Quantum Machine Learning promises access to exponentially large representational spaces, but before any computation can happen, classical data must first be embedded into quantum systems. This article explores one of the most overlooked bottlenecks in QML: getting data into a quantum computer efficiently.

The post The Hidden Bottleneck in Quantum Machine Learning: Getting Data into a Quantum Computer appeared first on Towards Data Science.

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