10 Posts
Machine learning models have predicted weather a few days ahead of time. A new approach substantially extends the time horizon. Remi Lam and colleagues at Google developed GraphCast, a weather-forecasting system based on graph neural networks (GNNs).
Machine learning models have predicted weather a few days ahead of time. A new approach substantially extends the time horizon. Remi Lam and colleagues at Google developed GraphCast, a weather-forecasting system based on graph neural networks (GNNs).
Machine learning is making wind power more predictable. Engie SA, a multinational energy utility based in France, is the first customer for an AI-powered tool from Google that predicts the energy output of wind farms.
Machine learning is making wind power more predictable. Engie SA, a multinational energy utility based in France, is the first customer for an AI-powered tool from Google that predicts the energy output of wind farms.
A new deep learning technique increased the precision of short-term rainfall forecasts. Researchers developed the Deep Generative Model of Radar (DGMR) to predict amounts of precipitation up to two hours in advance.
A new deep learning technique increased the precision of short-term rainfall forecasts. Researchers developed the Deep Generative Model of Radar (DGMR) to predict amounts of precipitation up to two hours in advance.
The White House called for new funding for AI research including a constellation of research centers. Nonetheless, the U.S. government’s annual spending on the technology still would lag behind that of several other...
The White House called for new funding for AI research including a constellation of research centers. Nonetheless, the U.S. government’s annual spending on the technology still would lag behind that of several other...
Severe heat waves and cold snaps are especially hard to forecast because atmospheric perturbations can have effects that are difficult to compute. Neural networks show promise where typical methods have stumbled.
Severe heat waves and cold snaps are especially hard to forecast because atmospheric perturbations can have effects that are difficult to compute. Neural networks show promise where typical methods have stumbled.
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