OpenAI's Dactyl Improves Dexterity of Robotic Hands Without Human Input

OpenAI has trained a human-like robot hand to manipulate physical objects with unprecedented dexterity.Their system, called Dactyl, is trained entirely in simulation and transfers its knowledge to reality, adapting to real-world physics.Dactyl learns from scratch using the same general-purpose reinforcement learning algorithm and code as OpenAI Five.The results show that it’s possible to train agents in simulation and have them solve real-world tasks, without physically-accurate modeling of the world.

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