Part of it is that training the superhuman Go player is more parallelizable. The challenge is entirely virtual, and you can have unlimited synthetic training da

Part of it is that training the superhuman Go player is more parallelizable. The challenge is entirely virtual, and you can have unlimited synthetic training data by having Go-playing algorithms play each other. I've never worked with machine learning in robotics, but my understanding is that physics simulators are still insufficient environments for training state-of-the-art robotic agents. Especially when using reinforcement learning or a similar algorithm, many models are trained with several real robots picking up real objects.