Columbia & Cambridge unlock quantum AI for new material models

Researchers at Columbia and the University of Cambridge have established a new benchmark for evaluating machine learning models predicting material properties, addressing concerns that some models arrive at correct answers “for the wrong reasons.” The benchmark focuses on accurately simulating a key factor in determining whether a model is truly physics-aware, according to Michele Simoncelli, assistant professor of applied physics at Columbia. Atoms, approximately one ten-billionth of a metre across, present immense computational challenges; however, this new standard is already being adopted by companies including Meta, Microsoft, Radical AI, and Orbital Materials. “We can call an atomistic ML model ‘physics-aware’ when it predicts…