-
Europe wants to 'avoid escalation' on Trump tariff threat: Merz
-
Syrian army deploys in former Kurdish-held areas under ceasefire deal
-
Louvre closes for the day due to strike
-
Prince Harry lawyer claims 'systematic' UK newspaper group wrongdoing as trial opens
-
Centurion Djokovic romps to Melbourne win as Swiatek, Gauff move on
-
Brignone unsure about Olympics participation ahead of World Cup comeback
-
Roger Allers, co-director of "The Lion King", dead at 76
-
Senegal awaits return of 'heroic' AFCON champions
-
Trump to charge $1bn for permanent 'peace board' membership: reports
-
Trump says world 'not secure' until US has Greenland
-
Gold hits peak, stocks sink on new Trump tariff threat
-
Champions League crunch time as pressure piles on Europe's elite
-
Harry arrives at London court for latest battle against UK newspaper
-
Swiatek survives scare to make Australian Open second round
-
Over 400 Indonesians 'released' by Cambodian scam networks: ambassador
-
Japan PM calls snap election on Feb 8 to seek stronger mandate
-
Europe readying steps against Trump tariff 'blackmail' on Greenland: Berlin
-
What is the EU's anti-coercion 'bazooka' it could use against US?
-
Infantino condemns Senegal for 'unacceptable scenes' in AFCON final
-
Gold, silver hit peaks and stocks sink on new US-EU trade fears
-
Trailblazer Eala exits Australian Open after 'overwhelming' scenes
-
Warhorse Wawrinka stays alive at farewell Australian Open
-
Bangladesh face deadline over refusal to play World Cup matches in India
-
High-speed train collision in Spain kills 39, injures dozens
-
Gold, silver hit peaks and stocks struggle on new US-EU trade fears
-
Auger-Aliassime retires in Melbourne heat with cramp
-
Melbourne home hope De Minaur 'not just making up the numbers'
-
Risking death, Indians mess with the bull at annual festival
-
Ghana's mentally ill trapped between prayer and care
-
UK, France mull social media bans for youth as debate rages
-
Japan PM to call snap election seeking stronger mandate
-
Switzerland's Ruegg sprints to second Tour Down Under title
-
China's Buddha artisans carve out a living from dying trade
-
Stroking egos key for Arbeloa as Real Madrid host Monaco
-
'I never felt like a world-class coach', says Jurgen Klopp
-
Ruthless Anisimova races into Australian Open round two
-
Australia rest Cummins, Hazlewood, Maxwell for Pakistan T20 series
-
South Korea, Italy agree to deepen AI, defence cooperation
-
Vietnam begins Communist Party congress to pick leaders
-
China's 2025 economic growth among slowest in decades
-
Gauff, Medvedev through in Australia as Djokovic begins record Slam quest
-
Who said what at 2025 Africa Cup of Nations
-
Grizzlies win in London as heckler interrupts US anthem
-
Three-time finalist Medvedev grinds into Australian Open round two
-
Auger-Aliassime retires from Melbourne first round with cramp
-
Rams fend off Bears comeback as Patriots advance in NFL playoffs
-
Thousands march in US to back Iranian anti-government protesters
-
Gotterup charges to Sony Open victory in Hawaii
-
Gold, silver hit records and stocks fall as Trump fans trade fears
-
Auger-Aliassime retires injured from Melbourne first round
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.
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.
F.Mueller--VB