I literally sat at a table where the argument was made: The Intel accelerator is faster. It provides more FLOPs. But you can’t get actual users to use it outsid

I literally sat at a table where the argument was made: The Intel accelerator is faster. It provides more FLOPs. But you can’t get actual users to use it outside of our LINPack runs, since it just doesn’t provide bindings to all the software actually intended to run. Granted that was in the HPC space (ie FP64 performance), but that is literally the argument. That doesn’t mean, that ML people don’t care about some hardware specifics btw. Of course they do! Because CUDA is very, very good at exploiting the specific features of the newer cards (I’ve forgotten, what exactly this was though). But take away the simple integration into their favorite AI-SDK and it would be completely irrelevant. The point is just that, if Intel were to build strictly better hardware, but not provide the interface to torch, then they would still loose to Nvidia. Yes, yes, this is not completely true. Given enough advantage someone else would build the IntelCUDA. But this is literally the bet that those academics make. And it’s so risky, that only academics are doing that