AI data scientist for Earth problems that finds geographic data, cleans it, trains ML models and makes predictions from a natural-language question. It improved Nigeria food security accuracy from 31% to 66% and scored 88% on DRC Ebola prediction.
Planetary Prediction Engine
Google Research agent that turns a natural-language Earth-science question into a data-driven prediction.
Updated EU status checked Last shown
Planetary Prediction Engine at a glance
- What is Planetary Prediction Engine?
- Planetary Prediction Engine is an agent from Google Research. Google Research agent that turns a natural-language Earth-science question into a data-driven prediction.
- Who makes Planetary Prediction Engine?
- Planetary Prediction Engine is made by Google Research.
- Does Planetary Prediction Engine work in the EU?
- Unverified. No explicit evidence found. Last verified 14 Nov 2026.
- How much does Planetary Prediction Engine cost?
- Pricing unknown.
- Where was Planetary Prediction Engine shown?
- In 1 creator video by AI Search. Most recently by AI Search on 30 Aug 2026, at 4:51 in “Ox Alpha reveal, realtime Minimax, Qwen Next, Hy4, robot olympics: AI NEWS”.
Sources: creator videos at the linked timestamps. EU status is information, not legal advice; see how we check.
Planetary Prediction Engine (PPE) is a Google Research agent described as an AI data scientist for geographic and Earth-related problems. From a natural-language question, it finds relevant geospatial data, cleans it, trains machine-learning models and produces predictions.
According to a creator summary, it raised food-security prediction accuracy for Nigeria from 31% to 66% and scored 88% on predicting Ebola outbreaks in the Democratic Republic of the Congo. These figures come from a secondary source and have not been checked against an official publication.
No official page, documentation or access details could be retrieved. Availability, pricing, licensing and release date are unconfirmed, and it appears to be a research system rather than a public product.
- Accepts questions in natural language
- Finds and collects geographic data automatically
- Cleans data and trains ML models end to end
- Produces predictions for Earth-related problems such as food security and disease outbreaks
- Reported results: Nigeria food security accuracy 31% to 66%; DRC Ebola prediction 88%
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