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> The LIDAR folks were wrong, basically.

According to who? Tesla? Because Tesla has a vested interest in trying to prove that they're right even if they're obviously wrong. That's why they constantly try to downplay failures, software issues, device issues etc.

I'm very confused by the attempts to discredit the usefulness of LIDAR. It's another tool you can use to improve the accuracy of your model. Sure, you can use a screwdriver, flip it around and use it as a hammer. But if you need to deal with nails, it's better to grab a hammer instead.



The causality goes the other way. The LIDAR claim was that Tesla's vision approach couldn't work. It did.


Tesla’s vision approach doesn’t work. There is a reason it requires a driver to actively prevent crashes and has a disengagement rate in the single digit miles [1].

All over this thread you keep making grand statements that “it works”, which is just completely false. It’s simple — if it worked, there would be no driver.

[1] https://www.teslafsdtracker.com/


Who made this claim? You keep making these grand statements but without linking to people or providing any proof.

Like there are going to be some environments where Tesla's vision is going to struggle, that's just a fact because you're relying on a more linear set of data. That's why you incorporate as many data points as possible for reasons other commentators have brought up. And I'm confused by how you qualify it as 'working', given we've seen multiple issues which are directly related to their vision approach.


Tesla has not solved self driving, and by all accounts never will with their existing compute and sensor stack.


Let's do a thought experiment: if Waymo could have seen 10 years ago how well FSD perception works today, would they have invested so heavily into LiDAR? Maybe the answer is still yes, because with the low volumes of vehicles they have they can afford to put it in, but it's not clear cut. If you could show FSD to ML/CV engineers 10 years ago their minds would have been completely blown. My mind is still blown by how well it actually works.




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