Earlier quoted context omitted.
Analogies are just that, they are meant to put things in perspective. Obviously the LLM doesn't have "senses" in the human way, and it doesn't "see" words, but the point is that the LLM perceives (or whatever other word you want to use here that is less anthropomorphic) the word as a single indivisible thing (a token). In more machine learning terms, it isn't trained to autocomplete answers based on individual letter…
> Obviously the LLM doesn't have "senses" in the human way, and it doesn't "see" words > A different analogy could be, imagine a being that had a sense that you "see" magnetic lines, and they showed you an object and asked you If my grandmother had wheels she would have been a bicycle. At some point to hold the analogy, your mind must perform so many contortions that it defeats the purpose of the analogy itself.
That's irrelevant here, that was someone trying to convert one dish into another dish.
> your mind must perform so many contortions that it defeats the purpose
I disagree, what contortions? The only argument you've provided is that "LLMs don't have senses". Well yes, that's the whole point of an analogy. I still hold that the way LLMs interpret tokens is analogous to a "sense".