[ehsankia]

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 letters in the prompt. What we see as the 9 letters "blueberry", it "sees" as an vector of weights.

> Illusions don't fool our intelligence, they fool our senses

That's exactly why this is a good analogy here. The blueberry question isn't fooling the LLMs intelligence either, it's fooling its ability to know what that "token" (vector of weights) is made out of.

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 where the north pole was. You, not having this "sense", could try to guess based on past knowledge of said object, but it would just be a guess. You can't "see" those magnetic lines the way that being can.

[anon_e-moose]

> 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.

[ehsankia]

> If my grandmother had wheels she would have been a bicycle.

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".

[kaoD]

> the LLM perceives [...] the word as a single indivisible thing (a token).

Two actually, "blue" and "berry". https://platform.openai.com/tokenizer

"b l u e b e r r y" is 9 tokens though, and it still failed miserably.