MIT Researchers Develop Neural Networks for Computational Chemistry Using SDSC, PSC Supercomputers

Even though computational chemistry represents a challenging arena for machine learning, a team of researchers from the Massachusetts Institute of Technology (MIT) may have made it easier. Using Comet at the San Diego Supercomputer Center at UC San Diego and Bridges at the Pittsburgh Supercomputing Center, they succeeded in developing an artificial intelligence (AI) approach to detect electron correlation - the interaction between a system's electrons - which is vital but expensive to calculate in quantum chemistry.

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