Demis Hassabis was awarded the Nobel Prize in Chemistry, along with John Jumper, in 2024 for developing AlphaFold, an artificial intelligence algorithm that predicts protein structure. Many aspects of his life contributed to this achievement and they show how creativity advances science.
Hassabis was a chess prodigy who attained the rank of grand master at 13, and in his free time, he taught himself to code. His interest in programming lead him to work on a handful of AI-based video games and to study computer science at Cambridge. He went on to get his PhD, not in computer science, but in cognitive neuroscience. He wanted to understand how the human brain managed imagination and memory and try to apply that to AI algorithms. He went on to found DeepMind, an AI start-up which was later bought by Google. His company started by developing AI models that used deep learning to master games such as Go. What Hassabis really wanted to do, though, was use AI algorithms to solve real-world problems, namely in the field of biochemistry.
This lead him and Jumper to create AlphaFold, which uses AI to predict protein structures. Proteins are large molecules that perform all of the major functions of the body, many having major ramifications on health and disease. Each has a unique structure that dictates how it interacts with other molecules and what tasks it can perform. Understanding this structure, then, is essential to understanding how these proteins work. This can give new insights into how these proteins are related to disease and how to cure those diseases. AlphaFold strives to do just that.
We learned in class about analogy, which is the creative process of drawing connections between domains. From his ability to connect his work in game development and AI to biology, it is evident that Hassabis excels at analogy. This is a trait he shares with Jennifer Doudna, whose work on CRISPR also brought together different scientific disciplines and ways of thinking.
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