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 ...
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Quantum reservoir computing hits its peak at the brink of many body chaos
Researchers at the University of Tokyo have identified a precise sweet spot where quantum reservoir computing, a machine learning approach that treats quantum systems as computational engines, reaches ...
Long confined to theoretical labs and sci-fi thrillers, quantum computing is fast emerging as a real-world technology with ...
Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...
Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
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, ...
By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...
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 ...
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