Researchers from the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and Google DeepMind have developed a new machine learning algorithm that enables highly accurate and efficient molecular dynamics simulations. This algorithm decouples physical invariances from other information, drastically reducing computational costs and allowing simulations to be performed in days instead of months. This advancement could significantly enhance drug development and material design by enabling deeper insights into complex atomic interactions. The study was published in Nature Communications.
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