An interdisciplinary team of researchers thinks health AI could benefit from some of the aviation industry’s long history of hard-won lessons that have created one of the safest activities today.
MIT’s Improbable AI Lab, a group within CSAIL, has offered these machines a helping hand with a new multimodal framework: Compositional Foundation Models for Hierarchical Planning (HiP), which develops detailed, feasible plans with the expertise of three different foundation models.
MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.
The programming included a flagship full-day symposium as well as four subject-specific symposia, all aimed at fostering a dialogue about the opportunities and potential applications of generative artificial intelligence technologies across a diverse range of disciplines.