It is both. I do not understand why you would assert that both cannot hold simultaneously. Pattern recognition becomes "understanding" once individually recognized concepts become sufficiently sparsified and compactified. Or, at least, that is to my knowledge the only mathematically valid definition of "understanding" one can produce at this scale (it is valid under Solomonoff induction). Philosophy is fine, but we need to have a consistent definition of what "understanding" means, or we will just talk past each other. I argue that for any proper definition you provide which humans satisfy, a strong LLM is very likely to satisfy that as well.
I also would not argue that humans are "simple token generators". That is not what I said. I said that just about everything can fall under the classification of "statistical token generators" at an abstract level, so it isn't a useful distinction. We are not talking about a Markov chain generator from the 90s, so if that is the frame of reference, I think we should all get that out of our heads.
I also would not argue that humans are "simple token generators". That is not what I said. I said that just about everything can fall under the classification of "statistical token generators" at an abstract level, so it isn't a useful distinction. We are not talking about a Markov chain generator from the 90s, so if that is the frame of reference, I think we should all get that out of our heads.