alt Hacker News> my infographic would be an original work.
> AI training follows the same principle.
If you really believe that then we can't have a meaningful conversation about this, that's not even ELIF territory, that's just disconnected. You should be asking questions, not telling people how it works.
How exactly is it different? All the model itself is is a probability distribution for next token given input, fitted to a giant corpus. i.e. a description of statistical properties. On its own it doesn't even "do" anything, but even if you wrap that in a text generator and feed it literal gcc source code fragments as input context, it will quickly diverge. Because it's not a copy of gcc. It doesn't contain a copy of gcc. It's a description of what language is common in code in general.
In fact we could make this concrete: use the model as the prediction stage in a compressor, and compress gcc with it. The residual is the extent to which it doesn't contain gcc.