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LLMs have always been next token predictors and generators. What it will produce next will depend on its dataset. Feed it outdated answers from StackOverflow an
by moezd 4mo ago
LLMs have always been next token predictors and generators. What it will produce next will depend on its dataset. Feed it outdated answers from StackOverflow and you will get that. Feed it bootcamp material, and you will get that. Feed it a hodgepodge of disorganized corporate data, and you, will, get that. I don't know how to make it sound easier than this.
- smokel 4mo agoWhat would happen if you also feed it a book or two on logic, and some books on mathematics and physics?
- ofjcihen 4mo agoCurrent LLMs have mainlined 1000s of books on those and every other subject and the answer is what the parent details: it’ll predict tokens based on the text.
- halJordan 4mo agoThe point is that the next token predicted will change; and in a way everyone not being a anti-ai contrarian will say is smarter. And as far as TFA, we've know you can prompt models into being smarter for years know. Thats what CoT/thinking/reasoning is.
- lostmsu 4mo agoFirst half is right, but the second... That's not how CoT works.
- smokel 4mo agoI don't think that is what the parent said, but I'm afraid my comment was too snarky (apologies), and the audience in this thread is not eager to be changed in their beliefs. Thanks for taking the time to reply though. LLMs are fed a lot of data, and there are many patterns in there, including reasoning and some logic. Adding a little domain specific data will not immediately learn that domain, but it will also not be limited to only that data in its reasoning.
- CamperBob2 4mo agoAnd that's all we do, and it's all we need, and it's probably all there is. The discovery that reinforcement learning allows next-token prediction to extrapolate beyond its pretrained data set is harder to explain than the discovery of fire or the wheel or electricity, but it's up there on that level.