Google DeepMind leaders Hassabis and Jumper win Nobel Prize in Chemistry

On Wednesday, the Royal Swedish Academy of Sciences announced that Demis Hassabis and John Jumper are this year’s winners of the Nobel Prize in Chemistry. Hassabis is CEO of Google’s DeepMind AI unit, while Jumper is a director there.

The pair received the award for their work on the AlphaFold2 AI model, which in 2020 stunned the scientific world with its ability to correctly predict the structure of almost all known proteins from their DNA sequences. Previously, computer software was much less accurate at predicting protein structures, while imaging methods to figure out protein shape were time-consuming and expensive.

This discovery had an enormous impact because proteins are the engines behind most biological processes, their form determining function. Among other things, being able to predict the shape of a protein unlocks a better understanding of disease and could allow researchers to develop new drugs more quickly.

AlphaFold 2 helped solve a nearly 50-year-old grand challenge in biology, first raised by Nobel Prize-winning chemist Christian Anfisen, who in 1973 suggested that it should be possible to determine the structure of a protein from its sequence alone of DNA.

“Since their discovery, AlphaFold2 has been used by more than two million people in 190 countries,” the Academy said in a statement. “Among a multitude of scientific applications, researchers can better understand antibiotic resistance and image the enzymes that can break down plastic.”

AlphaFold 2 has also been used to help researchers find potential treatments for neglected tropical diseases such as Chagas disease, which affects millions of people in less developed countries, as well as to explore the pore structure that allows the material to pass in and out. cell nucleus.

Hassabis and Jumper share this year’s prize with David Baker, a University of Washington scientist who pioneered the creation of entirely new proteins two decades ago. Baker gets half of the 11 million Swedish kroner ($1.06 million) prize money, while DeepMinders gets a quarter each.

“This is a monumental achievement for AI, for computational biology, and for science itself,” the DeepMind team posted on X.

It’s clearly a big year for AI at the most prestigious science awards. The Nobel Prize in Physics was awarded on Tuesday to Geoffrey Hinton and John Hopfield for their work in developing artificial neural networks – the basis of today’s AI systems, including AlphaFold 2.

Hinton was also a leading figure in Google’s AI efforts as part of its Brain unit (which developed the transformer deep learning technology that enables today’s generative AI). Shortly after Google merged its Brain unit with DeepMind last April, Hinton stepped down so he could warn the world about the risks of AI.

Hinton and Jumper’s award was controversial among some physicists, who saw the connections between their field and AI as tenuous. The framing of Wednesday’s Nobel in Chemistry is much clearer, rewarding the development of a specific AI tool that is rapidly transforming biological research.

Since its initial work on AlphaFold 2, DeepMind has continued to make advances in biology. AlphaFold 3, a successor model to AlpahFold 2, can predict the structures and interactions not only of proteins, but also of other molecules found in living things. Last month, it unveiled AlphaProteo, a system that provides recipes for synthetic proteins that will bind with any given target molecule. This could become a key tool for drug development. It also launched AlphaMssense, an AI model that can predict the effect of various mutations in human DNA.

Hassabis is the co-founder of DeepMInd, whose mission is to create AGI, or artificial general intelligence, a single AI system that would be as intelligent as a human. He has been fascinated by the idea of ​​protein folding since his days as a student at Cambridge University. Google acquired DeepMind in 2014, but Hassabis remained CEO of the separate unit and continues to lead the merged research division Google DeepMind.

Jumper, who originally trained as a physicist, began working in computational biology at DE Shaw Research in New York. He later obtained a Ph.D. in computational biophysics from the University of Chicago. When DeepMind started working on trying to solve Anfinsen’s protein folding problem, it hired Jumper to lead the team working on what became AlphaFold. Jumper continues to lead a group within DeepMind researching AI methods related to proteins and other biology questions.

Recommended newsletter
Data sheet: Stay on top of the tech business with close analysis of the industry’s biggest names.
Register here.