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, ...

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

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

AI-powered penetration testing is an advanced approach to security testing that uses artificial intelligence, machine learning, and autonomous agents to simulate real-world cyberattacks, identify ...

AMD requires a Senior AI/ML and GPU Performance QA Engineer who will manage validation and performance testing for machine ...

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

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

New Aston team principal Adrian Newey says the AI tools fans talk about aren’t what F1 teams rely on ...

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 ...

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

Digital twins and prognostic models deliver detailed insights into a battery’s behaviour and lifespan, and machine learning..

A single clear image can rewire the visual brain, making later recognition faster without relying on memory systems.