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Timeline of OpenAI

248 bytes added, 14:17, 4 April 2020
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| 2018|| {{dts|June 2}} || Publication || OpenAI publishes "GamePad: A Learning Environment for Theorem Proving" in {{w|arXiv}}. The paper introduces a system called GamePad that can be used to explore the application of machine learning methods to theorem proving in the Coq proof assistant.<ref>{{cite web |last1=Huang |first1=Daniel |last2=Dhariwal |first2=Prafulla |last3=Song |first3=Dawn |last4=Sutskever |first4=Ilya |title=GamePad: A Learning Environment for Theorem Proving |url=https://arxiv.org/abs/1806.00608 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{dts|June 11}} || Milestone release || OpenAI announces having obtained {{w|unsupervised learning}} state-of-the-art results improving language understanding on a suite of diverse language tasks with a scalable, task-agnostic system.
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| 2018 || {{dts|June 17}} || Publication || OpenAI publishes paper on learning policy representations in multiagent systems. The paper proposes a general learning framework for modeling agent behavior in any multiagent system using only a handful of interaction data.<ref>{{cite web |title=Learning Policy Representations in Multiagent Systems |url=https://arxiv.org/abs/1806.06464 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{Dts|June 25}} || AI development || OpenAI announces set of AI algorithms able to hold their own as a team of five and defeat human amateur players at {{w|Dota 2}}, a multiplayer online battle arena video game popular in e-sports for its complexity and necessity for teamwork.<ref>{{cite web |last1=Gershgorn |first1=Dave |title=OpenAI built gaming bots that can work as a team with inhuman precision |url=https://qz.com/1311732/OpenAI-built-gaming-bots-that-can-work-as-a-team-with-inhuman-precision/ |website=qz.com |accessdate=14 June 2019}}</ref> In the algorithmic A team, called OpenAI Five, each algorithm uses a {{w|neural network}} to learn both how to play the game, and how to cooperate with its AI teammates.<ref>{{cite web |last1=Knight |first1=Will |title=A team of AI algorithms just crushed humans in a complex computer game |url=https://www.technologyreview.com/s/611536/a-team-of-ai-algorithms-just-crushed-expert-humans-in-a-complex-computer-game/ |website=technologyreview.com |accessdate=14 June 2019}}</ref><ref>{{cite web |title=OpenAI’s bot can now defeat skilled Dota 2 teams |url=https://venturebeat.com/2018/06/25/OpenAI-trains-ai-to-defeat-teams-of-skilled-dota-2-players/ |website=venturebeat.com |accessdate=14 June 2019}}</ref>
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| 2018 || {{dts|June}} || Staff || Christine McLeavey Payne joins OpenAI's Deep Learning Scholars Program.<ref>{{cite web |title=Christine McLeavey Payne |url=https://www.linkedin.com/in/mcleavey/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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| 2018 || {{dts|June 17}} || Publication || OpenAI publishes paper on learning policy representations in multiagent systems. The paper proposes a general learning framework for modeling agent behavior in any multiagent system using only a handful of interaction data.<ref>{{cite web |title=Learning Policy Representations in Multiagent Systems |url=https://arxiv.org/abs/1806.06464 |website=arxiv.org |accessdate=26 March 2020}}</ref>
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| 2018 || {{dts|June}} || Staff || Johannes Otterbach joins OpenAI as Member Of Technical Staff (Fellow).<ref>{{cite web |title=Johannes Otterbach |url=https://www.linkedin.com/in/jotterbach/ |website=linkedin.com |accessdate=28 February 2020}}</ref>
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