Demis Hassabis: From Chess Prodigy to Nobel Laureate in AI-Driven Protein Research

Demis Hassabis, from chess prodigy to Nobel-winning AI pioneer

Long before Demis Hassabis pioneered artificial intelligence techniques to earn a Nobel prize, he was a master of board games. The London-born son of a Greek-Cypriot father and a Singaporean mother started playing chess when he was just four, rising to the rank of master at 13. "That's what got me into AI in the first place, playing chess from a young age and thinking and trying to improve my own thought processes," the 48-year-old told journalists after sharing the Nobel prize in chemistry with two other scientists on Wednesday. It was the second Nobel award in as many days involving artificial intelligence (AI), and Hassabis followed Tuesday's chemistry laureates in warning that the technology they had championed can also "be used for harm". But rather than doom and gloom warnings of AI apocalypse, the CEO of Google's DeepMind lab described himself as a "cautious optimist". "I've worked on this my whole life because I believe it's going to be the most beneficial technology to humanity -- but with something that powerful and that transformative, it comes with risks," he said. Dabbling in video games Hassabis finished high school in north London at the age of 16, and took a gap year to work on video games, co-designing 1994's "Theme Park". In his 20s, Hassabis won the "pentamind" -- a London event that combines the results of bridge, chess, Go, Mastermind and Scrabble -- five times. "I would actually encourage kids to play games, but not just to play them... the most important thing is to try and make them," Hassabis said. He then studied neuroscience at University College London, hoping to learn more about the human brain with the aim of improving nascent AI. In 2007, the journal Science listed his research among the top 10 breakthroughs of the year. He co-founded the firm DeepMind in 2010, which then focused on using artificial neural networks -- which are loosely based on the human brain and underpin AI -- to beat humans at board and video games. Google bought the company four years later. In 2016, DeepMind became known around the world when its AI-driven computer programme AlphaZero beat the world's top player of the ancient Chinese board game Go. A year later, AlphaZero beat the world champion chess programme Stockfish, showing it was not a one-game wonder. It also conquered some retro video games. The point was not to have fun or win games, but to broaden out the capability of AI. "It's those kinds of learning techniques that have ended up fuelling the modern AI renaissance," Hassabis said. Protein power Hassabis then turned the power he had been building towards proteins. These are the building blocks of life, which take the information from DNA's blueprint and turn a cell into something specific, such as a brain cell or muscle cell -- or most anything else. By the late 1960s, chemists knew that the sequence of 20 amino acids that make up proteins should allow them to predict the three-dimensional structure they would twist and fold into. But for half a century, no one could accurately predict these 3D structures. There was even a biannual competition dubbed the "protein olympics" for chemists to try their hand. In 2018, Hassabis and his AlphaFold entered the competition. Previous predictions had at best an accuracy rate of 40 percent. AlphaFold nearly topped 60 percent. Two years later, it did so well that the 50-year-old problem was considered solved. Around 30,000 scientific papers have now cited AlphaFold, according to DeepMind's John Jumper, who shared Wednesday's Nobel win along with US biochemist David Baker. "AlphaFold has already been used by more than two million researchers to advance critical work, from enzyme design to drug discovery," Hassabis said.

Demis Hassabis, from chess prodigy to Nobel-winning AI pioneer

Paris (AFP) - Long before Demis Hassabis pioneered artificial intelligence techniques to earn a Nobel prize, he was a master of board games. The London-born son of a Greek-Cypriot father and a Singaporean mother started playing chess when he was just four, rising to the rank of master at 13. "That's what got me into AI in the first place, playing chess from a young age and thinking and trying to improve my own thought processes," the 48-year-old told journalists after sharing the Nobel prize in chemistry with two other scientists on Wednesday. It was the second Nobel award in as many days involving artificial intelligence (AI), and Hassabis followed Tuesday's chemistry laureates in warning that the technology they had championed can also "be used for harm". But rather than doom and gloom warnings of AI apocalypse, the CEO of Google's DeepMind lab described himself as a "cautious optimist". "I've worked on this my whole life because I believe it's going to be the most beneficial technology to humanity -- but with something that powerful and that transformative, it comes with risks," he said. Dabbling in video games Hassabis finished high school in north London at the age of 16, and took a gap year to work on video games, co-designing 1994's "Theme Park". In his 20s, Hassabis won the "pentamind" -- a London event that combines the results of bridge, chess, Go, Mastermind and Scrabble -- five times. "I would actually encourage kids to play games, but not just to play them... the most important thing is to try and make them," Hassabis said. He then studied neuroscience at University College London, hoping to learn more about the human brain with the aim of improving nascent AI. In 2007, the journal Science listed his research among the top 10 breakthroughs of the year. He co-founded the firm DeepMind in 2010, which then focused on using artificial neural networks -- which are loosely based on the human brain and underpin AI -- to beat humans at board and video games. Google bought the company four years later. In 2016, DeepMind became known around the world when its AI-driven computer programme AlphaZero beat the world's top player of the ancient Chinese board game Go. A year later, AlphaZero beat the world champion chess programme Stockfish, showing it was not a one-game wonder. It also conquered some retro video games. The point was not to have fun or win games, but to broaden out the capability of AI. "It's those kinds of learning techniques that have ended up fuelling the modern AI renaissance," Hassabis said. Protein power Hassabis then turned the power he had been building towards proteins. These are the building blocks of life, which take the information from DNA's blueprint and turn a cell into something specific, such as a brain cell or muscle cell -- or most anything else. By the late 1960s, chemists knew that the sequence of 20 amino acids that make up proteins should allow them to predict the three-dimensional structure they would twist and fold into. But for half a century, no one could accurately predict these 3D structures. There was even a biannual competition dubbed the "protein olympics" for chemists to try their hand. In 2018, Hassabis and his AlphaFold entered the competition. Two years later, it did so well that the 50-year-old problem was considered solved. Around 30,000 scientific papers have now cited AlphaFold, according to DeepMind's John Jumper, who shared Wednesday's Nobel win along with US biochemist David Baker. "AlphaFold has already been used by more than two million researchers to advance critical work, from enzyme design to drug discovery," Hassabis said.

Demis Hassabis: from video game designer to Nobel prize winner

The co-creator of Theme Park has gone on to work at the forefront of AI as head of Google DeepMind Most 17-year-olds spend their days playing video games, but Britain's latest Nobel prize winner spent his teenage years developing them. Sir Demis Hassabis, who was jointly awarded the chemistry prize on Wednesday, got his big break in the tech world as co-designer of 1994's hit game Theme Park, where players create and operate amusement parks. Born in London to a Greek Cypriot father and Singaporean mother, Hassabis went on to gain a double first in computer science at Cambridge University, complete a PhD in cognitive neuroscience and co-found the artificial intelligence startup DeepMind, which Google bought for £400m in 2014. The 48-year-old was knighted for services to AI this year. He is the chief executive of Google's AI unit, Google DeepMind, and its achievements in using AI to predict and design the structure of proteins has spurred the award of the Nobel to Hassabis and his colleague John Jumper, who are sharing half of the award with the other half going to US academic David Baker. Hassabis has always extolled the benefits of gaming and has described it as a gateway to AI after, as a chess prodigy, he became interested in how chess computers learn to play the game. "I think that started sparking off in my mind ideas about how does the chess computer play chess and learning about that," he told the BBC in 2020. "Many children start by playing games, like I did, and then getting into programming and then using this incredible tool, the computer, to create things." His startup was able to build AIs with top-class performances in games including Go, which caused a global sensation at the time, chess and the video game Starcraft II. Hassabis's expertise is sought after. He attended a meeting of the UK government's Scientific Advisory Group for Emergencies in 2020 to advise on its Covid-19 response and was feted by Dominic Cummings, and in July Tony Blair told him he was "advising the new government to talk to you". As the leader of Google's AI efforts, Hassabis is at the forefront of a multibillion-dollar AI boom in which US tech companies are playing a leading role, with Google competing against the likes of Meta, the ChatGPT developer OpenAI and Microsoft to produce further breakthroughs. He is well aware of the potential pitfalls of AI - a technology that can be loosely defined as computer systems performing tasks typically associated with intelligent beings - and last year signed a statement warning that the threat of extinction from AI should be considered a societal-scale risk on a par with pandemics and nuclear war. In an interview with the Guardian before the inaugural global AI safety summit last year, Hassabis said the risks from out-of-control AI systems were as serious as the climate crisis. "We must take the risks of AI as seriously as other major global challenges, like climate change," he said. "It took the international community too long to coordinate an effective global response to this, and we're living with the consequences of that now. We can't afford the same delay with AI." But Hassabis is also an emphatic believer in AI's positive potential, and the Nobel prize underscores that. He points to his work with DeepMind's AlphaFold, which predicts the structure of proteins based on their chemical sequence, as an example of AI's power to do good. "I am not in the pessimistic camp about AI obviously, otherwise I wouldn't be working on it," he said last year.

Black and White's AI programmer just won a Nobel prize: 'an incredible honor, it's the big one really'

Demis Hassabis, best-known for his work with DeepMind, is one of three recipients of the Nobel Prize for Chemistry. Professor Demis Hassabis, a co-founder of DeepMind who began his programming career working for Bullfrog and Lionhead, has been awarded the Nobel Prize for Chemistry, alongside Professor John Jumper and Professor David Baker. Hassabis and Jumper's share of the award is for their "complete revolution" in the prediction of protein structures through the AI tool AlphaFold2. AlphaFold first became available to researchers in 2018, and 2020's AlphaFold2 is the second iteration (the third, AlphaFold3, was announced in May this year). It is an AI dedicated to predicting protein structures, created by DeepMind, which has now been used to predict the structure of almost all known proteins, a feat unimaginable a mere decade ago, as well as create new proteins by David Baker and his researchers. Per the Nobel citation, Professor Baker receives half of the Nobel "for computational protein design", while the other half is shared jointly between Professor Hassabis and Professor Jumper of DeepMind "for protein structure prediction". The winners receive a share of 11m Swedish kronor ($1.05 million). "One of the discoveries being recognised this year concerns the construction of spectacular proteins,"says Heiner Linke, chair of the Nobel Committee for Chemistry. "The other is about fulfilling a 50-year-old dream: predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities." The Nobel press release says AlphaFold2 has been used "to predict the structure of virtually all the 200 million proteins that researchers have identified." "Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries," continues the org. "Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic. "Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind." The list of actual and potential medical benefits from this work is enormous: Proteins are commonly described as the "building blocks" of all human body cells. AlphaFold 2's work is used in countering antibiotic resistance and lies behind the creation of plastic-guzzling enzymes. "It's an incredible honour, you know, it's the big one really," laughs Hassbis on a phone call shortly afterwards. "My mind went blank it was so incredible, an unbelievable experience. I had a whole normal day of work ahead of me but I guess that has to change now." Hassabis has previously paid credit to his early days, encouraging children to not only be interested in games but in how they're created, and that this is what ultimately put him on the path of his AI passion. "I think that started sparking off in my mind ideas about how does the chess computer play chess and learning about that," Hassabis said in 2020. "Many children start by playing games, like I did, and then getting into programming and then using this incredible tool, the computer, to create things." Hassabis worked for Bullfrog before attending university, and after graduation began working at Lionhead, where he was lead AI programmer on Black & White. Thanks to the game's protracted development it would release in 2001, by which time Hassabis had left to found Elixir Studios, where he would act as executive director on Republic: The Revolution and Evil Genius. He would then move more towards academia, completing a PhD and working at several universities, before in 2010 co-founding the AI company DeepMind. The goal from the start was to create a general-purpose AI that can be used for anything, but it began with videogames from the '70s and '80s. In the early days DeepMind's AI's trained on games like Breakout and Pong, learning the rules in order to master the game, before the company would focus on more complex games like Go and even Starcraft 2. DeepMind was acquired by Google in 2014. In around 2016, with all that videogame training behind it, the company's focus turned to protein folding and AlphaFold: Software which, almost from the start, has made stunning advance after "stunning advance" in protein folding.

British Google AI boss Sir Demis Hassabis among scientists awarded Nobel Prize for chemistry

The 48-year-old said he was "overwhelmed" by the honour. He will share the prize with Americans David Baker and John Jumper. Briton Sir Demis Hassabis has been awarded the Nobel Prize for chemistry, jointly with two other scientists. The trio of Sir Demis, as well as Americans Professor David Baker and Dr John Jumper, were honoured on Wednesday for their work on decoding the structure of proteins and creating new ones. The research has helped advances across a range of areas including drug development. Half of the prize was awarded to Prof Baker "for computational protein design", while the other half was shared by Sir Demis and Dr Jumper "for protein structure prediction", the Royal Swedish Academy of Sciences said. Sir Demis, 48, is the chief executive of Google DeepMind, the artificial intelligence (AI) research subsidiary of Google. He studied Computer Science as an undergraduate at Queens' College, Cambridge, and went on to complete a PhD in cognitive neuroscience at University College London. He also created the videogame company Elixir Studios before co-founding DeepMind. Prof Baker, 62, is a professor at the University of Washington, in Seattle, while Dr Jumper, 39, also works as a senior research scientist. Sir Demis and Dr Jumper utilised AI to predict the structure of almost all known proteins, while Prof Baker learnt how to master life's building blocks and create entirely new proteins, the award body said. Sir Demis said: "It's totally surreal to be honest, quite overwhelming." After thanking his colleagues, including Dr Jumper, he added: "David Baker, we've got to know in the last few years, and he's done some absolutely seminal work in protein design. "So it's really, really exciting to receive the prize with both of them." Read more from Sky News: Plane makes emergency landing after pilot dies Florida braces for hurricane's arrival Man hunted over rape of 18-year-old It is the second Nobel Prize awarded this week related to artificial intelligence after John Hopfield and Geoffrey Hinton were honoured in the physics category. Speaking about AI, Sir Demis said: "That's always been my passion, but... it's like any powerful general-purpose technology, it can be used for harm as well if put in the wrong hands and used for the wrong ends." The prize, widely regarded as among the most prestigious in the scientific world, is worth 11 million Swedish krona (£810,000).