That was because the current trend in AI (deep learning) mainly just requires batched matrix computations, which makes an efficient implementation fairly langua

That was because the current trend in AI (deep learning) mainly just requires batched matrix computations, which makes an efficient implementation fairly language-agnostic (provided that only the internal kernels are written in high-performance C/C++ or CUDA). The same thing doesn’t hold for other computationally intensive tasks like ray tracing or physics simulation, where computation cannot be expressed in huge batched matrix operations but rather millions of highly variable small-sized computations. If mainstream AI moves beyond just deep learning and start to encompass other approaches and disciplines (for example, differentiable simulators/renderers), suddenly the language (and the compiler) will be much more important than before.