Good morning, CT! A decentralized spatial network can have thousands of contributors and still fail to capture the places that matter most. That’s one challenge I find interesting about @vangrid_io . Imagine thousands of captures coming from a busy city, while rural roads, smaller towns, and industrial zones remain largely undocumented. The network keeps growing, but its understanding of the physical world stays incomplete. For Physical AI, coverage matters just as much as scale. Robots and autonomous systems need spatial data from diverse environments, not just the same well-mapped streets. Vangrid is exploring a different approach: → Everyday smartphones become distributed capture devices → Contributors collect data from real-world locations → Demand-driven bounties can incentivize captures where fresh data is needed → Verification helps make the resulting spatial data more trustworthy Of course, expanding coverage is only part of the equation. Data must also be accurate, recent, and useful for the systems that depend on it. What makes this model promising is the potential to direct contributions toward the gaps that centralized mapping may leave behind. The goal isn’t simply to collect more data. It’s to help AI understand more of the world. For Vangrid, I think the real measure of progress will be how effectively its network turns distributed human contributions into fresh, verified spatial intelligence across different environments. The world is bigger than the places we’ve already mapped.