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Demosthenes 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 46)
London, England, UK
Nationality British
Education Christ's College, Finchley
Alma mater
Known for
  • Nature's 10 (2016)
  • Mullard Award (2014)
  • Golden Joystick Award
  • Pentamind World Champion (1998–2001; 2003)
  • Dan David Prize (2020)
Scientific career
Thesis Neural processes underpinning episodic memory (2009)
Doctoral advisor Eleanor Maguire
Influences Peter Molyneux

Demosthenes "Demis" Hassabis CBE FRS FREng FRSA (born 27 July 1976) is a significant figure in artificial intelligence. He is a British researcher, neuroscientist, video game designer, entrepreneur, and five times winner of the Pentamind board games championship.

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 University College London's Gatsby Computational Neuroscience Unit, and he and Suleyman had been friends through family. Hassabis also recruited his university friend and Elixir partner David Silver.

DeepMind's mission is to "solve intelligence" and then use intelligence "to solve everything else". More concretely, DeepMind aims to use powerful general-purpose learning algorithms to build an artificial general intelligence (AGI).

The company was bought by Google for £400 million.

They created AlphaGo, a program which 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. 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.

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.

Although Hassabis is expert at many games, he does not program specific rules into Deep Mind. For Go and chess, the machine played many games with itself, learning from its results. In other words it taught itself how to play, given the basic rules of the game.

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