A new artificial intelligence weather forecasting model developed by Google DeepMind has demonstrated superior performance compared to traditional numerical weather prediction systems in global medium-range forecasts. The model, named GraphCast, uses machine learning to analyze decades of historical weather data and current atmospheric conditions to predict weather patterns up to 10 days in advance. In head-to-head comparisons with the European Centre for Medium-Range Weather Forecasts’ high-resolution system (HRES), GraphCast provided more accurate predictions for over 90% of 1,380 test variables, including critical metrics like temperature, pressure, wind speed, and humidity. The AI system can generate a 10-day forecast in under one minute on a single Google TPU v4 machine, a significant reduction from the hours of computation required by conventional physics-based models. Researchers emphasize that AI models like GraphCast are designed to complement, not replace, existing forecasting infrastructure, offering a faster, more efficient tool for meteorologists. The technology represents a major shift toward data-driven weather prediction and could improve early warnings for extreme weather events. Read the full article at: https://technologyreview.com/2023/11/14/1083709/ai-weather-model-graphcast-outperforms-traditional-forecasts/