I keep hearing "the model is learning the physics" from machine learning people talking about AI weather models. What they usually mean is a specific kind of model: the generative, transformer-based emulators trained end-to-end on reanalysis data, no dynamical core, no equations, just a network fit to the data. GraphCast, Pangu, GenCast, and the generative-data-assimilation models coming out of places like NVIDIA (Manshausen et al.'s model is one example, not the point) all fall in that bucket. That's the question I actually want to answer for myself, and it's narrower than "do AI weather models learn physics" as a blanket...