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Robustness is a key property of the methods and models used in self driving cars. For a human, the noise isn't bad recognition, it's corrupted sensor data via
by nkozyra 9y ago
Robustness is a key property of the methods and models used in self driving cars.
For a human, the noise isn't bad recognition, it's corrupted sensor data via distraction. It's one of the most common causes of accidents. For the AI agent an elephant will never appear unless it's been trained to be recognized. More likely it's recognized as an obstacle, which is ok. But keep in mind that years of Google's autonomous vehicle success make this pretty improbable, certainly less than in the average driver.
Much of the fear here is irrational and natural when humans lose control.
- TeMPOraL 9y agoI'm not trying to express a fear that comes from humans losing control. I don't fear that - in fact, I can't wait until the day comes no humans are allowed to drive on public roads. I was just answering about the concerns of self-driving systems relying solely (or primarily) on visual data from cameras. It's true this is how humans drive, but human visual system is much more complicated than what the current (published) state of the art in image processing seems to be. I do not trust visual-only systems today (especially if they employ deep learning shenanigans). I know those problems aren't insurmountable, but I'd feel much safer if they threw in a LIDAR there too.
- nkozyra 9y agoWhile I'm sure more sensors gives a better chance at consensus I don't think relying solely on visual data is a problem if done well (low false positive false negative rate, comprehensive trained, fault tolerant)