The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”

Inspired by ideas from physics and biology, Hopfield and Hinton developed computer systems that can memorise and learn from patterns in data. Despite never directly collaborating, they built on each other’s work to develop the foundations of the current boom in machine learning and artificial intelligence (AI).

Artificial neural networks (ANN) are behind much of the AI technology we use today.

In the same way your brain has neuronal cells linked by synapses, artificial neural networks have digital neurons connected in various configurations. Each individual neuron doesn’t do much. Instead, the magic lies in the pattern and strength of the connections between them.

John Hopfield (born 1933) is a US theoretical physicist who made important contributions over his career in the field of biological physics. However, the Nobel physics prize was for his work developing Hopfield networks in 1982.

Hopfield networks were one of the earliest kinds of artificial neural networks. Inspired by principles from neurobiology and molecular physics, these systems demonstrated for the first time how a computer could use a “network” of nodes to remember and recall information.

This year’s Nobel Prize in Physics was awarded to neural network pioneers John Hopfield and Geoffrey Hinton, who laid the foundations for Artificial Intelligence

After receiving the Nobel prize, Hinton said AI will be “like the Industrial Revolution, but instead of our physical capabilities, it’s going to exceed our intellectual capabilities.” He also said he still worries that the consequences of his work might be “systems that are more intelligent than us that might eventually take control.”