Marine cone snails are host to a family of dangerous neurotoxins. Very little is known about how those toxins interact with ...

Payman Benham, Sixu Li, Irene Wang, and William Won were chosen from over 150 applicants based on their machine learning (ML) ...

When you listen to quantum enthusiasts, you may feel tempted to treat QML as an emerging silver bullet, which it isn’t.

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.

MLCommons has announced results for its MLPerf Storage v2.0 benchmark suite, designed to measure the performance of storage systems for machine learning workloads in an architecture-neutral, ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

“With this new toolkit and demo, D-Wave is enabling developers to build architectures that integrate our annealing quantum ...

More information: Maxwell T. West et al, Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning, Intelligent Computing (2024).

There’s a big problem faced by many organizations that are trying to unlock the promise of machine learning and artificial intelligence. The process of building and using machine learning architecture ...

Ohio State University. "New machine learning algorithm promises advances in computing." ScienceDaily. ScienceDaily, 9 May 2024. <www.sciencedaily.com / releases / 2024 / 05 / 240509155536.htm>.

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...