Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

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 ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...

From Deep Blue to modern AI, how chess exposed the shift from brute-force machines to learning systems, and why it matters AI ...

Modern conservation technology has one simple goal, even though achieving it is anything but simple: to spot a threat or ...

Updates to the VersaONE Universal SASE Platform include AI-enhanced data protection, AI-guided troubleshooting, and expanded ...

This story is part of an AI series looking at how WSU is driving innovation in research and teaching through artificial intelligence. View the entire ...

For patients taking medications that don't work as expected or pharmaceutical companies struggling with clinical trial failures, MetaOmics-10T represents a new starting point.

A new topology-based method predicts atomic charges in metal-organic frameworks from bond connectivity alone, making large-scale computational screening practical.

Two-sigma things happen all the time. But three sigma I’m listening now. Dragan Huterer Dark energy has been the most ...