Except I actually mean to infer the concept of adding things from examples. LLMs are amply capable of applying concepts to data that matches patterns not ever expressed in the training data. It’s called inference for a reason.
Anthropomorphic descriptions are the most expressive because of the fact that LLMs based on human cultural output mimic human behaviours, intrinsically. Other terminology is not nearly as expressive when describing LLM output.
Pattern matching is the same as saying text prediction. While being technically truthy, it fails to convey the external effect. Anthropomorphic terms, while being less truthy overall, do manage to effectively convey the external effect. It does unfortunately imply an internal cause that does not follow, but the externalities are what matter in most non-philosophical contexts.
>do manage to effectively convey the external effect
But the problem is that this does not inform about the failure mode. So if I am understanding correctly, you are saying that the behavior of LLM, when it works, is like it has internalized the concepts.
But then it does not inform that it can also say stuff that completely contradicts what it said before, there by also contradicting the notion of having "internalized" the concept.
So that will turn out to be a lie.
If you look at the failure modes, they very closely resemble the failure modes of humans in equivalent situations. I'd say that, in practice, anthropomorphic view is actually the most informative we have about failure modes.
>they very closely resemble the failure modes of humans in equivalent situations
I don't think they do if we are talking about a honest human being.
LLMs will happily hallucinate and even provide "sources" for their wrong responses. That single thing should contradict what you are saying.