The speaker compares current model training to open-loop control, in which data is supplied and the model is driven by it toward a very underspecified target.

“Perhaps that is an analogy that I'm like using quite a lot. You know, current training is much closer to our open loop control, where,”

“you know, you, you go towards the”

“you sort of put the data in and the model just goes wherever the data takes it um i realize that rl doesn't totally fit this analogy but it goes towards this like very underspecified point um but interpretability is sort of the thing that lets us go to a closed loop control because we can say like oh we're going to go in this direction you know yeah”