No one feeds random LLM output straight back though. The whole idea of reinforcement learning is you take some ML model output, check if it is good, and push the model in that direction if it is good.
As long as you believe that e.g. it’s easier to verify a mathematical result than to come up with one, then RL should work.
Reinforcement learning makes the model better over time, so why should there be fewer and fewer good results?
If you’re talking about the rate of improvement going down, then yes, of course. That’s bound to happen (unless you have an actual intelligence explosion, but in that case you won’t know what “good results” even mean anyway).
No one feeds random LLM output straight back though. The whole idea of reinforcement learning is you take some ML model output, check if it is good, and push the model in that direction if it is good.
As long as you believe that e.g. it’s easier to verify a mathematical result than to come up with one, then RL should work.
It will still, over time, give fewer and fewer good results to be fed back into it.
Reinforcement learning makes the model better over time, so why should there be fewer and fewer good results?
If you’re talking about the rate of improvement going down, then yes, of course. That’s bound to happen (unless you have an actual intelligence explosion, but in that case you won’t know what “good results” even mean anyway).