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Message: <blockquote data-quote="FrogReaver" data-source="post: 9078724" data-attributes="member: 6795602">Okay.  I watched the video.I think there's a bit of nuance.  A language model is just a probability distribution over sequences of words.  For a LLM a human never went in and assigned any weights to that probability distribution, instead we programed an algorithm to do that based on the large dataset we fed it.  So in that sense it wasn't created by a human.  But the same could really be said about anything produced by any computer algorithm.  So in what I would consider the more broad sense, it's meant to sound like a grand claim and be technically true, but it's a fairly typical claim when dealing with any computer generated outputs. Not quite accurate.  A language model is just a probability distribution over sequences of words.  The task a language model is used to solve is predicting the next word/words.Sure.  But while we don't know the precise innerworkings, with some knowledge of computer science and a basic understanding of LLM's we can certainly make educated guesses.High level we 'know' the logic they use - a probability distribution of words is created by an algorithm reading from a large data set.  The specifics of that algorithm is a mystery, but not because of emergent properties, it's simply because it's not public information.Then once we have the model, the next process step is how the response algorithm is programmed to respond to prompts based on that probability distribution.  Again, a black box there because we aren't privy to the precise algorithm being used.IMO there's alot of demystification that needs to happen about LLM based AI's.</blockquote>

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