In terms of hardware , they absolutely could scale up higher in the same way Nvidia does: more chips with interconnect on a blade.
Given their power efficiency, they could just go wider and come out on top.
And in terms of software, metal compute is the only real competitor to CUDA backends. Between their PyTorch backends, MPX, and large memory, a lot of ML engineers are going with a combo of Macs locally and NVIDIA in the cloud these days.
Intel and AMD don’t factor in at all comparatively for ML use because Intel doesn’t have a GPU backend for most things people want, and AMD has repeatedly made a mess of rocm
Given their power efficiency, they could just go wider and come out on top.
And in terms of software, metal compute is the only real competitor to CUDA backends. Between their PyTorch backends, MPX, and large memory, a lot of ML engineers are going with a combo of Macs locally and NVIDIA in the cloud these days.
Intel and AMD don’t factor in at all comparatively for ML use because Intel doesn’t have a GPU backend for most things people want, and AMD has repeatedly made a mess of rocm