Ten years doesn't sound sarcastic to me. With fully driverless operation starting in SF (and with several years in Phoenix), having it widely rolled out within ten years seems very plausible.
I'm glad that Cruise beat Waymo to driverless in SF because they are providing the swift kick in the butt that Waymo seems to require to actually make progress in a reasonable amount of time.
Their crash rate is 1 in 4.4 billion miles. That's crash, not a fatality. And it's getting better.
https://cleantechnica.com/2021/12/07/tesla-1-crash-per-4-41-...
Not with one version of the software. They are cheating: they should reset the mileage whenever they update the software.
Rider 1: I have 20 years experience riding a motorbike.
Rider 2: 20 years experience or 1 years "experience" repeated 20 times?
Waymo has 20 million miles IRL driverless, and 15 billion miles in simulated driving.
Fatalaties are not the only metric. Accidents are much more frequent and driverless cars have already proven they're safer in that regard.
Simulated miles are not convincing. Miles with a safety driver are better but still ultimately different. Also the type of miles matters too, and Waymo has been focusing on the easiest miles possible until Cruise forced them to up their game and try something a little more valuable.
Source? Because since 2020 Waymo has been primarily touting their "contact events" metric, which is what most people consider to be accidents.
Simulated miles are still better than no miles. Given the better accident rate it seems to contribute to a degree.
The point is that it's an argument from ignorance to narrowly focus on one metric and say we don't have enough information on whether autonomous vehicles are safe. We do have a range of metrics and information already that point to them being safer.
Provided your starting point is AV software with some ability to drive, this isn't necessarily true. Tuning on simulated miles can lead towards over-optimization for the conditions of the simulation.
https://youtu.be/gW6Wt2WQotY?t=232
https://youtu.be/o8rCOKSDMcg?t=60
There are countless other examples. It's one of the first things they bring up in almost every presentation to the general public. It's how they present themselves to the world, as the answer to traffic fatalities.
You may think it "ignorant" but the fact is that fatalities are going to be the single most important metric that the public and journalists and governments are going to focus on, and that's why it matters. The first few driverless car fatalities are going to be a huge, huge deal and are likely to result in action from all three branches of government. There will be court cases, there will be regulatory action, and there will be a lot of noise from politicians about laws and maybe even some laws passed about it. The first one already forced Uber out of the game.
As I understand it, they will only operate within a "grid". In other words, its use case will be limited to essentially a customized route city bus.
> widely rolled out within ten years seems very plausible.
Define "widely". We are decades away from a driverless car driving in snow.
I agree snow is a lot harder (I don't think it's decades, though). But the cases moritonal brought up mostly don't require that.
The mere fact that it won't panic on black ice is already a huge advantage. And it will have very detailed feedback to and from the traction control systems.
Parktronics routinely get covered by snow/slush/ice when driving.
When that happens I hit a button to turn on the defroster that then gets rid of the snow and ice.
Could they use a similar system?
Can I patent that?
What's the basis for your imagining? Whenever I read some strong "computer > human" statement like that, I can't help but think it's substantially based on science fiction (which can make technology work fantastically well because it's not real, e.g. like Six Million Dollar Man vs actual prosthetic limbs).
Also, have you heard about the time I was driving on the highway in winter weather, and my adaptive cruise control would stop working every few dozen miles because I had to get out and scrape ice off the sensor?
That doesn't really matter, because I was responding to the the sci-fi sentiment that "of course the computer must be better because computer." It doesn't matter if the humans are doing a poor job if the computer is still worse.
Especially because the claim is only about snowy situations. Even in a reply about snow, someone that thinks computers are automatically better would normally just say that directly.
Literally the two easiest places it could go into
So people should have been able to correctly predict how easy it would be for a computer to master go, right?
Said differently, I start from the assumption that some problems are obviously easy, some problems are obviously hard, and every other problem is somewhere in the middle. Self-driving is in the "obviously hard" bucket. Feel free to argue for where you think Go sits in the spectrum, but I would argue no board game is in the "obviously hard" bucket
Hard and easy defined as the ability to solve in a reasonable amount of time with the algorithms and computational models we have today or in the near future -- regardless of ~marginally increasing processing power.
Really? It seems to me that if people over-estimated the difficulty of an "easy" problem like mastering go, then they're even more likely to over-estimate the difficulty of a hard problem like self-driving. In fact, the over-estimation could scale up faster than linearly, if estimating two problems of size X is easier than estimating one problem of size 2X.
> with the algorithms and computational models we have today or in the near future
That's the thing. When predictions were being made about the difficulty of mastering go, people didn't have the algorithms and computational models that we have today. Similarly, predictions made today about the progress of self-driving cars may be lacking critical information about the algorithms and computational models that will be available in the near future.
Guess you missed this distinction.
If "customized route" counts any drive, then that's not really a limitation any more.
A lot of people were expecting electric cars to kick off right after that, so OP's claim is not unreasonable.
But: there are very large numbers of these edge cases and they are of the kind where new ones keep popping up all the time. This is a very easy problem for the first 99% or so and then the last 1% is super hard.
Indeed, and we aren't any closer compared to say 5 years ago. That is more or less my point: you can solve for some of this and then you are still left with a mountain more. And then at some point there is an even harder problem to deal with: how to ensure that fixing one problem won't regress one or more others.
That's just flat wrong.
And that may well require another leap of capabilities on the AI front, it might even require GAI. But you are entirely welcome to your own opinion, as I am to mine, but after watching the self driving industry since the 80's my timeframe is something like 25 years before fusion will arrive.
There may be some intermediary 'artificial artificial intelligence' solution where when stuck a remote driver can take over. But that has its own set of problems and I don't want to set this up as a strawman.
It's real progress. Anyone around Mountain View, or SF will have seen the progress with their own eyes. It's not a theoretical debate.
But that's the whole point: if this were a reality there wouldn't be a maybe there. So thanks for making my point.
"Materially closer" isn't the bar to cross the bar to cross is "It just works" which is for me what I'm getting at when I say that we are not 'closer', because it's a binary thing, arrival means 'it works' not that we have made some incremental change towards an ill defined goal.
The 'it works some of the time or even most of the time' bar was crossed years ago, but it needs to work all of the time.
I don't have a horse in this race, but I think what the other commenter was getting at is that: if there were 10 problems that needed solving 5 years ago, and in the course of solving those 10 problems you discovered 100 more than needed solving that you weren't initially aware of, then sure you got closer to the goal, but the progress was so tiny that it's almost not relevant.
I'm personally not arguing one way or another, but that's how I read the other person's comment.
I know the whole human flight is different to bird flight argument, so I guess we'll just have to wait and see how it all plays out. Exciting times :)
If the technology stagnates, the hardware stops improving, and the software stops getting better, then we would hit the limit pretty quickly.
> After all humans don't drive by analysing 1 frame at a time, we have a model of how the world works, we anticipate, we have intuition etc...
All self driving cars also maintain those models as well, and use frame by frame input to correct those models in real time (but they have already guessed where something is going to be 100+ frames from now).
In your view we are within striking distance of the moon, another couple of piles of stones and we are there. In my view, I'm not sure that it will just take more stones and not a better technology, and I'm beginning to lean more and more towards the latter because the problems that we were seeing 10 years ago we are still seeing today: more and more edge cases. And edge cases can be a symptom of a problem that is almost solved or it can be a symptom of a problem that is being solved using the wrong toolset, especially when there are lots of them and new ones keep popping up all the time.
Clear now?
And by the way: none of this is to imply that what has been done isn't impressive, the MB statement that they will accept liability if their software is in control of the vehicle is a step in the right direction and shows a lot of confidence. But it's incremental progress towards a goal that might not be reachable in that way.
Just come visit San Francisco and see the evidence. Look in the horse's mouth, so to speak. The cars are driving around a complex city, without a driver, and doing an amazing job. The progress is real.
Whether the grid is pre-mapped or not isn't particularly relevant. It's just how the technology works. The vehicles aren't driving on rails, they just have more semantic information about the world around them.
Fortunately, we also have a developing world where we can pay humans $2/hour to mechanical-turk tele-operate our 'mostly-working' AI.
Yet we're in 2022 and the best of the best image recognition systems spew out absolute nonsense no matter how much money is poured into them.
It's just the same sort of issue. It can work amazingly well 90% of the time, but the remaining 10% is basically impossible without some kind of actual general AI that can understand the context of what it's looking at. I honestly believe that current approaches to this tech will not get us to general self driving tech that is safe enough for use on our roads.
The Earth is big and complex, I can't see the singularity on the horizon yet, but my vision is aging.
I don't know that creating super-accurate species trees is really the most important problem to solve in biology, though. Certainly DNA sequencing for health has been a really mixed bag.
Ah, the old why bother since it's a "mixed bag" argument. If it wasn't a mixed bag I'd be really worried, as someone has some pretty good snake oil.
I vaguely recall something about sequencing and its role in creating a vaciine that turned out to be pretty useful, something recent maybe?
What i'm troubled by is the projects that sequence a million people, using $1B to do so, and then just dump a bunch of genomes with some hand-wavy claims about how it's going to cure cancer. The costs here are rathre significant, but the health outcomes are not.
On the other hand, most of the commercial jets we do fly are basically 1950s designs with bigger engines and some computers in the cockpit, and HN thinks it was crazily irresponsible for Boeing to have decided to use sensor-triggered autonomous systems to do something as simple as temporarily adjust the trim system...
Driverless cars in a European city center, during snow, ice and rain seems unlikely within 10 years. But we don't need that to see transformational change.
The fun thing about European cities is that many of them are extremely willing to make (to Americans) unthinkable changes to traffic patterns under their jurisdiction. I would not be the least bit surprised to see those downtown centers closed to all but driverless traffic (if they are not closed already).
BTW, humans are not ready for bad weather either, even though we drive in it all the time. However with driverless cars we will collect statistics proving it isn't ready and never noticing that it is better than humans.
I lived in Phoenix for nearly a decade. I moved there from the snow belt.
Teaching a car to drive itself in Phoenix is barely a step up from teaching it to drive in an empty parking lot.