Who is Demis Hassabis, the DeepMind founder who won the Nobel Prize in chemistry?

Hassabis, 48, is the eldest of three siblings. His parents are teachers. According to The Guardian, his sister is a pianist and composer, while his brother studied creative writing.

“My parents are technophobes,” he told The Guardian. “They don’t really like computers. They’re kind of bohemian. My sister and brother both went the artistic route, too. None of them really went in for maths or science … it’s weird, I’m not quite sure where all this came from.”

Hassabis became interested in chess at the age of four while watching his father play against his uncle, according to Wired. Two weeks later, Hassabis was beating adults at the game.

By the age of five, he was competing nationally. He won the London under-eights championships at six years old. When he was nine, he was captaining England’s under-11 team.

At the age of 13, Hassabis reached the rank of chess master.

Hassabis bought his first computer with money he won from a chess match.

“The amazing thing about computers in those days is you could just start programming them,” Hassabis told Wired. “I’d go with my dad to Foyles, and sit in the computer programming department to learn how to give myself infinite lives in games. I intuitively understood that this was a magical device, which you could unleash your creativity on.”

At Bullfrog Productions, a UK video game developer that has since merged with EA, he codesigned and led programming for “Theme Park,” which challenges players to build a successful theme park.

“The most fun I had in games was early in my career in the 90s,” Hassabis once told PCGamesN. “Especially at Bullfrog, I was lucky to be there at the most golden period it had. Maybe that has ever existed in the UK industry, if you look at the games it produced one after the other.”

While at the video game company, he worked under legendary games designer Peter Molyneux.

“I think we influenced each other a lot,” Hassabis said. “We worked together very closely for a number of years — it’s hard to say who [influenced who] more but it was a very important part of my life.”

“Theme Park” was released in 1994 when Hassabis was 17. It went on to sell millions of copies.

Undergraduates at the University of Cambridge were taught how to develop “narrow AI,” which learns to perform specific tasks. But Hassabis was always more interested in developing “general AI,” according to The Financial Times.

He graduated from Queens’ College, part of the University of Cambridge system, when he was 20 with a double first-class honors degree in 1997.

After graduating, Hassabis worked at Lionhead Studios, a video game company. While there, he worked on an early prototype version of the AI for the iconic game “Black & White.” He left Lionhead about a year later to found his own video game company, Elixer.

Elixir, which employed about 60 people at its peak, made AI simulation games like “Republic: The Revolution” and “Evil Genius,” which were both BAFTA-nominated.

According to The Financial Times, Hassabis sold a 5% stake in Elixir to Eidos, which created the Lara Croft “Tomb Raider” series. The stake was sold for £600,000, valuing the company at £12 million at the time.

During his Ph.D., Hassabis sought to find inspiration in the human brain for new AI algorithms.

In 2007, the journal Science listed his research on memory and imagination among the top 10 scientific breakthroughs of the year.

He went on to complete research stints at Harvard and MIT.

DeepMind is a London-based tech company now owned by Google that aims to “solve intelligence” and use it to “make the world a better place.”

Hassabis founded DeepMind alongside his childhood friend, Mustafa Suleyman. Suleyman is now the CEO of Microsoft AI. Shane Legg was also a cofounder. He remains at Google DeepMind developing artificial general intelligence.

The company has developed sophisticated self-learning algorithms that can excel at particular tasks when it is given a dataset from which to learn. The algorithms are created by blending research and expertise from neuroscience and machine learning.

Its algorithms managed to defeat the best human player of Go. Dating back more than 3,000 years, Go is a two-player board game that appears to be relatively simple on the surface — each player takes it in turns to lay a stone trying to surround the other player’s pieces.

However, the sheer number of potential moves on any given turn means that Go is one of the most complex games ever developed and AI scientists have been unable to master it for decades. DeepMind’s AlphaGo learns by playing thousands of games against itself and gradually learning from its mistakes.

Musk once explained his DeepMind investment to Vanity Fair:

“It gave me more visibility into the rate at which things were improving, and I think they’re really improving at an accelerating rate, far faster than people realize,” Musk said. “Mostly because in everyday life you don’t see robots walking around. Maybe your Roomba or something. But Roombas aren’t going to take over the world.”

Today, DeepMind is part of Google’s parent company, Alphabet, and employs a team worldwide, from its headquarters in London to Montreal to Google’s hub in Mountain View, California.

The division is working on applying DeepMind’s technology to Google products. In 2023, Google CEO Sundar Pichai announced that Google would merge DeepMind and the Brain team from Google Research to create a single AI unit called “Google DeepMind.”

AlphaFold is an artificial intelligence program that predicts the structure of proteins, DNA, RNA, and other molecules. The innovation made a splash, so Hassabis and one of DeepMind’s top scientists pushed forward on a second iteration.

AlphaFold 2 was released in 2020 and predicted protein structure at nearly 90% accuracy.

The model has seen explosive growth since then, evidenced in part by its prediction of some 200 million proteins by July 2022.

In May, DeepMind announced AlphaFold 3, which it says can predict “the structure and interactions of all life’s molecules with unprecedented accuracy.”

“It’s actually really surreal, to be honest. It hasn’t really sunk in, but it’s an incredible honor. You know, it’s the big one, really,” Hassabis told the Nobel Prize committee.

He hopes that the tool will enable scientists to achieve more.

“I think that, at least for the next foreseeable future, I feel like this allows individual scientists to do so much more,” he said. “Because, these systems, they’re tools. They’re very good for analyzing data and finding patterns and structure in data. But, you know, they can’t figure out what the right question is to ask, or the right hypothesis, or the right conjecture. All of that’s got to come from the human scientist.”

In May, Google announced Project Astra, a real-time AI assistant that can see and perceive the world around it. It also unveiled Veo, an AI video generator and rival to OpenAI’s Sora.

Hassabis said earlier this year that Google might spend over $100 billion to keep up with its AI competitors, like OpenAI.

He also noted that all the money going into the technology means it’s also overhyped. “In a way, AI’s not hyped enough, but in some senses, it’s too hyped,” he said in April. “And it clouds the science and the research, which is phenomenal.”