Google Uses Computer Vision to Cut 1% of Global Warming from Contrails
John Platt explains how Google predicts atmospheric supersaturation with computer vision and agentic AI to eliminate airplane contrails.
10+ hours of podcasts, in 5 minutes.
Google Fellow John Platt discusses Google's Empirical Research Assistance (ERA) framework, an agentic AI system combining LLMs with Monte Carlo tree search to automate scientific experimentation. Platt explains how ERA grew from an attempt to automate Kaggle, the critical distinction between predictive and descriptive scientific models, and how AI is unlocking real-world climate interventions from contrail mitigation to wildfire detection.
John Platt explains how Google predicts atmospheric supersaturation with computer vision and agentic AI to eliminate airplane contrails.
Google Fellow John Platt explains why relying entirely on AI coding tools robs engineers of domain taste, and why he protects 20% time for deep exploration.
Google Fellow John Platt explains how the Lawson criterion and simpler control systems bring commercial fusion within reach this decade.
Google Fellow John Platt explains why predictive AI fails at extrapolation and how agentic optimization triggers Goodhart's law in science.
John Platt explains how Google and Earth Fire Alliance use 50 LEO satellites and AI super-resolution to spot 5-meter wildfires in 20 minutes.
10+ hours of podcasts, distilled into one 5-minute read. Free, every Sunday morning.
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