AI Model Predicts Innovation Trends with Graph Analysis
Originally Published 1 year ago — by MIT News
MIT's Markus J. Buehler has developed a novel AI method that uses graph-based computational tools and category theory to uncover shared patterns of complexity across diverse fields, such as biological materials and music. This approach allows AI to make novel predictions and accelerate scientific discovery by revealing hidden connections and suggesting innovative designs, like a new mycelium-based composite material inspired by abstract art. The research highlights the potential of AI to drive interdisciplinary innovation in material design, technology, and the arts.