTMs on your own website, you could see that UA has a significantly greater session count than GA4. Filters: View filters that exclude data may be applied to the data in UA reporting. Filters that control which information from a source property appears in a sub property may be applied to the data in GA4 reporting for Google Analytics 360 clients. However, if you exclude the session start event from a subproperty, Google Analytics still creates a session ID. Estimation: Unlike Universal Analytics properties, Google Analytics 4 properties employ a statistical estimate of the number of sessions that took place on your website or app by calculating the number of unique session IDs. Google Analytics 4 properties count sessions more precisely and with a lower error rate using estimations. Purchase events are atomic and essential for businesses, therefore even though Google never anticipates flawless event collection across all events, it sees close agreement between event counts throughout UA or GA4. When comparing data, the transaction_id option might provide observable discrepancies if it is not used consistently and correctly. Please make sure that this data is gathered consistently in accordance with the instructions for purposes of comparison and data quality. You guarantee that ecommerce data is accurately collected, and be sure to utilise all of the necessary settings for GA4 ecommerce implementation (as well as for UA). Based on view filters, your UA reports could be ignoring some data. Because GA4 is still analysing data, you could notice discrepancies when comparing recent reports. Sounds complicated? Ask your SEO agency to do it for you! It is quite common to take the help of professionals, especially if the business is new to the idea of digital marketing. Bounce rate is one of the key enterprise SEO metrics that you need to consistently keep in check. The percentage of sessions in Google Analytics 4 that were not engaged sessions is known as the bounce rate. Bounce rate is therefore the opposite of engagement rate. Bounce rate in Universal Analytics is the proportion of all user sessions on your site during which they only saw one page and sent one request to the analytics server. Always remember to keep your bounce rate to a minimum. Although bounce rate, as it is determined in Universal Analytics, is a decent indicator of site engagement, as websites and applications have evolved, its value has diminished. Users may see a single-page application (SPA), for instance, and depart without causing an event; this is referred to as a bounce. Furthermore, Bounce rate, as computed in Google Analytics 4, offers a more practical approach to gauge how often customers interact with your website or app. If you run a blog, for instance, you might not care if visitors come to read a post on your site and then go. You probably give more thought to the amount of visitors to your website who rapidly depart after not finding what they were searching for. Cookie-Based To Event-Based Data Model Universal Analytics receives data from “cookie-based” tracking. A website that uses UA sends a cookie to the user’s browser, enabling the platform to track and record online behaviour on the concerned site during the user’s visit. A session-based data model is used for the measuring methodology. Google Analytics 4 enables “companies to measure across platforms and devices using numerous forms of identity,” according to Google. First party information and “Google signals” from users who have chosen to have their advertising personalised are included in this. Additionally, Google Analytics 4 will continue to employ cookies for tracking wherever they are available. The data model in GA4 is event-based rather than session-based. Will this change the mechanism of ads such as targeted ads and PPC? Ask your Google ads agency how this change will impact the outcome of your advertising campaigns. Analytics organises data into sessions in UA properties, and these sessions serve as the basis for all reporting. A session is a collection of user interactions with your website that happen over the course of a specific period of time. Pageviews, events, and eCommerce transactions are just a few examples of the user interactions that Analytics records and keeps as hits during a session. Depending on how a person uses your website, a single session may include several hits. Even though Analytics gathers and preserves user interactions with your website or app as events, you may still view session data in GA4 properties. Events, including pageviews, button clicks, user actions, or system events, provide you information about what’s occurring on your website or in your app. Events have the ability to gather and communicate data that better explains the action the user did or provides further context for the event or user. This data may contain particulars like the cost of the transaction, the URL of the page the user viewed, or their precise location. As a result, you can improve your Google ads remarketing campaign by deploying GA4. It’s reasonable to assume that such cookies may become less and less common in a world where privacy is becoming more and more crucial. Although this may be a net benefit to mankind, it now appears to be a major drawback for digital marketers. Event Tracking in UA Vs. GA4 We are aware that Universal Analytics uses pageviews to track data whether you use SEO for an ecommerce website, social media or any other purpose. As a result, GA may record a pageview when a URL loads. Users’ actions on the monitored site that do not cause a new page to load will not be recorded. This covers actions like clicking on videos, clicking on pages inside the domain, and clicking on pages outside the domain. Google Tag Manager is required by Universal Analytics in order to measure “events” like link click tracking or link click tracking. For marketers taking on this for the first time, it can be time-consuming and difficult. Setting up variables, triggers, and tags (like the tag setup below) to track particular occurrences that Google Analytics will record as data entails. On the Root and Branch website, this Universal Analytics event tag will monitor each link click. The “event parameters” are pre-designated with names like category, action, and label are the largest differences between UA va. GA4. These “parameters” transmit extra data with our event that we may use to interpret the data. As opposed to GA4, which is engineered to handle certain event tracking out of the box, GA4 is not dependent on pageview tracking. As we’ve already demonstrated, although some of those events (automatically gathered events and improved measurement events) are monitored by default, suggested events and custom events must be explicitly set with Tag Manager. By default, these events log a few “event parameters.” The list of event parameters that are supplied along with each event is provided here. - Page location - Page referrer - Page title - Screen resolution Both suggested events and bespoke events can include additional event parameters. There is a further action to do when this occurs. These event parameters need to be added as a custom dimension in GA4. This is a new step in the process, and before I got used to it, I found it to be quite perplexing. If it doesn’t make sense to you either, you might want to read this helpful guide to comprehending event parameters. The fact is, we are just now beginning to fully comprehend GA4. And it undergoes daily updates, just like every other Google product! In GA4, there is still so much to learn and discover, and everyone’s experience will be unique. We strongly advise you to get outside and experiment with GA4. Although it could be unpleasant, it is a lot more similar to UA than you might realise. All the best!
LidarNews customer interview with Towill about 3D technology Practical experience report on the PluraView 3D monitor Lidar News is interested in how innovative companies and individuals are leveraging advanced technologies for enhanced visualization and improved modeling and design outcomes. For this Q&A Feature, Lidar News Editor Gene Roe interviewes Towill, Inc.’s Chief Photogrammetrist George Maalouli to KELYN Technologies and the 3D PluraView technology from Schneider Digital. Can you please provide a brief overview of your professional background (s) and experience, particularly with 3D technologies and visualization, and/or a brief history of the growth of the company and its use of 3D technology? Please include an idea of the timelines. My name is George Maalouli. I am a Certified Photogrammetrist and have been in the Photogrammetry profession for the past 35 years or so. I have been through the technological evolution of stereo photogrammetry since the eighties. Starting with the “Kelch” system using anaglyph glasses, to the optical analog/analytical plotter stereo viewing which is achieved by re-directing each eye line-of-sight to each of the stereo image pair, to the fully digital stereo system using active or passive technique by means of flickering the glasses or the screen at high frequencies (above 100hz) to allow the left and right eye to see the two overlapping images simultaneously, and finally the latest “Beam-Splitting” flicker free stereo display used by PluraView monitors. This latest display technique allows for the highest resolutions at the standard frequencies without any cause of fatigue or discomfort. As the chief photogrammetrist at Towill, Inc. in the Bay area, we implemented the PluraView system and replaced all our NVidia active systems. Can you provide an inventory of some of the primary 3D surveying and mapping hardware and software that your company currently uses, as well as any other related products? Please include an idea of the timeline of purchases. The conventional stereo photogrammetry field is somewhat losing ground to some automation in image-based data extraction. However, these automation techniques may work well for elevation extraction, smart planimetric data extraction continue to pose a challenge for automation and are still being carried out by manual stereo extraction. Due to too many issues related to Nvidia-system hardware availability and problems, we decided at Towill in 2021 to upgrade all our four stereo workstations to the PluraView. We decided to add three systems followed shortly by the fourth and final system. The upgrade eliminated our dependencies on various hardware and software such as Microsoft and Nvidia. The system is very reliable and requires minimum maintenance time. The implementation was seamless and took less than a day once we had all systems in house. What attracted you to KELYN3D and the 3D PluraView monitors? Did you look at other products? Why did you choose KELYN3D and 3D PluraView? Around 2014, we implemented a fully digital stereo workflow and added the promising Nvidia active-stereo cheap system. In early 2021, it became clear to us that the NVidia-based system is no longer sustainable and is requiring more and more maintenance resulting in more cost and less productivity. As a Photogrammetrist, I kept abreast of ongoing display technology including stereo display. We decided to take another look at the beam-splitting technology that PluraView offers. As we searched for a better solution, it was obvious that KELYN3D is a better fit for us due to their reputation and their location in proximity to our offices in Colorado and in the Bay area. Yes, it is a bigger investment upfront, but it paid off in the past few years. How are you integrating KELYN3D products into your workflows? What were some of the challenges with that? What were some of the best practices and lessons learned? All of our four stereo workstations are equipped with the PluraView systems. These systems are fully utilized for all our stereo extraction processes as well as for the QC of all of our mapping products. It integrates well with our full photogrammetric workflow. Other than the initial setup and calibration, the system has been very reliable and did not pose any challenges. KELYN3D did a great job in supporting the initial setup and during the rare occasions when we called for support. The best lesson for us was the system selection criteria. Choosing the cheapest solution and not looking ahead for the future is not a good business strategy. Can you provide a brief overview of two or three of the projects where you made use of KELYN3D and 3D PluraView technology? Can you provide any thoughts on time savings vs. other methods? Any thoughts on return on investment? We use the PluraView system on all our stereo projects, small or large and without exceptions. We executed 100’s or more projects with these systems. A good example that comes to mind is the California Department of Transportation (CALTRANS) projects. CALTRANS continues to demand stereo-based manual data extraction of their products, and most times LiDAR elevation data is integrated in our stereo workflow. LiDAR data is viewed and QC’d in a stereo environment to remove remaining errors that are otherwise missed by the mono-classification alone. Another area we use stereo, is evaluating and integrating into final products our field-collected data to ensure accuracy and conformity to standards. For the ROI, the system’s benefit is clear to us, and it has fully paid for itself in a short time. We expect our system to be fully functioning and fully utilized for as long as the demand continues for high quality photogrammetric data. What do you see in the future for the use of KELYN3D and 3D PluraView technology on your projects? Are you investigating other advanced technologies that will create new business opportunities? As long as we have a demand for photogrammetric products, stereo-viewing will continue to be the main driver in our workflow. We recognize and see a shift towards automation with more LiDAR data integration. Stereo viewing will continue to be our main tool for QC and for data completeness checks.
In the age of automation, AI, and 5G connectivity, we often celebrate the technologies that define our daily lives—but rarely do we talk about the minds behind the machines. Enter the computer engineer: the digital architect who bridges the gap between hardware and software, between innovation and execution. Far from being confined to wires and screens, computer engineers are involved in shaping the future of smart cities, wearable tech, autonomous systems, and cybersecurity. But what does this field really encompass, and what does it take to thrive in it? From Circuit Boards to Cloud Systems Computer engineering is a fusion of two powerhouse disciplines: electrical engineering and computer science. That means graduates don’t just write code—they also design, build, and optimize the physical systems that power everything from mobile phones to industrial robots. A typical computer engineering course covers a wide spectrum of topics: microprocessors, embedded systems, data communication, signal processing, and software development. Students learn how these systems talk to each other, respond to real-world inputs, and evolve with changing technologies. What sets this discipline apart is its adaptability. While one engineer may develop firmware for medical devices, another could be optimizing the battery efficiency of electric vehicles. The versatility is vast, and the demand is global. The devices we use are only the tip of the iceberg. Behind every seamless user experience lies a complex system designed for efficiency, speed, and security. Here’s where computer engineers step in: - Smart homes: Engineers work on sensors and connectivity protocols that allow devices to “talk” to each other. - Healthcare tech: From wearable monitors to diagnostic machines, real-time data and reliability are critical—and so is the underlying hardware-software integration. - Banking and cybersecurity: Computer engineers help secure transaction systems and ensure compliance with the latest data protection standards. It’s not just about what they build—it’s about how these innovations shape industries and improve lives. The Skillset of a Tech Pioneer Success in computer engineering doesn’t rely on technical mastery alone. It requires: - Problem-solving mindset: Engineers often face complex, open-ended problems with no clear right answer. - Collaborative spirit: Projects are rarely solo missions; cross-functional teamwork is the norm. - Lifelong curiosity: Tech changes fast. Staying ahead means embracing constant learning. Soft skills like communication and project management are just as important as the ability to code or design circuits. Computer engineers are more than system designers—they’re visionaries. They anticipate the future’s technological needs and build the infrastructure to support it. As our world becomes more connected, the demand for thoughtful, adaptable, and skilled engineers only grows. Choosing to pursue a computer engineering course isn’t just a step toward a career in tech. It’s a commitment to shaping the very tools and systems that define how we live, work, and interact with the world around us.
in today's digital age, data has become an essential tool for transforming societies. this talk explores how the analysis of information, when used ethically and responsibly, can guide decision making in areas as diverse as security, health, and education. before drawing conclusions, it is essential to have clean and organized data. the quality of the information forms the foundation for accurate analysis and informed decision making. through intuitive visualizations and predictive models, we identify patterns and trends. these analyses allow us to anticipate scenarios and prioritize interventions, demonstrating the real impact that data can have in preventing conflicts and efficiently allocating resources. the middle east and afghanistan present a complex interplay of socio-economic, political, and cultural factors. our data analysis of the region reveals several key trends: conflict hotspots, resource scarcity, economic disparities, and demographic pressures. notably, afghanistan stands out with the highest number of fatal incidents, highlighting persistent instability and conflict in the area. further, economic indicators such as gdp per capita show an inverse correlation with conflict frequency, although the relationship is not strictly linear. additional variables—political dynamics, social inequality, and external influences—significantly contribute to the overall complexity. advanced predictive models, including xgboost, have been applied to forecast potential flashpoints, offering valuable insights for humanitarian organizations and policy makers. by integrating geospatial data and historical trends, we can identify emerging patterns that may inform early intervention strategies. for example, areas within afghanistan experiencing rapid economic decline or severe resource shortages often coincide with escalated conflict. this comprehensive, data-driven approach is crucial for addressing the root causes of instability in the middle east. advanced models, such as xgboost, enable us to predict risk situations before they materialize, facilitating strategic decision making and ultimately saving lives in critical contexts. digital transformation offers the opportunity to improve our decisions. by combining technology, data analysis, and an ethical approach, we can build a future where information drives change and generates a positive impact on society. check out the slides for the talk here. - a. r. brea, written 03/22/25
You must verify the integrity of the downloaded files. We provide OpenPGP signatures for every release file. This signature should be matched against the KEYS file which contains the OpenPGP keys of Tomcat's Release Managers. We also provide SHA-512 checksums for every release file. After you download the file, you should calculate a checksum for your download, and make sure it is the same as ours. Note: The attachment to this article is a zip file. It contains both the hotfix update package and the source code for any modified open source components. The source code is not necessary for hotfix installation: it is provided to fulfill licensing obligations. Decode Base64 to file using the free online decoder, which allows you to preview files directly in the browser, as well as download them, get the hex dump for any binary data, and get summary information about the original file. Please note that the preview is available only for textual values and known media files such as images, sounds, and videos. In any case, you can always convert Base64 to binary and download the result as file, regardless of its MIME type. If you are looking for the reverse process, check File to Base64. Navigate to the Setup.exe file.For example, if you have copied and extracted the zip file to the Adobe folder on your desktop, the folder hierarchy will be:C:\\Users\\\\Desktop\\Acrobat_DC_Web_WWMUI\\Adobe Acrobat\\Setup.exe State Education Agencies have one year to revise this data. Each year, we put out a revised file approximately one year after the original file is released. The original file is Version 1a, the revised file is Version 1b. This is all done programatically from Java - but I am wondering if it wouldn't be more efficient to copy the war file and then just append the files - then I wouldn't have to wait so long as the war expands and then has to be compressed again. As others mentioned, it's not possible to append content to an existing zip (or war). However, it's possible to create a new zip on the fly without temporarily writing extracted content to disk. It's hard to guess how much faster this will be, but it's the fastest you can get (at least as far as I know) with standard Java. As mentioned by Carlos Tasada, SevenZipJBindings might squeeze out you some extra seconds, but porting this approach to SevenZipJBindings will still be faster than using temporary files with the same library. I'll recommend you to try out the TrueZIP (open source - apache style licensed) library that exposes any archive as a virtual file system into which you can read and write like a normal filesystem. It worked like a charm for me and greatly simplified my development. Michael Krauklis is correct that you cannot simply \"append\" data to a war file or zip file, but it is not because there is an \"end of file\" indication, strictly speaking, in a war file. It is because the war (zip) format includes a directory, which is normally present at the end of the file, that contains metadata for the various entries in the war file. Naively appending to a war file results in no update to the directory, and so you just have a war file with junk appended to it. What's necessary is an intelligent class that understands the format, and can read+update a war file or zip file, including the directory as appropriate. DotNetZip does this, without uncompressing/recompressing the unchanged entries, just as you described or desired. I covered this library in my blog some months ago (sorry for the auto-promotion). Just as an example, extracting a 104MB zip file using the java.util.zip took me 12 seconds, while using this library took 4 seconds. Using append mode on any kind of structured data like zip files or tar files is not something you can really expect to work. These file formats have an intrinsic \"end of file\" indication built into the data format. If you really want to skip the intermediate step of un-waring/re-waring, you could read the war file file, get all the zip entries, then write to a new war file \"appending\" the new entries you wanted to add. Not perfect, but at least a more automated solution. Android apps are packaged as APKs, which are ZIP files with special conventions. Most of the content within the ZIP files (and APKs) is compressed using a technology called Deflate. Deflate is really good at compressing data but it has a drawback: it makes identifying changes in the original (uncompressed) content really hard. Even a tiny change to the original content (like changing one word in a book) can make the compressed output of deflate look completely different. Describing the differences between the original content is easy, but describing the differences between the compressed content is so hard that it leads to inefficient patches. File-by-File therefore is based on detecting changes in the uncompressed data. To generate a patch, we first decompress both old and new files before computing the delta (we still use bsdiff here). Then to apply the patch, we decompress the old file, apply the delta to the uncompressed content and then recompress the new file. In doing so, we need to make sure that the APK on your device is a perfect match, byte for byte, to the one on the Play Store (see APK Signature Schema v2 for why). When recompressing the new file, we hit two complications. First, Deflate has a number of settings that affect output; and we don't know which settings were used in the first place. Second, many versions of deflate exist and we need to know whether the version on your device is suitable. This table of file signatures (aka \"magic numbers\") is a continuing work-in-progress. I had found little information on this in a single place, with the exception of the table in Forensic Computing: A Practitioner's Guide by T. Sammes & B. Jenkinson (Springer, 2000); that was my inspiration to start this list in 2002. See also Wikipedia's List of file signatures. Comments, additions, and queries can be sent to Gary Kessler at email@example.com. This list is not exhaustive although I add new files as I find them or someone contributes signatures. Interpret the table as a one-way function: the magic number generally indicates the file type whereas the file type does not always have the given magic number. If you want to know to what a particular file extension refers, check out some of these sites: My software utility page contains a custom signature file based upon this list, for use with FTK, Scalpel, Simple Carver, Simple Carver Lite, and TrID. There is also a raw CSV file and JSON file of signatures. The National Archives' PRONOM site provides on-line information about data file formats and their supporting software products, as well as their multi-platform DROID (Digital Record Object Identification) software. I would like to give particular thanks to Danny Mares of Mares and Company, author of the MaresWare Suite (primarily for the \"subheaders\" for many of the file types here), and the people at X-Ways Forensics for their permission to incorporate their lists of file signatures. Finally, Dr. Nicole Beebe from The University of Texas at San Antonio posted samples of more than 32 file types at the Digital Corpora, which I used for verification and additional signatures. These files were used to develop the Sceadan File Type Classifier. The file samples can be downloaded from the Digital Corpora website. This document describes the on-disk structure of a PKZip (Zip) file. The documentation currently only describes the file layout format and meta information but does not address the actual compression or encryption of the file data itself. This documentation also does not discuss Zip archives that span multiple files in great detail. This documentation was created using the official documentation provided by PKWare Inc. The archive consists of a series of local file descriptors, each containing a local file header, the actual compressed and/or encrypted data, as well as an optional data descriptor. Whether a data descriptor exists or not depends on a flag in the local file header. Following the file descriptors is the archive decryption header, which only exists in PKZip file version 6.2 or greater. This header is only present if the central directory is encrypted and contains information about the encryption specification. The archive extra data record is also only for file of version 6.2 or greater and is not present in all Zip files. It is used in to support the encryption or compression of the central directory. The central directory summarizes the local file descriptors and carries additional information regarding file attributes, file comments, location of the local headers, and multi-file archive information. The data descriptor is only present if bit 3 of the bit flag field is set. In this case, the CRC-32, compressed size, and uncompressed size fields in the local header are set to zero. The data descriptor field is byte aligned and immediately follows the file data. The structure is as follows: This header is used to support the Central Directory Encryption Feature. It is present when the central directory is encrypted. The format of this data record is identical to the Decryption header record preceding compressed file data. The central directory contains more metadata about the files in the archive and also contains encryption information and information about Zip64 (64-bit zip archives) archives. Furthermore, the central directory contains information about archives that span multiple files. The structure of the central directory is as follows: The file headers are similar to the local file headers, but contain some extra information. The Zip64 entries handle the case of a 64-bit Zip archive, and the end of the central directory record contains information about the archive itself. 59ce067264
Support for AI (Artificial Intelligence) application and DX (Digital Transformation) We not only help our portfolio companies to promote DX by replacing their systems and introducing BI tools, but also help them to increase the possibility of promoting discontinuous growth in their businesses by proposing AI-based data analysis and utilization and IoT strategies. AI・DX Support Office is staffed by experts with knowledge and experience in AI, data science, cyber security, and system construction, etc., and provides optimal strategy planning and advice according to the environment of the portfolio company. We also provide consultation on general IT issues for our portfolio companies, and have a system in place to provide support including the basics. We provide support services regardless of industry, and our business support in the AI and DX sectors tailored to each portfolio company has been well received by our portfolio companies.
Shearwater Cloud, a leading provider of aviation weather solutions, is revolutionizing how pilots and aviation professionals access and interpret crucial weather data. This cloud-based platform delivers real-time weather information, sophisticated forecasting models, and integrated tools, empowering users to make informed decisions for safer and more efficient flight operations. Aviation weather forecasting has always been a critical component of flight safety. However, the traditional methods of accessing and analyzing this data were often time-consuming, complex, and limited in scope. Shearwater Cloud bridges this gap by providing a centralized, dynamic, and user-friendly platform that delivers the most up-to-date information directly to the user's fingertips. The platform's innovative approach to weather data processing and presentation sets it apart from other solutions. Shearwater Cloud leverages cutting-edge atmospheric modeling techniques to provide highly accurate and reliable forecasts, allowing users to anticipate potential weather-related challenges and mitigate risks effectively. Shearwater Cloud isn't just another weather app; it's a comprehensive suite of tools designed for various aviation needs. Key features include: Real-time weather data: Access to current weather conditions, including wind speed, direction, temperature, and precipitation, updated in real-time. Sophisticated forecasting models: Leveraging advanced algorithms and data sources, Shearwater Cloud provides reliable forecasts for various time horizons, helping pilots anticipate potential weather patterns. Integrated flight planning tools: Seamlessly integrate weather data into existing flight planning software, enabling pilots to make informed decisions regarding routes, altitudes, and potential delays. Customizable dashboards: Tailor the platform to individual needs and preferences by customizing dashboards to display specific weather parameters and alerts. Interactive maps and visualizations: Visually represent weather data through interactive maps and charts, providing a clear understanding of weather patterns and potential hazards. The benefits of adopting Shearwater Cloud extend beyond simply accessing weather data. The platform empowers users in numerous ways: Improved flight safety: By providing accurate and timely weather information, Shearwater Cloud helps pilots make informed decisions that reduce the risk of encountering adverse weather conditions. Enhanced operational efficiency: Streamlined flight planning and reduced delays contribute to increased operational efficiency and cost savings. Reduced risk of accidents: Early warning systems and detailed weather reports minimize the potential for accidents caused by unforeseen weather events. Increased pilot confidence: Access to comprehensive weather information empowers pilots with the knowledge needed to navigate challenging weather conditions with greater confidence. Shearwater Cloud's impact is evident in various aviation sectors. For example, commercial airlines utilize the platform to optimize flight schedules and routes, reducing fuel consumption and minimizing delays. General aviation pilots use it to plan safe and efficient flights, while air traffic controllers benefit from the real-time data for more effective airspace management. Several airlines and flight schools have reported significant improvements in safety and efficiency after integrating Shearwater Cloud into their operations. These improvements demonstrate the platform's effectiveness in enhancing decision-making processes and minimizing risks. While several aviation weather platforms exist, Shearwater Cloud stands out due to its comprehensive features and user-friendly interface. It often surpasses competitors in terms of forecast accuracy, data visualization, and integration with other aviation software. Key differentiators include the platform's advanced modeling algorithms, its real-time data updates, and its customizable dashboards. These features allow users to tailor the platform to their specific needs and preferences, making it a versatile tool for a wide range of aviation applications. Shearwater Cloud is constantly evolving to meet the ever-changing demands of the aviation industry. Future innovations may include enhanced predictive capabilities, integration with emerging technologies like AI and machine learning, and more personalized user experiences. The company's commitment to research and development ensures that the platform remains at the forefront of aviation weather technology, empowering users with the most accurate and reliable information for safer and more efficient flight operations. Shearwater Cloud has emerged as a game-changer in the aviation industry, transforming how pilots and professionals access and utilize weather data. Its comprehensive features, user-friendly interface, and commitment to innovation have made it a valuable asset for improved flight safety and operational efficiency. By leveraging cutting-edge technology and providing real-time insights, Shearwater Cloud empowers users to make informed decisions and navigate challenging weather conditions with greater confidence. Its continued evolution and expansion into new markets position it as a key player in the future of aviation weather solutions. The platform's ability to integrate with existing systems and its emphasis on user experience make it a valuable asset for a wide range of aviation stakeholders, from commercial airlines to individual pilots.
Trump unveils landmark AI initiative called ‘Stargate’ Coinciding with his repeal of former President Joe Biden’s 2023 AI Executive Order that required AI companies to share safety evaluations with the federal government, particularly when technologies pose risks to national security, public health, or the economy, President Donald Trump announced the launch of “Stargate,” an ambitious and monumental initiative designed to strengthen the United States’ AI infrastructure. Both the Stargate announcement and the revocation of the AI safeguard Biden had put in place has sparked widespread criticism from privacy advocates and security experts who argue that transparency and accountability are vital in AI development and deployment, especially by federal agencies. This unprecedented Stargate project is a mammoth collaboration with tech giants OpenAI, SoftBank Group Corp., and Oracle Corp. that aims to position the U.S. as a global leader in AI technology while driving significant economic and technological progress. At its core, the Stargate initiative seeks to address the nation’s growing need for advanced AI capabilities by constructing state-of-the-art data centers and related infrastructure. But while Stargate represents an extraordinary leap forward for U.S. AI capabilities, offering the promise of technological leadership and economic prosperity, its scale and ambition come with significant challenges, particularly in balancing innovation with privacy, security, and ethical responsibility. The ultimate success of the project will depend on how effectively these challenges are addressed. As the Stargate initiative unfolds, to succeed it will need to serve as a model of responsible AI development – one that prioritizes the public good while navigating the complexities of modern technology. If managed thoughtfully, Stargate could become a beacon of progress. If not, it risks becoming a cautionary tale of unchecked ambition in the age of AI. With an initial investment of $100 billion and a touted ability to be able to scale up to $500 billion over the next four years, the program is expected to stimulate economic growth and create over 100,000 jobs. The first facility, already under construction in Abilene, Texas, marks the beginning of what will eventually expand to multiple locations across the nation. Oracle co-founder Larry Ellison emphasized the scope of the project, stating, “We’re building ten data centers right now, with plans to double that and expand beyond Texas.” According to OpenAI, “the initial equity funders in Stargate are SoftBank, OpenAI, Oracle, and MGX. SoftBank and OpenAI are the lead partners for Stargate, with SoftBank having financial responsibility and OpenAI having operational responsibility. SoftBank CEO Masayoshi Son will be the chairman. Arm, Microsoft, NVIDIA, Oracle, and OpenAI are the key initial technology partners.” “The buildout is currently underway, starting in Texas, and we are evaluating potential sites across the country for more campuses as we finalize definitive agreements,” OpenAI said. “As part of Stargate, Oracle, NVIDIA, and OpenAI will closely collaborate to build and operate this computing system.” The Stargate announcement came as the impending ban on TikTok could adversely affect Oracle’s existing data operations in Texas. In response to U.S. national security concerns regarding data privacy, TikTok partnered with Oracle to manage and store its U.S. user data. This collaboration, known as “Project Texas,” was intended to ensure that American user information is stored within the United States and is overseen by an American company. However, if the ban on TikTok occurs, Oracle would need to reallocate the Texas cloud capacity it dedicated to TikTok operations. “If we are unable to provide those services to TikTok, and if we cannot redeploy that capacity in a timely manner, our revenues and profits would be adversely impacted,” the company wrote in a Securities and Exchange filing. The Stargate announcement was made during a White House event that featured key leaders from the partnering companies, including OpenAI CEO Sam Altman, Son, and Ellison. Trump underscored the strategic importance of keeping AI innovation within U.S. borders. He said, “China and others are our competitors. This is about ensuring that artificial intelligence is made in the USA and benefits Americans first.” Despite its promise, the Stargate initiative has ignited debate about privacy, security, and the ethical implications of such a large-scale effort. These concerns are amplified by the central role of private corporations like OpenAI, SoftBank, and Oracle, whose access to vast datasets raises questions about data usage, surveillance, and accountability. The success of AI relies heavily on the collection, storage, and analysis of massive amounts of data, much of which may include sensitive personal information. This dependency highlights the urgent need for robust data protection measures. Without stringent safeguards, there is a very real risk that personal information could be exploited, either for commercial gain or through unauthorized surveillance and hacking. Critics have pointed to the danger of “surveillance creep,” where data initially collected for benign purposes may eventually be used for more intrusive monitoring, tracking, or profiling. Adding to the complexity is the opacity of AI systems themselves. Often described as “black boxes,” these systems operate in ways that are difficult to understand, even for their creators. This lack of transparency not only undermines public trust, it also raises concerns about bias and discrimination in AI-driven decision-making processes. Without proper oversight, algorithms could perpetuate inequities in areas such as hiring, lending, or law enforcement. The absence of the oversight that Biden’s executive order – no longer available on the White House website – had put in place is now feared will increase the risk of unintended consequences. AI technologies are already integral to critical sectors like healthcare, finance, and national defense. Without comprehensive safety protocols, their misuse – or even errors – could have catastrophic consequences for individuals and national security. One of Stargate’s defining features – centralized data infrastructure – presents unique challenges. While centralized facilities enhance efficiency and scalability, they also become high-value targets for cyberattacks. Hackers could exploit vulnerabilities in these hubs, potentially accessing sensitive national and personal data. Moreover, systemic failures at one data center could disrupt interconnected systems across the country, affecting vital services like healthcare and finance. Ensuring the security of these facilities will require significant investment in advanced cybersecurity measures. The challenge extends beyond external threats; internal failures or mismanagement could also jeopardize the project’s integrity. The centralized approach, while efficient, introduces risks that must be carefully mitigated. Stargate’s broader implications extend into ethical and geopolitical domains. The potential militarization of AI technologies raises concerns about their use in autonomous warfare or mass surveillance. Furthermore, AI-driven systems could be weaponized to influence public opinion, spread misinformation, manipulate elections, and threaten democratic processes. On the global stage, Stargate’s ambitions could escalate an international AI arms race. Rival nations, particularly China, may prioritize rapid AI development to counter U.S. dominance. This competitive environment could overshadow critical discussions about ethics, safety, and equitable access to AI technologies. Indeed. The Chinese Communist Party has articulated a comprehensive strategy to position China as a global leader in AI by 2030. This ambition is outlined in the “Next Generation Artificial Intelligence Development Plan” released by the State Council in July 2017. The plan delineates a three-step roadmap: achieving parity with leading AI nations by 2020, making significant breakthroughs by 2025, and establishing China as the premier AI innovation center by 2030. Complicating matters further is the issue of cross-border data sovereignty. If Stargate involves collecting data from international sources, it risks legal challenges from countries with strict privacy laws, such as those governed by the European Union’s General Data Protection Regulation. Conflicts over data ownership and usage could strain diplomatic relationships and lead to prolonged legal disputes. The central involvement of corporations like OpenAI, SoftBank, and Oracle introduces another layer of complexity. Their influence on Stargate’s direction raises concerns about prioritizing profit over public interest. Critics argue that concentrating power among a few tech giants could stifle competition, limit innovation, and exacerbate societal inequalities. Additionally, these corporations’ control over extensive datasets necessitates clear regulatory frameworks to prevent potential misuse. Without proper oversight, there is a risk that private interests could dominate public welfare considerations, undermining the initiative’s long-term success. To navigate these multifaceted challenges, the Stargate initiative must adopt a proactive and collaborative approach that incorporates data protection and anonymization; transparency and accountability; cybersecurity investments; global collaboration; and public engagement.

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