John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in Physics for work that established key foundations of machine learning with artificial neural networks. The Royal Swedish Academy of Sciences announced that the researchers would share the 11 million Swedish kronor prize, worth about £810,000.
Hopfield, a 91-year-old professor emeritus at Princeton University, was recognised for developing an associative memory capable of storing and reconstructing images and other patterns in data. In 1982, he created a network in which information was represented as patterns. When given related input, the system could recover a stored image, demonstrating a computational approach inspired by memory in the brain.
Hinton, a 76-year-old British-Canadian professor emeritus at the University of Toronto, extended this line of research by adding probabilities to a multilayer network. His method could identify properties in data and, after training on images, recognise, classify and generate them. Those concepts became important to the large neural networks used in contemporary artificial-intelligence systems.
The two scientists began their pioneering work in the 1980s. Their combination of neural-network ideas and statistical methods helped establish techniques later applied to language translation, facial recognition and generative systems, including chatbots. Ellen Moons, chair of the Nobel physics committee, said neural networks had also advanced research in particle physics, materials science and astrophysics.
The award connected computer science with physics, a choice that prompted some debate. University of Oxford computer scientist Michael Wooldridge said it reflected how extensively artificial intelligence was changing scientific analysis. Wendy Hall, a University of Southampton computer scientist and UN adviser on AI, said the absence of a Nobel category for computer science made the selection interesting, while questioning whether artificial neural networks themselves should be treated as physics research.
Hinton reacted with surprise after receiving the call in California. He had left Google in 2023 so he could speak openly about risks from advanced AI. After the Nobel announcement, he compared the technology's potential influence with the Industrial Revolution, saying it could improve healthcare, digital assistants and productivity. He also warned of misinformation, labour-market disruption and systems becoming more intelligent than people and escaping human control.
Those concerns were not the basis of the prize, but they underscored the reach of the research being honoured. The academy's decision focused on the foundational discoveries and inventions that made neural-network machine learning possible, recognising both an early model of associative memory and a method for discovering structure in data.
The selection placed methods associated with modern AI inside the physics prize while leaving open the academic debate over how that work should be classified.
