The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made ...

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

PALO ALTO, Calif.--(BUSINESS WIRE)--D-Wave Quantum Inc. (NYSE: QBTS) (“D-Wave” or the “Company”), the only dual-platform quantum computing company, providing annealing and gate-model systems, software ...

At its recent Qubits 2026 user conference, D-Wave Quantum unveiled a series of significant operational and strategic ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...