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Yeah, but Google's vision + lidar tech also doesn't seem any better at solving it either. They have been working on this problem the longest and they aren't eve

Yeah, but Google's vision + lidar tech also doesn't seem any better at solving it either. They have been working on this problem the longest and they aren't even confident enough to produce a product with it. Google is probably the leader in AI and AI research. They are also the leader in data and mapping. They have billions of cash to play with. Yet it seem like they haven't gotten any closer at solving this problem as well. They are just going about it better but not trying to selling it. Any reason why everyone seems to be stuck on this problem?

Barrin92 4y ago
>Any reason why everyone seems to be stuck on this problem? ML maximalism focused on the narrow problem of 'solving driving' while not recognizing that any task as complex as driving requires probably something closer to general intelligence, and theoretically the field has been impoverished in favor of "throw more graphics cards at everything".
- hn_throwaway_99 4y ago
  Couldn't agree more. Especially when it comes to city driving, which would obviously be necessary for robotaxis, when AI zealots promise "it'll be here in a year or two", I always wondered "Have these people ever driven in the city?" I mean, to drive in a city, you basically: 1. Need to understand all standard signage (seems possible with AI). 2. Need to understand all "unstandard" signage (not sure how possible). 3. Need to understand the cop with the thick NY accent yelling at you saying "Can't you see there's been an accident and the road is covered with glass you dufus? Turn the F around." I can certainly see AI solving the problem of driving in specially designed limited access highways (which could also support normal human drivers), and that alone would be a huge benefit, but I never saw how so many were willing to make the leap to "robotaxis that can drive you anywhere in the city."
  - dmd 4y ago
    4. Need to understand the cop who is directing people into lanes by jutting his chin subtly in different directions when you make eye contact with him 5. Need to understand that occluded objects have not vanished from the universe never to be seen again
    - naijaboiler 4y ago
      6. Need to reasonably predict what that human that just made eye contact with you would likely do next, and how that's different from what he might do when he doesn’t make eye contact with you. And all of that differs if you're in NYC or SF or small town, Indiana
      - dibujante 4y ago
        7. Need to understand that drunk person staggering along the roadside has been repeatedly slipping off the sidewalk and there's a non-zero chance they trip and fall right in front of you.
        dekhn 4y ago
        This is a dance move known as the "tenderloin lurch". Well, not really, the Tenderloin Lurch is when a person staggers up to a crosswalk, waits until they have a NO WALK sign and proceeds to cross, while ignoring all the drivers who about to run them over.
        uoaei 4y ago
        I sincerely hope you are not this unpleasant in social settings.
        dekhn 4y ago
        when I float that joke in social settings in SF, everybody nods sagely
        4y ago
- highwaylights 4y ago
  Even then, even if you can solve every case involving actual roads with perfect markings and intact signs and functioning signals, I’ve found myself just this week: - driving across an unmarked grassy mound to park a car at a store in their designated area. - paying a fee with coins to enter and exit a toll road. - stopping to move around roadworks based solely on hand signals from one of the workers. These aren’t even scratching the surface in terms of edge cases that could be encountered regularly.
- steveBK123 4y ago
  Agreed. People point at statements like "it just needs to drive better than the average driver" and "well lots of idiots drive". On the flip side, lots of intelligent people with other skills do not have the confidence & comfort to drive outside of their towns local roads, or at all. There are problem sets for ML like quant trading or phone album image tagging where you just need to be right 51% of the time to make money / be novel & useful. We've seen plenty of examples showing ML is not appropriate for life&death problems like being the primary reviewer of diagnostic imaging for cancer screening. The bar for ML to drive a car is much much higher, and I'm not even sure we have the right sensor suites feeding into the models, not to mention the compute capacity to operate at low enough latency.
Jabbles 4y ago
> doesn't seem any better at solving it I thought they had real self-driving taxis in Pheonix that you can order? Real ones, with no safety driver. That definitely sounds "better", even if it is heavily geo-fenced.
- impulser_ 4y ago
  Yeah, but I am sure Tesla's software can do the same. Depending on the route, you could probably even do it with comma.ai hardware. When I think of FSD, I think any route under any condition.
  - kadoban 4y ago
    > Yeah, but I am sure Tesla's software can do the same. They absolutely cannot. They won't even try, they require a driver to be there to be ready to take over with no notice. Their software also makes so many basic mistakes that even what they're allowing it to do is dangerously reckless.
- jowday 4y ago
  They’ve also got real ones with no safety driver in San Francisco right now.
- espadrine 4y ago
  Waymo has superior performance based on their historical statistics. It makes sense, since their lidar sensors capture more of the environment, and directly in 3D. Their AI also seems better QA’ed. The Tesla AI Day[0] surprised me as it showed they only had a simple architecture for a very long time, simply feeding barely processed camera pixels to a DNN and hoping for the best with little more than supervised learning off human feeds. Their big claim to glory was that they rearchitectured it to produce a 2D map of the environment… which I thought they had years ago, and is still a far cry from the 3D modeling that is needed. After all, sure, we humans only take two video feeds as input… But we can appreciate from it the position, intent, and trajectory of a wealth of elements around us, with reasonable probability estimates for multiple possibilities, sometimes pertaining to things that are invisible, such as kids crossing from nowhere when near a school. Cruise also seems to have better tech; they had a barely-watched 2h30 description of their systems[1] which shows they do create a richer environment, evaluate the routing of many objects, and train their systems on a very realistic simulation, not just supervised training, which means it can learn from very low-probability events. They have a whole segment on including the probability that unseen cars may travel from perpendicular roads; Tesla’s creeping hit-or-miss are well-documented on Youtube. [0]: https://www.youtube.com/watch?v=j0z4FweCy4M https://www.youtube.com/watch?v=j0z4FweCy4M [1]: https://www.youtube.com/watch?v=uJWN0K26NxQ https://www.youtube.com/watch?v=uJWN0K26NxQ
alphabetting 4y ago
There's been a lot of progress despite AVs not meeting intitial hyped predictions. Waymo and Cruise are operating driverless robotaxis in SF. We're probably a couple years from many major cities having them.
tootie 4y ago
Probably because it's really, really, really hard to solve the thousands of edge cases that occur in real-world driving situations. I don't think FSD happens until government gets behind it and starts putting infrastructure behind it. If we start building roads (and cars) to be highly visible to AI one way or another, it all becomes much easier.
- aaaaaaaaaaab 4y ago
  >If we start building roads (and cars) to be highly visible to AI one way or another, it all becomes much easier. Or we could build 1-dimensional roads, which would make the AI's jobs much easier. Like, we could put down two parallel piece of metal, which vehicles could "hook" onto somehow...
cco 4y ago
I paid ~$10 for two rides after signing up as a regular ole user in Mesa AZ. It was great, the first ride was a bit nerve wracking, but the second felt very nice. I certainly wouldn't argue with you that it isn't ready for prime time and wide distribution, but it is interesting to see their progress in San Francisco, a much different driving problem. If it takes them 10 years to get to prod in Mesa, two (maybe three?) in SF, maybe they start shrinking that a lot in metros without winters. ¯\_(ツ)_/¯
dreamcompiler 4y ago
Because self-driving has a bunch of tricky edge cases and most of them will kill people. Problems with hundreds of important edge cases cannot be solved by simply throwing more training data at the problem; that's how you solve AI problems in a "dumb" manner, and it works for lots of problems (like recognizing dogs in images) -- but not for self-driving. To solve the self-driving problem we need "smart" A.I., which means we have to approach it with systematic engineering, and the solution will probably involve some combination of better sensors, introspectable neural nets, symbolic A.I., and logical A.I.
- function_seven 4y ago
  I remain convinced that "real" self driving (as in: go ahead and sleep in the backseat) will never happen without changes to road infrastructure and possibly some sort of segregation between robot-driven cars and people-driven cars. Things like traffic signals that actively communicate their status to nearby robot cars (more than just a red lamp that can be occluded by weather, other vehicles, or mud on the camera lens). Or lane markings that are more than just reflective paint, but can be sensed via RF. Rules around temporary construction that dictate the manner of signage and cone placement that the robot cars can understand. The cones might have little transponders in them, I don't know. But without a massive leap forward in AI capability, our current road system—optimized for human drivers over the past century—is not going to work. If we can't make the cars just as smart as an alert and capable driver, then maybe we need to meet halfway and make the roads a littler "dumber" (simpler) to accommodate the robots.
  - highwaylights 4y ago
    What if we just, you know, walk a bit more instead? Or even cycle? I hear great things.
    - actionablefiber 4y ago
      The pattern of zoning and development that the U.S. has used for the past 70 years assumes that nobody wants to walk or cycle anywhere and that they feel so strongly about it that they want cities to be built such that people will die if they attempt to do so. I grew up in a neighborhood where the elementary school was about half a mile away... on the other side of a five lane highway with no crosswalk and no sidewalk on the other side. Zero chance to assert your independence as a kid. Zero chance to live responsibly as an adult. A part of the reason people wish they had FSD so badly is because they want to be rescued from this fundamental failure of NA-style urban planning that necessities driving, all the time, across both short and long distances.
sonofhans 4y ago
Driving is a social problem, not a technical one. It's functionally the same as walking down a crowded sidewalk. The car is just a tool, just an extension of our bodies. We can't build a robot which can walk down a sidewalk without running into people either. The sensor tech and mapping fidelity are red herrings. People drive well because only people are good at predicting human behavior.
- raydiatian 4y ago
  Sort of. Your wording actually assumes down to its core that driving is inherently social, when in fact I think it may be only provisionally social. Driving currently “is social” in a few senses, But of course the important (and obvious) one is that it currently involves accounting for human-operated vehicles. Alternatively, an autonomous vehicle operator in a homogenous network full of other autonomous operators has capabilities and characteristics that greatly simplify failure modes. Maybe even majority autonomous, partially heterogeneous? You can literally slow or stop the whole show to deal with a catastrophic event. It’s still “social” but probably much reduced from the scenario where you’ve got the full scope of human expressivity behind the wheel. The REAL problem is how do we take our roads to the crossover point where those simplified network features become accessible.
  - aidenn0 4y ago
    This assumes that roads are used exclusively by autonomous vehicles, when our roads are not used exclusively by motor vehicles to begin with.
    - raydiatian 4y ago
      > “This assumes our roads are used exclusively by autonomous vehicles” I not only assume it, I say it out loud: “[fully autonomous, …] maybe even majority homogenous, partly heterogenous?” > “When our roads are not used exclusively by motor vehicles to begin with.” I’m not following what you’re saying here in the context of the earlier clause. If you mean not used exclusively by autonomous vehicles, yes, and that’s why I’m pointing out the provisional aspect.
rsynnott 4y ago
> Any reason why everyone seems to be stuck on this problem? Because it's really, really difficult. A lot of AI-ish stuff pretty rapidly gets to the point where it _looks_ quite impressive, but struggles to make the jump to actual feasibility. Like, there were convincing demos of voice recognition in the mid-90s. You could buy software to transcribe voice on your home computer, and people did. And, now, well, it's better than in the mid-90s certainly, but you wouldn't trust it to write a transcript, not of anything important. Maybe in 2040 we'll have voice recognition that can produce a perfect transcript, and human transcription will be a quaint old-fashioned concept. But I wouldn't like to bet on it, honestly. And voice recognition is arguably a far, far easier problem.
- UncleOxidant 4y ago
  I'm old enough to remember all the breathless pronouncements in 2015 about how self-driving cars would be everywhere within 5 years. I was skeptical then and I'm still skeptical that it will ever happen outside of some limited range of well known paths that have been pre-determined to be safe - ie we'll have (and we do have) some self driving cars but they'll essentially be on a closed course and will not leave the course. There are already some small bus lines like that - the bus just goes around a closed circuit picking up and dropping off people always taking the same route.
  - sorry_outta_gas 4y ago
    we're still trying to convert to electric, self dirving is far out there
    - xnx 4y ago
      These are mostly unrelated. Some of Waymo's vehicles are ICE.
      - sorry_outta_gas 4y ago
        My mistake, I trying to imply to `mass adpotion of` and bungled it
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turzmo 4y ago
We often can figure out how to take a product that works 90% and bring it to 99%, and then to 99.9%. The engineering challenges involved in each nine are often vastly more than the percentages indicate, but they're conceivable. With AI we have absolutely no idea how much effort might be required to get to that next level of reliability. We hope that bigger models, or better AI technology might get us there, but there's also a chance that they won't.
relueeuler 4y ago
Zoox has solved it.
- AlotOfReading 4y ago
  Has Zoox even gotten the permits to do fleet-scale driverless testing? Last I heard, they were still limited to 2 vehicles on specific streets in foster city. Doesn't seem very solved.
deleted 4y ago
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toss1 4y ago
Google/Alphabet is stuck and will make advances in specific territories but will never get there without a fundamental change in approach. Their approach relies on very detailed mapping/modeling of specific terrain, so they can make a usable case sooner, but outside of the map/model territory, they're literally lost. And maps/models change constantly and rapidly. Tesla is taking a fundamentally more broad and deep approach - working with the fundamental fact that a pair of visual sensors and a compute engine (eyes & brain) can successfully figure out driving in strange areas in real time, ergo, it should be possible without a map/model or lidar. Once they get it solved, it will be solved once and for all. Bigger gamble, bigger payoff. Equipping the car with dozens of eyes is the easy part. The question is whether enough compute power can be brought to bear on solving the recognition problems, and the edge cases. They have obvious issues with failing to recognize large objects like trucks in unexpected orientations, left turns etc. Using millions of miles of live human driver data as a training set is great, except that the average driver is really bad, so it's entirely polluted with bad examples, ESPECIALLY around the edge cases that get people killed. There, examples from professionally trained drivers, who really understand the physics and limits of the car, adhesion, traffic dynamics, etc, are what you want to train on, but that isn't what they have. It is also possible that even if the set of training data would actually be sufficient, the big question will kill them - perhaps the solution requires orders of magnitude more compute power to approach human performance, and they just don't have the hardware to simulate human compute power. So, have they just hit the limits of what their compute power can do? I think Tesla's approach is fundamentally the way to go, as it is a general solution, compared to everyone else's limited map/model approach. But both may require either or both a more specifically programmed higher-level behaviors, and/or something much closer to AGI than exists, something that has actual understanding of the machine-learned objects and relationships, which does not yet exist (if one is known, pleas correct me - I'd love to know about it).
Animats 4y ago
Waymo and Cruise routinely have driverless cars on city streets. In California, all collisions, however minor, have to be reported, and DMV posts them on their web site.[1] Most are very minor. Here's a more serious one from last month: "A Cruise autonomous vehicle ("Cruise AV") operating in driverless autonomous mode, was traveling eastbound on Geary Boulevard toward the intersection with Spruce Street. As it approached the intersection, the Cruise AV entered the left hand turn lane, turned the left turn signal on, and initiated a left turn on a green light onto Spruce Street. At the same time, a Toyota Prius traveling westbound in the rightmost bus and turn lane of Geary Boulevard approached the intersection in the right turn lane. The Toyota Prius was traveling approximately 40 mph in a 25 mph speed zone. The Cruise AV came to a stop before fully completing its turn onto Spruce Street due to the oncoming Toyota Prius, and the Toyota Prius entered the intersection traveling straight from the turn lane instead of turning. Shortly thereafter, the Toyota Prius made contact with the rear passenger side of the Cruise AV. The impact caused damage to the right rear door, panel, and wheel of the Cruise AV. Police and Emergency Medical Services were called to the scene, and a police report was filed. The Cruise AV was towed from the scene. Occupants of both vehicles received medical treatment for allegedly minor injuries." Now, this shows the strengths and weaknesses of the system. The Cruise vehicle was making a left turn from Geary onto Spruce. Eastbound Geary at this point has a dedicated left turn lane cut out of a grass median, two through lanes, a right turn bus/taxi lane, and a bus stop lane. It detected cross traffic that shouldn't have been in that lane and was going too fast. So it stopped, and was hit. It did not take evasive action, which might have worked. Or it might have made the situation worse. By not doing so, it did the legally correct thing. The other driver will be blamed for this. But it may not have done the thing most likely to avoid an accident. This is the real version of the trolley problem. [1] https://www.dmv.ca.gov/portal/vehicle-industry-services/autonomous-vehicles/autonomous-vehicle-collision-reports/ https://www.dmv.ca.gov/portal/vehicle-industry-services/auto... [2] https://earth.google.com/web/@37.78169591,-122.45337171 https://earth.google.com/web/@37.78169591,-122.45337171 [3] https://patch.com/california/san-francisco/speed-limit-lowered-parts-geary-boulevard https://patch.com/california/san-francisco/speed-limit-lower...
- ryantgtg 4y ago
  > In California, all collisions, however minor, have to be reported. Just to be clear, this statement only applies to AVs, right?
uoaei 4y ago
> Any reason why everyone seems to be stuck on this problem? Because they're all trying visual- or line-of-sight methods only, I call this the "robo-human" fallacy in ML: trying to automate the processes that humans undergo so that you eventually have a drop-in replacement for a human. But that is a myopic and unimaginative approach because you could be re-assessing the system itself and eliminating inefficiencies that lead to poor performance. In the autonomous vehicles space, there is massive potential for self-organizing swarm algorithms to control pelotons of cars, rather than individual cars with no intrinsic sense of the general flow of traffic. You wouldn't need a top-down "commander" style architecture, it could be designed so that cars only talk to their immediate neighbors and emergent patterns keep traffic flowing smooth and fast. I have always been skeptical of the attempts to reduce the amount of information about the road that a car receives. (Moving from stereoscopic to monocular vision to save the cost of one camera seems just stupid.) But people who dream of "smart cities" really seem to see little more than The Jetsons in their mind, and it limits the scope of research to our detriment.
- dlkf 4y ago
  I’d like to hear an actual response from the people downvoting this comment. It’s an interesting perspective, and while I can imagine legit criticisims (SPOF, privacy concerns, coordination with vehicles outside the system, etc) actually articulating them would yield a more productive discussion than downvoting without comment.
realitysballs 4y ago
Answer me this; How is AI supposed to confidently distinguish a real stop sign from someone/something holding up a picture of a stop sign? Yes, this is a weird edge case, but I think it gets at the core issue being that it takes way more sophistication to release this tech into the wild then ppl would like to admit.

Barrin92 4y ago

>Any reason why everyone seems to be stuck on this problem? ML maximalism focused on the narrow problem of 'solving driving' while not recognizing that any task as complex as driving requires probably something closer to general intelligence, and theoretically the field has been impoverished in favor of "throw more graphics cards at everything".

hn_throwaway_99 4y ago
Couldn't agree more. Especially when it comes to city driving, which would obviously be necessary for robotaxis, when AI zealots promise "it'll be here in a year or two", I always wondered "Have these people ever driven in the city?" I mean, to drive in a city, you basically: 1. Need to understand all standard signage (seems possible with AI). 2. Need to understand all "unstandard" signage (not sure how possible). 3. Need to understand the cop with the thick NY accent yelling at you saying "Can't you see there's been an accident and the road is covered with glass you dufus? Turn the F around." I can certainly see AI solving the problem of driving in specially designed limited access highways (which could also support normal human drivers), and that alone would be a huge benefit, but I never saw how so many were willing to make the leap to "robotaxis that can drive you anywhere in the city."
- dmd 4y ago
  4. Need to understand the cop who is directing people into lanes by jutting his chin subtly in different directions when you make eye contact with him 5. Need to understand that occluded objects have not vanished from the universe never to be seen again
  - naijaboiler 4y ago
    6. Need to reasonably predict what that human that just made eye contact with you would likely do next, and how that's different from what he might do when he doesn’t make eye contact with you. And all of that differs if you're in NYC or SF or small town, Indiana
    - dibujante 4y ago
      7. Need to understand that drunk person staggering along the roadside has been repeatedly slipping off the sidewalk and there's a non-zero chance they trip and fall right in front of you.
      - dekhn 4y ago
        This is a dance move known as the "tenderloin lurch". Well, not really, the Tenderloin Lurch is when a person staggers up to a crosswalk, waits until they have a NO WALK sign and proceeds to cross, while ignoring all the drivers who about to run them over.
        uoaei 4y ago
        I sincerely hope you are not this unpleasant in social settings.
        dekhn 4y ago
        when I float that joke in social settings in SF, everybody nods sagely
        4y ago
highwaylights 4y ago
Even then, even if you can solve every case involving actual roads with perfect markings and intact signs and functioning signals, I’ve found myself just this week: - driving across an unmarked grassy mound to park a car at a store in their designated area. - paying a fee with coins to enter and exit a toll road. - stopping to move around roadworks based solely on hand signals from one of the workers. These aren’t even scratching the surface in terms of edge cases that could be encountered regularly.
steveBK123 4y ago
Agreed. People point at statements like "it just needs to drive better than the average driver" and "well lots of idiots drive". On the flip side, lots of intelligent people with other skills do not have the confidence & comfort to drive outside of their towns local roads, or at all. There are problem sets for ML like quant trading or phone album image tagging where you just need to be right 51% of the time to make money / be novel & useful. We've seen plenty of examples showing ML is not appropriate for life&death problems like being the primary reviewer of diagnostic imaging for cancer screening. The bar for ML to drive a car is much much higher, and I'm not even sure we have the right sensor suites feeding into the models, not to mention the compute capacity to operate at low enough latency.

Jabbles 4y ago

> doesn't seem any better at solving it I thought they had real self-driving taxis in Pheonix that you can order? Real ones, with no safety driver. That definitely sounds "better", even if it is heavily geo-fenced.

impulser_ 4y ago
Yeah, but I am sure Tesla's software can do the same. Depending on the route, you could probably even do it with comma.ai hardware. When I think of FSD, I think any route under any condition.
- kadoban 4y ago
  > Yeah, but I am sure Tesla's software can do the same. They absolutely cannot. They won't even try, they require a driver to be there to be ready to take over with no notice. Their software also makes so many basic mistakes that even what they're allowing it to do is dangerously reckless.
jowday 4y ago
They’ve also got real ones with no safety driver in San Francisco right now.
espadrine 4y ago
Waymo has superior performance based on their historical statistics. It makes sense, since their lidar sensors capture more of the environment, and directly in 3D. Their AI also seems better QA’ed. The Tesla AI Day[0] surprised me as it showed they only had a simple architecture for a very long time, simply feeding barely processed camera pixels to a DNN and hoping for the best with little more than supervised learning off human feeds. Their big claim to glory was that they rearchitectured it to produce a 2D map of the environment… which I thought they had years ago, and is still a far cry from the 3D modeling that is needed. After all, sure, we humans only take two video feeds as input… But we can appreciate from it the position, intent, and trajectory of a wealth of elements around us, with reasonable probability estimates for multiple possibilities, sometimes pertaining to things that are invisible, such as kids crossing from nowhere when near a school. Cruise also seems to have better tech; they had a barely-watched 2h30 description of their systems[1] which shows they do create a richer environment, evaluate the routing of many objects, and train their systems on a very realistic simulation, not just supervised training, which means it can learn from very low-probability events. They have a whole segment on including the probability that unseen cars may travel from perpendicular roads; Tesla’s creeping hit-or-miss are well-documented on Youtube. [0]: https://www.youtube.com/watch?v=j0z4FweCy4M https://www.youtube.com/watch?v=j0z4FweCy4M [1]: https://www.youtube.com/watch?v=uJWN0K26NxQ https://www.youtube.com/watch?v=uJWN0K26NxQ

alphabetting 4y ago

There's been a lot of progress despite AVs not meeting intitial hyped predictions. Waymo and Cruise are operating driverless robotaxis in SF. We're probably a couple years from many major cities having them.

tootie 4y ago

Probably because it's really, really, really hard to solve the thousands of edge cases that occur in real-world driving situations. I don't think FSD happens until government gets behind it and starts putting infrastructure behind it. If we start building roads (and cars) to be highly visible to AI one way or another, it all becomes much easier.

aaaaaaaaaaab 4y ago
>If we start building roads (and cars) to be highly visible to AI one way or another, it all becomes much easier. Or we could build 1-dimensional roads, which would make the AI's jobs much easier. Like, we could put down two parallel piece of metal, which vehicles could "hook" onto somehow...

cco 4y ago

I paid ~$10 for two rides after signing up as a regular ole user in Mesa AZ. It was great, the first ride was a bit nerve wracking, but the second felt very nice. I certainly wouldn't argue with you that it isn't ready for prime time and wide distribution, but it is interesting to see their progress in San Francisco, a much different driving problem. If it takes them 10 years to get to prod in Mesa, two (maybe three?) in SF, maybe they start shrinking that a lot in metros without winters. ¯\_(ツ)_/¯

dreamcompiler 4y ago

Because self-driving has a bunch of tricky edge cases and most of them will kill people. Problems with hundreds of important edge cases cannot be solved by simply throwing more training data at the problem; that's how you solve AI problems in a "dumb" manner, and it works for lots of problems (like recognizing dogs in images) -- but not for self-driving. To solve the self-driving problem we need "smart" A.I., which means we have to approach it with systematic engineering, and the solution will probably involve some combination of better sensors, introspectable neural nets, symbolic A.I., and logical A.I.

function_seven 4y ago
I remain convinced that "real" self driving (as in: go ahead and sleep in the backseat) will never happen without changes to road infrastructure and possibly some sort of segregation between robot-driven cars and people-driven cars. Things like traffic signals that actively communicate their status to nearby robot cars (more than just a red lamp that can be occluded by weather, other vehicles, or mud on the camera lens). Or lane markings that are more than just reflective paint, but can be sensed via RF. Rules around temporary construction that dictate the manner of signage and cone placement that the robot cars can understand. The cones might have little transponders in them, I don't know. But without a massive leap forward in AI capability, our current road system—optimized for human drivers over the past century—is not going to work. If we can't make the cars just as smart as an alert and capable driver, then maybe we need to meet halfway and make the roads a littler "dumber" (simpler) to accommodate the robots.
- highwaylights 4y ago
  What if we just, you know, walk a bit more instead? Or even cycle? I hear great things.
  - actionablefiber 4y ago
    The pattern of zoning and development that the U.S. has used for the past 70 years assumes that nobody wants to walk or cycle anywhere and that they feel so strongly about it that they want cities to be built such that people will die if they attempt to do so. I grew up in a neighborhood where the elementary school was about half a mile away... on the other side of a five lane highway with no crosswalk and no sidewalk on the other side. Zero chance to assert your independence as a kid. Zero chance to live responsibly as an adult. A part of the reason people wish they had FSD so badly is because they want to be rescued from this fundamental failure of NA-style urban planning that necessities driving, all the time, across both short and long distances.

sonofhans 4y ago

Driving is a social problem, not a technical one. It's functionally the same as walking down a crowded sidewalk. The car is just a tool, just an extension of our bodies. We can't build a robot which can walk down a sidewalk without running into people either. The sensor tech and mapping fidelity are red herrings. People drive well because only people are good at predicting human behavior.

raydiatian 4y ago
Sort of. Your wording actually assumes down to its core that driving is inherently social, when in fact I think it may be only provisionally social. Driving currently “is social” in a few senses, But of course the important (and obvious) one is that it currently involves accounting for human-operated vehicles. Alternatively, an autonomous vehicle operator in a homogenous network full of other autonomous operators has capabilities and characteristics that greatly simplify failure modes. Maybe even majority autonomous, partially heterogeneous? You can literally slow or stop the whole show to deal with a catastrophic event. It’s still “social” but probably much reduced from the scenario where you’ve got the full scope of human expressivity behind the wheel. The REAL problem is how do we take our roads to the crossover point where those simplified network features become accessible.
- aidenn0 4y ago
  This assumes that roads are used exclusively by autonomous vehicles, when our roads are not used exclusively by motor vehicles to begin with.
  - raydiatian 4y ago
    > “This assumes our roads are used exclusively by autonomous vehicles” I not only assume it, I say it out loud: “[fully autonomous, …] maybe even majority homogenous, partly heterogenous?” > “When our roads are not used exclusively by motor vehicles to begin with.” I’m not following what you’re saying here in the context of the earlier clause. If you mean not used exclusively by autonomous vehicles, yes, and that’s why I’m pointing out the provisional aspect.

rsynnott 4y ago

> Any reason why everyone seems to be stuck on this problem? Because it's really, really difficult. A lot of AI-ish stuff pretty rapidly gets to the point where it _looks_ quite impressive, but struggles to make the jump to actual feasibility. Like, there were convincing demos of voice recognition in the mid-90s. You could buy software to transcribe voice on your home computer, and people did. And, now, well, it's better than in the mid-90s certainly, but you wouldn't trust it to write a transcript, not of anything important. Maybe in 2040 we'll have voice recognition that can produce a perfect transcript, and human transcription will be a quaint old-fashioned concept. But I wouldn't like to bet on it, honestly. And voice recognition is arguably a far, far easier problem.

UncleOxidant 4y ago
I'm old enough to remember all the breathless pronouncements in 2015 about how self-driving cars would be everywhere within 5 years. I was skeptical then and I'm still skeptical that it will ever happen outside of some limited range of well known paths that have been pre-determined to be safe - ie we'll have (and we do have) some self driving cars but they'll essentially be on a closed course and will not leave the course. There are already some small bus lines like that - the bus just goes around a closed circuit picking up and dropping off people always taking the same route.
- sorry_outta_gas 4y ago
  we're still trying to convert to electric, self dirving is far out there
  - xnx 4y ago
    These are mostly unrelated. Some of Waymo's vehicles are ICE.
    - sorry_outta_gas 4y ago
      My mistake, I trying to imply to `mass adpotion of` and bungled it

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turzmo 4y ago

We often can figure out how to take a product that works 90% and bring it to 99%, and then to 99.9%. The engineering challenges involved in each nine are often vastly more than the percentages indicate, but they're conceivable. With AI we have absolutely no idea how much effort might be required to get to that next level of reliability. We hope that bigger models, or better AI technology might get us there, but there's also a chance that they won't.

relueeuler 4y ago

Zoox has solved it.

AlotOfReading 4y ago
Has Zoox even gotten the permits to do fleet-scale driverless testing? Last I heard, they were still limited to 2 vehicles on specific streets in foster city. Doesn't seem very solved.

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toss1 4y ago

Google/Alphabet is stuck and will make advances in specific territories but will never get there without a fundamental change in approach. Their approach relies on very detailed mapping/modeling of specific terrain, so they can make a usable case sooner, but outside of the map/model territory, they're literally lost. And maps/models change constantly and rapidly. Tesla is taking a fundamentally more broad and deep approach - working with the fundamental fact that a pair of visual sensors and a compute engine (eyes & brain) can successfully figure out driving in strange areas in real time, ergo, it should be possible without a map/model or lidar. Once they get it solved, it will be solved once and for all. Bigger gamble, bigger payoff. Equipping the car with dozens of eyes is the easy part. The question is whether enough compute power can be brought to bear on solving the recognition problems, and the edge cases. They have obvious issues with failing to recognize large objects like trucks in unexpected orientations, left turns etc. Using millions of miles of live human driver data as a training set is great, except that the average driver is really bad, so it's entirely polluted with bad examples, ESPECIALLY around the edge cases that get people killed. There, examples from professionally trained drivers, who really understand the physics and limits of the car, adhesion, traffic dynamics, etc, are what you want to train on, but that isn't what they have. It is also possible that even if the set of training data would actually be sufficient, the big question will kill them - perhaps the solution requires orders of magnitude more compute power to approach human performance, and they just don't have the hardware to simulate human compute power. So, have they just hit the limits of what their compute power can do? I think Tesla's approach is fundamentally the way to go, as it is a general solution, compared to everyone else's limited map/model approach. But both may require either or both a more specifically programmed higher-level behaviors, and/or something much closer to AGI than exists, something that has actual understanding of the machine-learned objects and relationships, which does not yet exist (if one is known, pleas correct me - I'd love to know about it).

Animats 4y ago

Waymo and Cruise routinely have driverless cars on city streets. In California, all collisions, however minor, have to be reported, and DMV posts them on their web site.[1] Most are very minor. Here's a more serious one from last month: "A Cruise autonomous vehicle ("Cruise AV") operating in driverless autonomous mode, was traveling eastbound on Geary Boulevard toward the intersection with Spruce Street. As it approached the intersection, the Cruise AV entered the left hand turn lane, turned the left turn signal on, and initiated a left turn on a green light onto Spruce Street. At the same time, a Toyota Prius traveling westbound in the rightmost bus and turn lane of Geary Boulevard approached the intersection in the right turn lane. The Toyota Prius was traveling approximately 40 mph in a 25 mph speed zone. The Cruise AV came to a stop before fully completing its turn onto Spruce Street due to the oncoming Toyota Prius, and the Toyota Prius entered the intersection traveling straight from the turn lane instead of turning. Shortly thereafter, the Toyota Prius made contact with the rear passenger side of the Cruise AV. The impact caused damage to the right rear door, panel, and wheel of the Cruise AV. Police and Emergency Medical Services were called to the scene, and a police report was filed. The Cruise AV was towed from the scene. Occupants of both vehicles received medical treatment for allegedly minor injuries." Now, this shows the strengths and weaknesses of the system. The Cruise vehicle was making a left turn from Geary onto Spruce. Eastbound Geary at this point has a dedicated left turn lane cut out of a grass median, two through lanes, a right turn bus/taxi lane, and a bus stop lane. It detected cross traffic that shouldn't have been in that lane and was going too fast. So it stopped, and was hit. It did not take evasive action, which might have worked. Or it might have made the situation worse. By not doing so, it did the legally correct thing. The other driver will be blamed for this. But it may not have done the thing most likely to avoid an accident. This is the real version of the trolley problem. [1] https://www.dmv.ca.gov/portal/vehicle-industry-services/autonomous-vehicles/autonomous-vehicle-collision-reports/ https://www.dmv.ca.gov/portal/vehicle-industry-services/auto... [2] https://earth.google.com/web/@37.78169591,-122.45337171 https://earth.google.com/web/@37.78169591,-122.45337171 [3] https://patch.com/california/san-francisco/speed-limit-lowered-parts-geary-boulevard https://patch.com/california/san-francisco/speed-limit-lower...

ryantgtg 4y ago
> In California, all collisions, however minor, have to be reported. Just to be clear, this statement only applies to AVs, right?

uoaei 4y ago

> Any reason why everyone seems to be stuck on this problem? Because they're all trying visual- or line-of-sight methods only, I call this the "robo-human" fallacy in ML: trying to automate the processes that humans undergo so that you eventually have a drop-in replacement for a human. But that is a myopic and unimaginative approach because you could be re-assessing the system itself and eliminating inefficiencies that lead to poor performance. In the autonomous vehicles space, there is massive potential for self-organizing swarm algorithms to control pelotons of cars, rather than individual cars with no intrinsic sense of the general flow of traffic. You wouldn't need a top-down "commander" style architecture, it could be designed so that cars only talk to their immediate neighbors and emergent patterns keep traffic flowing smooth and fast. I have always been skeptical of the attempts to reduce the amount of information about the road that a car receives. (Moving from stereoscopic to monocular vision to save the cost of one camera seems just stupid.) But people who dream of "smart cities" really seem to see little more than The Jetsons in their mind, and it limits the scope of research to our detriment.

dlkf 4y ago
I’d like to hear an actual response from the people downvoting this comment. It’s an interesting perspective, and while I can imagine legit criticisims (SPOF, privacy concerns, coordination with vehicles outside the system, etc) actually articulating them would yield a more productive discussion than downvoting without comment.

realitysballs 4y ago

Answer me this; How is AI supposed to confidently distinguish a real stop sign from someone/something holding up a picture of a stop sign? Yes, this is a weird edge case, but I think it gets at the core issue being that it takes way more sophistication to release this tech into the wild then ppl would like to admit.