@eviraDemis Hassabis is betting his career on a timeline where AI helps cure every human disease within the next two decades. He just stepped back from the day-to-day CEO grind at Google DeepMind, becoming its chairman and Alphabet’s chief scientist, while staying CEO of Isomorphic Labs, the drug discovery spin-out. The goal isn’t a modest bump in pharma efficiency. He’s expecting roughly 6 to 12 more breakthroughs on the scale of AlphaFold, eventually leading to treatments or cures for all diseases over that stretch. AlphaFold itself didn’t crack biology or drug discovery, but it blew past a decades-old roadblock in predicting 3D protein structures. Its database now covers more than 200 million predictions, and millions of researchers have tapped its tools. Isomorphic Labs is pushing that mindset into designing drugs computationally, building AI that understands biological targets, predicts molecular interactions, and aims to shrink years of lab trial and error into months or even weeks. That doesn’t mean a new medicine zips from concept to pharmacy shelf in weeks. Human trials, safety testing, and regulatory approval are still major bottlenecks. But Hassabis thinks the discovery engine itself can be radically accelerated. There’s another layer to his pivot: he believes AGI is only a few years away, so rather than running daily operations at a giant AI lab, he wants to focus on the scientific questions that come after increasingly capable AI arrives. For him, the ultimate payoff may not be another chatbot. It’s about treating biology as an engineering discipline and using AI to methodically design treatments for diseases once seen as unsolvable. #DemisHassabis #GoogleDeepMind

@eviraDemis Hassabis is betting his career on a timeline where AI helps cure every human disease within the next two decades. He just stepped back from the day-to-day CEO grind at Google DeepMind, becoming its chairman and Alphabet’s chief scientist, while staying CEO of Isomorphic Labs, the drug discovery spin-out. The goal isn’t a modest bump in pharma efficiency. He’s expecting roughly 6 to 12 more breakthroughs on the scale of AlphaFold, eventually leading to treatments or cures for all diseases over that stretch. AlphaFold itself didn’t crack biology or drug discovery, but it blew past a decades-old roadblock in predicting 3D protein structures. Its database now covers more than 200 million predictions, and millions of researchers have tapped its tools. Isomorphic Labs is pushing that mindset into designing drugs computationally, building AI that understands biological targets, predicts molecular interactions, and aims to shrink years of lab trial and error into months or even weeks. That doesn’t mean a new medicine zips from concept to pharmacy shelf in weeks. Human trials, safety testing, and regulatory approval are still major bottlenecks. But Hassabis thinks the discovery engine itself can be radically accelerated. There’s another layer to his pivot: he believes AGI is only a few years away, so rather than running daily operations at a giant AI lab, he wants to focus on the scientific questions that come after increasingly capable AI arrives. For him, the ultimate payoff may not be another chatbot. It’s about treating biology as an engineering discipline and using AI to methodically design treatments for diseases once seen as unsolvable. #DemisHassabis #GoogleDeepMind