| --- |
| title: Outerview |
| emoji: 🌍 |
| colorFrom: blue |
| colorTo: purple |
| sdk: static |
| pinned: true |
| thumbnail: >- |
| https://cdn-uploads.huggingface.co/production/uploads/649228ce740c5b0bd771c0a1/q5eGhRwGlmrBXPfrQfTXO.png |
| --- |
| |
| # 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. |
