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This invention describes a way to teach a special kind of computer, called a quantum neural network, to solve problems. It involves feeding the network examples where it learns to recognize patterns by adjusting how its quantum bits interact. The claims specifically focus on the method for training such a network, rather than just the network's design.
Why it matters: Quantum computing hardware and software are still rapidly evolving. Since 2023, incremental advancements in qubit stability and error correction may have made the practical implementation and training of such quantum neural networks more feasible.
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