Teamplay
Volker Knecht · 2022
This chapter highlights how AI and physics mutually affect each other in both directions. On the one hand, AI in the form of machine learning (ML) is an increasingly essential tool in physical research. Examples are presented where ML enabled the classification of 111,000,000 astronomic light sources, the study of physical conditions short after the Big Bang, and the discovery of the “God particle”. It is demonstrated how ML enables us to handle Big Data, dissect signal from noise, and relate computer simulations to experiment. Furthermore, ML is shown to (re)discover fundamental laws by Newton, Maxwell, and Einstein – as well as from thermodynamics and statistical mechanics – within seconds! On the other hand, physics is inversely presented as having a strong impact on machine learning. First, it provides a theoretical framework to understand AI through the connection between statistical mechanics and learning theory and yields a fundamental understanding of why deep learning works so well. Second, it drives the development of new hardware platforms providing help with expensive information processing pipelines by laying the foundations of advanced analog computing and quantum computing. In 2020, a prototype quantum computer was released which was claimed to be able to calculate 100,000 billion times faster than today’s best supercomputers!