What irq11 has said is valid and important. You cannot just handwave actual engineering problems with some buzzwords
It's valid and important to say, "I have experience in this field and sensor quality will always be more important than a suite of regression tests, no matter how large".
It's not valid and important to say, "You're just saying that because you like Elon Musk, and read an article about 'big data' once"
It would be a perfectly reasonable response to my comment to say "why yes, I do, and here's my evidence (along with a great reason that I didn't provide it in my original comment!)"
It stands to reason that if the parent had a better argument than "test-driven development on steroids", then they'd have provided it. But asserting that someone's well-informed comment about sensor quality "underestimates" the power of big-data-AI-TDD-learning-rapid-innovation-foo, well, that sounds like magical thinking.
In any case, this is a meta-discussion about voting, which is definitely not okay, so I'll leave it at that.
Here's Mobileeye's CTO talking in detail about their technology.[1] They use a a deep neural network that recognizes cars. Just cars. Look at this point in the video.[2] There's a stationary obstacle on the left, and it doesn't recognize that. Maybe this is why Tesla, using Mobileye hardware, plowed into three different stationary vehicles at the left of a highway. They were all trucks (one was a street sweeper), and seen from the back while stationary, may not have matched the trained model of "car".
Mobileeye's algorithms are good at recognizing moving cars from most angles, and that's valuable for feeding into the model of "what's the other player doing". But it's not enough for the "where are all the obstacles" and "where is the road surface" questions. Those questions have objective answers, which can be answered with a LIDAR, and maybe millimeter radar if it has the angular resolution.
[1] https://www.youtube.com/watch?v=GCMXXXmxG-I [2] https://youtu.be/GCMXXXmxG-I?t=1758
The existing sensor suite was is sufficient for the existing driving assist functions. The existing suite was never expected to be sufficient to provide the predicted, future levels of autodrive.
What do human sensors cover? Primarily our eyes. Have we had sensors that provide about the same dynamic range as our human vision?
I am NOT a part of this field, so please excuse my presumption.
I believe that most/all(?) current/previous 'automated control' systems used sensors that were lower resolution than our eyes, but that also provided some indication of range data.
Do our eyes provide distance data? I think that data is calculated with quite a bit of accuracy in our brains.
Again, I'm not part of this field, so this is just speculation.
In theory, given a fast enough computer and advanced enough algorithm, given nothing but visual input streams no more advanced than are available with existing optics, could a car autopilot not be just as good a driver as a human?
Do you have any basis for that statement, other than that you like Elon Musk, and read an article about "big data" once?
I have actual experience in this field. The parent is right: the sensors matter more than hypothetical gains from "big data". Because right now, sensors suck. There's a reason every serious player in this game is plopping pairs of $10,000 lidar units on their test cars (and still failing to work in the rain). You can't distinguish signal from noise by collecting more noise, and until you have a decent sensor suite, "big data" is just garbage-in, garbage-out.
Reading this discussion, you'd almost forget that the reason Tesla is doing this is because its existing sensor suite was proven to be a total joke in actual use...but hey, here's to the emperor's new outfit! One hundred percent less naked than the old one!