For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...

An international research team involving the University of Bayreuth has, for the first time, analyzed the "inner workings" of ...

This research assesses data provenance in widely used health datasets, revealing flaws that could undermine clinical prediction models and patient care.

Summary: A new study utilizes Koopman operator learning to prove that certain complex, chaotic systems have fundamental ...

While AI shows promise in healthcare, the way some AI tools are tested and approved doesn't generate much confidence.

How a team at UC Berkeley devised a multi-sensor smell system and combined it with machine learning to create a more ...

Google's TabFM skips per-dataset training and still predicts on unseen tables, matching tuned baselines and cutting pipeline ...

It's the company's first public proof point after a year and a half spent building AI infrastructure largely out of public ...

Predictive maintenance tools based on artificial intelligence (AI) are already used in electricity grids around the world.

Dana-Farber Cancer Institute investigators and collaborators at Mass General Brigham have created a single algorithm that ...

A multi-cloud MLOps framework improves AI service reliability through automated deployment, canary releases, and ...

A new analysis of seismic “families” reveals that some large earthquakes may be preceded by hidden patterns in clustering, ...