[shoyer]

The short answer is that tracing is way, way easier to implement in a predictable and reliably performant way. This especially matters for distributed computation and automatic differentiation, two areas where JAX shines.

AST parsing via reflection means your ML compiler needs to re-implement all of Python, which is not a small language. This is a lot of work and hard to do well with abstractions that are not designed for those use-cases. (I believe Julia's whole language auto-diff systems struggle for essential the same reason.)