Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

New Wireless Broadband Alliance report lays out the frameworks and priorities needed to scale intelligent Wi-Fi without ...

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

AI-powered malware in 2026 has evolved far beyond traditional viruses. Instead of static code, ...

Mark Zuckerberg’s court testimony that companies should build “useful” products has reignited debate on morality of algorithms ...

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

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

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

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, ...

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the scientific journal ...