NSF congratulates laureates of the 2024 Nobel Prize in physics

The U.S. National Science Foundation congratulates John J. Hopfield and Geoffrey E. Hinton for their Nobel Prize in physics. Their research and innovations helped make possible "machines that learn" - artificial neural networks with the ability to store and reconstruct information and recognize complex patterns within data.

NSF supported their pioneering work in the 1980s, which helped create the foundation for the AI revolution of today, including Hopfield's seminal 1982 paper "Neural networks and physical systems with emergent collective computational abilities." Hopfield and Hinton's multiple breakthroughs, achieved independently, used fundamental concepts and methods from physics to develop new computer technologies that mimic an organic brain's ability to process information through memory and learning.

For example, Hopfield created a computer model of a neural network of interconnected nodes that could influence one another, akin to the physical interactions between atoms in magnetic materials. Hinton expanded on Hopfield's network by using statistical methods traditionally used to determine the properties of systems with many elements - like the temperature of a gas made of many molecules. Named after 1800s physicist Ludwig Boltzmann, who studied statistical and probabilistic properties of such systems, Hinton's "Boltzmann machine" was an early example of a computer model that can generate probability-based solutions and be trained to recognize new information and how it is similar or different from existing information.

"The laureates brought their understanding of the fundamental physical workings of nature into a new realm and created an entirely new foundation that has led to what we now call AI - perhaps the greatest innovation of our generation," says NSF Director Sethuraman Panchanathan. "Beyond their scientific breakthroughs, they have also provided invaluable training for many students, who now carry on their legacy as innovators and leaders in the U.S. scientific enterprise."

Select NSF awards supporting Hopfield or Hinton

• Theoretical Physics
• Experimental and Theoretical Studies on the Physics of Biological Molecules (multiple awards)
• Analysis of the Collective Properties of Neural Networks and Their Relation to the Structure and Concepts of Memory
• Knowledge and Distributed Intelligence: Neuromorphic Knowledge Systems
• Search Methods for Massively Parallel Networks