A new study published in Nature demonstrates that artificial intelligence models can produce accurate global weather forecasts faster and with less computational power than traditional physics-based systems. Researchers trained a neural network on decades of historical weather data, enabling it to predict atmospheric conditions up to 10 days in advance. The AI system matched or exceeded the accuracy of leading conventional models for most weather variables, including temperature and humidity, while generating forecasts in minutes instead of hours. While experts note that long-term reliability and extreme event prediction require further validation, the approach represents a significant shift toward data-driven meteorology. This could lead to more frequent and accessible high-resolution forecasts for various industries. Read the full article at https://sciencedaily.com/releases/2024/05/240521123456.htm.