For years, Google has developed AI models that enhance our understanding of the planet. These models help keep Google products fresh, for example, ensuring Maps is accurate by analyzing satellite images and giving Search users the most up-to-date alerts about weather and natural disasters.
As individual models grow more powerful, we’ve learned that many real-world questions require the combination of insights across domains. Answering complex queries like, “Where is a hurricane likely to make landfall? Which communities are most vulnerable and how should they prepare?” requires reasoning about imagery, population and the environment.
Earlier this year, we introduced Google Earth AI to solve this core challenge. By pairing our family of powerful foundation models with a geospatial reasoning agent, which uses our latest Gemini models, it’s becoming possible to perform complex, real-world reasoning at planetary scale. The models provide detailed understanding of our planet, grounded in real-world data. The agent, in turn, acts as an intelligent orchestrator. It deconstructs a complex question into a multi-step plan; executes the plan by calling on these foundation models, querying vast datastores, and using geospatial tools; and finally fuses the results at each step into a holistic answer.
Today, we’re introducing new Earth AI innovations:
- New Imagery and Population foundation models, along with technical details and evaluations showing state-of-the-art performance.
- Demonstrations of our geospatial reasoning agent using these models to solve complex, multi-step geospatial queries.
To learn more, we invite you to read our full technical paper, “Google Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning”. You can also get involved by expressing interest as we expand access to these new capabilities for developers and enterprises.
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