> "The growing body of Big-data, HPC, and especially machine learning applications don’t need Windows and don’t perform on X86. So 2017 is the year Nvidia slips its leash and breaks free to become a genuinely viable competitive alternative to x86 based enterprise computing in valuable new markets that are unsuited to x86 based solutions."

Google's TPU paper [0] showed the CPUs were relatively competitive in the machine learning space (within 2x of a K80). It's not true that x86 doesn't perform on these workloads.

The existence of the TPU itself threatens Nvidia's dominance in the ML processor space. Google built an ASIC in a short time period that more than rivals a GPU on these tasks. The TPU performance improvements (section 7) make it look very straightforward to get even better performance with a few more years of development effort. With developers moving to higher level libraries, migration between GPU/CPU/TPU becomes painless, so they'll just go with whatever has the lowest TCO. (Google hosted TPUs?)

Aside from machine learning tasks, the author seems to be advocating for the cpu/gpu combinations that AMD is already selling to game console manufacturers. Granted, Nvidia has a piece of this via the Switch. If Microsoft/Qualcomm goes full-on with their ARM-based x86 emulation, then perhaps a future ARM-based Xbox is in the cards driven by an Nvidia chip? /speculation

[0] https://arxiv.org/abs/1704.04760