The starting states being at different points in the task and having success-guided starting state sampling seem like really neat ideas. I haven't kept up with RL in a while, how novel is this?
I’m highly entertained by the way the robot tightens nuts. There is no way this would work in the real world :)
(This whole thing is awesome. I think they will need to get the number of rollouts needed down before it translates well to real robots — running hundreds of thousands of rollouts on small parts with a real rollout will be a real logistical mess when cleaning up parts on the floor and dealing with everything that the robots physically break while learning.)
It is not an Alphabet/Deepmind paper, and it also has nothing to do with the "NIST" OCR dataset.
Was there really not a more appropriate name than "AlphaNIST"?
Alpha historically had meant "Google DeepMind" not RL
(This whole thing is awesome. I think they will need to get the number of rollouts needed down before it translates well to real robots — running hundreds of thousands of rollouts on small parts with a real rollout will be a real logistical mess when cleaning up parts on the floor and dealing with everything that the robots physically break while learning.)
Alphanist - Some app/lib/code that does something
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