> AI is supposed have solved the

Which AI? LLMs are coding facilitators and code producers.

A problem is solved when the solution is reliable. Non-deterministic Neural Networks are not reliable. In fact,

> more mechanical[] task

that suggests an expectation of process and procedure, which is still not a capability of current architectures.

Sure, you can ask a brains-deficient operator to perform a huge task, but then you'll have to check the whole product, and that remains not cheap.

The tool itself (AI) may not be reliable, but that is also very true for every other tool (e.g. Human). Also, you are right about when a problem is solved, but this doesn't need the tool to be reliable as you said, just the solution part. Hence, as long as the produced code works as intended, it doesn't matter what you used to produce the output.

> but this doesn't need the tool to be reliable as you said, just the solution part

And where are the warranties that the solution built be reliable (and optimal, etc.)?.

Saw this on the web:

"AMD and Anthropic also formed a multiyear engineering partnership to optimize ROCm using Claude"

FROM: https://finance.yahoo.com/markets/stocks/articles/ex-amd-exe...

No, because the two platforms often don't share the same underlying kernels; this has been one of the main issues and complaints with ROCm/MIOpen since the start, although they are catching up slowly.

This is actually a corollary to the point I was making about "CUDA" usually also including a ton of the included kernels and not just referring to a crappy programming environment; translating mid-level C that does math between two runtimes wouldn't be hard for an LLM, but translating "doBigDNNThingNVidiaGaveMeInAKernel()" to "doBigDNNThingByHandBecauseAMDDoesntSupportIt()" isn't a rote translation at all.

Of course, once you accept that it's _not_ "why don't you just translate it," you _can_ iteratively use an LLM to implement the ThingNVidiaGaveYouInAKernel, but it probably isn't well-trained, yet, on low-level AMD optimization tricks, so the kernel you end up with will likely be slower than the CUDA one.

> translating "doBigDNNThingNVidiaGaveMeInAKernel()" to "doBigDNNThingByHandBecauseAMDDoesntSupportIt()" isn't a rote translation at all.

I wonder if this points to a deeper limitation of AI, it can not do coding tasks it has not seen in its training material. Or could it possibly "generalize" to accompllish something like this anyway?

Undoubtedly, the frontier labs are already doing something akin to this as part of their new chip design endeavors.