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Demis Hassabis

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Sir
Demis Hassabis
CBE FRS FREng FRSA
Demis Hassabis at the Royal Society admissions day in London, July 2018
Born (1976-07-27) 27 July 1976 (age 48)[4]
London, England[4]
Alma mater
Known for
Awards
Scientific career
Fields
Institutions
ThesisNeural processes underpinning episodic memory (2009)
Doctoral advisorEleanor Maguire[3]
Chess career
CountryEngland
TitleCandidate Master
Years active1988–2019[6]
FIDE rating2220 (March 2019)
Peak rating2300 (January 1990)[7]

Sir Demis Hassabis (born 27 July 1976) is a British artificial intelligence (AI) researcher, and entrepreneur. He is the chief executive officer and co-founder of Google DeepMind,[8] and Isomorphic Labs,[9][10][11] and a UK Government AI Adviser.[12] In 2024, Hassabis and John M. Jumper were jointly awarded the Nobel Prize in Chemistry for their AI research contributions for protein structure prediction.[13][14]

Hassabis is a Fellow of the Royal Society, and has won many prestigious awards for his research work including the Breakthrough Prize, the Canada Gairdner International Award, and the Lasker Award. In 2017 he was appointed a CBE and listed in the Time 100 most influential people list. In 2024 he was knighted for services to AI.[15]

Early life and education

Hassabis was born to a Greek Cypriot father[16] and a Singaporean mother[17] and grew up in North London.[18][19] In his early career, he was a video game AI programmer and designer, and an expert board games player.[18][20][21] A child prodigy in chess from the age of four,[22][23] Hassabis reached master standard at the age of 13 with an Elo rating of 2300 and captained many of the England junior chess teams.[24] He represented the University of Cambridge in the Oxford–Cambridge varsity chess matches of 1995,[25] 1996[26] and 1997,[27] winning a half blue.

Between 1988 and 1990, Hassabis was educated at Queen Elizabeth's School, Barnet, a boys' grammar school in North London. He was subsequently home-schooled by his parents, during which time he bought his first computer, a ZX Spectrum 48K funded from chess winnings, and taught himself how to program from books.[23] He wrote its first AI program on a Commodore Amiga based on the reversi board game. [28] He then studied at the comprehensive school Christ's College, Finchley.[18] He completed his A-level exams two years early at 16.[29][30]

Bullfrog Productions

Asked by Cambridge University to take a gap year due to his young age,[23] Hassabis began his computer games career at Bullfrog Productions after entering an Amiga Power "Win-a-job-at-Bullfrog" competition.[31] He began first by level designing on Syndicate, and then at 17 co-designing and lead programming on the 1994 game Theme Park, with the game's designer Peter Molyneux.[32] Theme Park, a simulation video game, sold several million copies[24] and inspired a whole genre of simulation sandbox games. He earned enough from his gap year to pay his own way through university.[23]

University of Cambridge

Hassabis left Bullfrog to study at Queens' College, Cambridge, where he completed the Computer Science Tripos and graduated in 1997 with a Double First.[24]

Career and research

Lionhead

After graduating from Cambridge, Hassabis worked at Lionhead Studios.[33] 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.[24]

Elixir Studios

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.[34] In addition to managing the company, Hassabis served as executive designer of the games Republic: The Revolution and Evil Genius.[24] Each received BAFTA Nominations for their interactive music scores, created by James Hannigan.

The release of Elixir's first game, Republic: The Revolution, a highly ambitious and unusual political simulation game,[35] was delayed due to its huge scope, which involved an AI simulation of the workings of an entire fictional country. The final game was reduced from its original vision and greeted with lukewarm reviews, receiving a Metacritic score of 62/100.[36] Evil Genius, a tongue-in-cheek Bond villain simulator, fared much better with a score of 75/100.[37] In April 2005 the intellectual property and technology rights were sold to various publishers and the studio was closed.[38][39]

Neuroscience research at University College London

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.[3] He sought to find inspiration in the human brain for new AI algorithms.[40]

He continued his neuroscience and artificial intelligence research as a visiting scientist jointly at Massachusetts Institute of Technology (MIT), in the lab of Tomaso Poggio, and Harvard University,[18] before earning a Henry Wellcome postdoctoral research fellowship to the Gatsby Computational Neuroscience Unit at UCL in 2009 working with Peter Dayan.[41]

Working in the field of imagination, memory, and amnesia, he co-authored several influential papers published in Nature, Science, Neuron, and PNAS.[1] His very first academic work, published in PNAS,[42] was a landmark paper that 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,[43] 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.[44] This work received widespread coverage in the mainstream media[45] and was listed in the top 10 scientific breakthroughs of the year by the journal Science.[46] He later generalised these ideas to advance the notion of a 'simulation engine of the mind' whose role it was to imagine events and scenarios to aid with better planning.[47][48]

DeepMind

Hassabis is the CEO and co-founder of DeepMind, a machine learning AI startup, founded in London in 2010 with Shane Legg and Mustafa Suleyman. Hassabis met Legg when both were postdocs at the Gatsby Computational Neuroscience Unit, and he and Suleyman had been friends through family.[49] Hassabis also recruited his university friend and Elixir partner David Silver.[50]

DeepMind's mission is to "solve intelligence" and then use intelligence "to solve everything else".[51] More concretely, DeepMind aims to combine insights from systems neuroscience with new developments in machine learning and 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 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.[52]

DeepMind's early investors included several high-profile tech entrepreneurs.[53][54] In 2014, Google purchased DeepMind for £400 million. Although most of the company has remained an independent entity based in London,[55] DeepMind Health has since been directly incorporated into Google Health.[56]

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.[57][58] 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.[59][60] Additional DeepMind accomplishments include creating a neural Turing machine,[61] reducing the energy used by the cooling systems in Google's data centers by 40%,[62] advancing research on AI safety,[63][64] 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.[65]

DeepMind has also been responsible for technical advances 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.[66] Hassabis has predicted that artificial intelligence will be "one of the most beneficial technologies of mankind ever" but that significant ethical issues remain.[67]

Hassabis has also warned of the potential dangers and risks of AI if misused, and has been a strong advocate of further AI safety research being needed.[68] In 2023, he signed the statement that "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war".[69] He considers however that a pause on AI progress would be very hard to enforce worldwide, and that the potential benefits (e.g. for health and against climate change) make it worth continuing. He said that there is an urgent need for research on evaluation tests that measure how capable and controllable new AI models are.[70]

AlphaFold

In 2016, DeepMind turned its artificial intelligence to protein folding, a 50-year grand challenge in science, to predict the 3D structure of a protein from its 1D amino acid sequence. This is an important problem in biology, as proteins are essential to life, almost every biological function depends on them, and the function of a protein is thought to be related to its structure. Knowing the structure of a protein can be very helpful in drug discovery and disease understanding. 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.[71]

Hassabis at 2024 Nobel Week

In November 2020, DeepMind again announced world-beating results in the CASP14 edition of the competition with AlphaFold 2, a new version of the system. It achieved a median global distance test (GDT) score of 87.0 across protein targets in the challenging free-modeling category, much higher than the same 2018 results with a median GDT < 60, and an overall error of less than the width of an atom (<1 Angstrom), making it competitive with experimental methods, and leading the organisers of CASP to declare the problem essentially solved.[72][73] Over the next year DeepMind used AlphaFold2 to fold all 200 million proteins known to science, and made the system and these structures openly and freely available for anyone to use via the AlphaFold Protein Structure Database developed in collaboration with EMBL-EBI.[74]

Personal life

Hassabis is married to an Italian molecular biologist with whom he has two sons. He resides in North London with his family.[75][76][77] He is also a lifelong fan of Liverpool FC.[23] Hassabis is the main subject of the documentary called The Thinking Game, which premiered in 2024's Tribeca Festival, from the same filmmaker as the award-winning documentary AlphaGo (2016).[78]

Awards and honours

Entrepreneurial and scientific

Research

Hassabis's research work has been listed in the Top 10 Scientific Breakthroughs of the Year by Science Magazine on four separate occasions:

  • 2021 Breakthrough of the Year (Winner) – for AlphaFold v2[126]
  • 2020 Breakthrough of the Year (Top 10) – for AlphaFold v1[127]
  • 2016 Breakthrough of the Year (Top 10) – for AlphaGo[128]
  • 2007 Breakthrough of the Year (Top 10) – for neuroscience research on imagination[129]

DeepMind

Games

Hassabis is a five-times winner of the all-round world board games championship (the Pentamind), and an expert player of many games including:[34]

References

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