ROVR 🌐｜World Nodic lBuilder.network

everyone says robotics needs more data. thats wrong. there's more useful robotics data sitting in S3 buckets right now than most foundation model teams have ever trained on. every robotics company that's been deploying for more than six months has the same problem. their robots generate sensor data on every single mission: IMU, camera feeds, lidar, joint states, behaviour logs. terabytes of it. real-world production data from real environments. it all goes into storage and mostly stays there. meanwhile the foundation model teams are spending millions on simulation environments and teleoperation rigs to generate training data from scratch. manufacturing the thing that production teams already have. except the production data is real. it has noise, edge cases, actual physics. but it's trapped. different sensors, different formats, different schemas, different robots. nothing is labelled, nothing is standardised, nothing is searchable. to actually use any of it you'd need to normalise it, time-align it, index it, make it queryable, embedded. the data bottleneck in robotics isn't scarcity. it's accessibility. the data is there. nobody can use it, fast, when they need it.

State of DePIN 2025: THE RESURRECTION