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Timeline of DeepMind

597 bytes added, 15:19, 29 June 2019
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| 2016 || December 5 || Userbase || DeepMind announces open-sourcing DeepMind Lab, its 3D game-like platform for agent-based AI research, so that others can try and make advances in the field of AI. The DeepMind Lab project was used to create enviroments capable of testing AI systems’ ability to achieve goals in a wide range of environments. Tasks such as navigation in mazes, collecting fruit, traversing dangerous passages, laser tag and interaction with bots have been developed to refine the programs. The development of mazes and challenges were designed using video game {{w|Quake III Arena}}’s 17-year-old software, to teach its artificial intelligence programs how to operate in 3D spaces.<ref>{{cite web |last1=McCarthy |first1=John |title=Google DeepMind releases source code to the Quake III levels its using to train AIs |url=https://www.thedrum.com/news/2016/12/05/google-deepmind-releases-source-code-the-quake-iii-levels-its-using-train-ais |website=thedrum.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Condon |first1=Stephanie |title=OpenAI, DeepMind open source AI training platforms |url=https://www.zdnet.com/article/openai-deepmind-open-source-ai-training-platforms/ |website=zdnet.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind is opening up its 'flagship' platform to AI researchers outside the company |url=https://www.businessinsider.com/deepmind-opens-up-lab-to-ai-researchers-2016-12 |website=businessinsider.com |accessdate=30 May 2019}}</ref><ref>{{cite web |last1=Kahn |first1=Jeremy |title=Google DeepMind Makes AI Training Platform Publicly Available |url=https://www.bloomberg.com/news/articles/2016-12-05/google-deepmind-makes-ai-training-platform-publicly-available |website=bloomberg.com |accessdate=30 May 2019}}</ref>
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| 2016 || || Financial || DeepMind records £40.3 million (US$ 52 million) in revenue in the year.<ref name="DeepMind Losses Grew To $368 Million In 2017"/>
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| 2017 || January || Collaboration || DeepMind's experts pledge to pass on their knowledge to students enrolled on machine learning master's programs at {{w|University College London}}.<ref>{{cite web |last1=Shead |first1=Sam |title=DeepMind's AI experts have pledged to pass on their knowledge to students at UCL |url=https://www.businessinsider.com/deepmind-ai-experts-are-going-to-teach-at-ucl-2017-1 |website=businessinsider.com |accessdate=1 June 2019}}</ref>
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| 2017 || December 5 || {{w|AI}} development || DeepMind team introduces AlphaZero, a program using generalized AlphaGo Zero's approach, which achieved within 24 hours a superhuman level of play in {{w|chess}}, {{w|shogi}}, and [[w:Go (game)|Go]], defeating world-champion programs, [[w:Stockfish (chess)|Stockfish]], [[w:Elmo (shogi engine)|Elmo]], and 3-day version of AlphaGo Zero in each case.<ref>{{Cite web|first1=David|last1= Silver|first2=Thomas|last2= Hubert|first3= Julian|last3=Schrittwieser|first4= Ioannis|last4=Antonoglou |first5= Matthew|last5= Lai|first6= Arthur|last6= Guez|first7= Marc|last7= Lanctot|first8= Laurent|last8= Sifre|first9= Dharshan|last9= Kumaran|first10= Thore|last10= Graepel|first11= Timothy|last11= Lillicrap|first12= Karen|last12= Simonyan|first13=Demis |last13=Hassabis|title=Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm|class=cs.AI|date=5 December 2017|url=https://arxiv.org/abs/1712.01815}}</ref>
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| 2017 || || Financial || DeepMind recorded £54.4 million (US$ 71 million) in revenue in 2017, up 35% from £40.3 million (US$ 52 million) in 2016.<ref name="DeepMind Losses Grew To $368 Million In 2017">{{cite web |title=DeepMind Losses Grew To $368 Million In 2017 |url=https://www.forbes.com/sites/samshead/2018/10/05/deepmind-losses-grew-to-302-million-in-2017/#7719dff2490e |website=forbes.com |accessdate=29 June 2019}}</ref>
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| 2018 || February || Partnership || DeepMind announces that it is teaming with the [[w:United States Department of Veterans Affairs|U.S. Department of Veterans Affairs]] in an attempt to use machine learning to predict the onset of acute kidney injury in patients, and also more broadly the general deterioration of patients during a hospital stay so that doctors and nurses can more quickly treat patients in need.<ref>{{cite web|url=https://venturebeat.com/2018/02/22/googles-deepmind-wants-ai-to-spot-kidney-injuries/|title=Google's DeepMind wants AI to spot kidney injuries|date=22 February 2018|website=Venture Beat}}</ref>
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