Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings
Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fidelity geospatial modeling. However, building predictive planetary models remains bottlenecked by a fragmented data ecosystem, requiring manual data retrieval, multimodal data curation and fusion along with iterative model selection. We present the Planetary Prediction Engine (PPE), an autonomous AI system that executes this end-to-end workflow directly from natural-language queries. PPE synthesizes multimodal datasets on the fly, retrieving spatiote
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- PossiblePossibly related (embedding) · 55%Embed the world: Multimodal AI for searchable aerial imagery at scale →
- PossiblePossibly related (embedding) · 49%Large Language Models: Qwen3 Offers AI Models For Deeper Reasoning And Faster Responses - Trend Hunter →
- LinkedLinked via arxiv author · 85%Evelyn Ma →
“Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embedd”
- LinkedLinked via arxiv author · 85%Rama Kumar Pasumarthi →
“Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embedd”
- LinkedLinked via arxiv author · 85%Kishwar Shafin →
“Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embedd”
- LinkedLinked via arxiv author · 85%Mandar Sharma →
“Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embedd”
- LinkedLinked via arxiv author · 85%Mimi Sun →
“Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embedd”
- LinkedLinked via arxiv author · 85%Hamed Sadeghi →
“Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embedd”