Zoom in a bit. Freeze Pyou to a single conversation. A single spoken sentence, then another. There isn't enough time for emotions or imagination to shift. It's you in a particular situation, with some thought to express, words flowing out of your mouth.
I don't know about you, but to me this moment feels exaxtly like being an LLM.
I keep arguing that LLMs aren't similar to humans in entirety, but rather just to the "inner voice" - the bit that feeds your consciousness strings of words, which you utter, or consider, or send back if they make no sense.
The problem here is that the actual Pyou isnt a distribution over all possible words.. that's just the observer's model of what's going on -- ie., your friend supposes that you could say anything.
Actually: (1) there's very very small number of possible words you are considering; (2) you arent considering 'words' at all, but future cognitive and sensory-motor states/vocalisation actions; (3) your vocalisation is moderated by a vast array of other causes/reasons (eg., being kind); etc.
The P(next word|previous, LLM-model, corpus...) for an LLM isnt an abstraction; it's actually implemented in its training.
The only sense in which, even in an instance, we seem to compute P(next|previous) is purely a radical abstraction which has nothing to do with any property we posess, but is an epistemic artefact from the outside.
Comments
Zoom in a bit. Freeze Pyou to a single conversation. A single spoken sentence, then another. There isn't enough time for emotions or imagination to shift. It's you in a particular situation, with some thought to express, words flowing out of your mouth.
I don't know about you, but to me this moment feels exaxtly like being an LLM.
I keep arguing that LLMs aren't similar to humans in entirety, but rather just to the "inner voice" - the bit that feeds your consciousness strings of words, which you utter, or consider, or send back if they make no sense.
The problem here is that the actual Pyou isnt a distribution over all possible words.. that's just the observer's model of what's going on -- ie., your friend supposes that you could say anything.
Actually: (1) there's very very small number of possible words you are considering; (2) you arent considering 'words' at all, but future cognitive and sensory-motor states/vocalisation actions; (3) your vocalisation is moderated by a vast array of other causes/reasons (eg., being kind); etc.
The P(next word|previous, LLM-model, corpus...) for an LLM isnt an abstraction; it's actually implemented in its training.
The only sense in which, even in an instance, we seem to compute P(next|previous) is purely a radical abstraction which has nothing to do with any property we posess, but is an epistemic artefact from the outside.