Chess Master to AI Pioneer: How DeepMind’s CEO Found Nobel Success

You might think the head of a cutting-edge AI company like DeepMind would have always been focused on algorithms and coding. But DeepMind CEO Demis Hassabis? His story starts on a chessboard.

Yep, years before he was even close to winning a Nobel Prize for his work on AI, Hassabis was a kid playing chess. And not just playing – dominating. He started at age four. By 13, he was a chess master, taking on adults in big competitions.

Thinking About Thinking

How did chess lead to AI? That’s what Hassabis explored in a recent talk at the University of Cambridge. Chess, he said, got him “thinking about thinking itself. ”

He wondered: How do we come up with plans? Ideas? He was fascinated by the mental process behind the game.

The Spark: An Electronic Chessboard

His first taste of programming came from an electronic chessboard. You know, the kind where you could play against the computer? He was supposed to use it to test strategies. But he was more interested in how it worked.

He wondered how someone programmed this thing to play chess so well. That question? It hooked him.

Building AI on an Old Computer

In his early teens, Hassabis started building his own AI programs on an Amiga 500, an early home computer. That was it. He was “hooked” on AI and decided to make it his life’s work.

DeepMind and a Chess-Playing AI

Fast forward to 2010. Hassabis co-founded DeepMind. Then, in 2014, Google bought it for over $500 million. Pretty good, right?

But the story gets better. In 2017, he created AlphaZero. This AI only needed the rules of chess and four hours of practice against itself. The result? It became the best chess player ever, beating human masters.

A Nobel Prize for Predicting Proteins

In 2024, Hassabis and his colleague John Jumper won the Nobel Prize in Chemistry. Why? They created AlphaFold2, an AI that can predict the structures of almost all 200 million proteins in minutes.

This is huge. The AlphaFold Protein Structure Database, which makes these structures available for free, has over two million users in 190 countries. It’s helping speed up research on things like Parkinson’s and antibiotic resistance.

Faster, Cheaper Drug Development?

Hassabis pointed out that it usually takes 10 years and billions of dollars to create a new drug. According to the London School of Economics, it can cost anywhere from $314 million to $2. 8 billion.

But what if AI could make the process faster and cheaper? Hassabis thinks it could cut the time “from potentially years down to minutes and seconds. ”

The Future of AI

Hassabis even told DeepMind employees that he believes AI will be smarter than humans within the next decade.

From a childhood spent mastering chess to leading the charge in AI, Demis Hassabis’ journey is a reminder that sometimes the most unexpected paths lead to the greatest discoveries.