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## What is a Large Geospatial Model?

Large Language Models (LLMs) are having an undeniable impact on our everyday lives and across multiple industries. Trained on internet-scale collections of text, LLMs can understand and generate written language in a way that challenges our understanding of “intelligence”.

Large Geospatial Models will help computers perceive, comprehend, and navigate the physical world in a way that will seem equally advanced. Analogous to LLMs, geospatial models are built using vast amounts of raw data: billions of images of the world, all anchored to precise locations on the globe, are distilled into a large model that enables a location-based understanding of space, structures, and physical interactions.

The shift from text-based models to those based on 3D data mirrors the broader trajectory of AI’s growth in recent years: from understanding and generating language, to interpreting and creating static and moving images (2D vision models), and, with current research efforts increasing, towards modeling the 3D appearance of objects (3D vision models).

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Geospatial models are a step beyond even 3D vision models in that they capture 3D entities that are rooted in specific geographic locations and have a metric quality to them. Unlike typical 3D generative models, which produce unscaled assets, a Large Geospatial Model is bound to metric space, ensuring precise estimates in scale-metric units. These entities therefore represent next-generation maps, rather than arbitrary 3D assets. While a 3D vision model may be able to create and understand a 3D scene, a geospatial model understands how that scene relates to millions of other scenes, geographically, around the world. A geospatial model implements a form of geospatial intelligence, where the model learns from its previous observations and is able to transfer knowledge to new locations, even if those are observed only partially.

While AR glasses with 3D graphics are still several years away from the mass market, there are opportunities for geospatial models to be integrated with audio-only or 2D display glasses. These models could guide users through the world, answer questions, provide personalized recommendations, help with navigation, and enhance real-world interactions. Large language models could be integrated so understanding and space come together, giving people the opportunity to be more informed and engaged with their surroundings and neighborhoods. Geospatial intelligence, as emerging from a large geospatial model, could also enable generation, completion or manipulation of 3D representations of the world to help build the next generation of AR experiences. Beyond gaming, Large Geospatial Models will have widespread applications, ranging from spatial planning and design, logistics, audience engagement, and remote collaboration.