I am already acquainted with them but to be honest, I am no longer in the field so I am not able to comment on latest developments. However, as of two years ago, the consistent result was that you could get models that reproduce really good physics for problems in the same physical regimes as the training data, but such models had poor generalizability, so depending on the use case, they weren't of much use. The only exception I know is FourCastNet, which is a weather model FNO from NVIDIA.