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

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Machine learning redesigns microscopic web sensors to be five times more flexible than nature-inspired versions, enabling detection of masses as small as trillionths of a gram.

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, ...

Houston-based testing lab delivers 24-hour turnaround for mission-critical semiconductor verification HOUSTON, TX, ...

AI-powered spectral sensor performs machine learning during light capture, identifying materials and chemicals in real time ...

Non-terrestrial networks have their own challenges that cellular networks didn't have. Will AI help solve them dynamically?

GeneMetrics was established by a group of clinicians, scientists, and legal experts committed to addressing a fragmented ...

Artificial intelligence (AI) has rapidly become one of the most frequently referenced concepts in high-performance sport. It ...