

Reinforcement Learning and Quantum Decoding | Vlad Sivak Google Quantum AI
How can reinforcement learning help quantum computers learn from their own errors? In this episode, Vlad Sivak, researcher at Google Quantum AI, joins us to discuss how reinforcement learning can improve quantum computing, from error correction and decoding to the calibration of quantum hardware. Sivak explains how…

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“Such an interesting use case for RL, seems like it has a lot of potential”
“Could a hierarchical RL architecture preserve scalability by learning both local control policies and a smaller global policy for correlated errors?”
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