Continuous Generation, Inference Loops, and the Return of Real Grounding

A few video labs stopped treating a clip as a finished object. The model keeps generating. That changes the data problem more than it changes the demo.

A dataset is a snapshot. A loop drifts unless the world keeps showing up: rooms, hands, tools, the dull minutes between the useful ones. Retrieval used to be the whole answer to grounding. It isn’t, once the model is supposed to stay in a place.

If you don’t have that footage, another generic pack will not fix the drift. You commission the capture. You write the rubric before the camera is on. You keep consent and chain of custody on the file, not in a folder someone promises to send later.

Harbor’s side of this is plain. If the data is not on a shelf, we go get it. Prompt-to-Earn is a different door: people talking to Harbor-1 and choosing to send the thread in. Useful. Not a robotics programme. The funds are separate. The jobs are separate.