Those 3 also have a lot of training data as well. Hoping Lean gets more support as it is very friendly.

As a basic learning resource focused on software engineering, there's [1]. But nothing more advanced I am aware of.

[1] The Hitchhiker's Guide to Logical Verification. https://cs.brown.edu/courses/cs1951x/static_files/main.pdf

I read that to say the model's token weights are adjusted as it goes, so in an LLM sense it is kind of learning. It isn't reasoning through an answer in the way a human does though. Meaning, the model is still just statistically predicting what an answer may be and checking if it worked.

I wouldn't chalk that up to learning at all. An AI solving complex math doesn't even seem too impressive to me with the predictive loop approach. Computers are well adept at math, throwing enough compute hardware at it to brute force an answer isn't suprising. I'd be really impressed if it could reliably get there with a similar number of failed attempts as a human, that could indicate that it really learned and reasoned rather than rammed through a mountain of failed guesses.

I do think this language is considerably more robust than the typical programming language, which means a sound program is more likely to end up being valid/“correct”. But still, that’s a difference of degree, not kind, IMO