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Timeline of OpenAI

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| 2018 || {{Dts|July 30}} || AI development || 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.<ref>{{cite web |title=OpenAI’s ‘state-of-the-art’ system gives robots humanlike dexterity |url=https://venturebeat.com/2018/07/30/OpenAIs-state-of-the-art-system-gives-robots-humanlike-dexterity/ |website=venturebeat.com |accessdate=14 June 2019}}</ref><ref>{{cite web |last1=Coldewey |first1=Devin |title=OpenAI’s robotic hand doesn’t need humans to teach it human behaviors |url=https://techcrunch.com/2018/07/30/OpenAIs-robotic-hand-doesnt-need-humans-to-teach-it-human-behaviors/ |website=techcrunch.com |accessdate=14 June 2019}}</ref>
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| 2018 || {{dts|August 1}} || Publication || OpenAI publishes paper describing the use of {{w|reinforcement learning}} to learn dexterous in-hand manipulation policies which can perform vision-based object reorientation on a physical Shadow Dexterous Hand.<ref>{{cite web |title=Learning Dexterous In-Hand Manipulation |url=https://arxiv.org/abs/1808.00177 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{Dts|August 7}} || Achievement || Algorithmic team OpenAI Five defeats a team of semi-professional {{w|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 {{w|San Francisco}}.<ref>{{cite web |last1=Whitwam |first1=Ryan |title=OpenAI Bots Crush the Best Human Dota 2 Players in the World |url=https://www.extremetech.com/gaming/274907-OpenAI-bots-crush-the-best-human-dota-2-players-in-the-world |website=extremetech.com |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Quach |first1=Katyanna |title=OpenAI bots thrash team of Dota 2 semi-pros, set eyes on mega-tourney |url=https://www.theregister.co.uk/2018/08/06/OpenAI_bots_dota_2_semipros/ |website=theregister.co.uk |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Savov |first1=Vlad |title=The OpenAI Dota 2 bots just defeated a team of former pros |url=https://www.theverge.com/2018/8/6/17655086/dota2-OpenAI-bots-professional-gaming-ai |website=theverge.com |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Rigg |first1=Jamie |title=‘Dota 2’ veterans steamrolled by AI team in exhibition match |url=https://www.engadget.com/2018/08/06/OpenAI-five-dumpsters-dota-2-veterans/ |website=engadget.com |accessdate=15 June 2019}}</ref>
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| 2018 || {{dts|August}} || Staff || Jeffrey Wu joins OpenAI as Member of Technical Staff.<ref>{{cite web |title=Jeffrey Wu |url=https://www.linkedin.com/in/wu-the-jeff/ |website=linkedin.com |accessdate=29 February 2020}}</ref>
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| 2018 || {{dts|August 16}} || 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.<ref>{{cite web |last1=Chu |first1=Timothy |last2=Cohen |first2=Michael B. |last3=Pachocki |first3=Jakub W. |last4=Peng |first4=Richard |title=Constant Arboricity Spectral Sparsifiers |url=https://arxiv.org/abs/1808.05662 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{dts|September}} || Staff || Christopher Olah joins OpenAI as Member Of Technical Staff.<ref>{{cite web |title=Christopher Olah |url=https://www.linkedin.com/in/christopher-olah-b574414a/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2018 || {{dts|September}} || Staff || Dario Amodei becomes OpenAI's Research Director.<ref name="Dario Amodeiy"/>
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| 2018 || {{dts|October 2}} || Publication || OpenAI publishes paper on FFJORD (free-form continuous dynamics for scalable reversible generative models), aiming to demonstrate their approach on high-dimensional density estimation, image generation, and variational inference.<ref>{{cite web |last1=Grathwohl |first1=Will |last2=Chen |first2=Ricky T. Q. |last3=Bettencourt |first3=Jesse |last4=Sutskever |first4=Ilya |last5=Duvenaud |first5=David |title=FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models |url=https://arxiv.org/abs/1810.01367 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{dts|October 19}} || Publication || OpenAI publishes paper proposing Iterated Amplification, an alternative training strategy which progressively builds up a training signal for difficult problems by combining solutions to easier subproblems.<ref>{{cite web |last1=Christiano |first1=Paul |last2=Shlegeris |first2=Buck |last3=Amodei |first3=Dario |title=Supervising strong learners by amplifying weak experts |url=https://arxiv.org/abs/1810.08575 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{Dts|October}} || Staff || Daniela Amodei joins OpenAI as NLP Team Manager and Head of People Operations.<ref>{{cite web |title=Daniela Amodei |url=https://www.linkedin.com/in/daniela-amodei-790bb22a/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2018 || {{Dts|November 1}} || Publication || OpenAI publishes research paper detailing AI able to defeat humans at the retro platformer [[w:Montezuma's Revenge (video game)|Montezuma’s Revenge]]. The top-performing iteration found 22 of the 24 rooms in the first level, and occasionally discovered all 24.<ref>{{cite web |last1=Wiggers |first1=Kyle |title=OpenAI made a system that’s better at Montezuma’s Revenge than humans |url=https://venturebeat.com/2018/11/01/OpenAI-made-a-system-thats-better-at-montezumas-revenge-than-humans/ |website=venturebeat.com |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Vincent |first1=James |title=New research from OpenAI uses curious AI to beat video games |url=https://www.theverge.com/2018/11/1/18051196/ai-artificial-intelligence-curiosity-OpenAI-montezumas-revenge-noisy-tv-problem |website=theverge.com |accessdate=15 June 2019}}</ref>
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| 2018 || {{dts|November 5}} || Publication || OpenAI publishes paper proposing a plan online and learn offline (POLO) framework for the setting where an agent, with an internal model, needs to continually act and learn in the world.<ref>{{cite web |last1=Lowrey |first1=Kendall |last2=Rajeswaran |first2=Aravind |last3=Kakade |first3=Sham |last4=Todorov |first4=Emanuel |last5=Mordatch |first5=Igor |title=Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{Dts|November 8}} || 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.<ref>{{cite web |title=Spinning Up in Deep RL |url=https://OpenAI.com/blog/spinning-up-in-deep-rl/ |website=OpenAI.com |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Ramesh |first1=Prasad |title=OpenAI launches Spinning Up, a learning resource for potential deep learning practitioners |url=https://hub.packtpub.com/OpenAI-launches-spinning-up-a-learning-resource-for-potential-deep-learning-practitioners/ |website=hub.packtpub.com |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Johnson |first1=Khari |title=OpenAI launches reinforcement learning training to prepare for artificial general intelligence |url=https://flipboard.com/@venturebeat/OpenAI-launches-reinforcement-learning-training-to-prepare-for-artificial-genera/a-TxuPmdApTGSzPr0ny7qXsw%3Aa%3A2919225365-bafeac8636%2Fventurebeat.com |website=flipboard.com |accessdate=15 June 2019}}</ref>
| 2018 || {{dts|November}} || Staff || Amanda Askell joins OpenAI as Research Scientist (Policy).<ref>{{cite web |title=Amanda Askell |url=https://www.linkedin.com/in/amanda-askell-1ab457175/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2018 || {{Dts|December 6}} || AI development Publication || OpenAI publishes CoinRun, which is designed to test the adaptability of reinforcement learning agents.<ref>{{cite web |title=OpenAI teaches AI teamwork by playing hide-and-seek |url=https://venturebeat.com/2019/09/17/OpenAI-and-deepmind-teach-ai-to-work-as-a-team-by-playing-hide-and-seek/ |website=venturebeat.com |accessdate=24 February 2020}}</ref><ref>{{cite web |title=OpenAI’s CoinRun tests the adaptability of reinforcement learning agents |url=https://venturebeat.com/2018/12/06/OpenAIs-coinrun-tests-the-adaptability-of-reinforcement-learning-agents/ |website=venturebeat.com |accessdate=24 February 2020}}</ref>|-| 2018 || {{dts|December 14}} || Publication || OpenAI publishes paper demonstrating that a simple and easy-to-measure statistic called the gradient noise scale predicts the largest useful batch size across many domains and applications, including a number of {{w|supervised learning}} datasets, {{w|reinforcement learning}} domains, and even generative model training.<ref>{{cite web |last1=McCandlish |first1=Sam |last2=Kaplan |first2=Jared |last3=Amodei |first3=Dario |last4=OpenAI Dota Team |title=An Empirical Model of Large-Batch Training |url=https://arxiv.org/abs/1812.06162 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2018 || {{dts|December}} || Staff || Mateusz Litwin joins OpenAI as Member Of Technical Staff.<ref>{{cite web |title=Mateusz Litwin |url=https://www.linkedin.com/in/mateusz-litwin-06b3a919/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2019 || {{dts|January}} || Staff || Bianca Martin joins OpenAI as Special Projects Manager.<ref>{{cite web |title=Bianca Martin |url=https://www.linkedin.com/in/biancamartin1/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2019 || {{dts|February 4}} || Publication || OpenAI publishes paper showing computational limitations in robust classification and win-win results.<ref>{{cite web |last1=Degwekar |first1=Akshay |last2=Nakkiran |first2=Preetum |last3=Vaikuntanathan |first3=Vinod |title=Computational Limitations in Robust Classification and Win-Win Results |url=https://arxiv.org/abs/1902.01086 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2019 || {{Dts|February 14}} || AI development || OpenAI unveils its language-generating system called GPT-2, a system able to write the news, answer reading comprehension problems, and is beginning to show promise at tasks like translation.<ref>{{cite web |title=An AI helped us write this article |url=https://www.vox.com/future-perfect/2019/2/14/18222270/artificial-intelligence-open-ai-natural-language-processing |website=vox.com |accessdate=28 June 2019}}</ref> However, the data or the parameters of the model are not released, under expressed concerns about potential abuse.<ref>{{cite web |last1=Lowe |first1=Ryan |title=OpenAI’s GPT-2: the model, the hype, and the controversy |url=https://towardsdatascience.com/OpenAIs-gpt-2-the-model-the-hype-and-the-controversy-1109f4bfd5e8 |website=towardsdatascience.com |accessdate=10 July 2019}}</ref>
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| 2019 || {{dts|February}} || Staff || Danny Hernandez joins OpenAI as Research Scientist.<ref>{{cite web |title=Danny Hernandez |url=https://www.linkedin.com/in/danny-hernandez-2b748823/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2019 || {{dts|March 2}} || Publication || OpenAi publishes paper presenting an artificial intelligence research environment that aims to simulate the {{w|natural environment}} setting in microcosm.<ref>{{cite web |last1=Suarez |first1=Joseph |last2=Du |first2=Yilun |last3=Isola |first3=Phillip |last4=Mordatch |first4=Igor |title=Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents |url=https://arxiv.org/abs/1903.00784 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2019 || {{Dts|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.<ref>{{cite web |last1=Johnson |first1=Khari |title=OpenAI launches new company for funding safe artificial general intelligence |url=https://venturebeat.com/2019/03/11/OpenAI-launches-new-company-for-funding-safe-artificial-general-intelligence/ |website=venturebeat.com |accessdate=15 June 2019}}</ref><ref>{{cite web |last1=Trazzi |first1=Michaël |title=Considerateness in OpenAI LP Debate |url=https://medium.com/@MichaelTrazzi/considerateness-in-OpenAI-lp-debate-6eb3bf4c5341 |website=medium.com |accessdate=15 June 2019}}</ref>
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| 2019 || {{dts|March 20}} || Publication || OpenAI publishes paper presenting techniques to scale MCMC based energy base models training on continuous neural networks.<ref>{{cite web |last1=Du |first1=Yilun |last2=Mordatch |first2=Igor |title=Implicit Generation and Generalization in Energy-Based Models |url=https://arxiv.org/abs/1903.08689 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2019 || {{dts|March}} || Staff || Ilge Akkaya joins OpenAI as Member Of Technical Staff.<ref>{{cite web |title=Ilge Akkaya |url=https://www.linkedin.com/in/ilge-akkaya-311b4631/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
| 2019 || {{dts|March}} || Staff || Karson Elmgren joins OpenAI at People Operations.<ref>{{cite web |title=Karson Elmgren |url=https://www.linkedin.com/in/karson-elmgren-32417732/ |website=linkedin.com |accessdate=29 February 2020}}</ref>
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| 2019 || {{Dts|April 23}} || AI development Publication || OpenAI announces 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.<ref>{{cite web |last1=Alford |first1=Anthony |title=OpenAI Introduces Sparse Transformers for Deep Learning of Longer Sequences |url=https://www.infoq.com/news/2019/05/OpenAI-sparse-transformers/ |website=infoq.com |accessdate=15 June 2019}}</ref><ref>{{cite web |title=OpenAI Sparse Transformer Improves Predictable Sequence Length by 30x |url=https://medium.com/syncedreview/OpenAI-sparse-transformer-improves-predictable-sequence-length-by-30x-5a65ef2592b9 |website=medium.com |accessdate=15 June 2019}}</ref><ref>{{cite web |title=Generative Modeling with Sparse Transformers |url=https://OpenAI.com/blog/sparse-transformer/ |website=OpenAI.com |accessdate=15 June 2019}}</ref>
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| 2019 || {{Dts|April 25}} || AI development || OpenAI announces MuseNet, a deep {{w|neural network}} able to generate 4-minute musical compositions with 10 different instruments, and can combine multiple styles from [[w:Country music|country]] to {{w|Mozart}} to {{w|The Beatles}}. The neural network uses general-purpose unsupervised technology.<ref>{{cite web |title=MuseNet |url=https://OpenAI.com/blog/musenet/ |website=OpenAI.com |accessdate=15 June 2019}}</ref>
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| 2019 || {{dts|April}} || Staff || Todor Markov joins OpenAI as Machine Learning Researcher.<ref>{{cite web |title=Todor Markov |url=https://www.linkedin.com/in/todor-markov-4aa38a67/ |website=linkedin.com/ |accessdate=28 February 2020}}</ref>
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| 2019 || {{dts|May 3}} || Publication || OpenAI publishes study on the transfer of adversarial robustness of [[w:deep learning|deep neural networks]] between different perturbation types.<ref>{{cite web |last1=Kang |first1=Daniel |last2=Sun |first2=Yi |last3=Brown |first3=Tom |last4=Hendrycks |first4=Dan |last5=Steinhardt |first5=Jacob |title=Transfer of Adversarial Robustness Between Perturbation Types |url=https://arxiv.org/abs/1905.01034 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2019 || {{Dts|May}} || AI development || 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.<ref>{{cite web |title=A poetry-writing AI has just been unveiled. It’s ... pretty good. |url=https://www.vox.com/2019/5/15/18623134/OpenAI-language-ai-gpt2-poetry-try-it |website=vox.com |accessdate=11 July 2019}}</ref> The potential of the new system is recognized by various experts.<ref>{{cite web |last1=Vincent |first1=James |title=AND OpenAI's new multitalented AI writes, translates, and slanders |url=https://www.theverge.com/2019/2/14/18224704/ai-machine-learning-language-models-read-write-OpenAI-gpt2 |website=theverge.com |accessdate=11 July 2019}}</ref>
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| 2019 || {{dts|May 28}} || Publication || OpenAI publishes study on the dynamics of Stochastic Gradient Descent (SGD) in learning [[w:Deep learning|deep neural networks]] for several real and synthetic classification tasks.<ref>{{cite web |last1=Nakkiran |first1=Preetum |last2=Kaplun |first2=Gal |last3=Kalimeris |first3=Dimitris |last4=Yang |first4=Tristan |last5=Edelman |first5=Benjamin L. |last6=Zhang |first6=Fred |last7=Barak |first7=Boaz |title=SGD on Neural Networks Learns Functions of Increasing Complexity |url=https://arxiv.org/abs/1905.11604 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2019 || {{dts|June}} || Staff || Long Ouyang joins OpenAI as Research Scientist.<ref>{{cite web |title=Long Ouyang |url=https://www.linkedin.com/in/longouyang/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2019 || {{dts|July 10}} || Publication || OpenAI publishes paper arguing that competitive pressures could incentivize AI companies to underinvest in ensuring their systems are safe, secure, and have a positive social impact.<ref>{{cite web |last1=Askell |first1=Amanda |last2=Brundage |first2=Miles |last3=Hadfield |first3=Gillian |title=The Role of Cooperation in Responsible AI Development |url=https://arxiv.org/abs/1907.04534 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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| 2019 || {{dts|July 22}} || Partnership || OpenAI announces an exclusive partnership with {{w|Microsoft}}. As part of the partnership, Microsoft invests $1 billion in OpenAI, and OpenAI switches to exclusively using {{w|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."<ref>{{cite web|url = https://OpenAI.com/blog/microsoft/|title = Microsoft Invests In and Partners with OpenAI to Support Us Building Beneficial AGI|date = July 22, 2019|accessdate = July 26, 2019|publisher = OpenAI}}</ref><ref>{{cite web|url = https://news.microsoft.com/2019/07/22/OpenAI-forms-exclusive-computing-partnership-with-microsoft-to-build-new-azure-ai-supercomputing-technologies/|title = OpenAI forms exclusive computing partnership with Microsoft to build new Azure AI supercomputing technologies|date = July 22, 2019|accessdate = July 26, 2019|publisher = Microsoft}}</ref><ref>{{cite web|url = https://www.businessinsider.com/microsoft-OpenAI-artificial-general-intelligence-investment-2019-7|title = Microsoft is investing $1 billion in OpenAI, the Elon Musk-founded company that's trying to build human-like artificial intelligence|last = Chan|first= Rosalie|date = July 22, 2019|accessdate = July 26, 2019|publisher = Business Insider}}</ref><ref>{{cite web|url = https://www.forbes.com/sites/mohanbirsawhney/2019/07/24/the-real-reasons-microsoft-invested-in-OpenAI/|title = The Real Reasons Microsoft Invested In OpenAI|last = Sawhney|first = Mohanbir|date = July 24, 2019|accessdate = July 26, 2019|publisher = Forbes}}</ref>
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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. 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 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|January 23}} || Publication || OpenAI publishes study on empirical scaling laws for language model performance on the cross-entropy loss.<ref>{{cite web |last1=Kaplan |first1=Jared |last2=McCandlish |first2=Sam |last3=Henighan |first3=Tom |last4=Brown |first4=Tom B. |last5=Chess |first5=Benjamin |last6=Child |first6=Rewon |last7=Gray |first7=Scott |last8=Radford |first8=Alec |last9=Wu |first9=Jeffrey |last10=Amodei |first10=Dario |title=Scaling Laws for Neural Language Models |url=https://arxiv.org/abs/2001.08361 |website=arxiv.org |accessdate=25 March 2020}}</ref>
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