The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Innatera’s Pulsar blends analog and digital SNN accelerators to deliver always-on neural-network operation for low-power applications. 1. Innatera’s Pulsar system-on-chip incorporates analog and ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

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 is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

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

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...