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 ...
Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...
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 ...
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 ...
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 ...
Tech Mahindra has announced a collaboration with University College London to advance joint research and solution development in Generative AI and quantum computing. Tech Mahindra has announced a ...
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 ...
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 ...
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