| title: Outerview | |
| emoji: 🌍 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: static | |
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| # Outerview | |
| **A research lab building world models.** | |
| Outerview is a research lab focused on understanding the physical world at planetary scale. | |
| We are building systems that can organize the world’s physical information and make it accessible and usable — transforming raw imagery, video, location, and spatial context into knowledge that people and machines can search, interpret, and act on. | |
| Our belief is simple: the physical world should be as searchable and understandable as the digital world. | |
| --- | |
| ## What we work on | |
| We work on world models: systems that help machines understand **what exists, where it is, how it changes, and how to navigate it**. | |
| This includes research and infrastructure for: | |
| - large-scale physical world understanding | |
| - geospatial search and retrieval | |
| - visual and spatial representation learning | |
| - earth-scale indexing of imagery and video | |
| - real-world reasoning across time and place | |
| --- | |
| ## Our mission | |
| **Organize the world’s physical information and make it accessible and usable.** | |
| We see this as foundational infrastructure for the next generation of AI systems, robotics, mapping, autonomy, logistics, science, and real-world discovery. | |
| --- | |
| ## Why this matters | |
| Today, most of the world’s physical information is fragmented, unstructured, and difficult to use. | |
| Images, street-level video, geographic context, and changes over time exist in massive quantities, but they are not yet organized into a system that can be queried like knowledge. | |
| We are working toward that system. | |
| A world model should not only describe the world, but help people and machines: | |
| - search the physical environment | |
| - understand real places and objects | |
| - reason over change through time | |
| - build applications grounded in reality | |
| --- | |
| ## Research direction | |
| Our work sits at the intersection of: | |
| - computer vision | |
| - geospatial intelligence | |
| - multimodal representation learning | |
| - search and retrieval systems | |
| - physical-world AI | |
| We are interested in building models and datasets that improve how AI systems perceive, index, and interact with the real world. | |
| --- | |
| ## On Hugging Face | |
| This organization is where we share selected research artifacts, datasets, and experiments related to physical-world understanding. | |
| These releases are part of a broader effort to help make the world more observable, searchable, and computable. | |
| --- | |
| ## Vision | |
| We believe world models will become core infrastructure. | |
| Not just for understanding text, images, or the web but for understanding reality itself. | |
| Outerview exists to help build that future. |