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 ...

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 ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

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 ...

Quantum Machines, a provider of advanced hybrid quantum-classical control solutions, announced today the release of Qualibrate (which the company spells QUAlibrate), an open-source framework for ...

SQC's Founder and CEO, Michelle Simmons, said: "Quantum Twins represents a window into the quantum world that customers can use for materials discovery today. The enabler is that we can engineer ...

The Graduate School of Information Science (GSIS) at Tohoku University, together with the Physics and Informatics (PHI) Lab at NTT Research, Inc., have jointly published a paper in the journal Quantum ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of two-dimensional memories, systems that can reliably store information despite ...