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The only selling point of FSD (Supervised) is that it (can) work "everywhere." This is because it only relies on navigation information and what the car can see

The only selling point of FSD (Supervised) is that it (can) work "everywhere." This is because it only relies on navigation information and what the car can see. Waymo and similar companies all use HD Mapping. Ignoring the specifics, it can be thought of as a centimeter-level perfect reconstruction of the environment, including additional metadata such as slopes, exact lane positions, road markings, barriers, traffic signs, and much more. HD Mapping is great when it's accurate and available. But it requires a ton of data and constant updating, or the car will get "lost," and realistically will never be implemented in general, at best in certain cities. Reliance on HD Mapping gets you to "robotaxis" quicker and easier, but it doesn't and likely cannot scale. It remains to be seen if Tesla can generalize FSD enough to reach the same level as HD Mapping everywhere. Still, they have shown that the current limiting factor is not what the car sees or knows but what it does with that information. It is unclear how or why HD mapping would help them at that point.

kajecounterhack 2y ago
> Reliance on HD Mapping gets you to "robotaxis" quicker and easier, but it doesn't and likely cannot scale. If you can make the unit economics work for a large quantity of individual cars, mapping is a small fixed cost. I agree that it's not economical to map every city and road in the US, since you need to generate revenue from every mapped road and city. So you can think of HD maps as amounting to building roads. They will be built in lucrative places. Cruise and Waymo won't make money from putting taxis in nowhere Arkansas, so they don't need to map it. > the current limiting factor is not what the car sees or knows but what it does with that information. It is unclear how or why HD mapping would help them at that point. That's simply untrue. All the hard stuff continues to be reliability and sensor gated. Cruise and Waymo have amazing sensors and even they struggle with sensor range, sensor reliability, model performance on tail cases, etc. For example, at night these cars typically do not have IR or Thermal sensing. They are relying on the limited dynamic range of their cameras + active illumination + hoping laser gets enough points / your object is reflective enough. Laser perception also hits limits when lasers shine on small objects (think: skinny railroad arm). Cars also have limits with regard to interpreting written signs, which is a big part of driving. Occlusions are still public enemy #1. Waymo killed a dog. Cruise crashed into a fire truck coming out of a blind intersection even though their sensors saw the truck within 100ms. LiDAR and HD mapping together are supremely useful, even if you don't drive with it, for enabling you to simulate accurately. You cannot simulate reliably while guessing at distances and locations. HD maps let you use visual odometry to localize, and distance measurements grounded in physics backstop the realism of your simulation at least in terms of the world's shape. Tesla lacks the ability to resim counterfactuals with confidence since they don't have HD ground truth. There are believers at the company that maybe you could make "good enough" ground truth from imagery alone but that in and of itself is a huge risk, and it's what skipping steps looks like. Most in the industry agree that barring a major change in strategy they just have no way to regression test their software to the level of reliability required for L4 / no human supervision.
- Workaccount2 2y ago
  Google already has a fleet of vehicles driving around continuously taking new street view photos.
  - bangaladore 2y ago
    Google Maps seems to update at a frequency of 2-8 years. Maybe longer in some areas and we don't know what they do other than stitch it together. HD mapping, on the other hand, likely needs to be updated frequently and immediately when any construction occurs. It seems pretty clear that what they are doing today is nowhere near what they need to do. And again, I don't think that is possible.
    - TulliusCicero 2y ago
      The obvious thing to do is to just have every Waymo robotaxi or car with licensed Waymo tech report in its daily mapping/obstacle data to the mothership, so you can get new changes almost immediately. I dunno if said data would be as high quality as dedicated HD mapping cars, but it's probably at least decent, given the variety of cameras and lidars every Waymo car has.
      - singleshot_ 2y ago
        Further, it seems to me that if you brake hard to avoid a dog, your car should warn me as I’m approaching. I’m not sure why we are trying to teach each car to drive when we could be teaching all the cars and the road to drive.
        c22 2y ago
        This is a good point. Do Waymo cars ever use their horn?
        nolist_policy 2y ago
        They do: https://youtu.be/YxVihk4c-h8?t=3m5s https://youtu.be/YxVihk4c-h8?t=3m5s
consumer451 2y ago
> The only selling point of FSD (Supervised) is that it (can) work "everywhere." I seem to recall Musk saying in the last couple years that "full self driving will basically require AGI." This appeared to me to be extremely honest and accurate, though I believe that in the moment he was trying to promote the idea that Tesla was an AGI company. Does anyone happen to remember when he said that?
- Mockapapella 2y ago
  Would have been at one of their AI days in the last few years
ra7 2y ago
> HD Mapping is great when it's accurate and available. But it requires a ton of data and constant updating, or the car will get "lost," and realistically will never be implemented in general, at best in certain cities. Waymo have said time and again they don’t rely on maps being 100% accurate to be able to drive. It's one of the key assumptions of the system. They use it as prior knowledge to aid in decision making. If they got "lost" whenever there was a road change, they wouldn't be successfully navigating construction zones in San Francisco as we've seen in many videos. They can also do constant updates because the cars themselves are able to detect road changes, self update maps and rollout changes to the entire fleet. See https://waymo.com/blog/2020/09/the-waymo-driver-handbook-mapping/ https://waymo.com/blog/2020/09/the-waymo-driver-handbook-map... At this point, the whole “HD maps are not practical” is just a trope perpetuated by the Tesla community for years.
- flutas 2y ago
  > They can also do constant updates because the cars themselves are able to detect road changes, self update maps and rollout changes to the entire fleet. Which leads to mapping failures being unchecked, as the system that generated the data is the one checking the data by driving it. See bullet point 1 in their recent recall for an example. > Prior to the Waymo ADS receiving the remedy described in this report, a collision could occur if the Waymo ADS encountered a pole or pole-like permanent object and all of the following were true: > 1) the object was within the the boundaries of the road and the map did not include a hard road edge between the object and the driveable surface; > 2) the Waymo ADS’s perception system assigned a low damage score to the object; > 3) the object was located within the Waymo ADS’s intended path (e.g. when executing a pullover near the object); and > 4) there were no other objects near the pole that the ADS would react to and avoid.
  - cstejerean 2y ago
    > the Waymo ADS’s perception system assigned a low damage score to the object; and Tesla would do better how in this case? It also routinely crashes into stationary objects, presumably because the system assumes it wouldn't cause damage.
hindsightbias 2y ago
I’ve watched Waymos navigate the Tenderloin. It doesn’t get any more random than that.
solardev 2y ago
The obvious question here is "why not both". Use mapping data where you can, LIDAR and other sensors where you can, and visual cameras when you must. There's no reason to limit yourself to just one input type. Elon claims that, sure, but it doesn't seem like a given at all.
ddalex 2y ago
> requires a ton of data Not a problem for Google, right? > constant updating I guess the cars can and will update the mapping in real time ? > at best in certain cities If mapping a city is possible, so it's mapping a highway, even easier. If cars do update the maps themselves, they require might just a couple of human-driven passes of the standard WWaymo cars on a highway to generate the maps.

kajecounterhack 2y ago

> Reliance on HD Mapping gets you to "robotaxis" quicker and easier, but it doesn't and likely cannot scale. If you can make the unit economics work for a large quantity of individual cars, mapping is a small fixed cost. I agree that it's not economical to map every city and road in the US, since you need to generate revenue from every mapped road and city. So you can think of HD maps as amounting to building roads. They will be built in lucrative places. Cruise and Waymo won't make money from putting taxis in nowhere Arkansas, so they don't need to map it. > the current limiting factor is not what the car sees or knows but what it does with that information. It is unclear how or why HD mapping would help them at that point. That's simply untrue. All the hard stuff continues to be reliability and sensor gated. Cruise and Waymo have amazing sensors and even they struggle with sensor range, sensor reliability, model performance on tail cases, etc. For example, at night these cars typically do not have IR or Thermal sensing. They are relying on the limited dynamic range of their cameras + active illumination + hoping laser gets enough points / your object is reflective enough. Laser perception also hits limits when lasers shine on small objects (think: skinny railroad arm). Cars also have limits with regard to interpreting written signs, which is a big part of driving. Occlusions are still public enemy #1. Waymo killed a dog. Cruise crashed into a fire truck coming out of a blind intersection even though their sensors saw the truck within 100ms. LiDAR and HD mapping together are supremely useful, even if you don't drive with it, for enabling you to simulate accurately. You cannot simulate reliably while guessing at distances and locations. HD maps let you use visual odometry to localize, and distance measurements grounded in physics backstop the realism of your simulation at least in terms of the world's shape. Tesla lacks the ability to resim counterfactuals with confidence since they don't have HD ground truth. There are believers at the company that maybe you could make "good enough" ground truth from imagery alone but that in and of itself is a huge risk, and it's what skipping steps looks like. Most in the industry agree that barring a major change in strategy they just have no way to regression test their software to the level of reliability required for L4 / no human supervision.

Workaccount2 2y ago
Google already has a fleet of vehicles driving around continuously taking new street view photos.
- bangaladore 2y ago
  Google Maps seems to update at a frequency of 2-8 years. Maybe longer in some areas and we don't know what they do other than stitch it together. HD mapping, on the other hand, likely needs to be updated frequently and immediately when any construction occurs. It seems pretty clear that what they are doing today is nowhere near what they need to do. And again, I don't think that is possible.
  - TulliusCicero 2y ago
    The obvious thing to do is to just have every Waymo robotaxi or car with licensed Waymo tech report in its daily mapping/obstacle data to the mothership, so you can get new changes almost immediately. I dunno if said data would be as high quality as dedicated HD mapping cars, but it's probably at least decent, given the variety of cameras and lidars every Waymo car has.
    - singleshot_ 2y ago
      Further, it seems to me that if you brake hard to avoid a dog, your car should warn me as I’m approaching. I’m not sure why we are trying to teach each car to drive when we could be teaching all the cars and the road to drive.
      - c22 2y ago
        This is a good point. Do Waymo cars ever use their horn?
        nolist_policy 2y ago
        They do: https://youtu.be/YxVihk4c-h8?t=3m5s https://youtu.be/YxVihk4c-h8?t=3m5s

consumer451 2y ago

> The only selling point of FSD (Supervised) is that it (can) work "everywhere." I seem to recall Musk saying in the last couple years that "full self driving will basically require AGI." This appeared to me to be extremely honest and accurate, though I believe that in the moment he was trying to promote the idea that Tesla was an AGI company. Does anyone happen to remember when he said that?

Mockapapella 2y ago
Would have been at one of their AI days in the last few years

ra7 2y ago

> HD Mapping is great when it's accurate and available. But it requires a ton of data and constant updating, or the car will get "lost," and realistically will never be implemented in general, at best in certain cities. Waymo have said time and again they don’t rely on maps being 100% accurate to be able to drive. It's one of the key assumptions of the system. They use it as prior knowledge to aid in decision making. If they got "lost" whenever there was a road change, they wouldn't be successfully navigating construction zones in San Francisco as we've seen in many videos. They can also do constant updates because the cars themselves are able to detect road changes, self update maps and rollout changes to the entire fleet. See https://waymo.com/blog/2020/09/the-waymo-driver-handbook-mapping/ https://waymo.com/blog/2020/09/the-waymo-driver-handbook-map... At this point, the whole “HD maps are not practical” is just a trope perpetuated by the Tesla community for years.

flutas 2y ago
> They can also do constant updates because the cars themselves are able to detect road changes, self update maps and rollout changes to the entire fleet. Which leads to mapping failures being unchecked, as the system that generated the data is the one checking the data by driving it. See bullet point 1 in their recent recall for an example. > Prior to the Waymo ADS receiving the remedy described in this report, a collision could occur if the Waymo ADS encountered a pole or pole-like permanent object and all of the following were true: > 1) the object was within the the boundaries of the road and the map did not include a hard road edge between the object and the driveable surface; > 2) the Waymo ADS’s perception system assigned a low damage score to the object; > 3) the object was located within the Waymo ADS’s intended path (e.g. when executing a pullover near the object); and > 4) there were no other objects near the pole that the ADS would react to and avoid.
- cstejerean 2y ago
  > the Waymo ADS’s perception system assigned a low damage score to the object; and Tesla would do better how in this case? It also routinely crashes into stationary objects, presumably because the system assumes it wouldn't cause damage.

hindsightbias 2y ago

I’ve watched Waymos navigate the Tenderloin. It doesn’t get any more random than that.

solardev 2y ago

The obvious question here is "why not both". Use mapping data where you can, LIDAR and other sensors where you can, and visual cameras when you must. There's no reason to limit yourself to just one input type. Elon claims that, sure, but it doesn't seem like a given at all.

ddalex 2y ago

> requires a ton of data Not a problem for Google, right? > constant updating I guess the cars can and will update the mapping in real time ? > at best in certain cities If mapping a city is possible, so it's mapping a highway, even easier. If cars do update the maps themselves, they require might just a couple of human-driven passes of the standard WWaymo cars on a highway to generate the maps.