Google’s New AI Learns Table Tennis! 🏓
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Google’s New AI Learns Table Tennis! 🏓

Two Minute Papers 08.11.2022 81 236 просмотров 2 780 лайков

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Segment 1 (00:00 - 05:00)

dear fellow Scholars this is two minute papers with Dr Carol jonai fahir do you see this new table tennis robot it barely played any games in the real world yet it can return the ball more than a hundred times without failing wow so how is this even possible well this is a seem to real paper which means that first the robot starts learning in the simulation openai did this earlier by teaching the robot hand in a simulated environment to manipulate this Ruby Cube and Tesla also trains its cars in a computer simulation why well in the real world some things are possible but in a simulated World anything is possible yes even this and the self-driving car can safely train in this environment and when it is ready it can be safely brought into the real world how cool is that now how do we apply this concept to Table Tennis well in this case the robot would not move but it would play a computer game in its head if you will but not so fast that is impossible what are we simulating exactly the machine doesn't even know how humans play there is no one to play against now check this out to solve this first the robot asks for some human data look it won't do anything it just observes how we play and it only requires these short sequences and then it builds a model of how we play and embeds us into a computer simulation where it plays against us over and over again without any real physical movement it is training the brain if you will and now comes the key step this knowledge from the computer simulation is now transferred to the real robot and now let's see if this computer game knowledge really translates to the real world so can it return this ball it can well kind of one more time okay better and now well it missed again I see some signs of learning here but this is not great so is that it so much for learning in a simulation and bringing this knowledge into the real world right well do not despair because there is still hope what can we do well now it knows how it failed and how it interacted with the human yes that is great why because it can feed this new knowledge back into the simulation can now be fired up once again and with all this knowledge it can repeat until the simulation starts looking very similar to the real world that is where the real fun begins why well check this out this is the previous version of this technique and as you see this does not play well so how about the new method now hold on to your papers and Marvel at this rally 82 hits and not one mistake this is so much better wow this seem to real concept really works and wait a minute we are experienced fellow Scholars here so we have a question if the training set was built from data when it played against this human being does it really know how to play against only this person or did it obtain more general knowledge and can it play with others well let's have a look the robot hasn't played this person before and let's see how the previous technique fares well that was not a long rally and neither is this one and now let's see the new method oh my this is so much better it learns much more general information from the very limited human data it was given so it can play really well with all kinds of players of different skill levels here you see a selection of them and all this from learning in a computer game with just a tiny bit of human behavioral data and it can even perform a rally of over a hundred hits what a time to be alive so does this get your mind going what would you use this seem to real concept for let me know in the comments below if you are looking for inexpensive Cloud gpus for AI Lambda now offers the best prices in the world for GPU Cloud

Segment 2 (05:00 - 05:00)

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