Most AI today is built to understand the digital world. But Physical AI has a different problem. A robot can process billions of parameters, yet still struggle with something humans do naturally: understanding what is actually around it, right now. A road can change. A building can change. An obstacle can appear. A space can look completely different from the last time it was mapped. This is why I find @vangrid_io interesting. Vangrid is building a spatial data layer for Physical AI by turning smartphones into distributed edge nodes that can capture real world environments and transform those observations into usable spatial intelligence. The interesting part isn’t simply collecting more data. It’s making that data more useful through privacy preserving capture, 3D reconstruction, provenance, verification and multi node corroboration. In other words, the goal isn’t just to create another map of the world. It’s to build a continuously refreshed, verifiable layer of ground truth that machines can actually use. If AI is moving from screens into the physical world, then reliable spatial data may become just as important as the models interpreting it.