Nvidia invested in CUDA for decades! Following research papers in computer graphics or physics for example, you'd find a transition from Fortran to CUDA over ma

Nvidia invested in CUDA for decades! Following research papers in computer graphics or physics for example, you'd find a transition from Fortran to CUDA over many years. That helped quite a lot when ML came back and CUDA made it easy. They ported many basics like FFT, BLAS, etc. to CUDA so the building blocks were there already when AI grew too. Of course, it helped that many Python ML library backends also supported GPU via CUDA. If you look at the same landscape from AMD's side, it's lackluster to say the least. And they're only now trying to catch up... And they have to make it CUDA compatible! Nvidia won on the tools side, the GPUs aren't necessarily faster, but the only way to use them easily is CUDA.