John J. Hopfield and Geoffrey E. Hinton - image credit: The Nobel Prize Foundation

Author: Christian Beck

EPS congratulates the winners of the 2024 Nobel Prize in Physics, John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.” The laureates used tools from physics to develop methods which underpin machine learning and artificial intelligence (AI.) These tools have applications in many areas of science and form the basis for the developments in protein structure prediction recognised by the 2024 Nobel Prize in Chemistry.

Prof. Christian Beck, member of the EPS executive committee said that the award of the 2024 prize "illustrates that fundamental research in statistical physics can ultimately lead to ground-breaking applications in machine learning and artificial intelligence (AI). John Hopfield developed his first model of neural networks more than 40 years ago, since then the developments have been rapid. Geoffrey Hinton is sometimes regarded as the 'godfather' of AI, and these days modern machine learning techniques and AI are used in almost all fields of science to process information, analyse the structure of complex systems, make forecasts, and much more. The dynamics of neural networks provides a tool to identify patterns given some incomplete information, aiming for states that locally minimize the effective free energy. Applications are numerous and have created an 'industrial revolution' of powerful new algorithms that learn from past experience, in a similar manner to how human brain does this.