Information on how large language models are trained is not hard to come by, there are numerous articles that cover this material. Even a brief skimming of this material will make it clear that the training of large language models is materially different in almost every way from how human beings "learn" and build knowledge. There are still many open questions around the process of how humans collect, store, retrieve and synthesize information.

There is little mystery to how large language models function and it's clear that their output is parroting back portions of their training data, the quality of output degrades greatly when novel input is provided. Is your argument that people fundamentally function in the same way? That would be a bold and novel assertion!

i do listen to music.

i listen to it on apple music.

i pay money to apple for this.

some of that money that i pay to apple goes to the rights holders of that music for the copying and performance of their work through my speakers.

that’s a pretty big difference to how most LLMs are trained right there! i actually pay original creators some money.

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i am a human being. you cannot reduce me down to some easy information theory.

an LLM is a tool. an algorithm. with the same random seed etc etc it will get the same results. it is not human.

you put me in the same room as yesterday i’ll behave completely differently.

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i have listened to way more than terabytes of music in my life. doesn’t mean i have the ability to regurgitate any of it verbatim though. i’m crap at that stuff.

LLMs seem to be really good at it though.