Molecular dynamics is central to many questions in modern chemistry. However, computer models of molecular dynamics must balance computational cost and accuracy. Scientists have now used a machine learning technique called transfer learning to create a novel model of molecular motion that is as accurate as calculations that use quantum-mechanical physics but much faster.