this post was submitted on 28 Jun 2024
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If you fine tune a LLM on math equations, odds are it won't actually learn how to reliably solve novel problems. Just the same as it won't become a subject matter expert on any topic, but it's a lot harder to write simple math that "looks, but is not, correct" than it is to waffle vaguely about a topic. The idea of a LLM creating a robust model of the semantics of the text it's trained on is, at face value, plausible; it just doesn't seem to actually happen in practice.
Prompt:
ChatGPT:
It's trained to generate what is most plausible, but with math, the only plausible response is the correct answer (assuming it has been trained on data where that has been the case)
ChatGPT uses auxiliary models to perform certain tasks like basic math and programming. Your explanation about plausibility is simply wrong.
It has access to a python interpreter and can use that to do math, but it shows you that this is happening, and it did not when i asked it.
I asked it to do another operation, this time specifying i wanted it to use an external tool, and it did
You have access to a dictionary, that doesn't prove you're incapable of spelling simple words on your own, like goddamn people what's with the hate boners for ai around here
That's not what I meant.
??? You just don't understand the difference between a LLM and a chat application using many different tools.