The speaker says pre-training is relatively mature, whereas reinforcement learning has substantial room for improvement and may offer roughly 30-fold efficiency gains depending on the model’s ability to improve itself.

“with less compute and so when you say 7x it's actually a very concrete thing that you're studying and now I would say across the systems of you know I mean pre-training is probably a bit more hardened but there's a lot of a lot of headroom in reinforcement learning we're probably at a point where”

“it's you know 30x like efficiency depending how good your model is for actually improving itself so that is one thing that's happening”