Ha ha, as if.

Base models have a lot of capabilities - arranged in all the wrong ways for high performance reasoning and problem-solving. The power of fine tuning on "a couple thousand of input-output pairings" is that it can fix some of that. If your pairings are very well chosen, that is.

If that were the case, Anthropic wouldn't be throwing a fit over distillation "attacks".

Yes, neural networks are famously poor at generalising.