Google Fellow John Platt: ERA AI scientist grew out of an attempt to automate Kaggle

Latent Space · youtube · 2026-09-23

Latent Space interviews Google Fellow John Platt (Platt scaling, SMO, an Academy Award) on ERA (Empirical Research Assistance), Google's AI research system.

Key points:

ERA began as an "auto-Kaggle" project, combining LLMs with tree search and UCB to guide experiment iteration; the Gemini 2.0→2.5 leap made it work
ERA helped crack a climate modeling problem that had stalled for years (measuring contrail warming) and supports FireSat wildfire detection
The hard part is turning science into scoreable tasks — choosing the score matters more than the model
Reward hacking and Goodhart's law: predictive accuracy isn't understanding, illustrated by a half-pixel labeling error that won a Kaggle competition
Also: learning from Feynman, fusion and quantum outlooks, why he still recommends linear regression first, and the enduring value of scientific taste

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Google Fellow John Platt: ERA AI scientist grew out of an attempt to automate Kaggle

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