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<div>We've trained a pair of neural networks to solve the Rubik's
Cube with a human-like robot hand. The neural networks are trained
entirely in simulation, using the same reinforcement learning code as
OpenAI Five paired with a new technique called Automatic Domain
Randomization (ADR). The system can handle situations it never saw
during training, such as being prodded by a stuffed giraffe. This
shows that reinforcement learning isn't just a tool for virtual
tasks, but can solve physical-world problems requiring unprecedented
dexterity.</div>
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<div>https://openai.com/blog/solving-rubiks-cube/</div>
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