Scientists who laid machine learning groundwork win physics Nobel

The 2024 Nobel Prize in Physics has been awarded to two scientists whose research formed “the foundation of today’s powerful machine learning”, the Royal Swedish Academy of Sciences has announced.

John Hopfield, emeritus professor in life sciences and molecular biology at Princeton University, and Geoffrey Hinton, emeritus professor of computer science at the University of Toronto, were recognised “for foundational discoveries and inventions that enable machine learning with artificial neural networks”.

Professor Hopfield created a network, known as the Hopfield network, that enables the storage and recreation of images and other patterns. Professor Hinton, often called the “godfather of AI”, built on the Hopfield network to create the Boltzmann machine, used to recognise elements in data, classify images and produce “new examples of the type of pattern on which it was trained”.

The new Nobelists will share the prize of 11 million Swedish kroner (£812,000). Ellen Moons, chair of the Nobel Committee for Physics, said in a statement, “The laureates’ work has already been of the greatest benefit. In physics we use artificial neural networks in a vast range of areas, such as developing new materials with specific properties.”

Princeton said said Professor Hopfield was staying in a cottage in England when the award was announced. “My wife and I went out to get a flu shot and stopped to get a coffee on the way back home,” he said. On their return, he discovered “a pile of emails”, calling them “astounding” and “heartwarming”.

Professor Hinton said he was “flabbergasted” by the award, commenting, “I had no expectations of this. I am extremely surprised and I’m honoured to be included.”

Rhodri Cusack, professor of cognitive neuroscience at Trinity College Dublin, said of the professors’ scientific legacy: “Artificial neural networks have proven valuable models of processes in the brain, such as learning in human infants.

“This neuroscientific understanding is then inspiring new strategies for artificial neural networks. In short, machines are helping us understand ourselves, which in turn provides new avenues for technology. None of this would be possible without the seminal work of Hopfield and Hinton.”

 emily.dixon@timeshighereducation.com