I'll know that we've achieved full self driving when it can brave thru the streets of a South American city :)
Welcoming our first riders in San Francisco
401–410 of 691 posts
Re: Welcoming our first riders in San Francisco
#402You cannot predict the future with patterns from the past, regardless of how many patterns you crunch - the world is always changing. ML can just never solve FSD - conceptual understanding and causality is needed to achieve human level driving capability. We instantly classify things conceptually from our perception, instantly understand how those things may behave, and then learn the specifics of what that thing is…
I think you uave some major misconceptions about how this stuff works. Most vision models output the current state of the world, to be integrated with other sensor data like lidar that is then used for planning. There are models that try to guess things like the crossing intent of pedestrians, but even those models just output a confidence of them crossing. I work for a different self driving company, but this high l…
Exactly, that is how that stuff works. Past patterns in the Ml neural net generated from massive data and training try to figure out the label of things from various sensors, and then given that label, try to figure out other things that might happen based on the label and event stream. These patterns can recognize with a certain probability similar patterns, but they have no way to cope with brand new patterns. Those brand new patterns, although they may only occur 1 out of 100 experiences - or lets say 3 days a year when your're driving, something fully novel occurs, this will kill you if you are relying on FSD. Until the systems try to think like humans, they simply wont.
Re: Welcoming our first riders in San Francisco
#403You cannot predict the future with patterns from the past, regardless of how many patterns you crunch - the world is always changing. ML can just never solve FSD - conceptual understanding and causality is needed to achieve human level driving capability. We instantly classify things conceptually from our perception, instantly understand how those things may behave, and then learn the specifics of what that thing is…
I think you uave some major misconceptions about how this stuff works. Most vision models output the current state of the world, to be integrated with other sensor data like lidar that is then used for planning. There are models that try to guess things like the crossing intent of pedestrians, but even those models just output a confidence of them crossing. I work for a different self driving company, but this high l…
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Re: Welcoming our first riders in San Francisco
#404“All rides in the program will have an autonomous specialist on board for now” This tells me that we’re still a long way from full level 4 (and certainly level 5) autonomy in a busy city like San Francisco. The edge cases requiring immediate human attention are still too frequent for the human safety driver to be remote, as is the case in Phoenix. Also, just a reminder that Waymo in Phoenix is nowhere close to being…
Note sure about the AGI requirement. The current systems will always need the heavy involvement of human intelligence to be able to rescue stuck cars, drive in new areas or monitor for changing driving conditions and update the driving model. There does seem to be at least some hope these systems will be able to run a true driverless taxi service with minimal geofencing. On the other hand, a human can go to a new country with different road markings, signage, rules, and traffic flows and be able to drive safely pretty much immediately or maybe a quick Google search. That would truly require AGI.
Re: Welcoming our first riders in San Francisco
#405Earlier quoted context omitted.
Unless it comes with the ability to eject participants, how would that help?
> Unless it comes with the ability to eject participants, how would that help? System locks all doors and calls police?
And if it turns out the thrashing of said car was an in-cabin fire? You just locked them in.
Re: Welcoming our first riders in San Francisco
#406Earlier quoted context omitted.
For the computer it doesn't make much difference if there's a passanger or if there isn't.
For a company having paying customers does matter a lot. Having customers paying for the R&D will help make it sustainable.
I suspect the revenue from passengers in this case looks like a rounding error. But the PR and feedback from early adopters is very valuable.
Re: Welcoming our first riders in San Francisco
#407Earlier quoted context omitted.
Surely this is just moving the goal posts. If they can launch in Chandler and in San Francisco then a huge amount of the contiguous United States is on the table.
Nope, not even close. There's a very specific reason they've picked Chandler, and it's that there's relatively little weather and the roads are fairly simple (among many other things specific to Chandler). The vast majority of the contiguous United States is decidedly not "on the table" as of now. "The contiguous United States" is still a decade (or more) away. It may literally never happen.
> The vast majority of the contiguous United States is decidedly not "on the table" as of now.
So the vast majority of the US has either significantly worse weather than SF, or a significantly harder ODD than SF?
Could you elaborate on that?
Re: Welcoming our first riders in San Francisco
#408Earlier quoted context omitted.
> It may not scale to rural areas though. Most products, including this one, don't need to do everything to be both useful and profitable.
So long as it is only urban areas it is a band-aid for the lack of good transit options. Not that you are wrong, just that you should be wrong because if cities actually had useful transit rural areas would be a much larger share of demand despite not having many people.
Very true, but retrofitting good transit into a city that didn't plan for it is extremely expensive and disruptive. I see these kinds of services being a great complement to public transit in cities that have struggled to make them attractive.
For example, I am way more likely to take Cal Train into SF if I can use a point-to-point service like Uber/Lyft/Waymo to get me the rest of the way there. Without that missing link, I'm much more likely to just give up and drive instead.
Re: Welcoming our first riders in San Francisco
#409“All rides in the program will have an autonomous specialist on board for now” This tells me that we’re still a long way from full level 4 (and certainly level 5) autonomy in a busy city like San Francisco. The edge cases requiring immediate human attention are still too frequent for the human safety driver to be remote, as is the case in Phoenix. Also, just a reminder that Waymo in Phoenix is nowhere close to being…
This tells me that you can show progress and draw magnifying glass criticism from people.
can only please some of the people some of the time.
Re: Welcoming our first riders in San Francisco
#410Earlier quoted context omitted.
I would suggest visiting r/idiotsincars sometime. Humans are terrible at reacting to situation outside of their experience, and essentially do random things all the time. If an AI system's default response is "come to a stop safely" then it's going to be way ahead of a lot of human "unexpected situation" handling in cars.
There are many situations where "come to a stop safely" is the worst possible thing you could do. Yes, people are bad at driving, because they don't pay attention, panic, make mistakes etc. But ML models tend to freak out at slight variations on mundane circumstances; a cyclist crossing the road at just the right angle and the wrong colour of bike, that sort of thing. The thing self driving cars need to avoid is kill…
> The thing self driving cars need to avoid is killing people in broad daylight for no discernable reason
This, I think, is the thing that people miss when they say "self-driving cars don't need to be perfect, they just need to be better than human-drivers, who aren't actually all that great".
From a public confidence perspective, it doesn't matter if a self-driving car crashes one tenth, one one-hundredth as often as human drivers; as soon as you see a self-driving car kill someone in a situation that a human driver obviously would have avoided (like in the adversarial image kind of scenario), you've totally destroyed any and all confidence in this car's driving ability, because "I would never, ever have crashed there."