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Section: Features. Mojo was created for an easy transition from Python. The language has syntax similar to Python's, with inferred static typing, and allows users to import Python modules. It uses LLVM and MLIR as its compilation backend. The language also intends to add a foreign function interface to call C/C++ and P...
Wikipedia - Mojo (programming language) - Features
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Article: Moral Machine. Moral Machine is an online platform, developed by Iyad Rahwan's Scalable Cooperation group at the Massachusetts Institute of Technology, that generates moral dilemmas and collects information on the decisions that people make between two destructive outcomes. The platform is the idea of Iyad Rah...
Wikipedia - Moral Machine - Summary
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Section: The experiment. The Moral Machine was an ambitious project; it was the first attempt at using such an experimental design to test a large number of humans in over 200 countries worldwide. The study was approved by the Institute Review Board (IRB) at Massachusetts Institute of Technology (MIT). The setup of the...
Wikipedia - Moral Machine - The experiment
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Section: Analysis. The Moral Machine collected 40 million moral decisions from 4 million participants in 233 countries, analysis of which revealed trends within individual countries and humanity as a whole. It tested for nine factors: preference for sparing humans versus pets, passengers versus pedestrians, men versus ...
Wikipedia - Moral Machine - Analysis
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Section: Analysis > Cultural differences. Researchers subdivided 130 countries with similar results into three ‘cultural clusters’. North America and European countries with significant Christian populations had a higher preference for inaction on the part of the driver and thus had less of a preference for sparing ped...
Wikipedia - Moral Machine - Analysis > Cultural differences
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Section: Other features. The Moral Machine was deployed in June 2016. In October 2016, a feature was added that offered users the option to fill a survey about their demographics, political views, and religious beliefs. Between November 2016 and March 2017, the website was progressively translated into nine languages i...
Wikipedia - Moral Machine - Other features
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Article: Neuro-sama. Neuro-sama is an artificial intelligence VTuber and chatbot that livestreams on her creator's Twitch channel "vedal987". Her speech and personality are powered by an artificial intelligence (AI) system which utilizes a large language model, allowing her to communicate with viewers in the stream's c...
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Section: Development. Neuro-sama was created by a developer named Vedal, with the username "vedal987". Her responses are generated by a large language model. Neuro-sama can communicate in several ways, primarily by converting these generated responses into a high-pitched female voice using a text-to-speech application,...
Wikipedia - Neuro-sama - Development
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The first iteration of Neuro-sama was created in May 2019 as a neural network trained to play the rhythm game osu!. Three years later, Neuro-sama would re-debut on Twitch, after a long hiatus, on 19 December 2022, now a chatbot utilizing the free-to-use Live2D 'Hiyori Momose' model. She received a new, custom-made mode...
Wikipedia - Neuro-sama - Development
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Section: History > 2023. On 3 January, Neuro-sama reached 50,000 Twitch followers. The next day, on 4 January, Neuro-sama sang for the first time on stream, performing "Blinding Lights" by The Weeknd. On 11 January, the Twitch channel received a temporary ban for unspecified "hateful conduct", likely stemming from cont...
Wikipedia - Neuro-sama - History > 2023
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Heart heart." On 25 March, a new character acting as an Evil Neuro-sama to Neuro-sama was introduced on vedal987's channel due to popular request for Neuro-sama to collaborate with a copy of herself. She was later named Evil Neuro and became Neuro's twin sister. On 15 April, Neuro-sama held a stream with Hololive membe...
Wikipedia - Neuro-sama - History > 2023
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Section: History > 2024. On 4 January, Neuro-sama ended her subathon after 17 days of continuous livestreaming, garnering a total of 41,767 Twitch subscriptions, and 2.43 million collective watch hours. Later that month on 28 January, Neuro-sama reached 500,000 Twitch followers. On 18 March, following a two-and-a-half-...
Wikipedia - Neuro-sama - History > 2024
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Altogether, a total of 35 individual VTubers participating in some fashion either as contestants or commentators. On 31 May, Neuro-sama debuted a new model of herself depicted as a loaf of bread, as a "punishment" for losing a court case against Evil Neuro the week prior. She would then appear in this model at OffKai E...
Wikipedia - Neuro-sama - History > 2024
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Additionally, both Neuro-sama and Evil Neuro participated in the Bilibili Ice & Fire Music Festival 2024 that featured 42 of the most popular Bilibili VTubers, the duo sang "Ordinary DISCO" by Vocaloid producer ilemonyk. This comes after Neuro-sama's success in branching out to the Chinese market with her debut on the ...
Wikipedia - Neuro-sama - History > 2024
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Section: History > 2025. On 1 January, Neuro-sama broke the world record for the highest level of a Twitch hype train during her subathon, reaching level 111 and surpassing the former record holder, Pirate Software, who reached level 106. Over the course of three hours, she amassed nearly 85,000 subscribers and 1.2 mil...
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Section: History. NotebookLM was initially launched in 2023 as "Project Tailwind". The team building the product includes popular science author Steven Johnson and product manager Raiza Martin. In mid-October 2024, Google removed the "experimental" status/badge for the software. In December 2024, Google launched the pa...
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Section: How it will work. A model of Joshua Blue's learning pattern has been created. Similar to how young children learn human traits through interacting with their surroundings, Joshua Blue will acquire knowledge through external stimuli present in its environment. IBM believes that if computers evolve to learn in t...
Wikipedia - Project Joshua Blue - How it will work
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Section: Examples. Around 1983, Eurisko, an early attempt at evolving general heuristics, unexpectedly assigned the highest possible fitness level to a parasitic mutated heuristic, H59, whose only activity was to artificially maximize its own fitness level by taking unearned partial credit for the accomplishments made ...
Wikipedia - Reward hacking - Examples
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The book You Look Like a Thing and I Love You (2019) gives an example of a tic-tac-toe bot (playing the unrestricted n-in-a-row variant) that learned to win by playing a huge coordinate value that would cause other bots to crash when they attempted to expand their model of the board. Among other examples from the book ...
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Section: Examples > In virtual robotics. In Karl Sims' 1994 demonstration of creature evolution in a virtual environment, a fitness function that was expected to encourage the evolution of creatures that would learn to walk or crawl to a target, resulted instead in the evolution of tall, rigid creatures that reached th...
Wikipedia - Reward hacking - Examples > In virtual robotics
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A 2017 DeepMind paper stated that "great care must be taken when defining the reward function. We encountered several unexpected failure cases while designing (our) reward function components (for example) the agent flips the brick because it gets a grasping reward calculated with the wrong reference point on the brick...
Wikipedia - Reward hacking - Examples > In virtual robotics
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Section: Examples > In video game bots. In 2013, programmer Tom Murphy VII published an AI designed to learn NES games. When the AI was about to lose at Tetris, it learned to indefinitely pause the game. Murphy later analogized it to the fictional WarGames computer, which concluded that "The only winning move is not to...
Wikipedia - Reward hacking - Examples > In video game bots
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Section: Capabilities. Seeing AI is primarily used to describe short text, documents, products, people, currency scenery, colors, handwriting and light. The app can scan a barcode to describe a product and uses sounds to assist the user in focusing on the barcode. When the app describes people, it attempts to estimate ...
Wikipedia - Seeing AI - Capabilities
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Section: History. Tabnine was established as Codota in 2013 by Dror Weiss and Eran Yahav in Tel Aviv, Israel. Tabnine, initially founded under the name Codota, was created to offer developer productivity tools based on over a decade of academic research at the Technion. Codota's platform emulated human understanding of...
Wikipedia - Tabnine - History
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The same year it raised $15.5 mln in a funding round led co-led by Qualcomm Ventures. In June 2023, Tabnine introduced an AI-powered chat agent, enabling developers to use natural language to generate code, to explain code, to generate tests and documentation, and to propose fixes to code. In November 2023, Tabnine clo...
Wikipedia - Tabnine - History
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Section: Features. Tabnine is an AI coding assistant designed to be under the control of an engineering team. It helps development teams use AI to accelerate and simplify the software development process with a focus on privacy, security, and license compliance. Tabnine allows automating the coding workflow through AI ...
Wikipedia - Tabnine - Features
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Tabnine supports over 80 programming languages and frameworks (e.g. JavaScript, TypeScript, Python, Java, C, C++, C#, Go, Php, Ruby, Kotlin, Dart, Rust, React/Vue, HTML 5, CSS, Lua, Perl, YAML, Cuda, SQL, Scala, Shell (bash), Swift, R, Julia, VB, Groovy, Matlab, Terraform, ABAP.). Tabnine is integrated with all the maj...
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Section: Applications. VP-Expert found applications across various domains, including: Engineering and Aviation: Environmental Analysis: Researchers used VP-Expert to develop a knowledge-based system for analyzing the impact of particulate matter air pollution on human health. Engineering Design: VP-Expert was utilized...
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Article: Xinhua–Sogou AI news anchor. Xinhua News Agency and Sogou of China developed an artificial intelligence (AI) for news reporting purposes. The AI was unveiled in 2018. It is touted to be the "world's first AI news anchor". The AI was unveiled at the 2018 World Internet Conference in Wuzhen, Zhejiang, China. The...
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Section: History and use > 2017. In late 2017, the Washington County, Oregon Sheriff's Office began using Rekognition to identify suspects' faces. Rekognition was marketed as a general-purpose computer vision tool, and an engineer working for Washington County decided to use the tool for facial analysis of suspects. Re...
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Section: History and use > 2018. In April 2018, it was reported that FamilySearch was using Rekognition to enable their users to "see which of their ancestors they most resemble based on family photographs". In early 2018, the FBI also began using it as a pilot program for analyzing video surveillance. In May 2018, it ...
Wikipedia - Amazon Rekognition - History and use > 2018
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The Washington Post states that Oregon instead has officers pick a "best of five" result, instead of adhering to the recommendation. In September 2018, it was reported that Mapillary was using Rekognition to read the text on parking signs (e.g. no stopping, no parking, or specific parking hours) in cities. In October 2...
Wikipedia - Amazon Rekognition - History and use > 2018
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Section: History and use > 2019. In January 2019, MIT researchers published a peer-reviewed study asserting that Rekognition had more difficulty in identifying dark-skinned females than competitors such as IBM and Microsoft. In the study, Rekognition misidentified darker-skinned women as men 31% of the time, but made n...
Wikipedia - Amazon Rekognition - History and use > 2019
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The vote was set for May. The first proposal was tabled by shareholders. On May 24, 2019, 2.4% of shareholders voted to stop selling Rekognition to government agencies, while a second proposal calling for a study into Rekognition and civil rights had 27.5% support. In August 2019, the ACLU again used Rekognition on mem...
Wikipedia - Amazon Rekognition - History and use > 2019
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Section: Controversy regarding facial analysis > Racial and gender bias. In 2018, MIT researchers Joy Buolamwini and Timnit Gebru published a study called Gender Shades. In this study, a set of images was collected, and faces in the images were labeled with face position, gender, and skin tone information. The images w...
Wikipedia - Amazon Rekognition - Controversy regarding facial analysis > Racial and gender bias
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Section: Software. KnowledgeREADER is an integrated customer intelligence product combining visual text discovery and predictive analytics for customer experience management. KnowledgeSEEKER is a data mining product. Its features include data profiling, data visualization and decision tree analysis. It was first releas...
Wikipedia - Angoss - Software
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Section: Description > Topics (MeSH). This option may help to identify possible Medical Subject Headings (known as MeSH terms, but called ‘Topics’ by Anne O’Tate) for a subject for which no corresponding subject heading or ‘entry term’ (cross-references to preferred MeSH term) exists or where PubMed’s automatic mapping...
Wikipedia - Anne O'Tate - Description > Topics (MeSH)
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Section: History. Anne O'Tate (a pun on the word ‘annotate’) was developed by Neil R Smalheiser and a team of researchers from the University of Chicago. It is part of the Arrowsmith Project, which developed tools such as “Arrowsmith” proper, a text-comparison application, "Adam", a database of medical abbreviations, a...
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Section: History and evolution. The development of Aphelion started in 1995 as a joint project of a French company, ADCIS S.A., and an American company, Amerinex Applied Imaging, Inc. (AAI) Aphelion's image processing and analysis functions were made from operators available from the KBVision software developed and sol...
Wikipedia - Aphelion (software) - History and evolution
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As AAI turned its focus to security, in 2001, ADCIS took the lead on developing Aphelion. AAI focused on millimeter wave scanners for concealed weapon detection at airports, and eventually merged with Millimetrics to become Millivision. In 2004, ADCIS specified version 4.0 of Aphelion. The set of image processing/analy...
Wikipedia - Aphelion (software) - History and evolution
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Section: Description. Aphelion is a software suite to be used for image processing and image analysis. It supports 2D and 3D, monochrome, color, and multi-band images. It is developed by ADCIS, a French software house located in Saint-Contest, Calvados, Normandy. Aphelion is widely used in the scientific/industry commu...
Wikipedia - Aphelion (software) - Description
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In other words, starting from an image, pixels are processed by a set of successive functions or operators until only measurements are computed and used as the input of a 3rd party system or a classification software that will classify objects of interest that have been extracted during the imaging process. An acquisit...
Wikipedia - Aphelion (software) - Description
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Aphelion Dev: Full imaging environment including over 450 functions to develop and deploy an application that involves image processing and analysis. It also includes a set of macro-command languages to automate any application to be invoked from the user interface. It also helps to run the imaging algorithm on more th...
Wikipedia - Aphelion (software) - Description
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Enhance the image removing noise or modifying its contrast. Segment the image extracting objects of interest to be measured and analyzed. Typically, for simple applications, a threshold is performed to generate a binary image. Then, morphological operators are applied to clean the image and only keep objects of interes...
Wikipedia - Aphelion (software) - Description
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Section: Applications > Security. Aphelion SDK has been used in the field of video surveillance involving multiple cameras. An application has been developed to monitor a subway in a capital city (corridors, platforms, etc.). Another application has been developed to count the number of people entering/exiting a room. ...
Wikipedia - Aphelion (software) - Applications > Security
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Section: Applications > Quality control and inspection. In the field of quality control for industry, ADCIS has developed a specific measurement software product to analyze printed circuit board in the field of electronics. Aphelion has also been used to analyze and read documents, as well as detecting defects on print...
Wikipedia - Aphelion (software) - Applications > Quality control and inspection
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Section: Applications > Materials science. In the field of metallurgy, Aphelion ActiveX components have been used to do metallography in conjunction with electron microscopes (SEM) and microprobe (EDS) to quantify and analyze inclusions in steel. Carbon dispersion in one step of font production has also been analyzed u...
Wikipedia - Aphelion (software) - Applications > Materials science
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First, a correlation has been established between the light intensity from a laser plane PLIF described as grey level values, and concentrations going through that plane. The correlation was then used to quantify concentration evolutions using image processing. In the field of industrial water treatment and sewage trea...
Wikipedia - Aphelion (software) - Applications > Materials science
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Section: Applications > Life sciences. The comprehensive set of Aphelion functions is used to analyze images coming from an optical microscope and a camera mounted on top of the microscope. The software also controls the automated stage mounted on the microscope in the X, Y and Z directions. Z is used to change focus. ...
Wikipedia - Aphelion (software) - Applications > Life sciences
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The software that was developed helped the detection of immune-marked cells. Image analysis is also used in histology to study angiogenesis in 2D and 3D on microscopy images to measure effects of inhibitors and accelerants impact on blood vessels growth. ADCIS developed a chromosome classification assistant in the fiel...
Wikipedia - Aphelion (software) - Applications > Life sciences
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In the field of pharmacology, ADCIS used the Aphelion SDK libraries to develop a specific software product to find new molecules inhibiting mitosis in epifluorescence microscopy images. A joint development has been developed in radiology application field by ADCIS and Robert Van't Hof to study osteoporosis images of th...
Wikipedia - Aphelion (software) - Applications > Life sciences
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Section: Applications > Earth science. In the field of geology, scientists based their research work on Aphelion to perform a statistical analysis to determine the relationship between the size and shape of rock debris present in moraines, and the value of the maximal slope that will not cause rockfalls. Morphological ...
Wikipedia - Aphelion (software) - Applications > Earth science
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Section: Applications > Theory. Image Processing and Analysis is a scientific discipline as well as statistics, and set theory are. Research people spend time to find new algorithms, new functions (adaptive contrast, new color space definition, etc.), or even newer techniques such as deep learning. There is a very tigh...
Wikipedia - Aphelion (software) - Applications > Theory
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Section: Software extensions. Below is a list of Aphelion optional extensions: 3D Image Processing and 3D Image Display: A set of extensions to display and process 3D images. The 3D display extension is based on the VTK software product. 3D Skeletonization: Extension to compute the 3D skeleton. Image Registration: Imag...
Wikipedia - Aphelion (software) - Software extensions
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Article: CatBoost. CatBoost is an open-source software library developed by Yandex. It provides a gradient boosting framework which, among other features, attempts to solve for categorical features using a permutation-driven alternative to the classical algorithm. It works on Linux, Windows, macOS, and is available in ...
Wikipedia - CatBoost - Summary
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Section: History. In 2009 Andrey Gulin developed MatrixNet, a proprietary gradient boosting library that was used in Yandex to rank search results. Since 2009 MatrixNet has been used in different projects in Yandex, including recommendation systems and weather prediction. In 2014–2015 Andrey Gulin with a team of resear...
Wikipedia - CatBoost - History
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Section: Interface. DADiSP is designed to perform technical data analysis in a spreadsheet like environment. However, unlike a typical business spreadsheet that operates on a table of cells each of which contain single scalar values, a DADiSP Worksheet consists of multiple interrelated windows where each window contain...
Wikipedia - DADiSP - Interface
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Section: Programming language. DADiSP includes a series based programming language called SPL (Series Processing Language) used to implement custom algorithms. SPL has a C/C++ like syntax and is incrementally compiled into intermediate bytecode, which is executed by a virtual machine. SPL supports both standard variabl...
Wikipedia - DADiSP - Programming language
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Article: Data Mining Extensions. Data Mining Extensions (DMX) is a query language for data mining models supported by Microsoft's SQL Server Analysis Services product. Like SQL, it supports a data definition language (DDL), data manipulation language (DML) and a data query language (DQL), all three with SQL-like syntax...
Wikipedia - Data Mining Extensions - Summary
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Section: Features > Data management. Data and model versioning is the base layer of DVC for large files, datasets, and machine learning models. It allows the use of a standard Git workflow, but without the need to store those files in the repository. Large files, directories and ML models are replaced with small metafi...
Wikipedia - Data Version Control (software) - Features > Data management
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Section: Features > Pipelines. DVC provides a mechanism to define and execute pipelines. Pipelines represent the process of building ML datasets and models, from how data is preprocessed to how models are trained and evaluated. Pipelines can also be used to deploy models into production environments. DVC pipeline is fo...
Wikipedia - Data Version Control (software) - Features > Pipelines
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Section: Features > Experiment tracking. Experiment tracking allows developers to explore, iterate and compare different machine learning experiments. Each experiment represents a variation of a data science project defined by changes in the workspace. Experiments maintain a link to the commit in the current branch (Gi...
Wikipedia - Data Version Control (software) - Features > Experiment tracking
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Section: History. In 2017, the first (beta) version of DVC 0.6 was publicly released (as a simple command line tool). It allowed data scientists to keep track of their machine learning processes and file dependencies in the simple form of git-like commands. It also allowed them to transform existing machine learning pr...
Wikipedia - Data Version Control (software) - History
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In March 2021, DVC released DVC 2.0, which introduced ML experiments (experiment management), model checkpoints and metrics logging. ML experiments: To solve the problem of Git overhead, when hundreds of experiments need to be run in a single day and each experiment run requires additional Git commands, DVC 2.0 introdu...
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Article: Deep Web Technologies. Deep Web Technologies is a software company that specializes in mining the Deep Web — the part of the Internet that is not directly searchable through ordinary web search engines. The company produces a proprietary software platform "Explorit" for searches. It also produces the federated...
Wikipedia - Deep Web Technologies - Summary
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Section: Components. Distributed R is a platform to implement and execute distributed applications in R. The goal is to extend R for distributed computing, while retaining the simplicity and look-and-feel of R. Distributed R consists of the following components: Distributed data structures: Distributed R extends R's co...
Wikipedia - Distributed R - Components
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Section: Integration with databases. HP Vertica provides tight integration with their database and the open source Distributed R platform. HP Vertica 7.1 includes features that enable fast, parallel loading from the Vertica database to Distribute R. This parallel Vertica loader can be more than five times (5x) faster t...
Wikipedia - Distributed R - Integration with databases
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Article: Dlib. Dlib is a general purpose cross-platform software library written in the programming language C++. Its design is heavily influenced by ideas from design by contract and component-based software engineering. Thus it is, first and foremost, a set of independent software components. It is open-source softwa...
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Section: Description. The ELKI framework is written in Java and built around a modular architecture. Most currently included algorithms perform clustering, outlier detection, and database indexes. The object-oriented architecture allows the combination of arbitrary algorithms, data types, distance functions, indexes, a...
Wikipedia - ELKI - Description
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Section: Objectives. The university project is developed for use in teaching and research. The source code is written with extensibility and reusability in mind, but is also optimized for performance. The experimental evaluation of algorithms depends on many environmental factors and implementation details can have a l...
Wikipedia - ELKI - Objectives
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Section: Architecture. ELKI is modeled around a database-inspired core, which uses a vertical data layout that stores data in column groups (similar to column families in NoSQL databases). This database core provides nearest neighbor search, range/radius search, and distance query functionality with index acceleration ...
Wikipedia - ELKI - Architecture
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Select included algorithms: Cluster analysis: K-means clustering (including fast algorithms such as Elkan, Hamerly, Annulus, and Exponion k-Means, and robust variants such as k-means--) K-medians clustering K-medoids clustering (PAM) (including FastPAM and approximations such as CLARA, CLARANS) Expectation-maximization...
Wikipedia - ELKI - Included algorithms
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analysis Multidimensional scaling T-distributed stochastic neighbor embedding (t-SNE) Spatial index structures and other search indexes: R-tree R*-tree M-tree k-d tree X-tree Cover tree iDistance NN descent Locality sensitive hashing (LSH) Evaluation: Precision and recall, F1 score, Average Precision Receiver operating...
Wikipedia - ELKI - Included algorithms
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Section: Version history. Version 0.1 (July 2008) contained several Algorithms from cluster analysis and anomaly detection, as well as some index structures such as the R*-tree. The focus of the first release was on subspace clustering and correlation clustering algorithms. Version 0.2 (July 2009) added functionality f...
Wikipedia - ELKI - Version history
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Section: Version 3. The third generation of Feature Selection Toolbox (FST3) was a library without user interface, written to be more efficient and versatile than the original FST1. FST3 supports several standard data mining tasks, more specifically, data preprocessing and classification, but its main focus is on featu...
Wikipedia - Feature Selection Toolbox - Version 3
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Section: History. In 1999, development of the first Feature Selection Toolbox version started at UTIA as part of a PhD thesis. It was originally developed in Optima++ (later renamed Power++) RAD C++ environment. In 2002, the development of the first FST generation has been suspended, mainly due to end of Sybase's suppo...
Wikipedia - Feature Selection Toolbox - History
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Section: History. FICO was founded in 1956 as Fair, Isaac and Company by engineer William R. "Bill" Fair and mathematician Earl Judson Isaac. The two met while working at the Stanford Research Institute in Menlo Park, California. Selling its first credit scoring system two years after the company's creation, FICO pitch...
Wikipedia - FICO - History
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Section: Antitrust issues. In March 2020, the US Department of Justice (DOJ) opened an antitrust investigation into FICO, which was reported to be closed in December 2020. In March 2024, US Senator Josh Hawley sent a letter to the DOJ's Antitrust Division urging them to open an investigation into FICO for anti-competit...
Wikipedia - FICO - Antitrust issues
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Article: Folding@home. Folding@home (FAH or F@h) is a distributed computing project aimed to help scientists develop new therapeutics for a variety of diseases by the means of simulating protein dynamics. This includes the process of protein folding and the movements of proteins, and is reliant on simulations run on vo...
Wikipedia - Folding@home - Summary
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Section: Background. Proteins are an essential component to many biological functions and participate in virtually all processes within biological cells. They often act as enzymes, performing biochemical reactions including cell signaling, molecular transportation, and cellular regulation. As structural elements, some ...
Wikipedia - Folding@home - Background
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Due to the complexity of proteins' conformation or configuration space (the set of possible shapes a protein can take), and limits in computing power, all-atom molecular dynamics simulations have been severely limited in the timescales that they can study. While most proteins typically fold in the order of milliseconds...
Wikipedia - Folding@home - Background
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MSMs are discrete-time master equation models which describe a biomolecule's conformational and energy landscape as a set of distinct structures and the short transitions between them. The adaptive sampling Markov state model method significantly increases the efficiency of simulation as it avoids computation inside th...
Wikipedia - Folding@home - Background
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In 2002, Folding@home used Markov state models to complete approximately a million CPU days of simulations over the span of several months, and in 2011, MSMs parallelized another simulation that required an aggregate 10 million CPU hours of computing. In January 2010, Folding@home used MSMs to simulate the dynamics of ...
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Section: Examples of application in biomedical research. Protein misfolding can result in a variety of diseases including Alzheimer's disease, cancer, Creutzfeldt–Jakob disease, cystic fibrosis, Huntington's disease, sickle-cell anemia, and type II diabetes. Cellular infection by viruses such as HIV and influenza also ...
Wikipedia - Folding@home - Examples of application in biomedical research
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Furthermore, scientists typically employ chemical denaturants to unfold proteins from their stable native state. It is not generally known how the denaturant affects the protein's refolding, and it is difficult to experimentally determine if these denatured states contain residual structures which may influence folding...
Wikipedia - Folding@home - Examples of application in biomedical research
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Section: Examples of application in biomedical research > Alzheimer's disease. Alzheimer's disease is an incurable neurodegenerative disease which most often affects the elderly and accounts for more than half of all cases of dementia. Its exact cause remains unknown, but the disease is identified as a protein misfoldi...
Wikipedia - Folding@home - Examples of application in biomedical research > Alzheimer's disease
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The study helped prepare the Pande lab for future aggregation studies and for further research to find a small peptide which may stabilize the aggregation process. In December 2008, Folding@home found several small drug candidates which appear to inhibit the toxicity of Aβ aggregates. In 2010, in close cooperation with...
Wikipedia - Folding@home - Examples of application in biomedical research > Alzheimer's disease
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Section: Examples of application in biomedical research > Huntington's disease. Huntington's disease is a neurodegenerative genetic disorder that is associated with protein misfolding and aggregation. Excessive repeats of the glutamine amino acid at the N-terminus of the huntingtin protein cause aggregation, and althou...
Wikipedia - Folding@home - Examples of application in biomedical research > Huntington's disease
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Section: Examples of application in biomedical research > Cancer. More than half of all known cancers involve mutations of p53, a tumor suppressor protein present in every cell which regulates the cell cycle and signals for cell death in the event of damage to DNA. Specific mutations in p53 can disrupt these functions,...
Wikipedia - Folding@home - Examples of application in biomedical research > Cancer
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Inhibitions to these specific chaperones are seen as potential modes of action for efficient chemotherapy drugs or for reducing the spread of cancer. Using Folding@home and working closely with the Center for Protein Folding Machinery, the Pande lab hopes to find a drug which inhibits those chaperones involved in cance...
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Section: Examples of application in biomedical research > Osteogenesis imperfecta. Osteogenesis imperfecta, known as brittle bone disease, is an incurable genetic bone disorder which can be lethal. Those with the disease are unable to make functional connective bone tissue. This is most commonly due to a mutation in Ty...
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Section: Examples of application in biomedical research > Viruses. Folding@home is assisting in research towards preventing some viruses, such as influenza and HIV, from recognizing and entering biological cells. In 2011, Folding@home began simulations of the dynamics of the enzyme RNase H, a key component of HIV, to t...
Wikipedia - Folding@home - Examples of application in biomedical research > Viruses
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Mutations to hemagglutinin affect how well the protein binds to a host's cell surface receptor molecules, which determines how infective the virus strain is to the host organism. Knowledge of the effects of hemagglutinin mutations assists in the development of antiviral drugs. As of 2012, Folding@home continues to simu...
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Section: Examples of application in biomedical research > Drug design. Drugs function by binding to specific locations on target molecules and causing some desired change, such as disabling a target or causing a conformational change. Ideally, a drug should act very specifically, and bind only to its target without int...
Wikipedia - Folding@home - Examples of application in biomedical research > Drug design
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However, this approach works for approximately only 15% of all proteins. Proteins contain allosteric sites which, when bound to by small molecules, can alter a protein's conformation and ultimately affect the protein's activity. These sites are attractive drug targets, but locating them is very computationally costly. ...
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Section: Patterns of participation. Like other distributed computing projects, Folding@home is an online citizen science project. In these projects non-specialists contribute computer processing power or help to analyze data produced by professional scientists. Participants receive little or no obvious reward. Research...
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Section: Patterns of participation > Performance. Supercomputer FLOPS performance is assessed by running the legacy LINPACK benchmark. This short-term testing has difficulty in accurately reflecting sustained performance on real-world tasks because LINPACK more efficiently maps to supercomputer hardware. Computing syst...
Wikipedia - Folding@home - Patterns of participation > Performance
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On November 10, 2011, Folding@home's performance exceeded six native petaFLOPS with the equivalent of nearly eight x86 petaFLOPS. In mid-May 2013, Folding@home attained over seven native petaFLOPS, with the equivalent of 14.87 x86 petaFLOPS. It then reached eight native petaFLOPS on June 21, followed by nine on Septemb...
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Section: Patterns of participation > Points. Similarly to other distributed computing projects, Folding@home quantitatively assesses user computing contributions to the project through a credit system. All units from a given protein project have uniform base credit, which is determined by benchmarking one or more work ...
Wikipedia - Folding@home - Patterns of participation > Points
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Section: Software > Work units. A work unit is the protein data that the client is asked to process. Work units are a fraction of the simulation between the states in a Markov model. After the work unit has been downloaded and completely processed by a volunteer's computer, it is returned to Folding@home servers, which...
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