Microsoft-backed AI out-forecasts hurricane experts without crunching the physics
Scientists have developed a machine learning model that can outperform official agencies at predicting tropical cyclone tracks, and do it faster and cheaper than traditional physics-based systems.
Aurora, a foundation model developed by researchers from Microsoft, the University of Pennsylvania (UPenn), and several other institutions, is designed to improve the speed and accuracy of Earth system forecasts, from air quality and ocean waves to tropical cyclone tracks and high-resolution weather.
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On top of a failing business model, newsrooms must navigate the powerful — and not fully reliable — new capabilities of artificial intelligence and the deployment of large language models.
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