Early-2026 explainer reframes transformer attention: tokenized text becomes Q/K/V self-attention maps, not linear prediction.

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine learning algorithm designed to identify physical anomalies in solar ...

Two concepts haunt modern science like unsolved riddles. Information—the currency of the digital age, the stuff of genes and neurons, perhaps the fabric of reality itself. And consciousness—the inner ...

Patients at primary care clinics received more dementia diagnoses after implementation of a machine-learning tool designed to flag potential cases, according to a study published in JAMA Network. The ...

A fully booked flight used to mean turning away higher-value, last-minute bookings, resulting in lost earnings for airlines and disappointment for passengers. Not anymore. At TravelX, we have ...

Joseph Alderman et al argue that predictive models in healthcare lack adequate oversight and regulation. They highlight the potential risks to patients and call for improved governance to ensure the ...

Machine learning operations (MLOps) have rapidly evolved from experimental workflows to production-critical systems powering everything from fraud detection to autonomous vehicles. But as ...

A new Apple-backed AI model trained on Apple Watch behavioral data can now predict a wide range of health conditions more accurately than traditional sensor-based approaches, according to a recently ...

Image generators are designed to mimic their training data, so where does their apparent creativity come from? A recent study suggests that it’s an inevitable by-product of their architecture. We were ...