Microsoft Research Podcast Abstracts: Aurora with Megan Stanley and Wessel Bruinsma
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May 21, 2025 Join researchers as they unveil Aurora, a groundbreaking AI model transforming environmental forecasting. Discover how this innovative approach enhances predictions for weather, air pollution, and ocean waves. They delve into the remarkable dual pre-training and fine-tuning processes that power Aurora's performance. While celebrating its achievements, the team candidly discusses current limitations and the future of probabilistic forecasting. Explore the collaborative efforts driving advancements in environmental science!
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Aurora Revolutionizes Environmental Forecasting
- Aurora extends AI advancements in weather prediction to multiple environmental domains like air pollution and ocean waves.
- This model represents a major step in making diverse environmental forecasting more efficient and accurate.
Foundation Model Approach Works
- Aurora is a foundation model trained on vast Earth system data to learn general dynamics.
- It can then be fine-tuned efficiently for diverse environmental forecasting tasks, enhancing flexibility and power.
Scaling Data and Model Size Benefits
- Training Aurora on multiple diverse large datasets significantly improves its performance.
- Larger models also make more efficient use of computational resources despite slower runtime.