Quantum AI/ML is an informal umbrella term describing a variety of algorithms and approaches that integrate quantum computing with artificial intelligence (AI) and machine learning (ML). These can include:
Quantum machine learning (QML) methods that use quantum computation for a machine learning task, e.g., hybrid classical–quantum algorithms for AI/ML, where parts of the workload (such as feature encoding or variational circuit evaluation) run on a quantum processor while the rest runs on classical hardware.
Utilizing AI for the design, control, and calibration of technologies used in developing quantum computing systems, including automated tuning of control parameters, system identification, circuit optimization, and error mitigation.
Using quantum computers as the backbone for developing advanced AI/ML systems, leveraging quantum resources (superposition, entanglement, interference) to accelerate or enhance learning algorithms and enable new model architectures.
