AI is supposed have solved the "coding problem". But shouldn't translating a program from one platform to another be an even easier, more mechanical, task for the AI?
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.
And where are the warranties that the solution built be reliable (and optimal, etc.)?.
"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...
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.
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?