At GTC 2026, Jensen Huang, Aravind Srinivas, Harrison Chase, Mira Murati, and Michael Truell made a compelling case that the future of AI belongs to open agent systems, not just open models.

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...

Ad fraud is no longer a fringe issue. It is a systemic threat to digital advertising, and its scale demands a technological ...

Mistral AI launches Forge, an enterprise AI training platform that lets companies build custom models on proprietary data and ...

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...

Epshtein argues that a deeper understanding of generalization and principled use of prior knowledge are essential to building ...

Translational bioinformatics lies at the intersection of computational biology, multi-omics, and clinical data science, offering a powerful toolkit for ...

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.

Fraud remains a critical operational risk for banks, particularly with the surge in Authorised Push Payment (APP) fraud, which is a primary target of current FCA and PSR regulatory attention. Static, ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

NORRISTOWN, PA - March 12, 2026 - PRESSADVANTAGE - Magic Memories underscores the role of small group classrooms in ...