but that’s kind of my point: I don’t think we *have* (or have ever had) ‘definitions of learning’ by which NNs ‘don’t learn’, precisely because “learn” is a the (crude) description of a behaviour, not something defined in mechanistic terms…
I’ve never understood NNs as attempting to provide a ‘definition of learning’ itself, though they provide a mechanism, which might or might not have relevant similarities to human learning depending on level of description or detail one is interested in….
“adjusting weights via backprop” is a mechanism, not a system level behaviour and my original reply was that the statment “LLMs don’t “think” they just compute probability distributions” confuses behaviours and behaviour generating mechanisms…
to my mind, that’s not a ‘semantic debate’ or argument about meaning but about a deeper conceptual confusion that seems common in those kinds of articles…
whether pointing *that* out is interesting or enlightening is, of course, a different matter ;-)
