Hopfield and Hinton win Nobel Prize in Physics for breakthroughs in AI
The Royal Swedish Academy of Sciences has awarded the 2024 Nobel Prize in Physics to John J. Hopfield, Princeton University, USA, and Geoffrey E. Hinton, University of Toronto, Canada. Both laureates are recognized for their groundbreaking work in the field of machine learning, in particular using artificial neural networks. Their research, based on physical principles, forms the basis of modern machine learning systems. Hopfield developed an associative memory system that can store and reconstruct data patterns, while Hinton introduced methods that allow networks to autonomously discover data properties and perform tasks such as image recognition.
Artificial neural networks and physics
Artificial neural networks are computer systems modeled after the neurons of the brain. These neurons, represented as nodes, influence each other through connections similar to synapses, adjusting their strength based on training. This year’s laureates have been instrumental in shaping the use of these networks in machine learning since the 1980s. Their contributions laid the foundation for today’s advanced AI technologies.
Contribution by John J. Hopfield
John J. Hopfield’s major contribution was his invention of a network that could store and reconstruct patterns. Applying principles from physics, specifically atomic spin, his network is designed to function by minimizing energy, much like systems in nature. The network updates its nodes to gradually reveal a stored image when presented with an incomplete or distorted image.
The impact of Geoffrey E. Hinton
Geoffrey E. Hinton expanded on Hopfield’s work by developing the Boltzmann machine, a neural network that can identify features in data. Using statistical physics, Hinton’s invention allows the network to learn by analyzing common examples, allowing it to recognize and generate patterns. His research has been crucial to the rapid advancement of machine learning. The prize of 11 million Swedish crowns is divided equally among the laureates
(This story has not been edited by NDTV staff and is auto-generated from a syndicated feed.)
