41–50 of 187 posts
Earlier quoted context omitted.
Yes. This is exactly what LIDAR is for. This is the reason every single team in the 2007 DARPA Urban challenge that finished the race was equipped with a Velodyne laser. We knew it was a critical enabling technology 14 years ago, and it baffles me Tesla is eschewing it. Tesla's lack of this technology is the main reason I feel they will never achieve what they claim to without a huge breakthrough in AI.
What was their reasoning for not using Lidar?
I like Andrej and I think he's a brilliant guy. At the end of the day though, there is no way for me or anyone to audit the neural networks or their training data. How can anyone trust them? I think this is really a fundamental problem with using neural networks in self-driving cars--I don't want to put my life in the hands of a fragile system that I, and no one alive, can understand. We are being asked to close our…
That's why I think Tesla's approach is wrong. It tries to replicate a human driver. The argument against lidar is "we don't need a lidar to drive, our eyes and brain are enough". Yes, enough to kill thousands of people. You can easily find pictures of involuntarily camouflaged obstacles that take way too long for us to notice, and as expected, vision based system fail just like us, but lidar have no problem.
It is hard for computers to be as good as humans when it comes to vision. That's something our brain is exceptionally good at, and a large part of it is dedicated to it. But here, for true self driving cars to be a reality, they need to be way better than we are. It means that we should throw every advantage machines can have at the problem, and extra sensors are part of it, don't be limited to visible light cameras. lidar, radar, sonar, IR, inter-car communication, satellite maps, use everything.
And BTW, focusing on seeing roads is nice, but don't forget that there is more to driving that seeing roads. People communicate with their cars, sometimes in subtle ways, current self driving tech doesn't, and that's a big reason why they feel so alien and other drivers hate them. Self driving cars should communicate too, and better than humans.
Earlier quoted context omitted.
What was their reasoning for not using Lidar?
I think originally it was because of the cost of the equipment. Elon and team saw how expensive lidar was and thought they needed to be able to solve the problem without it. However lidar has dropped drastically in price, so at this point I think they aren't using it just for ego reasons (i.e., we claimed it was possible to get self driving without lidar in the past, so we have to continue down that path)
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"We trained a model, overfit on 1.4 trillion accident scenarios, and if behaved correctly on all of them."
Unless your model actually has trillions of parameters (and it doesn't, even gpt-3 only has 175 billion) it is not even possible to overfit on 1.4 trillion training inputs. You can't actually pigeonhole it.
Suppose you had 1.4 trillion examples in the following test set (using a model with 175 billion parameters):
(1,2)->3
(2,3)->4
(3,4)->5
...
Do you think it is possible to overfit and score perfect on the test set, while failing to generalize?
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> We are being asked to close our eyes, take a leap of faith Actually, you're being asked to "Always watch the road in front of you and be prepared to take corrective action at all times. Failure to do so can result in serious injury or death.", until FSD gets released :) Do you trust cab drivers to "be trained on every edge case under the sun"? Self driving only needs to beat humans, who have some serious flaws, not…
How can you know that it beats humans? You would have to drive tens of trillions of miles to have any worthwhile data on this, all the while putting humans at risk.
I might be completely wrong here, but hasn’t their collision incidents often been with weird things in the road such as sideways 18 wheelers and yellow lines heading into barricades? They’ve put lots of effort into tracking some pedestrian waaaaay over on the side passing behind trees, and that is really really impressive. But it seems to me the only reason it doesn’t hit a car in front on the road is because the neu…
The flip side of this is false positives: you don’t want a car slamming on the brakes because of a plastic shopping bag or other soft piece of trash lying in the road. This is a hard problem, regardless of technology employed.
On the other hand, you need the car to distinguish a mattress lying in the road from road markings. This is an easy problem if you have depth sensors, which brings me to my next point:
> But could someone help me understand why Teslas don’t just have the run of the mill Camry collision braking as a secondary measure independently?
Because for whatever reason (hubris?) Tesla insists on eschewing LIDAR/RADAR for 100% camera based systems. Not being able to explicitly sense depth is really kneecapping their system’s abilities.
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Would QA solve that problem? As in, "we replayed 1.4 trillion accident scenarios and our AI behaved correctly on all of them". Safety in numbers.
It depends. How many of those scenarios were in fog conditions? How many where a spotlight suddenly blinds some of the cameras? How many where a power line is down, or a manhole cover is missing, or a barn owl/hippo/bear is in the road? If we estimate that it takes 10e5 to 10e6 incidents of a certain type to appropriately train the network for that situation... it's just too difficult. Reality contains infinite edge…
I like Andrej and I think he's a brilliant guy. At the end of the day though, there is no way for me or anyone to audit the neural networks or their training data. How can anyone trust them? I think this is really a fundamental problem with using neural networks in self-driving cars--I don't want to put my life in the hands of a fragile system that I, and no one alive, can understand. We are being asked to close our…
> At the end of the day though, there is no way for me or anyone to audit the neural networks or their training data. How can anyone trust them? By external measurements and statistics. You measure an ML engine by performance. Literally no one anywhere knows how to debug these things by looking inside the model. If it's a "fragile system" then it will be shown to be so in data. At the end of the data, either cars cra…
Earlier quoted context omitted.
I think originally it was because of the cost of the equipment. Elon and team saw how expensive lidar was and thought they needed to be able to solve the problem without it. However lidar has dropped drastically in price, so at this point I think they aren't using it just for ego reasons (i.e., we claimed it was possible to get self driving without lidar in the past, so we have to continue down that path)
Also they marketed autonomous driving features as future software updates (including a discount/price hike for early/later adopters). Early adopters would be unhappy if future features required additional hardware.