
IBM and NASA have unveiled a groundbreaking open-source AI model called Surya, designed to predict solar weather and protect critical infrastructure from space-based disruptions. The powerful AI model is trained on 14 years of observations from NASA’s Solar Dynamics Observatory (SDO).
Here's a breakdown of what makes this initiative so impactful:
What Is Surya?
- Name Origin: “Surya” is Sanskrit for “Sun,” reflecting its heliophysics focus.
- Purpose: Predict solar flares, coronal mass ejections, and other solar phenomena that can disrupt satellites, GPS, power grids, and telecommunications.
- Availability: Open-source and hosted on Hugging Face.
Technical Highlights
- Foundation Model: Trained on 14 years of high-resolution solar data from NASA’s Solar Dynamics Observatory (SDO).
- Data Types: Includes solar coronal EUV images, magnetic field maps, and solar surface velocity data.
- Model Size: 366 million parameters—lightweight enough for broader deployment.
Capabilities & Performance
- Forecasting Power:
- Predicts solar flares up to 2 hours in advance.
- Achieved 16% improvement in flare classification accuracy over previous models.
- Use Cases:
- Early warnings for satellite operators.
- Infrastructure protection for energy grids and aviation.
- Academic research in heliophysics and space weather.
Why It Matters
- Economic Risk: A major solar storm could cost the global economy up to $2.4 trillion over five years.
- Recent Events: Solar storms have already disrupted GPS, diverted flights, and damaged satellites.
- Future-Proofing: As humanity ventures deeper into space, accurate solar forecasting becomes essential for safety and continuity.
Open Science Impact
- SuryaBench Dataset: IBM and NASA also released the largest curated heliophysics dataset to support further research.
- Community Collaboration: Encourages scientists and developers to build on Surya for new applications in space weather prediction.
Summary Table
| Feature | Details |
|---|---|
| Model Name | Surya |
| Developed By | IBM & NASA |
| Training Data | 14 years of solar observations from NASA's SDO |
| Parameter Count | 366 million |
| Forecast Window | Up to 2 hours before solar flare events |
| Accuracy Improvement | 16% over prior models |
| Hosted On | Hugging Face |
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