[gonehome]

I think Tesla does use Lidar in training for what it's worth (at least I recall someone telling me this - I think it was a friend that worked there but not 100% sure I'm remembering correctly).

It's possible the lidar approach only really works with up to date high resolution maps and without that you end up in a local max you can't really escape with that approach.

That's been Tesla's argument up to this point anyway and I don't think the success in cities really proves things either way.

It may not matter since robotaxis in cities is still worth a lot and highway driving is mostly a solved problem.

True full self driving though will probably require solving vision - in that case I think the argument that lidar is a local max could very well be true.

[ra7]

> It's possible the lidar approach only really works with up to date high resolution maps and without that you end up in a local max you can't really escape with that approach.

Sorry, but you’re just repeating Elon Musk’s buzzwords like “local maximum”. It doesn’t make sense. There’s no such thing as “lidar approach”. All sensor inputs are fused (early/late fusion) and run through perception algorithms. Lidar is used for localization with maps, but that’s not even its primary use (that’s object detection). And it does not require maps to be up to date either.

[xnx]

I expect Tesla's rationalization will suddenly change when the cost for lidar units drops to hundreds of dollars. At that point, Waymo will have a huge head start.

[ra7]

Lidar cost has already dropped a lot. Waymo’s lidar on their I-Pace is 90% cheaper than the previous gen. We’re also seeing car manufacturers (GM, Volvo/Polestar, Mercedes, Chinese OEMs) include inexpensive lidar units for driver assistance.

Tesla’s problem is that they’ve promised their existing cars on the road are capable of full self driving. They can’t add hardware to them, so they will maintain the “camera is sufficient” stance for a long time.