‘To become a proficient table tennis player, humans require excellent hand-eye coordination, the ability to move rapidly and make quick decisions reacting to their opponent—all of which are significant challenges for robots. Google DeepMind’s researchers used a two-part approach to train the system to mimic these abilities: they used computer simulations to train the system to master its hitting skills; then fine tuned it using real-world data, which allows it to improve over time.’
https://www.technologyreview.com/2024/08/09/1096102/google-deepmind-trained-a-robot-to-beat-humans-at-table-tennis/
halalmoney /
npub1vd…97rjz
2024-08-15 14:54:09
Author Public Key
npub1vdaz78d96t7pjakpfmqqlr4wgq26l6vmkf25782n05qgdgtfmk8s297rjzPublished at
2024-08-15 14:54:09Event JSON
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"tags": [],
"content": "‘To become a proficient table tennis player, humans require excellent hand-eye coordination, the ability to move rapidly and make quick decisions reacting to their opponent—all of which are significant challenges for robots. Google DeepMind’s researchers used a two-part approach to train the system to mimic these abilities: they used computer simulations to train the system to master its hitting skills; then fine tuned it using real-world data, which allows it to improve over time.’\n\nhttps://www.technologyreview.com/2024/08/09/1096102/google-deepmind-trained-a-robot-to-beat-humans-at-table-tennis/",
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}