I have no idea whether Tesla will or won’t succeed. But they do have one major advantage over just about every other AV company out there, which addresses the point above. That is, their huge network of camera-equipped cars (a million and counting) provides probably the deepest, richest AV learning dataset on the planet, and probably by orders of magnitude. If accessing the dataset and thus novel edge cases is one of the major challenges in AV development, Tesla is very well placed.
The issue is that if I paid a ton of money for something, I do generally expect to get what I paid for. And in this case that's not gonna happen.
[*] Hypothetically, I'm not presently a Tesla customer.
I've had 30 hours of driving in a Tesla, and I had to intervene 6 times, twice with no warning. That doesn't mean that Autopilot isn't a useful tool, but it does require operator diligence.
Umm, what? Source?
My quote was from a person internal to Uber. Below is a TC article citing a public report on US Data. Numbers in that are roughly 50/year, or a fatality in America every week. Every day may have been a stretch, but I'd guess you could deduce that Uber drivers worldwide are involved in a fatality accident at least every day.
*also - this is obviously a lower rate than non-Uber drivers per mile
https://techcrunch.com/2019/12/05/ubers-fatal-accident-tally...
Humans do it really well with just two cameras. It's not a hardware problem; it is entirely software. Whether self driving is possible or not with current AI techniques is debatable, but we're not waiting on any advances in hardware to do it.
If you don't mind, I think I'm going to steal that quote. It makes a really good point very succinctly.
It's a pithy response that undermines the challenge of a problem nobody has been able to solve even with years of effort and billions of dollars.
As the OP said, "it's not a hardware problem," in that the quality or number of cameras, sensors, etc. isn't the bottleneck to solving this problem.
That level of resolution doesn't matter at all for driving. People can drive just as well through a video feed, like Starsky was doing. Yes general AI does not exist yet, but my point is simply that the parent made a comment about the need for hardware which is simply not true.
I can tell you from experience this is false. It usually works, but when it doesn't you're fucked. People wildly underestimate, by orders of magnitude, how many and how complicated the edge-cases are for self-driving.
Has Elon musk invented artificial general intelligence? If not, the point isn't a good one at all.
This is because we're totally unable to come up with a coherent model for why the emergent behavior occurs given the input data and NN training. We know how individual elements of the NN work, and we can describe how the training system works. But the whole notion of repeatedly letting perturbations in a control value or control values dictate the entirety of the performance of a system is nuts.
The only way to determine how a NN will perform in a given situation outside of the training set is to actually feed it the stimulus and check the outputs. Given the amount of stimulus that we as drivers routinely get, it's impossible to say with any degree of certainty that a self-driving car that is built on an NN classifying engine will accurately classify everything in all situations and lighting conditions, because it's impossible to feed it a training set large enough to encompass those situations.
That leaves the question of making a classifier that is better than humans. And whether an NN is better than a human depends very much on the situation. We could make some statistical arguments, but when you're gambling with peoples' lives here it becomes difficult to tolerate such arguments. It's easy to be blase about it until it's your child chasing a ball in front of an AV, at which point any discussion of the statistics is academic.
What makes this challenging is that there are more such scenarios that might occur than there are grains of sand, or stars in the universe.
Those teams end up thinking they did all the necessary work and then go test, just to find out that there's a new edge case. At Starsky we called it Safety Theatre
FTFY. You can thank me later.
We don't fully know how the human hardware works either. Or rather, we don't fully know how the human hardware + software works.
> ...modifying the roads specifically for such cars, and segregating them from human drivers.
You were #this close# to answering your own question! Answer: https://boringcompany.com
Additionally, with highway-like vehicle spacing and high capacity stretched Model Xes (as the Boring Company proposed), the throughput is the same order of magnitude as a typical subway line. With denser spacing, potentially even higher.
Anyway, the question is about what Elon's backup plan was. This is it, regardless of whether it works or not. (And there's plenty of reason to think it won't, to be fair!)