In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

Explainability tools are commonly used in AI development to provide visibility into how models interpret data. In healthcare machine learning systems, explainability techniques may highlight factors ...

MIT researchers introduce a technique that improves how AI systems explain their predictions, helping users assess trust in ...

Apple researchers have created an AI model that reconstructs a 3D object from a single image, while keeping light effects consistent across viewing angles.

As researchers face mounting regulatory complexity, expanding research portfolios, and persistent resource constraints, compliance teams are increasingly turning to AI to move faster and gain better ...

Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on ...

A new study suggests AI systems could be a lot more efficient. Researchers were able to shrink an AI vision model to 1/1000th ...

AI video is moving from novelty to practical use, with creators valuing stable workflows, refinement, and more control ...

Artificial intelligence is rapidly transforming weather prediction, enabling forecasts that once required hours of supercomputing time to run in just minutes. But as AI tools play an expanding role in ...

Advice around AI search is getting simplistic. The real edge comes from knowledge graphs, expert entities, and influence in ...