[nelsonfavedra]

> but it seems like training actually uses radar data to help calibrate vision

They seem to use radar solely to automatically label data for training.

In the given example though where according to the vision system smog interrupted the persistence of the label for the leading car, I wonder if the use of radar data to persist the label is strictly necessary.

A car disappeared then reappeared in the data, why not just tween the bounding box over time and assume the car had always been there, like, if it looked the same when it reappears or something. An extra sensor just for labelling data seems silly.

[Robotbeat]

I don't think it's silly at all, although there are probably other ways to do it (license plates are a known size, so they could be used for calibration... to some extent). In fact, I think going to a sort of mapping solution where some portion of the Teslas on the road provide mapping data (using just calibrated vision) may be appropriate. If the reason you aren't using maps as an extra layer of capability is just because of the cost of mapping, then using Teslas to provide mapping capability "for free" is a good solution.

The argument may be that humans do fine without mapping, but that's not strictly true. Humans remember and anticipate the road based on past memory. When there's a change in the road due to construction, there's often a sign placed to warn drivers of the change in traffic pattern, showing that humans definitely at least partially rely on "mapping," so it could help even a pure vision system.

[jowday]

They use radar for way more than that given that Autopilot has it's capabilities limited in the new cars without radar vs. the old ones with radar.