here is a real video of a unitree robot playing ping pong https://www.youtube.com/watch?v=tOfPKW6D3gE

how do you know this is a better model? I wouldn't take any of the numbers at face value especially when all they have done is more/better post-training and thus the base pre-trained model capabilities is still the same. The model may just elicit some of the benchmark capabilities better. You really need to spend time using the model to come to any reliable conclusions.

This is probably very similar to what happened!

the problem here is that text as the communication interface is not good for this. the model should be reasoning in the pose space (and generally in more geometric spaces), then interpolation and drawing is pretty easy. I think this will happen in some time.

How are you defining dextrous? I think it can be somewhat challenging but not dextrous -- the robot doesn't need to be very precise (few cms here and there do not matter), there are no forces involved, motions are all pick-place. Dextrous tasks would be things like shoe-lace tying, origami folding etc.