AI in Materials Science: Discovery, Data Gaps, and Active Learning
MIT Professor Heather Kulik discusses AI-driven materials discovery, the power of active learning for multi-objective optimization, and critical challenges including data scarcity, LLM limitations, and the need for experimental validation in computational chemistry.