R to @GoogleDeepMind: We’re open sourcing the code and model weights on @Github, making them freely…
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TL;DR - Google DeepMind announced it is open sourcing the code and model weights for WeatherNext, its AI weather model that improves tropical cyclone forecasting, on GitHub. This lowers the barrier for academic groups and operational forecasting agencies to run and adapt state-of-the-art cyclone prediction themselves.
- Both code and trained model weights are released freely on GitHub, not just an API or paper — enabling independent reproduction and fine-tuning.
- DeepMind cites the model's cyclone forecasts as accurate enough to provide roughly an extra day of warning lead time versus prior approaches.
- Stated intended uses: academic research, operational forecasting deployment, and building more specialized or region-localized derivative models.
- Content is a short announcement thread; no benchmark numbers, architecture details, license terms, or evaluation methodology are given here — those would be in the linked DeepMind research post.
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R to @GoogleDeepMind: We’re open sourcing the code and model weights on @Github, making them freely…
Public signals
N/A
TL;DR - Google DeepMind announced it is open sourcing the code and model weights for WeatherNext, its AI weather model that improves tropical cyclone forecasting, on GitHub. This lowers the barrier for academic groups and operational forecasting agencies to run and adapt state-of-the-art cyclone prediction themselves.
- Both code and trained model weights are released freely on GitHub, not just an API or paper — enabling independent reproduction and fine-tuning.
- DeepMind cites the model's cyclone forecasts as accurate enough to provide roughly an extra day of warning lead time versus prior approaches.
- Stated intended uses: academic research, operational forecasting deployment, and building more specialized or region-localized derivative models.
- Content is a short announcement thread; no benchmark numbers, architecture details, license terms, or evaluation methodology are given here — those would be in the linked DeepMind research post.