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Demis Hassabis CBE FRS FREng FRSA[7] (born 27 July 1976) is a British artificial intelligence researcher, neuroscientist, video game designer, entrepreneur, and world-class games player.[5][1][8][9][10][11][12][13]

Demis Hassabis

Demis Hassabis Royal Society.jpg
Demis Hassabis at the Royal Society admissions day in London, July 2018
Born (1976-07-27) 27 July 1976 (age 42)
London, England, UK
NationalityBritish
EducationChrist's College, Finchley
Alma mater
Known for
Awards
Scientific career
Fields
Institutions
ThesisNeural processes underpinning episodic memory (2009)
Doctoral advisorEleanor Maguire[6]
InfluencesPeter Molyneux
Websitedemishassabis.com

Contents

Early life and educationEdit

Hassabis was born to a Greek Cypriot father and a Chinese Singaporean mother and grew up in North London.[8][14] A child prodigy in chess,[15] Hassabis reached master standard at the age of 13 with an Elo rating of 2300 and captained many of the England junior chess teams.[16] He represented the University of Cambridge in the Oxford-Cambridge varsity chess matches of 1995,[17] 1996[18] and 1997,[19] winning a half blue.

Hassabis was educated at Christ's College, Finchley,[8] a state-funded comprehensive school in East Finchley, North London. He completed his GCE Advanced Level and Scholarship Level exams early at the age of 15 and 16.

BullfrogEdit

Hassabis began his computer games career at Bullfrog Productions, first level designing on Syndicate and then at 17 co-designing and lead programming on the 1994 game Theme Park, with the games designer Peter Molyneux. Theme Park, a simulation video game, sold several million copies and won a Golden Joystick Award,[citation needed] and inspired a whole genre of management sim games.

University of CambridgeEdit

Hassabis then left Bullfrog to study at Queens' College, Cambridge, where he completed the Computer Science Tripos graduating in 1997 with a Double First[16] from the University of Cambridge.[13]

Career after graduationEdit

LionheadEdit

After graduating from Cambridge, Hassabis worked at Lionhead Studios.[13] Renowned games designer Peter Molyneux, with whom Hassabis had worked at Bullfrog Productions, had recently founded the company. At Lionhead, Hassabis worked as lead AI programmer on the 2001 "god" game Black & White.[16]

Elixir StudiosEdit

Hassabis left Lionhead in 1998 to found Elixir Studios, a London-based independent games developer, signing publishing deals with Eidos Interactive, Vivendi Universal and Microsoft.[20] In addition to managing the company, Hassabis served as executive designer of the BAFTA-nominated games Republic: The Revolution and Evil Genius.[16]

The release of Elixir's first game, Republic: The Revolution, a highly ambitious and unusual political simulation game,[21] was delayed due to its huge scope. The final game was reduced from its original vision and greeted with lukewarm reviews, receiving a Metacritic score of 62/100.[22] Evil Genius, a tongue-in-cheek Bond villain simulator, fared much better with a score of 75/100.[23] In April 2005 the intellectual property and technology rights were sold to various publishers and the studio was closed.[24][25]

University College London and neuroscienceEdit

 
Demis Hassabis (left) with Blaise Agüera y Arcas (right) in 2014, at the Wired conference in London

Following Elixir Studios, Hassabis returned to academia to obtain his PhD in cognitive neuroscience from University College London (UCL) in 2009 supervised by Eleanor Maguire.[6] He sought to find inspiration in the human brain for new AI algorithms.[26]

He continued his neuroscience and artificial intelligence research as a visiting scientist jointly at Massachusetts Institute of Technology (MIT) and Harvard University,[8] before earning a Henry Wellcome postdoctoral research fellowship to the Gatsby Charitable Foundation Computational Neuroscience Unit, UCL in 2009.[27]

Working in the field of autobiographical memory and amnesia, he co-authored several influential papers[5] published in Nature, Science, Neuron and PNAS. One of his most highly cited papers,[28] published in the Proceedings of the National Academy of Sciences of the United States of America, showed systematically for the first time that patients with damage to their hippocampus, known to cause amnesia, were also unable to imagine themselves in new experiences. The finding established a link between the constructive process of imagination and the reconstructive process of episodic memory recall. Based on this work and a follow-up Functional magnetic resonance imaging (fMRI) study,[29] Hassabis developed a new theoretical account of the episodic memory system identifying scene construction, the generation and online maintenance of a complex and coherent scene, as a key process underlying both memory recall and imagination.[30] This work received widespread coverage in the mainstream media[31] and was listed in the top 10 scientific breakthroughs of the year in any field by the journal Science.[32]

DeepMindEdit

In 2010, Hassabis co-founded DeepMind,[33][34] a London-based machine learning AI startup, with Shane Legg and Mustafa Suleyman. Hassabis and Suleyman had been friends since childhood, and he met Legg when both were postdocs at University College London's Gatsby Computational Neuroscience Unit.[35] Hassabis also recruited his university friend and Elixir partner David Silver.[36]

DeepMind's mission is to "solve intelligence" and then use intelligence "to solve everything else".[37] More concretely, DeepMind aims to meld insights from neuroscience and machine learning with new developments in computing hardware to unlock increasingly powerful general-purpose learning algorithms that will work towards the creation of an artificial general intelligence (AGI). The company has focused on training learning algorithms to master games, and in December 2013 it famously announced that it had made a pioneering breakthrough by training an algorithm called a Deep Q-Network (DQN) to play Atari games at a superhuman level by only using the raw pixels on the screen as inputs.[38]

DeepMind's early investors included several high-profile tech entrepreneurs.[39][40] In 2014, Google purchased DeepMind for £400 million, although it has remained an independent entity based in London.[41]

Since the Google acquisition, the company has notched up a number of significant achievements, perhaps the most notable being the creation of AlphaGo, a program that defeated world champion Lee Sedol at the complex game of Go. Go had been considered a holy grail of AI, for its high number of possible board positions and resistance to existing programming techniques.[42][43] However, AlphaGo beat European champion Fan Hui 5-0 in October 2015 before winning 4-1 against former world champion Lee Sedol in March 2016.[44][45] Additional DeepMind accomplishments include creating a Neural Turing machine,[46] advancing research on AI safety,[47][48] and the creation of a partnership with the National Health Service (NHS) of the United Kingdom and Moorfields Eye Hospital to improve medical service and identify the onset of degenerative eye conditions.[49]

More recently, DeepMind turned its artificial intelligence to protein-folding, one of the toughest problems in science. In December 2018, DeepMind's tool AlphaFold won the 13th Critical Assessment of Techniques for Protein Structure Prediction (CASP) by successfully predicting the most accurate structure for 25 out of 43 proteins. “This is a lighthouse project, our first major investment in terms of people and resources into a fundamental, very important, real-world scientific problem,” Hassabis said to the Guardian.[50] This demonstration to the power of AI, specifically DeepMind's application, bodes well to understanding the causes and cures to diseases[51] and serves as a component to potential Noble-prize worth breakthroughs in the next decade.[52]

DeepMind has also been responsible for technical advancements in machine learning, having produced a number of award-winning papers. In particular, the company has made significant advances in deep learning and reinforcement learning, and pioneered the field of deep reinforcement learning which combines these two methods.[53] Hassabis has predicted that Artificial Intelligence will be "one of the most beneficial technologies of mankind ever" but that significant ethical issues remain.[54]

Awards and honoursEdit

Entrepreneurial and scientificEdit

DeepMindEdit

GamesEdit

Hassabis is an expert player of many games including:[20]

  • Chess: achieved Master standard at age 13 with ELO rating of 2300 (at the time the second-highest in the world for his age).
  • Diplomacy: World Team Champion in 2004, 4th in 2006 World Championship, 3rd in 2004 European Championship.
  • Poker: cashed at the World Series of Poker six times including in the Main Event.[80]
  • multi-games events at the London Mind Sports Olympiad: World Pentamind Champion (a record five times: 1998, 1999, 2000, 2001, 2003)[81] and World Decamentathlon Champion (twice: 2003, 2004).

ReferencesEdit

  1. ^ a b c Demis Hassabis on IMDb
  2. ^ Castelvecchi, Davide; Gibney, Elizabeth; Cressey, Daniel; Tollefson, Jeff; Butler, Declan; Van Noorden, Richard; Reardon, Sara; Ledford, Heidi; Witze, Alexandra (2016). "Nature's 10". Nature. 540 (7634): 507–515. doi:10.1038/540507a. ISSN 0028-0836.
  3. ^ a b "Acclaimed Neuroscientist and Google DeepMind founder wins Royal Society Mullard Award", The Royal Society, 21 November 2014
  4. ^ "Mind Sports Olympiad contestant page for Demis Hassabis". Mind Sports Olympiad. Retrieved 26 April 2019.
  5. ^ a b c Demis Hassabis publications indexed by Google Scholar  
  6. ^ a b Hassabis, Demis (2009). Neural processes underpinning episodic memory. discovery.ucl.ac.uk (PhD thesis). University College London. OCLC 926193578. EThOS uk.bl.ethos.564607.  
  7. ^ a b "Demis Hassabis". royalsociety.org.
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  9. ^ Demis Hassabis rating card at FIDE
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  11. ^ a b Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. Retrieved 10 December 2017. 
  12. ^ a b Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis (2015). "Human-level control through deep reinforcement learning". Nature. 518 (7540): 529–533. Bibcode:2015Natur.518..529M. doi:10.1038/nature14236. ISSN 0028-0836.
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  29. ^ Hassabis, D.; Kumaran, D.; Maguire, E. A. (2007). "Using Imagination to Understand the Neural Basis of Episodic Memory". Journal of Neuroscience. 27 (52): 14365–14374. doi:10.1523/JNEUROSCI.4549-07.2007. PMC 2571957. PMID 18160644.
  30. ^ Hassabis, D.; Maguire, E. A. (2007). "Deconstructing episodic memory with construction". Trends in Cognitive Sciences. 11 (7): 299–306. doi:10.1016/j.tics.2007.05.001. PMID 17548229.
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