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> Of course, the LLM is just regurgitating the facts from the textbooks as well as thousands or millions of test samples.

Sure, it is regurgitating facts. What's impressive is that it knows which facts to regurgitate.

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It also makes me question how different this is from what we (humans) do. We learn a bunch of information from a variety of sources and experiences and synthesize that into answers. Sometimes we are correct and sometimes we are not. I suppose the difference is that we can extrapolate from our synthesized information vs simply formulating answers, but what the best LLMs do doesn't seem radically different than the average person.

The difference is that we are reading and comprehending information, while the model is making a prediction of what word is most likely to come next based on a huge dataset of words. As such, there have been many documented cases of the model seeming correct at first glance, maybe even second glance, but its actually totally wrong in a way that a human isn't totally wrong. Like chatgpt will give you a summary and a title and an author and a year and be entirely confident that this is the truth, whereas the title was written by a different author in a related field perhaps or was made up entirely. A human would not behave like this at all. If I asked you for some info you hardly knew, you wouldn't word vomit a paragraph like this, you'd reply with a confidence score, "I don't know," or "I know about this but not that," perhaps. Seems that if there is any money or time on the line, you'd rather use the human.

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