Comment by atleastoptimal
3 years ago
There's got to be predictable ways of improving LLMs besides training data scale and parameter count. Arent LLMs robust enough to learn on their own via interacting with the world? Like put them in a turn based simulated environment.
I wonder if there's an assumption for how big an LLM should be before it could even conceivably be an LLM. Is there a minimum size necessary before that capability is plausible?
>Arent LLMs robust enough to learn on their own via interacting with the world?
As far as I know current LLMs are entirely static once trained, they don't learn at all in runtime.
Without RLHF, even a high parameter model performs very poorly. LLama-65B often hallucinated when I gave it the most basic of prompts.