Demis Hassabis, a London-born AI visionary, has had an extraordinary career path that has taken him from a chess prodigy to a Nobel Prize-winning scientist. His early passion for games and strategy led him to co-design the iconic video game Theme Park and later explore the potential of artificial intelligence through his company DeepMind. Hassabis’ pioneering work in using AI techniques to solve complex problems, such as predicting protein structures with AlphaFold, has earned him global recognition and a shared Nobel Prize in Chemistry.
Chess prodigy to AI visionary
Demis Hassabis, CEO and co-founder of DeepMind grew up playing chess. Brought up in north London by a Greek-Cypriot father and a mother from Singapore, Hassabis was mastering chess at four years, old and became the second-youngest-ever grandmaster when he was just 13.
I later asked Hassabis, during a news conference that followed his acceptance of the Nobel Prize in Chemistry award, what first sparked his interest in AI and he said it was because he had loved playing chess since he was very young and trying to think about how to make his thoughts better. At the time he was only 12 years old but this early interest in strategy and problem solving would form the basis of his later revolutionary work in the AI field.
The Machine Intelligence Techniques,pios (Machine learning Algorithm)
He finished high school at age 16 and then took a year off to work on video games, co-designing the hit game “Theme Park” in 1994. After that, He studied neuroscience at University College London because he wanted to understand the human brain and use those insights to develop artificial intelligence.
Hassabis’ work was named one of the 10 research breakthroughs of 2007 by the journal Science. That early success led to his co-founding of DeepMind in 2010, a company that would later push the boundaries of AI by using artificial neural networks to conquer complex board games and video games. Hassabis became an AI visionary in 2016 after that year when his system, AlphaGo, outplayed the top Go player in the world. A year later, it beat the Chess program Stockfish and won Hassabis glory as a symbol of where AI was headed.
Breakthrough predicting protein structures (Nobel Prize)
His latest and possibly single biggest feat is spearheading the AI advancements made in the protein folding problem, something that has stumped researchers for decades. Two years later, in 2018, his team at DeepMind took part in something called the “protein Olympics,” a competition among chemists to see who could do the best job predicting how proteins fold into their intricate three-dimensional shapes. The initial efforts managed an accuracy of about 40%, but Hassabis’ AlphaFold system scored close to 60% accuracy.
Then, just two years later, AlphaFold did so well that the 50-year-old problem was considered solved. This breakthrough has been a game-changer in the scientific community, and over 30,000 scientific papers now acknowledge AlphaFold’s work as inspiration. This recognition cements his place as a true trailblazer in the form of artificial intelligence and life science applications, something that came also to more universal fruition last year when Hassabis was awarded the Nobel Prize in Chemistry.
