Demis Hassabis

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Demis Hassabis, a British computer scientist, neuroscientist, artificial intelligence researcher, computer game developer, entrepreneur, and founder and CEO of DeepMind. He was a child prodigy in chess starting with age 4, with an Elo rating of 2300 at the age of 13, is an accomplished shogi and poker player, and further won the Mind Sports Olympiad in 1999, aged 23, and four more times in consecutive years. At age 8, he baught his first computer, a ZX Spectrum from a prize money of a chess match, and made his first practical AI experiences in developing chess and Othello programs.

At age 16, Demis Hassabis began his game developer career at Bullfrog Productions, working with Peter Molyneux on Theme Park, later continuing his collaboration with Molyneux at Lionhead Studios on Black & White. His further games Republic: The Revolution and Evil Genius were already developed under his 1998 founded Elixir Studios. He graduated in computer science from University of Cambridge in 1997 and defended his Ph.D. from University College London in cognitive neuroscience in 2009, followed by postdocs at MIT and Harvard.

=DeepMind= After finishing his academic career, Demis Hassabis founded DeepMind in 2010, which was acquired by Google in 2014. In January 2016, DeepMind reported archiving an AI "breakthrough" with their Go playing program AlphaGo by beating European Go champion Fan Hui in October 2015 with a 5 - 0 score. In December 2017, a breakthrough in the domains of chess and Shogi was reported, combining Deep learning with Monte-Carlo Tree Search.

=Selected Publications=

2009

 * Demis Hassabis (2009). The Neural Processes Underpinning Episodic Memory. Ph.D. thesis, University College London, Supervisor Eleanor A. Maguire, pdf
 * Demis Hassabis, Eleanor A. Maguire (2009). The construction system of the brain. Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 364, No. 1521

2015 ...
2016 2017 2018 2019
 * Joel Z. Leibo, Julien Cornebise, Sergio Gómez, Demis Hassabis (2015). Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation. arXiv:1512.08457
 * Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis (2015). Human-level control through deep reinforcement learning. Nature, Vol. 518
 * Dharshan Kumaran, Demis Hassabis, James L. McClelland (2016). What learning systems do intelligent agents need? Complementary Learning Systems Theory Updated. Trends in Cognitive Sciences, Vol. 20, No. 7, pdf
 * David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis (2016). Mastering the game of Go with deep neural networks and tree search. Nature, Vol. 529
 * James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, Raia Hadsell (2016). Overcoming catastrophic forgetting in neural networks. arXiv:1612.00796
 * David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis (2017). Mastering the game of Go without human knowledge. Nature, Vol. 550
 * David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, Demis Hassabis (2017). Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. arXiv:1712.01815 » AlphaZero
 * David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, Demis Hassabis (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, Vol. 362, No. 6419
 * Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy Lillicrap, David Silver (2019). Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model. arXiv:1911.08265

=External Links=
 * DH - Home
 * Demis Hassabis (@demishassabis) | Twitter
 * Demis Hassabis | LinkedIn
 * Demis Hassabis - Google Scholar Citations
 * Demis Hassabis from Wikipedia

DeepMind

 * Demis Hassabis: 15 facts about the DeepMind Technologies founder | Technology by Samuel Gibbs, The Guardian, January 28, 2014
 * Demis Hassabis: the secretive computer boffin with the £400 million brain by Tom Rowley, Telegraph, January 28, 2014
 * DeepMind expands to Canada with new research office in Edmonton, Alberta by Demis Hassabis, DeepMind, July 5, 2017 » Richard Sutton, Michael Bowling
 * Demis Hassabis, CEO, DeepMind Technologies - The Theory of Everything, YouTube Video

Gaming

 * Hassabis, Demis FIDE Chess Profile
 * Demis Hassabis - Poker Player

AlphaGo

 * Official Google Blog: AlphaGo: using machine learning to master the ancient game of Go by Demis Hassabis, January 27, 2016
 * The superhero of artificial intelligence: can this genius keep it in check? by Clemency Burton-Hill, The Guardian, February 16, 2016
 * Exploring the mysteries of Go with AlphaGo and China's top players by Demis Hassabis, DeepMind, April 10, 2017
 * AlphaGo's next move by Demis Hassabis and David Silver, DeepMind, May 27, 2017
 * AlphaGo Zero: Learning from scratch by Demis Hassabis and David Silver, DeepMind, October 18, 2017

=References=

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