physical ai has a data problem that bigger models alone cannot solve a robot can be trained on millions of images, but that still does not tell it what a warehouse looks like today, which path is blocked, or how a location has changed since the last capture that is why @vangrid_io keeps catching my attention. someone can request data for a specific place, a local contributor records it with a smartphone, and the accepted capture can be settled in USDC the interesting part is the verification layer too. privacy filtering happens on the device, while the data origin is anchored through Base and attestations the real test is whether demand keeps coming from robotics teams and whether the network can turn ordinary phone footage into reliable 3D data at scale but the direction makes sense. machines need a living view of the physical world, not just another static dataset