AI from Stanford Reads Disease Risks in Sleep: SleepFM Predicts Over 130 Ailments from One Night.

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

AI can use sleep data from a single night to identify patterns linked to disease risk years before symptoms appear.

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

A poor night's sleep portends a bleary-eyed next day, but it could also hint at diseases that will strike years down the road ...

A new AI model in the US, SleepFM, has found that patterns in human slumber can be used to predict a person's risk for about 130 diseases, including dementia and certain cancers.

CEO Jensen Huang gave a presentation on Monday to kick off CES 2026, the big tech expo formerly known as the "Consumer ...

A new ‘biomimetic’ model of brain circuits and function at multiple scales produced naturalistic dynamics and learning, and ...

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...