RLHF

“Which is that why can't it be another LLM or a pipeline of LLMs that can help with that feedback? I think manual labeling is very tedious, especially for our target user, which is a software engineer. And I don't think people should necessarily have to do all …”

“And it's that RL loop that is very interesting because since it's programmatic, since we have an Oracle of truth, we can scale this up far larger, right? Magnitudes larger than what you can do with human feedback today.”

“These reward models tend to have a lot of problems and you can over optimize them much more easily because the reward models will pick up on features that are maybe emojis or something like this that you don't actually care about where RLVR is much better matc…”

“So it was a bit of a brittle technique, but it was a bit of RL that was extremely crucial to making the models chat.”

“What we know though, is we moved from this pure, like human data, you know, that was first just pre-training on human data and then also aligning with like human preferences that was called RLHF, where we had a lot of human in the loop and human data. To like …”