Professor Anima Anandkumar on developing AI for new scientific discoveries (www.newindiaabroad.com)

Caltech professor Anima Anandkumar is building physics-aware AI intended not just to interpret scientific literature but to generate real, testable scientific inventions by embedding laws of physics into machine-learning models. She argues that language and vision models can point to equations but cannot produce functional designs without physical constraints; her lab has already produced concrete results, including a 3D‑printed medical catheter that reduces bacterial contamination 100× by using AI that models fluid dynamics, and a high‑resolution AI weather model that is both accurate and tens of thousands of times faster—capable of producing a two‑week forecast in under a minute on a consumer GPU. The work is significant because it moves ML from pattern recognition toward physics‑guided emulation and design, addressing the scarcity of labeled scientific data by incorporating domain knowledge (PDEs, conservation laws, and simulation priors) directly into architectures and optimization. Practically, this enables dramatically cheaper, faster surrogates for expensive simulations (weather, CFD, climate, carbon capture) and democratizes access to high‑fidelity modeling for researchers and practitioners. Key implications include greater sample efficiency, safer and more reliable designs when physical constraints are enforced, and new industry demands for researchers who can combine domain expertise with AI tooling—shifting emphasis from rote coding to using AI for higher‑value scientific problem‑solving.