collecting real world data for physical ai comes with a privacy challenge that is easy to overlook a phone can capture a warehouse or street in detail, but what happens when people and license plates enter the frame? thats what makes the approach from @vangrid_io interesting the capture process is designed to detect faces and plates on the device and blur them before the video is encoded according to the documentation, the original unblurred frames never leave the phone, and buyers receive the reconstructed 3d model rather than the source footage that means privacy protection is built into the collection process instead of being left entirely to a server side cleanup step for physical ai, this could make it easier to gather useful ground level views of places that robots need to understand without unnecessarily exposing identifiable details but the implementation matters as much as the idea faces can enter the camera view unexpectedly, and a privacy filter needs to handle those moments reliably throughout the recording one detail im still curious about is what happens when someone walks into the frame halfway through a capture does the on device system consistently detect and blur them before the footage can be submitted, including during sudden movements or difficult lighting? thats an important question because privacy protection needs to work throughout the entire capture, not just under ideal conditions @quipnetwork