Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how ...

Earth observation relies on diverse imaging systems whose varying spatial, spectral, radiometric, and temporal ...

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...

Researchers led by Universitätsmedizin Frankfurt and Goethe University Frankfurt have identified how particularly aggressive ...

Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...

Researchers introduce CASPER, proving AI story tools strip away mystery and rely on overly predictable characters.

For decades, scientists trying to build better catalysts have relied on a single guiding principle: there is one sweet spot, ...

For generations, writing up a summary of a patient exam was a vital step for physicians trying to make an accurate diagnosis.

A new study reveals that dual-atom catalysts behave in a fundamentally different way than scientists previously thought, challenging a long-standing model used to predict catalytic performance.

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

University of Pittsburgh postdoctoral researcher Mary Cundiff uses machine learning and single-cell genomics to study ...