Difference between revisions of "Timeline of OpenAI"

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| 2020 || {{dts|February 17}} || || Coverage || AI reporter Karen Hao at ''MIT Technology Review'' publishes review on OpenAI titled ''The messy, secretive reality behind OpenAI’s bid to save the world'', which suggests the company is surrendering its declaration to be transparent in order to outpace competitors.<ref>{{cite web|url = https://www.technologyreview.com/2020/02/17/844721/ai-openai-moonshot-elon-musk-sam-altman-greg-brockman-messy-secretive-reality/|title = The messy, secretive reality behind OpenAI’s bid to save the world. The AI moonshot was founded in the spirit of transparency. This is the inside story of how competitive pressure eroded that idealism.|last = Hao|first = Karen|publisher = Technology Review}}</ref> As a response, {{w|Elon Musk}} criticizes OpenAI, saying it lacks transparency.<ref name="Aaron">{{cite web |last1=Holmes |first1=Aaron |title=Elon Musk just criticized the artificial intelligence company he helped found — and said his confidence in the safety of its AI is 'not high' |url=https://www.businessinsider.com/elon-musk-criticizes-openai-dario-amodei-artificial-intelligence-safety-2020-2 |website=businessinsider.com |accessdate=29 February 2020}}</ref> On his {{w|Twitter}} account, Musk writes "I have no control & only very limited insight into OpenAI. Confidence in Dario for safety is not high", alluding to OpenAI Vice President of Research Dario Amodei.<ref>{{cite web |title=Elon Musk |url=https://twitter.com/elonmusk/status/1229546206948462597 |website=twitter.com |accessdate=29 February 2020}}</ref>
 
| 2020 || {{dts|February 17}} || || Coverage || AI reporter Karen Hao at ''MIT Technology Review'' publishes review on OpenAI titled ''The messy, secretive reality behind OpenAI’s bid to save the world'', which suggests the company is surrendering its declaration to be transparent in order to outpace competitors.<ref>{{cite web|url = https://www.technologyreview.com/2020/02/17/844721/ai-openai-moonshot-elon-musk-sam-altman-greg-brockman-messy-secretive-reality/|title = The messy, secretive reality behind OpenAI’s bid to save the world. The AI moonshot was founded in the spirit of transparency. This is the inside story of how competitive pressure eroded that idealism.|last = Hao|first = Karen|publisher = Technology Review}}</ref> As a response, {{w|Elon Musk}} criticizes OpenAI, saying it lacks transparency.<ref name="Aaron">{{cite web |last1=Holmes |first1=Aaron |title=Elon Musk just criticized the artificial intelligence company he helped found — and said his confidence in the safety of its AI is 'not high' |url=https://www.businessinsider.com/elon-musk-criticizes-openai-dario-amodei-artificial-intelligence-safety-2020-2 |website=businessinsider.com |accessdate=29 February 2020}}</ref> On his {{w|Twitter}} account, Musk writes "I have no control & only very limited insight into OpenAI. Confidence in Dario for safety is not high", alluding to OpenAI Vice President of Research Dario Amodei.<ref>{{cite web |title=Elon Musk |url=https://twitter.com/elonmusk/status/1229546206948462597 |website=twitter.com |accessdate=29 February 2020}}</ref>
 
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| 2020 || {{dts|May 28}} (release), June and July (discussion and exploration) || {{w|Natural-language generation}} || Software release || OpenAI releases the natural language model GPT-3 on GitHub<ref>{{cite web|url = http://github.com/openai/gpt-3|title = GPT-3 on GitHub|publisher = OpenAI|accessdate = July 19, 2020}}</ref> and uploads to the ArXiV the paper ''Language Models are Few-Shot Learners'' explaining how GPT-3 was trained and how it performs.<ref>{{cite web|url = https://arxiv.org/abs/2005.14165|title = Language Models are Few-Shot Learners|date = May 28, 2020|accessdate = July 19, 2020}}</ref> Games, websites, and chatbots based on GPT-3 are created for exploratory purposes in the next two months (mostly by people unaffiliated with OpenAI), with a general takeaway that GPT-3 performs significantly better than GPT-2 and past natural language models.<ref>{{cite web|url = https://twitter.com/nicklovescode/status/1283300424418619393|title = Nick Cammarata on Twitter: GPT-3 as therapist|date = July 14, 2020|accessdate = July 19, 2020}}</ref><ref>{{cite web|url = https://www.gwern.net/GPT-3|title = GPT-3 Creative Fiction|date = June 19, 2020|accessdate = July 19, 2020|author = Gwern}}</ref><ref>{{cite web|url = https://medium.com/@aidungeon/ai-dungeon-dragon-model-upgrade-7e8ea579abfe|title = AI Dungeon: Dragon Model Upgrade. You can now play AI Dungeon with one of the most powerful AI models in the world.|last = Walton|first = Nick|date = July 14, 2020|accessdate = July 19, 2020}}</ref><ref>{{cite web|url = https://twitter.com/sharifshameem/status/1282676454690451457|title = Sharif Shameem on Twitter: With GPT-3, I built a layout generator where you just describe any layout you want, and it generates the JSX code for you.|date = July 13, 2020|accessdate = July 19, 2020|publisher = Twitter|last = Shameem|first = Sharif}}</ref> Commentators also note many weaknesses such as: trouble with arithmetic because of incorrect pattern matchiing, trouble with multi-step logical reasoning even though it could do the individual steps separately, inability to identify that a question is nonsense, inability to identify that it does not know the answer to a question, and picking up of racist and sexist content when trained on corpuses that contain some such content.<ref>{{cite web|url = http://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.html|title = Giving GPT-3 a Turing Test|last = Lacker|first = Kevin|date = July 6, 2020|accessdate = July 19, 2020}}</ref><ref>{{cite web|url = https://minimaxir.com/2020/07/gpt3-expectations/|title = Tempering Expectations for GPT-3 and OpenAI’s API|date = July 18, 2020|accessdate = July 19, 2020|last = Woolf|first = Max}}</ref><ref>{{cite web|url = https://delian.substack.com/p/quick-thoughts-on-gpt3|title = Quick thoughts on GPT3|date = July 17, 2020|accessdate = July 19, 2020|last = Asparouhov|first = Delian}}</ref>
+
| 2020 || {{dts|May 28}} (release), June and July (discussion and exploration) || {{w|Natural-language generation}} || Software release || OpenAI releases the natural language model GPT-3 on GitHub<ref>{{cite web|url = http://github.com/openai/gpt-3|title = GPT-3 on GitHub|publisher = OpenAI|accessdate = July 19, 2020}}</ref> and uploads to the ArXiV the paper ''Language Models are Few-Shot Learners'' explaining how GPT-3 was trained and how it performs.<ref>{{cite web|url = https://arxiv.org/abs/2005.14165|title = Language Models are Few-Shot Learners|date = May 28, 2020|accessdate = July 19, 2020}}</ref> Games, websites, and chatbots based on GPT-3 are created for exploratory purposes in the next two months (mostly by people unaffiliated with OpenAI), with a general takeaway that GPT-3 performs significantly better than GPT-2 and past natural language models.<ref>{{cite web|url = https://twitter.com/nicklovescode/status/1283300424418619393|title = Nick Cammarata on Twitter: GPT-3 as therapist|date = July 14, 2020|accessdate = July 19, 2020}}</ref><ref>{{cite web|url = https://www.gwern.net/GPT-3|title = GPT-3 Creative Fiction|date = June 19, 2020|accessdate = July 19, 2020|author = Gwern}}</ref><ref>{{cite web|url = https://medium.com/@aidungeon/ai-dungeon-dragon-model-upgrade-7e8ea579abfe|title = AI Dungeon: Dragon Model Upgrade. You can now play AI Dungeon with one of the most powerful AI models in the world.|last = Walton|first = Nick|date = July 14, 2020|accessdate = July 19, 2020}}</ref><ref>{{cite web|url = https://twitter.com/sharifshameem/status/1282676454690451457|title = Sharif Shameem on Twitter: With GPT-3, I built a layout generator where you just describe any layout you want, and it generates the JSX code for you.|date = July 13, 2020|accessdate = July 19, 2020|publisher = Twitter|last = Shameem|first = Sharif}}</ref> Commentators also note many weaknesses such as: trouble with arithmetic because of incorrect pattern matching, trouble with multi-step logical reasoning even though it could do the individual steps separately, inability to identify that a question is nonsense, inability to identify that it does not know the answer to a question, and picking up of racist and sexist content when trained on corpuses that contain some such content.<ref>{{cite web|url = http://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.html|title = Giving GPT-3 a Turing Test|last = Lacker|first = Kevin|date = July 6, 2020|accessdate = July 19, 2020}}</ref><ref>{{cite web|url = https://minimaxir.com/2020/07/gpt3-expectations/|title = Tempering Expectations for GPT-3 and OpenAI’s API|date = July 18, 2020|accessdate = July 19, 2020|last = Woolf|first = Max}}</ref><ref>{{cite web|url = https://delian.substack.com/p/quick-thoughts-on-gpt3|title = Quick thoughts on GPT3|date = July 17, 2020|accessdate = July 19, 2020|last = Asparouhov|first = Delian}}</ref>
 
|}
 
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Revision as of 10:50, 20 December 2020

This is a timeline of OpenAI. OpenAI is a non-profit safety-conscious artificial intelligence capabilities company.

Sample questions

The following are some interesting questions that can be answered by reading this timeline:

  • What are some significant events previous to the creation of OpenAI?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Prelude".
    • You will see some events involving key people like Elon Musk and Sam Altman, that would eventually lead to the creation of OpenAI.
  • What are the various papers and posts published by OpenAI?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Publication".
    • You will see mostly papers submitted to the ArXiv by OpenAI-affiliated researchers. Also blog posts.
  • What are the several toolkits, implementations, algorithms, systems and software in general released by OpenAI?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Software release".
    • You will see a variety of releases, some of them open-sourced.
  • What are some other significant events describing advances in research?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Research progress".
    • You will see some discoveries and other significant results obtained by OpenAI.
  • What is the staff composition and what are the different roles in the organization?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Staff".
    • You will see the names of incorporated people and their roles.
  • What are the several partnerships between OpenAI and other organizations?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Partnership".
    • You will read collaborations with organizations like DeepMind and Microsoft.
  • What are some significant fundings granted to OpenAI by donors?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Donation".
    • You will see names like the Open Philanthropy Project, and Nvidia, among others.
  • What are some notable events hosted by OpenAI?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Event hosting".
  • What are some notable publications by third parties about OpenAI?
    • Sort the full timeline by "Event type" and look for the group of rows with value "Coverage".

Big picture

Time period Development summary More details
2014–2015 Background Nick Bostrom's book Superintelligence: Paths, Dangers, Strategies, about the dangers of superhuman machine intelligence, is published. Soon after the book's publication, Elon Musk and Sam Altman, the two people who would become co-chairs and initial donors of OpenAI, publicly state their concern of superhuman machine intelligence.
2015 Establishment OpenAI is founded as a nonprofit and begins producing research.
2019 Reorganization OpenAI shifts from nonprofit to ‘capped-profit’ with the purpose to attract capital.

Visual data

Wikipedia Views

The image below shows Wikipedia Views data for Open AI entry on English Wikipedia on desktop, mobile web, mobile app, desktop-spider, and mobile-web-spider; from July 2015 (see OpenAI creation around December 2015) to January 2020.[1]

OpenAI wikipedia views.png

Google Trends

The image below shows Google Trends data for OpenAI entry from December 2015 (OpenAI creation) to February 2020.[2]

OpenAI Google Trends.png

Full timeline

Year Month and date Domain Event type Details
2014 October 22–24 Prelude During an interview at the AeroAstro Centennial Symposium, Elon Musk, who would later become co-chair of OpenAI, calls artificial intelligence humanity's "biggest existential threat".[3][4]
2015 February 25 Prelude Sam Altman, president of Y Combinator who would later become a co-chair of OpenAI, publishes a blog post in which he writes that the development of superhuman AI is "probably the greatest threat to the continued existence of humanity".[5]
2015 May 6 Prelude Greg Brockman, who would become CTO of OpenAI, announces in a blog post that he is leaving his role as CTO of Stripe. In the post, in the section "What comes next" he writes "I haven't decided exactly what I'll be building (feel free to ping if you want to chat)".[6][7]
2015 June Prelude Sam Altman and Greg Brockman have a conversation about next steps for Brockman.[8]
2015 June 4 Prelude At Airbnb's Open Air 2015 conference, Sam Altman, president of Y Combinator who would later become a co-chair of OpenAI, states his concern for advanced artificial intelligence and shares that he recently invested in a company doing AI safety research.[9]
2015 July (approximate) Prelude Sam Altman sets up a dinner in Menlo Park, California to talk about starting an organization to do AI research. Attendees include Greg Brockman, Dario Amodei, Chris Olah, Paul Christiano, Ilya Sutskever, and Elon Musk.[8]
2015 December 11 Creation OpenAI is announced to the public. (The news articles from this period make it sound like OpenAI launched sometime after this date.)[10][11][12] Co-founders include Wojciech Zaremba[13],
2015 December Coverage The article "OpenAI" is created on Wikipedia.[14]
2015 December Team OpenAI announces Y Combinator founding partner Jessica Livingston as one of its financial backers.[15]
2016 January Team Ilya Sutskever joins OpenAI as Research Director.[16][17]
2016 January 9 Education The OpenAI research team does an AMA ("ask me anything") on r/MachineLearning, the subreddit dedicated to machine learning.[18]
2016 February 25 Optimization Publication "Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks", a paper on optimization, is first submitted to the ArXiv. The paper presents weight normalization: a reparameterization of the weight vectors in a neural network that decouples the length of those weight vectors from their direction.[19]
2016 March 31 Team A blog post from this day announces that Ian Goodfellow has joined OpenAI.[20] Previously, Goodfellow worked as Senior Research Scientist at Google.[21][17]
2016 April 26 Team A blog post from this day announces that Pieter Abbeel has joined OpenAI.[22][17]
2016 April 27 Software release The public beta of OpenAI Gym, an open source toolkit that provides environments to test AI bots, is released.[23][24][25]
2016 May 25 Safety Publication "Adversarial Training Methods for Semi-Supervised Text Classification" is submitted to the ArXiv. The paper proposes a method that achieves better results on multiple benchmark semi-supervised and purely supervised tasks.[26]
2016 May 31 Generative models Publication "VIME: Variational Information Maximizing Exploration", a paper on generative models, is submitted to the ArXiv. The paper introduces Variational Information Maximizing Exploration (VIME), an exploration strategy based on maximization of information gain about the agent's belief of environment dynamics.[27]
2016 June 5 Reinforcement learning Publication "OpenAI Gym", a paper on reinforcement learning, is submitted to the ArXiv. It presents OpenAI Gym as a toolkit for reinforcement learning research.[28] OpenAI Gym is considered by some as "a huge opportunity for speeding up the progress in the creation of better reinforcement algorithms, since it provides an easy way of comparing them, on the same conditions, independently of where the algorithm is executed".[29]
2016 June 10 Generative models Publication "Improved Techniques for Training GANs", a paper on generative models, is submitted to the ArXiv. It presents a variety of new architectural features and training procedures that OpenAI applies to the generative adversarial networks (GANs) framework.[30]
2016 June 12 Generative models Publication "InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets", a paper on generative models, is submitted to ArXiv. It describes InfoGAN, an information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner.[31]
2016 June 15 Generative models Publication "Improving Variational Inference with Inverse Autoregressive Flow", a paper on generative models, is submitted to the ArXiv. We propose a new type of normalizing flow, inverse autoregressive flow (IAF), that, in contrast to earlier published flows, scales well to high-dimensional latent spaces.[32]
2016 June 16 Generative models Publication OpenAI publishes post describing four projects on generative models, a branch of unsupervised learning techniques in machine learning.[33]
2016 June 21 Publication "Concrete Problems in AI Safety" by Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané is submitted to the arXiv. The paper explores practical problems in machine learning systems.[34] The paper would receive a shoutout from the Open Philanthropy Project.[35] It would become a landmark in AI safety literature, and many of its authors would continue to do AI safety work at OpenAI in the years to come.
2016 July Team Dario Amodei joins OpenAI[36], working on the Team Lead for AI Safety.[37][17]
2016 July 8 Publication "Adversarial Examples in the Physical World" is published. One of the authors is Ian Goodfellow, who is at OpenAI at the time.[38]
2016 July 28 OpenAI publishes post calling for applicants to work in the following problem areas of interest:
  • Detect if someone is using a covert breakthrough AI system in the world.
  • Build an agent to win online programming competitions.
  • Cyber-security defense.
  • A complex simulation with many long-lived agents.[39]
2016 August 15 Donation The technology company Nvidia announces that it has donated the first Nvidia DGX-1 (a supercomputer) to OpenAI. OpenAI plans to use the supercomputer to train its AI on a corpus of conversations from Reddit.[40][41][42]
2016 August 29 Infrastructure Publication "Infrastructure for Deep Learning" is published. The post shows how deep learning research usually proceeds. It also describes the infrastructure choices OpenAI made to support it, and open-source kubernetes-ec2-autoscaler, a batch-optimized scaling manager for Kubernetes.[43]
2016 October 11 Robotics Publication "Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model", a paper on robotics, is submitted to the ArXiv. It investigates settings where the sequence of states traversed in simulation remains reasonable for the real world.[44]
2016 October 18 Safety Publication "Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data", a paper on safety, is submitted to the ArXiv. It shows an approach to providing strong privacy guarantees for training data: Private Aggregation of Teacher Ensembles (PATE).[45]
2016 November 14 Generative models Publication "On the Quantitative Analysis of Decoder-Based Generative Models", a paper on generative models, is submitted to the ArXiv. It introduces a technique to analyze the performance of decoder-based models.[46]
2016 November 15 Partnership A partnership between OpenAI and Microsoft's artificial intelligence division is announced. As part of the partnership, Microsoft provides a price reduction on computing resources to OpenAI through Microsoft Azure.[47][48]
2016 December 5 Software release OpenAI's Universe, "a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications", is released.[49][50][51][52]
2017 January Staff Paul Christiano joins OpenAI to work on AI alignment.[53] He was previously an intern at OpenAI in 2016.[54]
2017 March Donation The Open Philanthropy Project awards a grant of $30 million to OpenAI for general support.[55] The grant initiates a partnership between Open Philanthropy Project and OpenAI, in which Holden Karnofsky (executive director of Open Philanthropy Project) joins OpenAI's board of directors to oversee OpenAI's safety and governance work.[56] The grant is criticized by Maciej Cegłowski[57] and Benjamin Hoffman (who would write the blog post "OpenAI makes humanity less safe")[58][59][60] among others.[61]
2017 March 24 Research progress OpenAI announces having discovered that evolution strategies rival the performance of standard reinforcement learning techniques on modern RL benchmarks (e.g. Atari/MuJoCo), while overcoming many of RL’s inconveniences.[62]
2017 March Reorganization Greg Brockman and a few other core members of OpenAI begin drafting an internal document to lay out a path to artificial general intelligence. As the team studies trends within the field, they realize staying a nonprofit is financially untenable.[63]
2017 April Coverage An article entitled "The People Behind OpenAI" is published on Red Hat's Open Source Stories website, covering work at OpenAI.[64][65][66]
2017 April 6 Software release OpenAI unveils an unsupervised system which is able to perform a excellent sentiment analysis, despite being trained only to predict the next character in the text of Amazon reviews.[67][68]
2017 April 6 Publication "Learning to Generate Reviews and Discovering Sentiment" is published.[69]
2017 April 6 Neuroevolution Research progress OpenAI unveils reuse of an old field called “neuroevolution”, and a subset of algorithms from it called “evolution strategies,” which are aimed at solving optimization problems. In one hour training on an Atari challenge, an algorithm is found to reach a level of mastery that took a reinforcement-learning system published by DeepMind in 2016 a whole day to learn. On the walking problem the system took 10 minutes, compared to 10 hours for DeepMind's approach.[70]
2017 May 15 Robotics Software release OpenAI releases Roboschool, an open-source software for robot simulation, integrated with OpenAI Gym.[71]
2017 May 16 Robotics Software release OpenAI introduces a robotics system, trained entirely in simulation and deployed on a physical robot, which can learn a new task after seeing it done once.[72]
2017 May 24 Reinforcement learning Software release OpenAI releases Baselines, a set of implementations of reinforcement learning algorithms.[73][74]
2017 June 12 Safety Publication "Deep reinforcement learning from human preferences" is first uploaded to the arXiv. The paper is a collaboration between researchers at OpenAI and Google DeepMind.[75][76][77]
2017 June 28 Robotics Open sourcing OpenAI open sources a high-performance Python library for robotic simulation using the MuJoCo engine, developed over OpenAI research on robotics.[78]
2017 June Reinforcement learning Partnership OpenAI partners with DeepMind’s safety team in the development of an algorithm which can infer what humans want by being told which of two proposed behaviors is better. The learning algorithm uses small amounts of human feedback to solve modern reinforcement learning environments.[79]
2017 July 27 Reinforcement learning Research progress OpenAI announces having found that adding adaptive noise to the parameters of reinforcement learning algorithms frequently boosts performance.[80]
2017 August 12 Achievement OpenAI's Dota 2 bot beats Danil "Dendi" Ishutin, a professional human player, (and possibly others?) in one-on-one battles.[81][82][83]
2017 August 13 Coverage The New York Times publishes a story covering the AI safety work (by Dario Amodei, Geoffrey Irving, and Paul Christiano) at OpenAI.[84]
2017 August 18 Reinforcement learning Software release OpenAI releases two implementations: ACKTR, a reinforcement learning algorithm, and A2C, a synchronous, deterministic variant of Asynchronous Advantage Actor Critic (A3C).[85]
2017 September 13 Reinforcement learning Publication "Learning with Opponent-Learning Awareness" is first uploaded to the ArXiv. The paper presents Learning with Opponent-Learning Awareness (LOLA), a method in which each agent shapes the anticipated learning of the other agents in an environment.[86][87]
2017 October 11 Software release RoboSumo, a game that simulates sumo wrestling for AI to learn to play, is released.[88][89]
2017 November 6 Team The New York Times reports that Pieter Abbeel (a researcher at OpenAI) and three other researchers from Berkeley and OpenAI have left to start their own company called Embodied Intelligence.[90]
2017 December 6 Neural network Software release OpenAI releases highly-optimized GPU kernels for networks with block-sparse weights, an underexplored class of neural network architectures. Depending on the chosen sparsity, these kernels can run orders of magnitude faster than cuBLAS or cuSPARSE.[91]
2017 December Publication The 2017 AI Index is published. OpenAI contributed to the report.[92]
2018 February 20 Safety Publication The report "The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation" is submitted to the ArXiv. It forecasts malicious use of artificial intelligence in the short term and makes recommendations on how to mitigate these risks from AI. The report is authored by individuals at Future of Humanity Institute, Centre for the Study of Existential Risk, OpenAI, Electronic Frontier Foundation, Center for a New American Security, and other institutions.[93][94][95][96][97]
2018 February 20 Donation OpenAI announces changes in donors and advisors. New donors are: Jed McCaleb, Gabe Newell, Michael Seibel, Jaan Tallinn, and Ashton Eaton and Brianne Theisen-Eaton. Reid Hoffman is "significantly increasing his contribution". Pieter Abbeel (previously at OpenAI), Julia Galef, and Maran Nelson become advisors. Elon Musk departs the board but remains as a donor and advisor.[98][96]
2018 February 26 Robotics Software release OpenAI releases eight simulated robotics environments and a Baselines implementation of Hindsight Experience Replay, all developed for OpenAI research over the previous year. These environments were to train models which work on physical robots.[99]
2018 March 3 Event hosting OpenAI hosts its first hackathon. Applicants include high schoolers, industry practitioners, engineers, researchers at universities, and others, with interests spanning healthcare to AGI.[100][101]
2018 April 5 – June 5 Event hosting The OpenAI Retro Contest takes place.[102][103] As a result of the release of the Gym Retro library, OpenAI's Universe become deprecated.[104]
2018 April 9 Commitment OpenAI releases a charter stating that the organization commits to stop competing with a value-aligned and safety-conscious project that comes close to building artificial general intelligence, and also that OpenAI expects to reduce its traditional publishing in the future due to safety concerns.[105][106][107][108][109]
2018 April 19 Financial The New York Times publishes a story detailing the salaries of researchers at OpenAI, using information from OpenAI's 2016 Form 990. The salaries include $1.9 million paid to Ilya Sutskever and $800,000 paid to Ian Goodfellow (hired in March of that year).[110][111][112]
2018 May 2 safety Publication The paper "AI safety via debate" by Geoffrey Irving, Paul Christiano, and Dario Amodei is uploaded to the arXiv. The paper proposes training agents via self play on a zero sum debate game, in order to adress tasks that are too complicated for a human to directly judge.[113][114]
2018 May 16 Computation Publication OpenAI releases an analysis showing that since 2012, the amount of compute used in the largest AI training runs has been increasing exponentially with a 3.4-month doubling time.[115]
2018 June 11 Unsupervised learning Research progress OpenAI announces having obtained significant results on a suite of diverse language tasks with a scalable, task-agnostic system, which uses a combination of transformers and unsupervised pre-training.[116]
2018 June 25 Neural network Software release OpenAI announces set of AI algorithms able to hold their own as a team of five and defeat human amateur players at Dota 2, a multiplayer online battle arena video game popular in e-sports for its complexity and necessity for teamwork.[117] In the algorithmic A team, called OpenAI Five, each algorithm uses a neural network to learn both how to play the game, and how to cooperate with its AI teammates.[118][119]
2018 June 26 Notable comment Bill Gates comments on Twitter:
AI bots just beat humans at the video game Dota 2. That’s a big deal, because their victory required teamwork and collaboration – a huge milestone in advancing artificial intelligence.
[120]
2018 July 18 Commitment Elon Musk, along with other tech leaders, sign a pledge promising to not develop “lethal autonomous weapons.” They also call on governments to institute laws against such technology. The pledge is organized by the Future of Life Institute, an outreach group focused on tackling existential risks.[121][122][123]
2018 July 30 Robotics Software release OpenAI announces a robotics system that can manipulate objects with humanlike dexterity. The system is able to develop these behaviors all on its own. It uses a reinforcement model, where the AI learns through trial and error, to direct robot hands in grasping and manipulating objects with great precision.[124][125]
2018 August 7 Achievement Algorithmic team OpenAI Five defeats a team of semi-professional Dota 2 players ranked in the 99.95th percentile in the world, in their second public match in the traditional five-versus-five settings, hosted in San Francisco.[126][127][128][129]
2018 August 16 Arboricity Publication OpenAI publishes paper on constant arboricity spectral sparsifiers. The paper shows that every graph is spectrally similar to the union of a constant number of forests.[130]
2018 September Team Dario Amodei becomes OpenAI's Research Director.[37]
2018 October 31 Reinforcement learning Software release OpenAI unveils its Random Network Distillation (RND), a prediction-based method for encouraging reinforcement learning agents to explore their environments through curiosity, which for the first time exceeds average human performance on videogame Montezuma’s Revenge.[131]
2018 November 8 Reinforcement learning Education OpenAI launches Spinning Up, an educational resource designed to teach anyone deep reinforcement learning. The program consists of crystal-clear examples of RL code, educational exercises, documentation, and tutorials.[132][133][134]
2018 November 9 Notable comment Ilya Sutskever gives speech at the AI Frontiers Conference in San Jose, and declares:
We (OpenAI) have reviewed progress in the field over the past six years. Our conclusion is near term AGI should be taken as a serious possibility.
[135]
2018 November 19 Reinforcement learning Partnership OpenAI partners with DeepMind in a new paper that proposes a new method to train reinforcement learning agents in ways that enables them to surpass human performance. The paper, titled Reward learning from human preferences and demonstrations in Atari, introduces a training model that combines human feedback and reward optimization to maximize the knowledge of RL agents.[136]
2018 December 4 Reinforcement learning Researh progress OpenAI announces having discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability of neural network training on a wide range of tasks.[137]
2018 December 6 Reinforcement learning Software release OpenAI releases CoinRun, a training environment designed to test the adaptability of reinforcement learning agents.[138][139]
2019 February 14 Natural-language generation Software release OpenAI unveils its language-generating system called GPT-2, a system able to write news, answer reading comprehension problems, and shows promise at tasks like translation.[140] However, the data or the parameters of the model are not released, under expressed concerns about potential abuse.[141] OpenAI initially tries to communicate the risk posed by this technology.[142]
2019 February 19 Safety Publication "AI Safety Needs Social Scientists" is published. The paper argues that long-term AI safety research needs social scientists to ensure AI alignment algorithms succeed when actual humans are involved.[143][144]
2019 March 4 Reinforcement learning Software release OpenAI releases a Neural MMO (massively multiplayer online), a multiagent game environment for reinforcement learning agents. The platform supports a large, variable number of agents within a persistent and open-ended task.[145]
2019 March 6 Software release OpenAI introduces activation atlases, created in collaboration with Google researchers. Activation atlases comprise a new technique for visualizing what interactions between neurons can represent.[146]
2019 March 11 Reorganization OpenAI announces the creation of OpenAI LP, a new “capped-profit” company owned and controlled by the OpenAI nonprofit organization’s board of directors. The new company is purposed to allow OpenAI to rapidly increase their investments in compute and talent while including checks and balances to actualize their mission.[147][148]
2019 March 21 Software release OpenAI announces progress towards stable and scalable training of energy-based models (EBMs) resulting in better sample quality and generalization ability than existing models.[149]
2019 March Team Sam Altman leaves his role as the president of Y Combinator to become the Chief executive officer of OpenAI.[150][151][17]
2019 April 23 Deep learning Publication OpenAI publishes paper announcing Sparse Transformers, a deep neural network for learning sequences of data, including text, sound, and images. It utilizes an improved algorithm based on the attention mechanism, being able to extract patterns from sequences 30 times longer than possible previously.[152][153][154]
2019 April 25 Neural network Software release OpenAI announces MuseNet, a deep neural network able to generate 4-minute musical compositions with 10 different instruments, and can combine multiple styles from country to Mozart to The Beatles. The neural network uses general-purpose unsupervised technology.[155]
2019 April 27 Event hosting OpenAI hosts the OpenAI Robotics Symposium 2019.[156]
2019 May Natural-language generation Software release OpenAI releases a limited version of its language-generating system GPT-2. This version is more powerful (though still significantly limited compared to the whole thing) than the extremely restricted initial release of the system, citing concerns that it’d be abused.[157] The potential of the new system is recognized by various experts.[158]
2019 June 13 Natural-language generation Coverage Connor Leahy publishes article entitled The Hacker Learns to Trust which discusses the work of OpenAI, and particularly the potential danger of its language-generating system GPT-2. Leahy highlights: "Because this isn’t just about GPT2. What matters is that at some point in the future, someone will create something truly dangerous and there need to be commonly accepted safety norms before that happens."[142]
2019 July 22 Partnership OpenAI announces an exclusive partnership with Microsoft. As part of the partnership, Microsoft invests $1 billion in OpenAI, and OpenAI switches to exclusively using Microsoft Azure (Microsoft's cloud solution) as the platform on which it will develop its AI tools. Microsoft will also be OpenAI's "preferred partner for commercializing new AI technologies."[159][160][161][162]
2019 August 20 Natural-language generation Software release OpenAI announces plan to release a version of its language-generating system GPT-2, which stirred controversy after it release in February.[163][164][165]
2019 September 17 Research progress OpenAI announces having observed agents discovering progressively more complex tool use while playing a simple game of hide-and-seek. Through training, the agents were able to build a series of six distinct strategies and counterstrategies, some of which were unknown to be supported by the environment.[166][167]
2019 October 16 Neural networks Research progress OpenAI announces having trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The experiment demonstrates that models trained only in simulation can be used to solve a manipulation problem of unprecedented complexity on a real robot.[168][169]
2019 November 5 Natural-language generation Software release OpenAI releases the largest version (1.5B parameters) of its language-generating system GPT-2 along with code and model weights to facilitate detection of outputs of GPT-2 models.[170]
2019 November 21 Reinforcement learning Software release OpenAI releases Safety Gym, a suite of environments and tools for measuring progress towards reinforcement learning agents that respect safety constraints while training.[171]
2019 December 3 Reinforcement learning Software release OpenAI releases Procgen Benchmark, a set of 16 simple-to-use procedurally-generated environments (CoinRun, StarPilot, CaveFlyer, Dodgeball, FruitBot, Chaser, Miner, Jumper, Leaper, Maze, BigFish, Heist, Climber, Plunder, Ninja, and BossFight) which provide a direct measure of how quickly a reinforcement learning agent learns generalizable skills. Procgen Benchmark prevents AI model overfitting.[172][173][174]
2019 December 4 Publication "Deep Double Descent: Where Bigger Models and More Data Hurt" is submitted to the ArXiv. The paper shows that a variety of modern deep learning tasks exhibit a "double-descent" phenomenon where, as the model size increases, performance first gets worse and then gets better.[175] The paper is summarized on the OpenAI blog.[176] MIRI researcher Evan Hubinger writes an explanatory post on the subject on LessWrong and the AI Alignment Forum,[177] and follows up with a post on the AI safety implications.[178]
2019 December Team Dario Amodei is promoted as OpenAI's Vice President of Research.[37]
2020 January 30 Deep learning Software adoption OpenAI announces migration to the social network’s PyTorch machine learning framework in future projects, setting it as its new standard deep learning framework.[179][180]
2020 February 5 Safety Publication Beth Barnes and Paul Christiano on lesswrong.com publish Writeup: Progress on AI Safety via Debate, a writeup of the research done by the "Reflection-Humans" team at OpenAI in third and fourth quarter of 2019.[181]
2020 February 17 Coverage AI reporter Karen Hao at MIT Technology Review publishes review on OpenAI titled The messy, secretive reality behind OpenAI’s bid to save the world, which suggests the company is surrendering its declaration to be transparent in order to outpace competitors.[182] As a response, Elon Musk criticizes OpenAI, saying it lacks transparency.[183] On his Twitter account, Musk writes "I have no control & only very limited insight into OpenAI. Confidence in Dario for safety is not high", alluding to OpenAI Vice President of Research Dario Amodei.[184]
2020 May 28 (release), June and July (discussion and exploration) Natural-language generation Software release OpenAI releases the natural language model GPT-3 on GitHub[185] and uploads to the ArXiV the paper Language Models are Few-Shot Learners explaining how GPT-3 was trained and how it performs.[186] Games, websites, and chatbots based on GPT-3 are created for exploratory purposes in the next two months (mostly by people unaffiliated with OpenAI), with a general takeaway that GPT-3 performs significantly better than GPT-2 and past natural language models.[187][188][189][190] Commentators also note many weaknesses such as: trouble with arithmetic because of incorrect pattern matching, trouble with multi-step logical reasoning even though it could do the individual steps separately, inability to identify that a question is nonsense, inability to identify that it does not know the answer to a question, and picking up of racist and sexist content when trained on corpuses that contain some such content.[191][192][193]

Meta information on the timeline

How the timeline was built

The initial version of the timeline was written by Issa Rice. It has been expanded considerably by Sebastian.

Funding information for this timeline is available.

What the timeline is still missing

Timeline update strategy

See also

External links

References

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  176. ↑ "Deep Double Descent". OpenAI. December 5, 2019. Retrieved May 23, 2020. 
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  193. ↑ Asparouhov, Delian (July 17, 2020). "Quick thoughts on GPT3". Retrieved July 19, 2020. 
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