DeepMind's AI models transition of glass from a liquid to a solid

In a paper published in the journal Nature Physics, DeepMind researchers describe an AI system that can predict the movement of glass molecules as they transition between liquid and solid states. The techniques and trained models, which have been made available in open source, could be used to predict other qualities of interest in glass, DeepMind says. Beyond glass, the researchers assert the work yields insights into general substance and biological transitions, and that it could lead to advances in industries like manufacturing and medicine. "Machine learning is well placed to investigate the nature of fundamental problems in a range of fields," a DeepMind spokesperson told VentureBeat. "We will apply some of the learnings and techniques proven and developed through modeling glassy dynamics to other central questions in science, with the aim of revealing new things about the world around us." Glass is produced by cooling a mixture of high-temperature melted sand and minerals.