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

Adaptive testing in integrated circuits (ICs) has emerged as an innovative strategy to optimise and streamline the evaluation of increasingly complex semiconductor devices. By incorporating machine ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...

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 ...

As the May 26th CE-IVDR compliance deadline comes into effect, Diagnostics.ai launches the industry's first fully-transparent machine learning platform for clinical real-time PCR diagnostics – ...