I'm not sure how close you are to working with RL/ML, possibly more than me! However, I don't think you it is useful to talk about the state of the field so bro

I'm not sure how close you are to working with RL/ML, possibly more than me! However, I don't think you it is useful to talk about the state of the field so broadly. If you say "supervised learning is well understood", I think you have a better chance of being right. The challenges that arise in taking sequential decisions, and learning from sequential observations is a lot harder, because all your data is temporally correlated. Yeah we have algorithms for RL, but actually there are still many theoretical things we cannot prove and in practice do not work well. I am not intimately familiar, but one example is value iteration with a non-linear value function approximation. I still maintain that RL is not well-understood, and I think evidence for that is that we don't see many examples of RL in our phones, cameras, search engines, etc. (which is not the case for supervised learning).