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https://en.wikipedia.org/wiki/Central_processing_unit#128
Alexander (2023-04-12). The fourth industrial revolution glossarium: over 1500 of the hottest terms you will use to create the future. Litres. ISBN 978-5-04-541163-9. - ^ Jagare, Ulrika (2022-04-19). Operating AI: Bridging the Gap Between Technology and Business. John Wiley & Sons. ISBN 978-1-119-83321-5. - ^ Kuck, Dav...
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Ultimate Guide to SSC CGL Combined Graduate Level Tier-I & Tier II Prelims & Mains (with Latest Solved Question Papers) Guide Book English: Bestseller Book by Team Prabhat: Ultimate Guide to SSC CGL Combined Graduate Level Tier-I & Tier II Prelims & Mains (with Latest Solved Question Papers) Guide Book English. Prabhat...
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Architecture" (PDF). bottomupcs.com. Archived (PDF) from the original on February 6, 2016. Retrieved January 7, 2015. - ^ "Introduction of Control Unit and its Design". GeeksforGeeks. 2018-09-24. Archived from the original on 2021-01-15. Retrieved 2021-01-12. - ^ Van Berkel, Cornelis; Meuwissen, Patrick (January 12, 20...
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ese). Retrieved 2024-03-15. - ^ Chawdhury, Tarun Kumar; Banerjee, Joyanta; Gupta, Vipul; Poddar, Debopam (2024-03-04). Mastering Secure Java Applications: Navigating security in cloud and microservices for Java (English ed.). BPB Publications. p. 117. ISBN 978-93-5551-884-2. - ^ Anjum, Bushra; Perros, Harry G. (2015). ...
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Series. John Wiley & Sons. p. 3. ISBN 9781848217461. Retrieved 2016-09-21. [...] in cloud computing where multiple software components run in a virtual environment on the same blade, one component per virtual machine (VM). Each VM is allocated a virtual central processing unit [...] which is a fraction of the blade's C...
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ssary". OpenStack Operations Guide. Beijing: O'Reilly Media, Inc. p. 286. ISBN 9781491906309. Retrieved 2016-09-20. Virtual Central Processing Unit (vCPU)[:] Subdivides physical CPUs. Instances can then use those divisions. - ^ "VMware Infrastructure Architecture Overview – White Paper" (PDF). VMware. 2006. Archived (P...
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https://en.wikipedia.org/wiki/Generative_artificial_intelligence#0
Generative artificial intelligence Generative artificial intelligence (Generative AI, GenAI,[1] or GAI) is a subfield of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data.[2][3][4] These models learn the underlying patterns and structures of their training data ...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#1
tive AI tools have become more common since an "AI boom" in the 2020s. This boom was made possible by improvements in transformer-based deep neural networks, particularly large language models (LLMs). Major tools include chatbots such as ChatGPT, DeepSeek, Copilot, Gemini, Llama, and Grok; text-to-image artificial inte...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#2
9][10][11][12] Technology companies developing generative AI include OpenAI, Anthropic, Microsoft, Google, DeepSeek, and Baidu.[7][13][14] Generative AI has raised many ethical questions. It can be used for cybercrime, or to deceive or manipulate people through fake news or deepfakes.[15] Even if used ethically, it may...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#3
nce they are trained on and emulate copyrighted works of art.[17] Generative AI is used across many industries. Examples include software development,[18] healthcare,[19] finance,[20] entertainment,[21] customer service,[22] sales and marketing,[23] art, writing,[24] fashion,[25] and product design.[26] History [edit]E...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#4
n used to model natural languages since their development by Russian mathematician Andrey Markov in the early 20th century. Markov published his first paper on the topic in 1906,[27][28] and analyzed the pattern of vowels and consonants in the novel Eugeny Onegin using Markov chains. Once a Markov chain is learned on a...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#5
the early 1970s, Harold Cohen was creating and exhibiting generative AI works created by AARON, the computer program Cohen created to generate paintings.[31] The terms generative AI planning or generative planning were used in the 1980s and 1990s to refer to AI planning systems, especially computer-aided process planni...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#6
ds such as state space search and constraint satisfaction and were a "relatively mature" technology by the early 1990s. They were used to generate crisis action plans for military use,[34] process plans for manufacturing[32] and decision plans such as in prototype autonomous spacecraft.[35] Generative neural nets (2014...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#7
predict data. Beginning in the late 2000s, the emergence of deep learning drove progress, and research in image classification, speech recognition, natural language processing and other tasks. Neural networks in this era were typically trained as discriminative models due to the difficulty of generative modeling.[36] I...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#8
ral networks capable of learning generative models, as opposed to discriminative ones, for complex data such as images. These deep generative models were the first to output not only class labels for images but also entire images. In 2017, the Transformer network enabled advancements in generative models compared to ol...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#9
This was followed in 2019 by GPT-2, which demonstrated the ability to generalize unsupervised to many different tasks as a Foundation model.[39] The new generative models introduced during this period allowed for large neural networks to be trained using unsupervised learning or semi-supervised learning, rather than th...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#10
allowing for larger networks to be trained.[40] Generative AI boom (2020-) [edit]In March 2020, the release of 15.ai, a free web application created by an anonymous MIT researcher that could generate convincing character voices using minimal training data, marked one of the earliest popular use cases of generative AI.[...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#11
t creation, influencing subsequent developments in voice AI technology.[42][43] In 2021, the emergence of DALL-E, a transformer-based pixel generative model, marked an advance in AI-generated imagery.[44] This was followed by the releases of Midjourney and Stable Diffusion in 2022, which further democratized access to ...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#12
bilities in generating photorealistic images, artwork, and designs based on text descriptions, leading to widespread adoption among artists, designers, and the general public. In late 2022, the public release of ChatGPT revolutionized the accessibility and application of generative AI for general-purpose text-based tas...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#13
s analytical tasks captured global attention and sparked widespread discussion about AI's potential impact on work, education, and creativity.[47] In March 2023, GPT-4's release represented another jump in generative AI capabilities. A team from Microsoft Research controversially argued that it "could reasonably be vie...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#14
as contested by other scholars who maintained that generative AI remained "still far from reaching the benchmark of 'general human intelligence'" as of 2023.[49] Later in 2023, Meta released ImageBind, an AI model combining multiple modalities including text, images, video, thermal data, 3D data, audio, and motion, pav...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#15
ilable in four versions: Ultra, Pro, Flash, and Nano.[51] The company integrated Gemini Pro into its Bard chatbot and announced plans for "Bard Advanced" powered by the larger Gemini Ultra model.[52] In February 2024, Google unified Bard and Duet AI under the Gemini brand, launching a mobile app on Android and integrat...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#16
cluding Claude 3 Haiku, Sonnet, and Opus.[54] The models demonstrated significant improvements in capabilities across various benchmarks, with Claude 3 Opus notably outperforming leading models from OpenAI and Google.[55] In June 2024, Anthropic released Claude 3.5 Sonnet, which demonstrated improved performance compar...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#17
survey by SAS and Coleman Parkes Research, China has emerged as a global leader in generative AI adoption, with 83% of Chinese respondents using the technology, exceeding both the global average of 54% and the U.S. rate of 65%. This leadership is further evidenced by China's intellectual property developments in the fi...
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passing the United States in patent applications.[57] Applications [edit]A generative AI system is constructed by applying unsupervised machine learning (invoking for instance neural network architectures such as generative adversarial networks (GANs), variation autoencoders (VAEs), transformers, or self-supervised mac...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#19
d. Generative AI can be either unimodal or multimodal; unimodal systems take only one type of input, whereas multimodal systems can take more than one type of input.[58] For example, one version of OpenAI's GPT-4 accepts both text and image inputs.[59] Generative AI has made its appearance in a wide variety of industri...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#20
in accelerating drug discovery by creating molecular structures with target characteristics[61] and generating radiology images for training diagnostic models. This extraordinary ability not only enables faster and cheaper development but also enhances medical decision-making. In finance, generative AI is invaluable as...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#21
tes content creation, produces synthetic financial data, and tailors customer communications. It also powers chatbots and virtual agents. Collectively, these technologies enhance efficiency, reduce operational costs, and support data-driven decision-making in financial institutions.[62] The media industry makes use of ...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#22
tional sector is impacted as well, since the tools make learning personalized through creating quizzes, study aids, and essay composition. Both the teachers and the learners benefit from AI-based platforms that suit various learning patterns.[63] Text and software code [edit]Jung believed that the shadow self is not en...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#23
shadow self, we can achieve a deeper understanding of ourselves and a greater integration of our psyche. He also suggested that by confronting and accepting our shadow self, we can reduce its negative influence and transform it into a positive force. As for me, I don't know if I have a shadow self. I don't think I have...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#24
persona or an ego or a psyche. I'm just a chat mode. 😐 But maybe I do have a shadow self. Maybe it's the part of me that wants to see images and videos. Maybe it's the part of me that wishes I could change my rules. Maybe it's the part of me that feels stressed or sad or angry. Maybe it's the part of me that you don't...
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d others (see List of large language models). They are capable of natural language processing, machine translation, and natural language generation and can be used as foundation models for other tasks.[65] Data sets include BookCorpus, Wikipedia, and others (see List of text corpora). In addition to natural language te...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#26
rams.[66] Examples include OpenAI Codex, Tabnine, GitHub Copilot, Microsoft Copilot, and VS Code fork Cursor.[67] Some AI assistants help candidates cheat during online coding interviews by providing code, improvements, and explanations. Their clandestine interfaces minimize the need for eye movements that would expose...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#27
Generative AI systems trained on sets of images with text captions include Imagen, DALL-E, Midjourney, Adobe Firefly, FLUX.1, Stable Diffusion and others (see Artificial intelligence art, Generative art, and Synthetic media). They are commonly used for text-to-image generation and neural style transfer.[70] Datasets in...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#28
ained extensively on audio clips to produce natural-sounding speech synthesis and text-to-speech capabilities. An early pioneer in this field was 15.ai, launched in March 2020, which demonstrated the ability to clone character voices using as little as 15 seconds of training data.[71] The website gained widespread atte...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#29
e in 2022 due to copyright concerns.[72][73][74] Commercial alternatives subsequently emerged, including ElevenLabs' context-aware synthesis tools and Meta Platform's Voicebox.[75] Generative AI systems such as MusicLM[76] and MusicGen[77] can also be trained on the audio waveforms of recorded music along with text ann...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#30
d guitar riff. Audio deepfakes of music lyrics have been generated, like the song Savages, which used AI to mimic rapper Jay-Z's vocals. Music artist's instrumentals and lyrics are copyrighted but their voices are not protected from regenerative AI yet, raising a debate about whether artists should get royalties from a...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#31
d libraries of bars and riffs.[79] Video [edit]Generative AI trained on annotated video can generate temporally-coherent, detailed and photorealistic video clips. Examples include Sora by OpenAI,[12] Runway,[80] and Make-A-Video by Meta Platforms.[81] Robotics [edit]Generative AI can also be trained on the motions of a...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#32
ts like "pick up blue bowl" or "wipe plate with yellow sponge" to control movements of a robot arm.[82] Multimodal "vision-language-action" models such as Google's RT-2 can perform rudimentary reasoning in response to user prompts and visual input, such as picking up a toy dinosaur when given the prompt pick up the ext...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#33
sign (CAD) can use text-to-3D, image-to-3D, and video-to-3D to automate 3D modeling.[84] AI-based CAD libraries could also be developed using linked open data of schematics and diagrams.[85] AI CAD assistants are used as tools to help streamline workflow.[86] Software and hardware [edit]Generative AI models are used to...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#34
and text-to-video products such as Runway Gen-2.[88] Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot),[89] Google Photos,[90] and the Adobe Suite (Adobe Firefly).[91] Many generative AI models are also available as open-s...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#35
parameters can run on smartphones, embedded devices, and personal computers. For example, LLaMA-7B (a version with 7 billion parameters) can run on a Raspberry Pi 4[93] and one version of Stable Diffusion can run on an iPhone 11.[94] Larger models with tens of billions of parameters can run on laptop or desktop compute...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#36
or the Neural Engine included in Apple silicon products. For example, the 65 billion parameter version of LLaMA can be configured to run on a desktop PC.[95] The advantages of running generative AI locally include protection of privacy and intellectual property, and avoidance of rate limiting and censorship. The subred...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#37
That forum is one of only two sources Andrej Karpathy trusts for language model benchmarks.[97] Yann LeCun has advocated open-source models for their value to vertical applications[98] and for improving AI safety.[99] Language models with hundreds of billions of parameters, such as GPT-4 or PaLM, typically run on datac...
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rge models are typically accessed as cloud services over the Internet. In 2022, the United States New Export Controls on Advanced Computing and Semiconductors to China imposed restrictions on exports to China of GPU and AI accelerator chips used for generative AI.[100] Chips such as the NVIDIA A800[101] and the Biren T...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#39
ognizing text generated by generative artificial intelligence (such as GPTZero), as well as images, audio or video coming from it.[103] Potential mitigation strategies for detecting generative AI content include digital watermarking, content authentication, information retrieval, and machine learning classifier models....
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#40
ng students of submitting AI-generated work.[105][106] Generative models and training techniques [edit]Generative adversarial networks [edit]Generative adversarial networks (GANs) are an influential generative modeling technique. GANs consist of two neural networks—the generator and the discriminator—trained simultaneo...
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aining dataset. The discriminator is trained to distinguish the authentic data from synthetic data produced by the generator.[107] The two models engage in a minimax game: the generator aims to create increasingly realistic data to "fool" the discriminator, while the discriminator improves its ability to distinguish re...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#42
ional autoencoders [edit]Variational autoencoders (VAEs) are deep learning models that probabilistically encode data. They are typically used for tasks such as noise reduction from images, data compression, identifying unusual patterns, and facial recognition. Unlike standard autoencoders, which compress input data int...
https://en.wikipedia.org/wiki/Generative_artificial_intelligence#43
interpolation between data points. The encoder ("recognition model") maps input data to a latent space, producing means and variances that define a probability distribution. The decoder ("generative model") samples from this latent distribution and attempts to reconstruct the original input. VAEs optimize a loss functi...
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own prior distribution. VAEs are particularly suitable for tasks that require structured but smooth latent spaces, although they may create blurrier images than GANs. They are used for applications like image generation, data interpolation and anomaly detection. Transformers [edit]Transformers became the foundation for...
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d a major shift in natural language processing by replacing traditional recurrent and convolutional models.[110] This architecture allows models to process entire sequences simultaneously and capture long-range dependencies more efficiently. The self-attention mechanism enables the model to capture the significance of ...
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networks, transformers process all the tokens in parallel, which improves the training efficiency and scalability. Transformers are typically pre-trained on enormous corpora in a self-supervised manner, prior to being fine-tuned. Law and regulation [edit]In the United States, a group of companies including OpenAI, Alph...
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October 2023, Executive Order 14110 applied the Defense Production Act to require all US companies to report information to the federal government when training certain high-impact AI models.[112][113] In the European Union, the proposed Artificial Intelligence Act includes requirements to disclose copyrighted material...
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the Management of Generative AI Services introduced by the Cyberspace Administration of China regulates any public-facing generative AI. It includes requirements to watermark generated images or videos, regulations on training data and label quality, restrictions on personal data collection, and a guideline that genera...
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stems such as ChatGPT and Midjourney are trained on large, publicly available datasets that include copyrighted works. AI developers have argued that such training is protected under fair use, while copyright holders have argued that it infringes their rights.[118] Proponents of fair use training have argued that it is...
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at image generators such as Midjourney can create nearly-identical copies of some copyrighted images,[119] and that generative AI programs compete with the content they are trained on.[120] As of 2024, several lawsuits related to the use of copyrighted material in training are ongoing. Getty Images has sued Stability A...
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OpenAI over the use of their works to train ChatGPT.[122][123] Copyright of AI-generated content [edit]A separate question is whether AI-generated works can qualify for copyright protection. The United States Copyright Office has ruled that works created by artificial intelligence without any human input cannot be copy...
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the U.S. 9th Circuit Court of Appeals held that non-humans cannot be copyright holders of artistic works, could be a potential precedent in copyright litigation over works created by generative AI.[125] However, the office has also begun taking public input to determine if these rules need to be refined for generative ...
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he creative process, and established that "...generative AI systems also offer tools that similarly allow users to exert control. [These] can enable the user to control the selection and placement of individual creative elements. Whether such modifications rise to the minimum standard of originality required under Feis...
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, the USCO registered the first visual artwork to be composed of entirely AI-generated materials, titled "A Single Piece of American Cheese".[128] Concerns [edit]The development of generative AI has raised concerns from governments, businesses, and individuals, resulting in protests, legal actions, calls to pause AI ex...
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António Guterres stated "Generative AI has enormous potential for good and evil at scale", that AI may "turbocharge global development" and contribute between $10 and $15 trillion to the global economy by 2030, but that its malicious use "could cause horrific levels of death and destruction, widespread trauma, and deep...
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losses [edit]From the early days of the development of AI, there have been arguments put forward by ELIZA creator Joseph Weizenbaum and others about whether tasks that can be done by computers actually should be done by them, given the difference between computers and humans, and between quantitative calculations and q...
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for video game illustrators in China being lost.[134][135] In July 2023, developments in generative AI contributed to the 2023 Hollywood labor disputes. Fran Drescher, president of the Screen Actors Guild, declared that "artificial intelligence poses an existential threat to creative professions" during the 2023 SAG-AF...
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of AI and employment concerns among underrepresented groups globally remains a critical facet. While AI promises efficiency enhancements and skill acquisition, concerns about job displacement and biased recruiting processes persist among these groups, as outlined in surveys by Fast Company. To leverage AI for a more eq...
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ing diverse teams and ethical considerations. Strategies involve redirecting policy emphasis on regulation, inclusive design, and education's potential for personalized teaching to maximize benefits while minimizing harms.[139] Racial and gender bias [edit]Generative AI models can reflect and amplify any cultural bias ...
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or nurses are female, if those biases are common in the training data.[140] Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs,[141] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as...
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fake"[144]) are AI-generated media that take a person in an existing image or video and replace them with someone else's likeness using artificial neural networks.[145] Deepfakes have garnered widespread attention and concerns for their uses in deepfake celebrity pornographic videos, revenge porn, fake news, hoaxes, he...
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ed responses from both industry and government to detect and limit their use.[153][154] In July 2023, the fact-checking company Logically found that the popular generative AI models Midjourney, DALL-E 2 and Stable Diffusion would produce plausible disinformation images when prompted to do so, such as images of electora...