While artificial intelligence (AI) models have proved useful in some areas of science, like predicting 3D protein structures, ...

In a nondescript building on the edge of a research campus, a small team of scientists is training machines to do something ...

Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...

Credit: VentureBeat made with Flux.2 [klein] on Fal.ai The German AI startup Black Forest Labs (BFL), founded by former ...

Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

Background: Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear ...

Background: Coronary artery disease (CAD) demonstrates a strong bidirectional association with diabetes mellitus, which not only elevates cardiovascular disease risk but also correlates with poorer ...

Abstract: This paper presents a comprehensive study on the application of Explainable Artificial Intelligence (XAI) for diabetes risk assessment, focusing on the interpretability of machine learning ...

Abstract: Predicting student performance accurately is essential for personalizing education, allocating resources, and helping at-risk students. This study explores application of Machine Learning ...

James is a published author with multiple pop-history and science books to his name. He specializes in history, space, strange science, and anything out of the ordinary.View full profile James is a ...

Chinese AI models have caught up to US models in power and performance. China is leading in model openness. Much of the world may adopt the freely available Chinese technology. The US artificial ...