I tried creating an emulator for CPU that is very well known but lacks working open source emulators.
Claude, Codex and Gemini were very good at starting something that looked great but all failed to reach a working product. They all ended up in a loop where fixing one issues caused something else to break and could never get out of it.
Better still invent a CPU instruction set, and get it to write an emulator for that instruction set in C.
Then invent a C-like HLL and get it to write a compiler from your HLL to your instruction set.
I tried asking Gemini and ChatGPT, "What opcode has the value 0x3c on the Intel 8048?"
They were both wrong. The datasheet with the correct encodings is easily found online. And there are several correct open source emulators, eg MAME.
An LLM by itself is like a lossy image of all text in the internet.
"This is, I think, in contradiction with the idea that LLMs are memorizing the whole training set and uncompress what they have seen. LLMs can memorize certain over-represented documents and code, but while they can extract such verbatim parts of the code if prompted to do so, they don’t have a copy of everything they saw during the training set, nor they spontaneously emit copies of already seen code, in their normal operation."
Can't things basically get baked into the weights when trained on enough iterations, and isn't this the basis for a lot of plagiarism issues we saw with regards to code and literature? It seems like this is maybe downplaying the unattributed use of open source code when training these models.
Probably bonus points for telling it that you're emulating the well known ZX Spectrum and then describe something entire different and see whether it just treats that name as an arbitrary label, or whether it significantly influences its code generation.
But you're right of course, instruction decoding is a relatively small portion of a CPU that the differences would be quite limited if all the other details remained the same. That's why a completely hypothetical system is better.