The call from the Royal Swedish Academy of Sciences woke him in the middle of the night. Or rather, his wife did. She answered the phone at their home in Washington, D.C. and screamed that he’d won the Nobel Prize for Chemistry. The prize is the ultimate recognition of his work as a biochemist at the University of Washington.
“I woke up at two [a.m.] and basically didn’t sleep through the whole day, which was all parties and stuff,” he told me the day after the announcement. “I’m looking forward to getting back to normal a little bit today.”
Last week was a major milestone for AI, with two Nobel prizes awarded for AI-related discoveries.
Baker wasn’t alone in winning the Nobel Prize for Chemistry. The Royal Swedish Academy of Sciences awarded it to Demis Hassabis, the cofounder and CEO of Google DeepMind, and John M. Jumper, a director at the same company, too. Google DeepMind was awarded for its research on AlphaFold, a tool which can predict how proteins are structured, while Baker was recognized for his work using AI to design new proteins. Read more about it here.
Meanwhile, the physics prize went to Geoffrey Hinton, a computer scientist whose pioneering work on deep learning in the 1980s and ’90s underpins all of the most powerful AI models in the world today, and fellow computer scientist John Hopfield, who invented a type of pattern-matching neural network that can store and reconstruct data. Read more about it here.
Speaking to reporters after the prize was announced, Hassabis said he believes that it will herald more AI tools being used for significant scientific discoveries.
But there is one problem. AI needs masses of high-quality data to be useful for science, and databases containing that sort of data are rare, says Baker.
The prize is a recognition for the whole community of people working as protein designers. It will help move protein design from the “lunatic fringe of stuff that no one ever thought would be useful for anything to being at the center stage,” he says.