Except Lvxferre is actually correct; LLMs are not capable of determining what is useful or not useful, nor can they ever be as a fundamental part of their models; they are simply strings of weighted tokens/numbers. The LLM does not “know” anything, it is approximating text similar to what it was trained on.
It would be like training a parrot and then being upset that it doesn’t understand what the words mean.
The only way to ensure they produce only useful output is to screen their answers against a known-good database of information, at which point you don’t need the AI model anyways.
AndrasKrigare@beehaw.org 2 weeks ago
Where I don’t think your argument fits is that it could be applied to things LLMs can currently do. If I have an insufficiently trained model which produces a word salad to every prompt, one could say “that’s not a malfunction, it’s still applying weights.”
The malfunction is in having a system that produces useful results. An LLM is just the means for achieving that result, and you could argue it’s the wrong tool for the job and that’s fine. If I put gasoline in my diesel car and the engine dies, I can still say the car is malfunctioning. It’s my fault, and the engine wasn’t ever supposed to have gas in it, but the car is now “failing to function in a normal or satisfactory manner,” the definition of malfunction.
t3rmit3@beehaw.org 2 weeks ago
The purpose of an LLM, at a fundamental level, is to approximate text it was trained on. If it was trained on gibberish, outputting gibberish wouldn’t be a bug. If it wasn’t, outputting gibberish would be indicative of a bug.
A better analogy would be selling someone a diesel car, when they wanted an electric vehicle, and them being upset when it requires refueling with gas. The car is t malfunctioning in that case, the salesman was.
AndrasKrigare@beehaw.org 2 weeks ago
I’d argue that’s what an LLM is, not its purpose. Continuing the car analogy, that’s like saying a car’s purpose is to burn gasoline to spin its wheels. That’s what a car does, the purpose of my car is to get me from place to place. The purpose of my friend’s car is to look cool and go fast. The purpose of my uncle’s car is to carry lumber.
I think we more or less agree on the fundamentals and it’s just differences between whether they are referring to a malfunction in the system they are trying to create, in which an LLM is a key tool/component, or a malfunction in the LLM itself. At the end of the day, I think we can all agree that it did a thing they didn’t want it to do, and that an LLM by itself may not be the correct tool for the job.
t3rmit3@beehaw.org 2 weeks ago
No, that was the purpose for you, that made you choose to buy it. Someone else could have chosen to buy a car to live in it, for example. The purpose of a tool is just to be a tool. A hammer’s purpose isn’t just to hit nails with, it’s to be a heavy thing you can use as-needed. You could hit a person with it, or straighten out dents in a metal sheet, or destroy a harddrive. I think you’re conflating the intended use of something, with its purpose for existing, and it’s leading you to assert that the purpose of LLMs is one specific use only.
An LLM is never going to be a fact-retrieval engine, but it has plenty of legitimate uses: generating creative text is very useful. Just because OpenAI is selling their creative-text engine under false pretenses doesn’t invalidate the technology itself.