Just when they believed they were passed over for this year's Nobel Prize in Chemistry, two scientists from Google's DeepMind AI research team got the call – just minutes before they were announced as honorees.
Demis Hassabiso CEO of Google's DeepMind, and John Jumper the project's American director, shared the award for their work on AlphaFold2, an AI model that can predict protein structures. The two were co-honored with David Baker, a University of Washington scientist who has used amino acids and computational power to create new types of proteins.
Hassabis and Jumper said they received word from the award's Swedish organization shortly before the news broke; Emergency calls and texts eventually reached Hassabis' wife and another member of the DeepMind team. “We received the call very late. We assumed that wouldn’t happen,” Hassabis said at a press conference held by Google following Wednesday’s announcement. “I tried to sleep in,” Jumper added. “I couldn’t sleep last night.”
The AlphaFold project was first introduced in 2020 and has since predicted the structure of 200 million proteins identified by researchers. AlphaFold2, for which Hassabis and Jumper won the award, has been used by more than 2 million people in 190 countries. At the press conference, the two stated that a new version in progress, AlphaFold3, will be released free of charge to the scientific community.
This year’s Nobel Prize in Physics, awarded the day before, also recognized pioneering work in AI, which revealed “a completely new way of using computers.” Geoffrey Hinton of the University of Toronto and John Hopfield of Princeton University shared the prize for using physics to train neural networks – systems inspired by the workings of the human brain – and thus enable the machine learning that drives much of that artificial intelligence can achieve.
Hinton, known as the “godfather of AI,” worked for a time at Google but left in 2023 citing concerns about the risks artificial intelligence poses. On Tuesday, he noted both the positive implications, such as advances in health care, and the negative implications and the unknowable as AI rapidly evolves. “We don’t have experience of what it’s like to have things smarter than us,” he said, as reported by The New York Times.
'AI as the ultimate tool'
The Nobel committee called AlphaFold2 an “impressive breakthrough.” At the press conference, Hassabis and Jumper acknowledged that their work is just the beginning of AI-assisted technology that could accelerate the development of medical treatments from years to months and that will help researchers understand what Hassabis called “fundamental mechanisms in biology”.
“I kind of see AI as potentially the ultimate tool for accelerating science and scientific knowledge,” Hassabis said.
Hassabis and Jumper will share the 11 million Swedish kronor (about US$1.06 million) prize with Baker.
The two credited the Google team and many other scientists who created the foundational work on which their research was based.
“It’s humiliating. Every time we train AI, each data point represents years of effort from someone training to be a doctoral student or someone who has already earned their doctorate,” Jumper said. “Every day it’s wonderful to see the work the scientific community has done on AlphaFold and I can’t wait to see the next advances.”
While AI was a significant part of AlphaFold, instrumental in identifying patterns that humans wouldn't be able to find, Hassabis highlighted that a lot of human work went into the project. “It wasn’t just ‘the AI did it,’” he said. “It was an iterative process. We developed, we did research, we tried to find the right combinations between what the community understood about proteins and how we built those intuitions into our architecture.”
“AI was the toolbox with which we achieved this incredible work,” said Hassabis
