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by fastball 1136 days ago
I think the overlooked part is "seamlessly integrate". Signal to noise ratio is important, and it is not trivial to "just add sensors". I think the analogy of "too many cooks in the kitchen" applies here.
3 comments

I think the keyword you’re looking for is ‘sensor fusion’, which apparently is only a problem for Tesla because the others have figured it out years ago. Perhaps there is a talent gap at Tesla or an unwillingness to invest in it. They generally avoid having to do anything that’s hard and try to look for shortcuts.

Case in point: the whole radar removal and reintroduction flip flop. It seems like they don’t believe themselves that cameras are sufficient.

I don't think anyone has "figured it out" if they still don't have unconstrained driverless cars.
That’s tangential to your original point of discussion which was sensor integration. Sensor fusion is absolutely a solved problem. Autonomous driving requires more than just sensor fusion though.
It's not tangential at all. If the purpose of these sensors is for autonomous driving, and "solving" sensor fusion hasn't gotten you there, how can you possibly say it is a solved problem? Sensor fusion (in this context) is not solved until you are using fused sensors for autonomous driving.
Why are you equating sensor fusion with solving the entirety of autonomous driving? That’s disingenuous. You understand sub problems can be solved, right? Sensor fusion is just combining different sensor inputs so you have high confidence in your object detection and you’re not “confused with disagreements” as Tesla likes to say. Self driving involves solving prediction and planning problems too, not just sensor fusion.
I'm not equating it with solving the entire problem, I am pushing back against the idea that autonomous driving can be sub-divided into completely discrete sub-problems. So I guess you could say no, I do not understand that sub-problems can be solved.

Object detection is inextricably linked with prediction which are both inextricably linked with planning.

Indeed. Ultimately humans do it remarkably well with just vision, too, when they’re not intoxicated, distracted, or falling asleep.
Yeah, adding sensors can sometimes make things worse.
Example? There are plenty of examples where mistakes that Tesla's cameras make (being blinded by the sun, having trouble with emergency vehicles) are no problem for systems with more sensors.
This talk was worth watching (any Karpathy or Carmack talk is imo): https://www.youtube.com/watch?v=g6bOwQdCJrc

Specifically this is the relevant part: https://youtu.be/g6bOwQdCJrc?t=1370

They removed radar because it was making things worse.

I interpreted that statement by Karpathy as an accidental admission of Tesla's own limitations and not of the approach itself. (Note: I'm upvoting all your comments because they're very reasonable and supported.)