Machine-learning accelerates deep molecular dynamics simulations by 4 orders of magnitude, preserving quantum-mechanical precision

https://www.eurekalert.org/news-releases/1131574

"atomic forces calculated step-by-step using femtosecond intervals, requiring massive supercomputing power/ billions of computational steps, overcome using Transferable Implicit Transfer Operator generative AI... predicts molecular motion, compressing chemistry lab testing from decades to hours... learns broader statistical/ physical rules governing atomic movement over extended time scales... predicts complex structural pathways for entirely new molecules... scalable: pharmaceutical testing/ material discovery"