Why machines don't speak biology: Toward native biological language models.

Recent advances in AI inspire visions of universal models of biology. Yet living systems are evolved, emergent processes whose behaviors cannot be inferred from their parts alone. We propose grounding AI in canonical biological processes, constructing data-driven world models with explicit mechanistic links across molecules, cells, and their dynamics in space and time.
Recent advances in AI inspire visions of universal models of biology. Yet living systems are evolved, emergent processes whose behaviors cannot be inferred from their parts alone. We propose grounding AI in canonical biological processes, constructing data-driven world models with explicit mechanistic links across molecules, cells, and their dynamics in space and time.




