NEW DELHI, Oct 27: US-based tech giant Google advanced its ‘Earth AI’ technology, which is a family of geospatial AI models and reasoning agents that provide users with actionable insights that are grounded in real-world understanding.
Geospatial AI (GeoAI) refers to the integration of artificial intelligence (AI) with geographic data and systems that use AI to analyze and extract insights from location-based information.
The official blog said, ” Today, we’re sharing our latest Earth AI innovations and expanding access to these capabilities on Google Earth and Google Cloud. Earlier this year, we introduced Google Earth AI to solve core challenges. 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 a planetary scale.”
Google CEO Sundar Pichai also posted on X, “Google Earth AI, our collection of geospatial AI Models and datasets, is expanding globally and adding new capabilities. That includes Geospatial Reasoning, powered by Gemini, which automatically connects different Earth AI models-like weather forecasts, population maps satellite imagery-to answer complex questions.”
” We’re also bringing new Earth AI models to Gemini capabilities in Google Earth, which make it easy to instantly find objects and discover patterns from satellite imagery. For example, analysts could spot harmful algae blooms that could impact drinking water supply, and issue warnings,” the post added.
Google has introduced new innovations in its ‘Earth AI’ model: (i) New imagery and Population foundation models, along with technical details and evaluations showing state-of-the-art performance (ii) Demonstrations of our geospatial reasoning agent to solve complex, multi-step geospatial queries.
This model provides a detailed understanding of our planet, which is grounded in real data. Moreover, the addition of an ‘agent’ turns it into an intelligent orchestrator.
It deconstructs a complex question into a multi-step plan: (i) executes the plan by calling on these foundation models, (ii) querying vast datastores, (iii) using geospatial tools.
(UNI)
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