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Today's Large Language Models are Essentially BS Machines
(quandyfactory.com)
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this post was submitted on 12 Sep 2023
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Technology
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The two types of loops you equivocate are totally different; saying that a computer executing a program, and an animal living, are actually the same, is very silly indeed. Like, air currents have a "core loop" of blowing around a lot but no one says that they're intelligent or that they're like computer programs or humans.
No; you are analogizing them but losing sense of their differences in the process. I am not abstracting LLMs. That is all they do. That is what they were designed to do and what they accomplish.
You are drawing a comparison between a process humans have that generates consciousness, and literally the entirety of an LLM's existence. There is nothing else to an LLM. Whereas if you say "well a human is basically just bouncing electro-chemical signals between neurons and moving muscles" people (like me) would rightly say you were missing the forest for the trees.
The "trees" for an LLM are their neural networks and word vectors. The forest is a word prediction algorithm. There is no higher level to what they do.
At what level do LLMs teach? Something was teaching me linear algebra and I thought it was the GPT4. When GPT4 was able to recognize a valid mathematical proof that was previously unknown to it, what level was it operating at?
LLMs do not "teach," and that is why learning from them is dangerous. They synthesize words and return other words, but they do not understand the content presented to them in any sense. Because of this, there is the chance that they are simply spouting bullshit.
Learn from them if you like, but remember they are absolutely no substitute for a human, and basically everything they tell you must be checked for correctness.
GPT4 did teach me. I say this as the one who learned, whatever that's worth.