Seeing, Mapping, Building

Hi All,

I spent most of July off the grid—hiking the full John Muir Trail with my 17-year-old son. We covered 220 miles through granite passes and past alpine lakes. After that much time immersed in real terrain, it’s hard not to reflect on how far we are from truly modeling the physical world—and how quickly AI is trying to catch up.

This month’s updates trace that arc—of how AI is learning to See, Map, and Build. From planetary-scale models, to infrastructure intelligence, to design-to-manufacturing automation, there’s real momentum toward systems that better understand and assist our physical world. Let’s take a look

🌍 DeepMind: A Foundation Model to See the Planet

DeepMind unveiled AlphaEarth Foundations, a new AI system trained on decades of climate and remote sensing data. It produces high-resolution environmental maps that can model droughts, predict land use change, and support conservation or agricultural planning.

For researchers, policymakers, and operators, AlphaEarth represents a new kind of tool: a generalizable model that can interpret complex geospatial patterns—and help link environmental perception to real-world decision-making. It’s a strong signal that foundation models are moving beyond language and images, and into physical systems.

Separately, the Google Earth Engine team released a public satellite embedding dataset—another sign of growing momentum in AI-powered Earth observation.

Did someone forward this to you? Want more? 

🏗 Looq: Mapping Physical Infrastructure

While DeepMind builds planetary-scale models from orbit, Looq.ai—founded by astrophysicist-turned-roboticist Dominique Meyer—is focused on critical real-world infrastructure—what cities depend on but rarely see clearly.

After working on camera systems for near-Earth object detection, Meyer turned his attention to urban  infrastructure. He founded Looq AI to combine LiDAR, computer vision, and AI to scan and map utility poles and related urban assets—making our aging infrastructure as machine-readable as the road ahead.

This kind of perception is critical to maintaining and upgrading the infrastructure cities depend on—especially as it ages, expands, and becomes more complex to manage.

Read more about Looq AI’s founding story

🔧 Drafter: Turning Design into Built Reality

Seeing the world is one thing—building for it is another.

Manufacturing drawings are a necessary—but often painful—step between CAD and production. Drawings convey critical tolerances and specs essential for bridging design intent and real-world fabrication. Yet few engineers are trained in producing this documentation accurately or efficiently.

To solve this, Drafter has integrated its solution directly into Solidworks, a leading modeling program for mechanical design. Drafter automatically generates annotated part and assembly documentation, ready for manufacturing. It’s a big step toward streamlining design-to-fabrication workflows in industries where documentation is still mostly manual.

Market & Events

📈 Computer Vision Is Gaining Ground A recent forecast put the computer vision market at $34.3B by 2033, driven by AI advances and physical-world automation. It’s a broad category—but the most interesting developments, to us, are where perception meets action.

📍Exploring Vision and Robotics at SIGGRAPH Doug will be in Vancouver next week for SIGGRAPH—tracking work at the intersection of computer vision, simulation, and robotics. Let him know if you’ll be there.

📍Joining the Conversation at Step SF Later this month, Doug will join Step SF—a new event focused on startups and venture capital in San Francisco.

Signing Off

We learn a lot from the physical world. The hard part is teaching machines to do the same— in ways that move the world forward and create value along the way.

More soon,
– Doug and the team at Spatial Capital