The next bottleneck in Physical AI isn't just intelligence. It's access to the real world. Google DeepMind has been advancing robotic reasoning, from understanding multiple camera views to interpreting industrial gauges and verifying task completion. But models can only reason about the environments they can actually observe. That's where @vangrid_io gets interesting. Instead of relying entirely on expensive mapping fleets or controlled lab environments, Vangrid turns smartphone captures into 3D spatial data that can be verified onchain and supplied to AI systems. The bigger idea is a decentralized perception layer for robotics: people capture reality, the network reconstructs it, and AI developers get access to structured ground-truth data. The challenge now is quality, coverage, freshness and consistency at scale. Collecting millions of captures means little if the resulting data isn't accurate and useful for real-world decisions. If @vangrid_io can solve that reliably, it could become an important piece of the infrastructure behind Physical AI. The models are getting smarter. Now the world needs to become machine-readable.