alt Hacker NewsAny sequence could be meaningful or meaningless depending on the grammar involved. Open a word document in photoshop and the program has no idea what it’s dealing with.
The reason the language term in LLM is meaningful is how the training, symbol mapping, etc is designed around human languages. The model doesn’t process raw text, instead there’s a critical processing step which allows the magic to happen.
Is the same processing step not happening here?
To my mind the argument against this model qualifying as a language model is that while the sequence of tokens may technically qualify as a sort of language it doesn't appear to be generalized by any reasonable interpretation. Further, the model doesn't appear to be able to handle unstructured inputs and outputs in the "language" - everything seems to be highly structured.
My line of reasoning could be approximately summarized as compiled binaries constituting a "real" (though not natural) language versus a sequential listing of chess positions that represent sequential game actions only being language "shaped".
Still, it's interesting to consider that if scaled up I expect the "repeat yourself" experiment would likely apply to the internal representation of the model in the same manner.