Google Research · Planetary Prediction

Planetary Prediction Engine

An LLM-orchestrated system that runs the entire geospatial prediction workflow from a natural-language query — data discovery, multimodal dataset curation via Population Dynamics Foundation Models and AlphaEarth embeddings, then training gradient-boosted decision trees and MLPs — with no manual data engineering, cutting model building from weeks to minutes. Google reports mean R-squared of 76.8% against 60.0% for expert and Bayesian baselines on US CDC health indicators, 66.1% against 31.5% on Nigerian food-security downscaling, and Recall@10 of 83.3% against roughly 73% on DRC Ebola nowcasting. Described as an experimental capability, with no product or API access.