New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

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, ...

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

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 ...

Intel is looking for a Data Scientist who specializes in Demand and Supply Planning to develop advanced analytics and machine learning systems that will optimiz ...

AI algorithms analyse complex medical images with speed and precision, supporting early disease detection.Radiology and ...

What is the Role of Agentic AI in DevOps Security? How can organizations ensure the security of machine identities and secrets? A comprehensive security strategy, encompassing Non-Human Identities ...

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 ...

Quiq reports on the role of automation in customer service, highlighting tools like AI for questions, ticket classification, ...