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Comment by munksbeer | Hacker News Reader

I can see close to zero possibility that the majority of the work will be shifted to the CPU. Anything a CPU can do can just be done better with specialised GPU hardware.

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Then why do we have powerful CPUs instead of a bunch of specialized hardware? It's because the value of a CPU is in its versatility and ubiquity. If a CPU can do a thing good enough, then most programs/computers will do that thing on a CPU instead of having the increased complexity and cost of a GPU, even if a GPU would do it better.

We have both? Modern computing devices like smart phones use SoCs with integrated GPUs. GPUs aren't really specialized hardware, either, they are general purpose hardware useful in many scenarios (built for graphics originally but clearly useful in other domains including AI).

People have been saying the exact same thing about other workloads for years, and always been wrong. Mostly claiming custom chips or FPGAs will beat out general purpose CPUs.

> Anything a CPU can do can just be done better

Nope. Anything inheriantly serial is better off on the CPU due to caching and it's architecture.

Many things that are highly parallizable are getting GPU enabled. Games and ML are GPU by default, but many things are migrating to CUDA.

You need both for cheap, high performance computing. They are different workloads.

The graphics in games are GPU by default. But the game logic itself is seldom run on the CPU as far as I can tell.

Yes, I was too hasty in my response. I should have been more specific that I mean ML/AI type tasks. I see no way that we end up on general purpose CPUs for this.

In terms of inference (and training) of AI models, sure, most things that a CPU core can do would be done cheaper per unit of performance on either typical GPU or NPU cores.

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