New research reveals that "foundation models" trained on vast, general time-series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.

Choosing an AI model is no longer about “best model wins.” Instead, the right choice is the one that meets accuracy targets, fits latency and cost budgets, respects compliance boundaries and ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

Microscopic images of human tissue are a cornerstone of biomedical research and clinical diagnostics. Yet despite their importance, these images often remain difficult to analyze systematically and to ...

I believe the future of work will not be defined by rigid employment categories, but by how effectively leaders can assemble ...

A powerful new real-world data platform could transform how scientists predict and understand Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD), reports a new study at Columbia ...

For two decades, a Georgia Tech professor has used simple data to track the best teams in college basketball and predict who will win the NCAA Tournament. Joel Sokol, director of the Master of Science ...

Accurate spatiotemporal prediction is fundamentally essential for anticipating and managing the dynamic evolutions within global physical, environmental, ...

A new collaboration between EMBL's European Bioinformatics Institute (EMBL-EBI), Google DeepMind, NVIDIA, and Seoul National University has made millions of AI-predicted protein complex structures ...