The enduring relevance of simple machine learning models

Department of Physics and Astronomy, University of Padova, Via Marzolo 8, Padua, Italy

Abstract

Hopfield’s associative memory model and Hinton’s Boltzmann machines showcase the importance of simplicity and interpretability in AI. Their work urges modern AI to balance power with transparency, ensuring models remain comprehensible for research, education, and broader applications.