Google DeepMind founder Demis Hassabis has won a joint Nobel Prize for Chemistry for using artificial intelligence to predict the structures of proteins. Hassabis shares half the prize with John M. Jumper, a director at Google DeepMind, while the other half has been awarded to David Baker, a professor in biochemistry at the University of Washington, for his work on computational protein design. The potential impact of this research is enormous. Proteins are fundamental to life, but understanding what they do involves figuring out their structure—a challenging puzzle that once took months or years to crack for each type of protein.
By cutting down the time it takes to predict a protein’s structure, computational tools such as those developed by this year’s award winners are helping scientists better understand how proteins work and opening up new avenues of research and drug development. The technology could unlock more efficient vaccines, speed up research for the cure to cancer, or lead to completely new materials.
It also marks a second Nobel win for AI, after computer scientist Geoffrey Hinton was awarded the 2024 Nobel Prize in physics for his foundational contributions to deep learning.
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