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, ...

A review led by Adelaide University researchers has found there's a lack of clear guidelines around the early testing of AI tools in health clinics during a process known as silent trials. The global ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

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

Opinion: A patent case involving inventor Guillaume Desjardins has evolved into a cornerstone of modern patent eligibility ...

McGill researchers have developed a diagnostic system capable of identifying bacteria—and determining which antibiotics can ...

The days of large blanket media buys are fading. Always-on testing reduces waste by directing spend toward what is proven to work. AI-powered automation and personalization are key drivers of ...

AI-powered overclocking uses machine learning to boost CPU and GPU performance safely in 2026, delivering higher FPS, better efficiency, and automatic stability.

In the pursuit of solutions to complex global challenges including disease, energy demands, and climate change, scientific ...