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Comment by sbierwagen | Hacker News Reader

If Intel was very bullish on AI, they might be tempted to design arbitrarily complicated architectures and just trust that GPT-6 will be able to write code for it.

This was a bet that completely failed for Itanium, but maybe this time...

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Is GPT-6 the proverbial magic wand that makes all your dreams come true? Because you just hand waved away all the complexity just by name dropping it. Let's get back to Earth for one second...

I think the hand-waving was the point. It was a dig at Intel, accusing them of not having a solid plan.

How could GPT-(arbitrarily large number) learn to write code for an architecture for which there is no training data?

By grokking multi threaded programming of course.

From reading the documentation in the context.

There's an obscene amount of chess literature, yet ChatGPT is mediocre and makes elementary mistakes (invalid moves).

This would work only if ChatGPT 6 is AGI, but then it doesn't make much sense to label it as ChatGPT.

If an AGI is a GPT and you can chat with it why wouldn't you call it ChatGPT?

Yeah, but that's a big IF.

If the actual requirement for this is AGI, then it's clearer to just say AGI instead of ChatGPT which might or might not ever become AGI.

Well... This is a research project, and they aren't betting the farm on it. It's not even x86-compatible.

And then, it'd require a lot of software rewriting, because we are not used to write for hundreds of threads for context switching is a very expensive operation on modern CPUs. On this CPU a context switch is fast and happens on any operation that makes the CPU wait for memory access, therefore, thinking in terms of hundreds of threads pays off. But, again, this will need some clever OS designs to hide everything under an API existing programs can recognize.

It may even be that nothing comes out of it except another lesson on how not to build a computer.

Why do we need x86 compatibility? x86 chips are already fast.

Existing programs don't need to see these things at all, they can just act like microservices, and we could load them with an image and call them as black boxes.

I would think a lot more work would be done by various accelerator cards by now.

They probably aren't insanely bullish. GPT is a revolution but it's a revolution because it can do "easy" general tasks for the first time, which makes it the first actually useful general purpose AI.

But it still can't really design things. It's probably about as far away from being able to design a complex CPU architecture as GPT-4 is from Eliza.

Nvidia released a toolkit to assist chip design a few months ago:

https://techmonitor.ai/technology/ai-and-automation/nvidia-a...

Google has been working on AI's to optimize code:

https://blog.research.google/2022/07/mlgo-machine-learning-f...

> But it still can't really design things.

What do you really mean by "really" in that sentence?

In any case, the claim you responeded to was not that the chips would be designed from the ground up by AI, only that AI will enable us to run code on top of chips that are even more complex than current chips.

The Nvidia toolkit you linked is for place & route, which is a much easier task than designing the actual architecture and microarchitecture. It's similar to laying out a PCB.

The Google research you linked is using AI to make better decisions about when to apply optimisations. For example when do you inline a function? Which register do you spill? Again this is a very simple (conceptually) low level task. Nothing like writing a compiler for example.

> What do you really mean by "really" in that sentence?

I mean successfully create complex new designs from scratch.

I really wouldn't say it's an easier task at all. It's so intense it's essentially impossible for a human to do from scratch. But it is "just" an optimization problem which is different from designing an architecture.

I doubt Intel leadership is that naive.

And a bet they didn't even know they made for iAPX 432. The ADA compiler was awful optimization-wise, but that came out in an external research paper too late to save it.

So the mill is going to be released then, right? Right?

Not too psyched to use some proprietary black box compilerthough.

They have been so careful not to leak anything that there is very little interest on it. I completely forgot about them and, if they never launch, I doubt anyone would notice.

Why not just have GPT-6 design the chip to start with?

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