Machine learning offers exciting opportunities to do new physics research
The Computational Chemical Physics group of the University of Twente is delighted to congratulate John J. Hopfield and Geoffrey E. Hinton on winning the 2024 Nobel Prize in Physics for their foundational discoveries in machine learning using artificial neural networks (ANNs). According to the official Nobel Prize announcement, Hopfield and Hinton’s pioneering work laid the groundwork for the ANN architectures that are transforming everything from scientific research to everyday technologies. Their achievements have helped revolutionize fields such as physics, chemistry, and even healthcare, by enabling computers to learn, adapt, and solve complex tasks much like biological systems. The pair’s contributions—especially in the development of recurrent and feedforward networks—have unlocked the power of artificial intelligence and made deep learning an integral part of modern science.
Their ANN has also been instrumental in developing Machine Learning Force Fields (MLFF) to study phases of complex materials with an accuracy comparable to ab initio quantum-mechanical models and a speedup by a factor as large as 1000! We are happy that the work of our colleague, Dr. Menno Bokdam, and his collaborators, on simulating phase transitions using MLFFs has (among others) been mentioned in the 'Scientific Background to the Nobel Prize in Physics 2024' as powerful new tools in physics.
Computational Chemical Physics group congratulates the Nobel Prize winners again!
