RL is unbelievably finicky, sensitive to hyperparameters, and hard to make work. If you are pursuing a research project and decide to use RL, you are making your life a lot more difficult and stressful.

It's exciting to see any progress in making accurate predictions about what settings will work for RL training. I hope that this research direction can be expanded in scope and that ultimately, people who want to do research in RL can become confident in their training recipes.

I am more excited about that, than about the dream of scaling compute per se.