NeuralGCM and the Hybrid Approach

Apple Podcasts | Spotify

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003 | 2025-07-28

Machine learning dominates the conversation, but what will happen to the centuries-old physical equations that built our understanding of the atmosphere? How are the two approaches at odds? How might they coexist?

Today’s paper, NeuralGCM, sheds light on how physics-based and AI approaches might be a powerful pairing for weather forecasting. For the first truly hybrid model we’ve discussed, it’s only fitting that we’ve also taken a hybrid approach in this conversation. So join us for hybrid models, data compression, Dragon Ball Z, and the strange future of primitive equations.

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Featured paper

Neural general circulation models for weather and climate

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Chapters

• 00:00 Intro
• 01:31 Weather report & books
• 18:01 Paper time
• 25:26 A theory of compression
• 48:07 Closing thoughts: Resolution, interpretability, & the future of primitive equations

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Recommended reading

• Chaos: Making a New Science — James Gleick
• Landmarks — Robert McFarlane
• Dandelion Wine — Ray Bradbury
• Webster’s 1913 Dictionary
• “The Bitter Lesson” — Rich Sutton
• MC-LSTM: Mass-Conserving LSTM
• Charisma and Disenchantment — Max Weber