This looks very singularity-ish to me; LLMs can construct a reward function that can be trained in simulation, and the trained reward function works surprisingl

This looks very singularity-ish to me; LLMs can construct a reward function that can be trained in simulation, and the trained reward function works surprisingly well in the physical world. Some of the videos raised questions in my mind as to whether or not the leash was doing stabilization work on the robot; it might be. But, if you watch the video where they deflate a yoga ball, you can see the difference when they're "saving" the robot and when they're just keeping it taut. The 'dextrous cube' manipulation video is also pretty compelling. This sort of 'automate a grad student' type work, in this case, coming up with a reasonable reward function, all stacks up over time. And, I'd bet a lot of people's priors would be "this probably won't work," so it's good to see it can work in some circumstances -- will save time and effort down the road.