analiza aiqbench
This article focuses on WeatherNext 2, a deep learning system developed by Google DeepMind specifically designed to predict tropical cyclones with unprecedented accuracy and lead time. By achieving state-of-the-art performance in forecasting track, intensity, and wind structure, the model represents a significant advancement in applying machine learning techniques to complex atmospheric dynamics. The open-sourcing of this architecture further contributes to global research efforts aimed at improving climate resilience through advanced AI-driven meteorology.
Our WeatherNext 2 AI model demonstrated a massive leap forward in predicting cyclones.

Google DeepMind’s WeatherNext 2 shows state-of-the-art accuracy in cyclone prediction.
Predicting how hurricanes and cyclones develop is a longstanding challenge, and every hour of warning counts. Tropical cyclones are among the most destructive weather events on Earth, and for meteorologists, issuing accurate, timely warnings is a constant race against time.
Today, in a paper published in Nature, Google researchers show that our WeatherNext AI model achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. This represents a massive leap forward — roughly a decade of meteorological progress in one model.
To help build climate resilience worldwide, we are now open-sourcing the WeatherNext 2 model to the global research community. For more information, check the Google DeepMind blog.
WeatherNext enables accurate cyclone forecasts that can give an extra day of warning. Now we are open sourcing the model.
Text integral sub licența deschisă a publicației · 130 cuvinte
Subiecte conexe

The latest AI news we announced in August 2026
Google · 1 sept. 2026

Ask a Scientist: How do researchers use AI to predict a cyclone?
Google · 1 sept. 2026
News Archive 2026
Quantum Computing Report · 25 iul. 2026

A New Era of Discovery: Google Research at I/O 2026
Google Research · 28 mai 2026