Hybrid Architecture

How Quantum Machine Learning Works: Superposition, Entanglement, and the Hybrid Architecture Behind Today's QML

Quantum Machine Learning (QML) employs a hybrid architecture, dividing tasks between classical and quantum processors to exploit quantum principles like superposition and entanglement. The workflow involves encoding classical data into quantum states for processing, followed by classical optimization, while navigating the constraints of current noisy quantum hardware.