That's exactly what Tesla is doing with their validation vehicles, the ones with Lidar towers on top. They establish the "ground truth" from Lidar and use that to train and/or test the vision model. Presumably more "test", since they've most often been seen in Robotaxi service expansion areas shortly before fleet deployment.

> you should theoretically be able to take the output of the Lidar + Cameras model and use it as training data for a Camera only model.

Why should you be able to do that exactly? Human vision is frequently tricked by it's lack of depth data.

No, I don't think that will be successful. Consider a day where the temperature and humidity is just right to make tail pipe exhaust form dense fog clouds. That will be opaque or nearly so to a camera, transparent to a radar, and I would assume something in between to a lidar. Multi-modal sensor fusion is always going to be more reliable at classifying some kinds of challenging scene segments. It doesn't take long to imagine many other scenarios where fusing the returns of multiple sensors is going to greatly increase classification accuracy.

Sure, but those models would never have online access to information only provided in lidar data…