University of Cambridge graduate wins 2024 Nobel Prize in Physics

Hinton (King's 1967) and Hopfield received the prize “for fundamental discoveries and inventions enabling machine learning with artificial neural networks.” Known as the “Godfather of AI,” Hinton is a professor emeritus of computer science at the University of Toronto. He is the 122nd member of Cambridge University to be awarded the Nobel Prize.

This year's two Nobel Prize winners in physics have used tools from physics to develop methods that form the basis of today's powerful machine learning. John Hopfield created associative memory that can store and reconstruct images and other types of patterns in data. Geoffrey Hinton invented a method that can independently find properties in data and perform tasks such as identifying specific elements in images.

When we talk about artificial intelligence, we often mean machine learning using artificial neural networks. This technology was originally inspired by the structure of the brain. In an artificial neural network, the brain's neurons are represented by nodes with different values. These nodes influence each other through connections that can be compared to synapses and that can be made stronger or weaker. The network is trained by, for example, building stronger connections between nodes while maintaining high values. This year's winners have carried out important work with artificial neural networks since the 1980s.

Geoffrey Hinton used a network invented by John Hopfield as the basis for a new network: the Boltzmann machine. This makes it possible to learn to recognize characteristic elements in a specific data type. Hinton used tools from statistical physics, the science of systems built from many similar components. The machine is trained by feeding it examples that are most likely to occur when the machine is running. The Boltzmann machine can be used to classify images or create new examples of the type of pattern it was trained on. Hinton built on this work and helped usher in the current explosive development of machine learning.

Vice-Chancellor Professor Deborah Prentice said:

“Congratulations to Professor Hinton on receiving the Nobel Prize. Our alumni are an important part of the Cambridge community and many of them, like Professor Hinton, have made discoveries and advances that have truly changed our world. On behalf of the University of Cambridge, I congratulate him on this tremendous achievement.”

“The work of the award winners has already been of great benefit. In physics, we use artificial neural networks in a wide variety of areas, such as developing new materials with specific properties,” says Ellen Moons, Chairwoman of the Nobel Committee for Physics.

In May 2023, Hinton gave a public lecture at the university's Center for the Study of Existential Risk entitled “Two Paths to Intelligence” in which he argued that “large-scale digital computations are likely to be far better at acquiring knowledge than biological computations and may soon be “much smarter than us”.