I think https://www.alexirpan.com/2019/10/29/openai-rubiks.html is a pretty good take. tldr: unfortunately, even tiny discrepancies between the simulation and reality (like the size of the cube's bezels or a few extra parts in the robotic hand) can significantly degrade your model's performance in the real world, even with tons of domain randomization during training. So, either we need to improve our simulations to randomize a lot more details, or we need to improve our neural nets to generalize more effectively.