We examine the historical development and underlying principles of foundation models realized in language and vision, and propose how physics-infused machine learning interaction potentials could dramatically transform at scale to create transformative foundation models for chemistry and materials science.
- Eric C.-Y. Yuan
- Yunsheng Liu
- Teresa Head-Gordon
