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{{see also|Organizations}} | |||
==Introduction== | |||
[[OpenAI]] is an [[Artificial Intelligence]] ([[AI]]) research [[company]] founded in 2015. Originally a [[non-profit]], intended to be free from the need to generate financial return, it has since also founded OpenAI LP, a for-profit corporation <ref name="”1”">OpenAI. About. OpenAI. https://openai.com/about/</ref> <ref name="”2”">Floridi, L and Chiriatti, M (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines 30:681-694.</ref> <ref name="”3”">Olanoff, D (2015). Artificial Intelligence Nonprofit OpenAI launches With Backing of Elon Musk and Sal Altman. TechCrunch. https://techcrunch.com/2015/12/11/non-profit-openai-launches-with-backing-from-elon-musk-and-sam-altman/</ref>. The stated mission is to promote and develop friendly AI beneficial to all humanity <ref name="”1”" /> <ref name="”2”" />. It received financial support by it's founders members Sam Altman, Greg Brockman and Elon Musk, and also from Jessica Livingston, Peter Thiel, Amazon Web Services, Infosys and YC Research with a $1 billion investment in total <ref name="”3”" />. In 2020, [[Microsoft]], another investor in OpenAI, announce an exclusive license agreement for [[GPT-3]] <ref name="”2”" />. | [[OpenAI]] is an [[Artificial Intelligence]] ([[AI]]) research [[company]] founded in 2015. Originally a [[non-profit]], intended to be free from the need to generate financial return, it has since also founded OpenAI LP, a for-profit corporation <ref name="”1”">OpenAI. About. OpenAI. https://openai.com/about/</ref> <ref name="”2”">Floridi, L and Chiriatti, M (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines 30:681-694.</ref> <ref name="”3”">Olanoff, D (2015). Artificial Intelligence Nonprofit OpenAI launches With Backing of Elon Musk and Sal Altman. TechCrunch. https://techcrunch.com/2015/12/11/non-profit-openai-launches-with-backing-from-elon-musk-and-sam-altman/</ref>. The stated mission is to promote and develop friendly AI beneficial to all humanity <ref name="”1”" /> <ref name="”2”" />. It received financial support by it's founders members Sam Altman, Greg Brockman and Elon Musk, and also from Jessica Livingston, Peter Thiel, Amazon Web Services, Infosys and YC Research with a $1 billion investment in total <ref name="”3”" />. In 2020, [[Microsoft]], another investor in OpenAI, announce an exclusive license agreement for [[GPT-3]] <ref name="”2”" />. | ||
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==Applications== | ==Applications== | ||
===OpenAI | ===OpenAI Gym=== | ||
[[OpenAI Gym]] is a toolkit for developing and comparing [[reinforcement learning]] (RL) algorithms. While best suited for RL research, it is not restrictive to only that, being able to support alternative methods such as hard coded game solver or other deep learning strategies <ref name="”7”">Brockman et al. (2016). OpenAI Gym. arXiv:1606.01540v1.</ref> <ref name="”8”">Sonawane, B (2018). Getting started with OpenAI Gym. Towards Data Science. https://towardsdatascience.com/getting-started-with-openai-gym-d2ac911f5cbc</ref> <ref name="”9”">OpenAI (2016). OpenAI Gym Beta. OpenAI. https://openai.com/blog/openai-gym-beta/#rl</ref>. The environments are written in Python but, in the future, they'll be easy to use from any language. OpenAI GYM is compatible with algorithms written in any framework, like [[Tensorflow]] and [[Theano]] <ref name="”9”" />. The platform includes a collection of benchmark problems using a common interface and website where the community can share results and compare the performance of algorithms. Users are also encouraged to share the source code and instructions on how to reproduce their results <ref name="”7”" />. | |||
[[OpenAI | |||
===DALL-E=== | ===DALL-E=== | ||
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OpenAI has granted users with "full usage rights to commercialize the images they create with DALL-E, including the right to reprint, sell, and merchandise <ref name="”13”">Rizo, J (2022). Who Will Own the Art of the Future? Wired. https://www.wired.com/story/openai-dalle-copyright-intellectual-property-art/</ref>." | OpenAI has granted users with "full usage rights to commercialize the images they create with DALL-E, including the right to reprint, sell, and merchandise <ref name="”13”">Rizo, J (2022). Who Will Own the Art of the Future? Wired. https://www.wired.com/story/openai-dalle-copyright-intellectual-property-art/</ref>." | ||
===GPT-1 and GPT-2=== | |||
[[GPT]] or [[Generative Pre-trained Transformer]] was introduced in the [[paper]] [[Improving Language Understanding by Generative Pre-Training]] in June 2018. [[GPT-1]] combined the [[transformers]] [[architecture]] with [[unsupervised learning]] to create a [[model]] with 117 million [[parameters]] and trained on 7000 books. [[GPT-2]], released in February 2019 with the paper [[Language Models are Unsupervised Multitask Learners]], had 1.5 billion parameters and was trained 40GB of web text from 8 million documents. | |||
===GPT-3=== | ===GPT-3=== | ||
[[GPT-3]] (Generative Pre-trained Transformer 3) is the third generation of a computational system that generates text, code or other data, starting from a source input, the prompt. This system uses deep learning to produce human-like text <ref name="”2”" /> <ref name="”14”">Wilhelm, A (2021). Ok, the GPT-3 Hype Seems Pretty Reasonable. TechCrunch. https://techcrunch.com/2021/03/17/okay-the-gpt-3-hype-seems-pretty-reasonable/</ref>(2, 14). According to Zhang & Li (2021), GPT-3 is the "language model with the most parameters, the largest scale, and the strongest capabilities. Using a large amount of Internet text data and thousands of books for model training, GPT-3 can imitate the natural language patterns of humans nearly perfectly. This language model is extremely realistic and is considered the most impressive model as of today <ref name="”15”">Zhang, M and Li, J (2021). A Commentary of GPT-3 in MIT Technology Review 2021. Fundamental Research 1(6):831-833.</ref>." | [[GPT-3]] (Generative Pre-trained Transformer 3) is the third generation of a computational system that generates text, code or other data, starting from a source input, the prompt. This system uses deep learning to produce human-like text <ref name="”2”" /> <ref name="”14”">Wilhelm, A (2021). Ok, the GPT-3 Hype Seems Pretty Reasonable. TechCrunch. https://techcrunch.com/2021/03/17/okay-the-gpt-3-hype-seems-pretty-reasonable/</ref>(2, 14). According to Zhang & Li (2021), GPT-3 is the "language model with the most parameters, the largest scale, and the strongest capabilities. Using a large amount of Internet text data and thousands of books for model training, GPT-3 can imitate the natural language patterns of humans nearly perfectly. This language model is extremely realistic and is considered the most impressive model as of today <ref name="”15”">Zhang, M and Li, J (2021). A Commentary of GPT-3 in MIT Technology Review 2021. Fundamental Research 1(6):831-833.</ref>." | ||
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===Universe=== | ===Universe=== | ||
[[OpenAI Universe]] is a software platform for measuring and training AI's general intelligence with video games, applications and websites. With this software, an AI agent can use a computer like a human, looking at screen pixels and using a virtual keyboard and mouse, allowing the training of a single agent in tasks that a human can complete with a computer <ref name="”16”">OpenAI (2016). Universe. OpenAI. https://openai.com/blog/universe/</ref> <ref name="”17”">Mannes, J (2016). OpenAI's Universe is the Fun Parent Every Artificial Intelligence Deserves. TechCrunch. https://techcrunch.com/2016/12/05/openais-universe-is-the-fun-parent-every-artificial-intelligence-deserves/</ref>. According to OpenAI, the goal is to "develop a single AI agent that can flexibly apply its past experience on Universe environments to quickly master unfamiliar, difficult environments, which would be a major step towards general intelligence <ref name="”16”" />." To achieve that, it was released with Atari 2600 games, 1000 flash games and 80 browser environments <ref name="”17”" />. | |||
[[Universe]] is a software platform for measuring and training AI's general intelligence with video games, applications and websites. With this software, an AI agent can use a computer like a human, looking at screen pixels and using a virtual keyboard and mouse, allowing the training of a single agent in tasks that a human can complete with a computer <ref name="”16”">OpenAI (2016). Universe. OpenAI. https://openai.com/blog/universe/</ref> <ref name="”17”">Mannes, J (2016). OpenAI's Universe is the Fun Parent Every Artificial Intelligence Deserves. TechCrunch. https://techcrunch.com/2016/12/05/openais-universe-is-the-fun-parent-every-artificial-intelligence-deserves/</ref>. According to OpenAI, the goal is to "develop a single AI agent that can flexibly apply its past experience on Universe environments to quickly master unfamiliar, difficult environments, which would be a major step towards general intelligence <ref name="”16”" />." To achieve that, it was released with Atari 2600 games, 1000 flash games and 80 browser environments <ref name="”17”" />. | |||
===Copilot=== | ===Copilot=== | ||
[[Copilot]] is an AI software developed by OpenAI and [[GitHub]] that suggests code and entire functions in real-time for programmers <ref name="”18”">Github. Your AI Pair Programmer. Github. https://github.com/features/copilot</ref> <ref name="”19”">Thompson, C (2022). It’s Like GPT-3 but for Code—Fun, Fast, and Full of Flaws. Wired. https://www.wired.com/story/openai-copilot-autocomplete-for-code/</ref>. It has been described as an autocomplete for software development. Released during the summer of 2021, the tool has been used by tens of thousands of programmers. While it makes erros, feedback provided by professionals has been positive, observing that it accelerates their pace. According to data provided by GitHub and OpenAI, Copilot writes 35 percent of it's users' newly posted code <ref name="”19”" />. | [[GitHub Copilot]] is an AI software developed by OpenAI and [[GitHub]] that suggests code and entire functions in real-time for programmers <ref name="”18”">Github. Your AI Pair Programmer. Github. https://github.com/features/copilot</ref> <ref name="”19”">Thompson, C (2022). It’s Like GPT-3 but for Code—Fun, Fast, and Full of Flaws. Wired. https://www.wired.com/story/openai-copilot-autocomplete-for-code/</ref>. It has been described as an autocomplete for software development. Released during the summer of 2021, the tool has been used by tens of thousands of programmers. While it makes erros, feedback provided by professionals has been positive, observing that it accelerates their pace. According to data provided by GitHub and OpenAI, Copilot writes 35 percent of it's users' newly posted code <ref name="”19”" />. | ||
===Whisper=== | ===Whisper=== | ||
[[OpenAI Whisper]] is an open-source [[automatic speech recognition]] (ASR) system that enables transcription in multiple languages and translation into English <ref name="”20”">Wiggers, K (2022). OpenAI open-sources Whisper, a Multilingual Speech Recognition System. TechCrunch. https://techcrunch.com/2022/09/21/openai-open-sources-whisper-a-multilingual-speech-recognition-system/</ref> <ref name="”21”">Bureau, ET (2022). OpenAI Open-Sources Multilingual Speech Recognition System, Dubbed Whisper. EnterpriseTalk. https://enterprisetalk.com/quick-bytes/openai-open-sources-multilingual-speech-recognition-system-dubbed-whisper/</ref> <ref name="”22”">OpenAI (2022). Introducing Whisper. OpenAI. https://openai.com/blog/whisper/</ref>. OpenAI stated that the system has been "trained on 680,000 hours of multilingual and multitask supervised data collected from the web. We show that the use of such a large and diverse dataset leads to improved robustness to accents, background noise and technical language <ref name="”22”" />." The primary users of Whisper are intended to be AI researchers "studying robustness, generalization, capabilities, biases and constraints of the current model." Several downloadable versions of Whisper are available at Github and, according to OpenAI, have shown strong ASR results in more or less 10 languages <ref name="”20”" />. | |||
[[ | ===ChatGPT=== | ||
[[ChatGPT]] is a [[large language model]] (LLM) trained to [[text generator|generate human-like text]] based on user [[input]]. The technology behind ChatGPT is based on an upgraded version of [[GPT-3]] called GPT-3.5. In addition to text, ChatGPT was trained on programming code, which gives it better reasoning and allows it to have logic in its responses. Additionally, it received [[supervised learning]] by [[fine-tune]]ing the model on labeled content like labeled dialogue and human-ranked answers in QnA to give it conversational abilities. ChatGPT was introduced in November 2022 and quickly became extremely popular. Millions of people signing up to try it out. ChatGPT has several distinctive features, including the ability to [[text generation|generate text]] in response to a [[prompt]], interact in a conversational way, provide information on a wide range of topics, and be embedded in various [[applications]]. The potential applications of ChatGPT are vast and could revolutionize many different commercial and non-commercial fields, such as content creation and programming.<ref name="”24”">OpenAI (2022). ChatGPT: Optimizing Language Models for Dialogue. OpenAI. https://openai.com/blog/chatgpt/</ref> | |||
=== | ===AI Text Classifier=== | ||
[[ | [[OpenAI AI Text Classifier|AI Text Classifier]] is a [[AI content detector]] trained to distinguish between text written by a human and text written by [[artificial intelligence]] from various sources. The classifier correctly identifies 26% of AI-written texts as “likely AI-written” while incorrectly labeling 9% of the human-written texts as such. OpenAI made this available for feedback on whether imperfect tools like this one are useful or not. Limitations of the classifier include short input length (below 1000 characters), incorrect labeling of confident predictions, only works in English language, predictable patterns cannot be reliably identified, and editing can evade detection. The training data includes pairs of human and AI-generated responses to prompts submitted to [[InstructGPT]], along with pretraining data sets collected from multiple sources.<ref name="”23”">Hendrik, J (2023). New AI classifier for indicating AI-written text. OpenAI. https://openai.com/blog/new-ai-classifier-for-indicating-ai-written-text/</ref> | ||
==References== | ==References== | ||
<references /> | <references /> | ||