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Yeah, they’re not trying to solve the same thing? I think Tesla is right that to solve it for real you need to solve the general case which can’t rely on high

Yeah, they’re not trying to solve the same thing? I think Tesla is right that to solve it for real you need to solve the general case which can’t rely on high resolution maps. The city cab case is smaller and can, so the cruise approach makes sense for that use case. It’s just narrower.

ghaff 5y ago
Or you solve for a subset of highways in a subset of weather conditions. That would be more useful to a lot of people than city cabs which exist today (with human drivers).
jowday 5y ago
The truth of it is that it’s just not possible (with currently existing technology/ML architectures) to create a truly autonomous taxi without HD maps. Everyone in the robotaxi industry knows this - even Tesla builds HD maps, they just don’t call them that.
- gonehome 5y ago
  My knowledge only comes from Karpathy's talks about this (which are great, worth watching if you haven't seen them). I found his and Tesla's arguments convincing for the general case. That doesn't mean that the narrow cases aren't super cool or valuable (I signed up for this Cruise thing in SF). I just think that if the software is unable to make decisions based on visual data alone without up to date high resolution maps it'll never achieve true FSD in the general case (not geo locked). You'll end up trapped in a local max otherwise because there are just too many conditions in the real world that vary (and the world is too large to economically map fast enough for that approach). You have to solve the vision problem. I don't know enough to comment on the approach differences beyond that, but my understanding was that Tesla did not rely on the same stuff that Waymo and Cruise require (largely Lidar and these high resolution maps).
  - jowday 5y ago
    > I just think that if the software is unable to make decisions based on visual data alone without up to date high resolution maps it'll never achieve true FSD in the general case (not geo locked). You'll end up trapped in a local max otherwise because there are just too many conditions in the real world that vary. My contention is that there’s no way to actually solve for the general case with currently existing technology. The amount of novelty in the real world is too great for any system to account for it without disambiguating via HD maps or remote support. >You have to solve the vision problem. This isn’t a vision problem specifically - even if you had LIDAR and high resolution imaging radar and 8 A100s on every Tesla, “true generalized self driving” wouldn’t be achievable without HD maps with our current understanding of Machine Learning. >My understanding was that Tesla did not rely on the same stuff that Waymo and Cruise require. Tesla maps individual traffic light elements, stop signs, and lane markings, but will attempt to drive even if the area isn’t mapped. Disparities in FSD performance in different areas is largely attributable to some areas being better mapped than others - the mapping data has a huge effect on its performance. There are key elements of the driving task (including recognizing and reacting to every single type of sign other than a stop sign) that FSD can’t do and relies entirely on maps for.
    - Retric 5y ago
      Novelty isn’t nearly as big of a problem as you might think. One of Wamo’s famous videos was someone on an electric scooter chasing a duck in the middle of the street. That’s very odd behavior, but the car followed the rather simple option of just not hitting them and going forward when possible. Cars really don’t need to identify what something is just it’s location and movement which is a vastly easier problem. A trash can rolling down the street can be treated just like an oil drum doing the same thing etc.
      - jowday 5y ago
        > Cars really don’t need to identify what something is just it’s location and movement which is a vastly easier problem. A trash can rolling down the street can be treated just like an oil drum doing the same thing etc. You’d think that, until you encounter something like a turn restriction sign with a bizarre conditional restriction that it’s never seen before. At which point the car needs to OCR the text, parse the semantic meaning, and apply to the scene.
justapassenger 5y ago
> I think Tesla is right that to solve it for real you need to solve the general case which can’t rely on high resolution maps. But they do relay on maps. You cannot use FSD without latest, high resolution maps.

ghaff 5y ago

Or you solve for a subset of highways in a subset of weather conditions. That would be more useful to a lot of people than city cabs which exist today (with human drivers).

jowday 5y ago

The truth of it is that it’s just not possible (with currently existing technology/ML architectures) to create a truly autonomous taxi without HD maps. Everyone in the robotaxi industry knows this - even Tesla builds HD maps, they just don’t call them that.

gonehome 5y ago
My knowledge only comes from Karpathy's talks about this (which are great, worth watching if you haven't seen them). I found his and Tesla's arguments convincing for the general case. That doesn't mean that the narrow cases aren't super cool or valuable (I signed up for this Cruise thing in SF). I just think that if the software is unable to make decisions based on visual data alone without up to date high resolution maps it'll never achieve true FSD in the general case (not geo locked). You'll end up trapped in a local max otherwise because there are just too many conditions in the real world that vary (and the world is too large to economically map fast enough for that approach). You have to solve the vision problem. I don't know enough to comment on the approach differences beyond that, but my understanding was that Tesla did not rely on the same stuff that Waymo and Cruise require (largely Lidar and these high resolution maps).
- jowday 5y ago
  > I just think that if the software is unable to make decisions based on visual data alone without up to date high resolution maps it'll never achieve true FSD in the general case (not geo locked). You'll end up trapped in a local max otherwise because there are just too many conditions in the real world that vary. My contention is that there’s no way to actually solve for the general case with currently existing technology. The amount of novelty in the real world is too great for any system to account for it without disambiguating via HD maps or remote support. >You have to solve the vision problem. This isn’t a vision problem specifically - even if you had LIDAR and high resolution imaging radar and 8 A100s on every Tesla, “true generalized self driving” wouldn’t be achievable without HD maps with our current understanding of Machine Learning. >My understanding was that Tesla did not rely on the same stuff that Waymo and Cruise require. Tesla maps individual traffic light elements, stop signs, and lane markings, but will attempt to drive even if the area isn’t mapped. Disparities in FSD performance in different areas is largely attributable to some areas being better mapped than others - the mapping data has a huge effect on its performance. There are key elements of the driving task (including recognizing and reacting to every single type of sign other than a stop sign) that FSD can’t do and relies entirely on maps for.
  - Retric 5y ago
    Novelty isn’t nearly as big of a problem as you might think. One of Wamo’s famous videos was someone on an electric scooter chasing a duck in the middle of the street. That’s very odd behavior, but the car followed the rather simple option of just not hitting them and going forward when possible. Cars really don’t need to identify what something is just it’s location and movement which is a vastly easier problem. A trash can rolling down the street can be treated just like an oil drum doing the same thing etc.
    - jowday 5y ago
      > Cars really don’t need to identify what something is just it’s location and movement which is a vastly easier problem. A trash can rolling down the street can be treated just like an oil drum doing the same thing etc. You’d think that, until you encounter something like a turn restriction sign with a bizarre conditional restriction that it’s never seen before. At which point the car needs to OCR the text, parse the semantic meaning, and apply to the scene.

justapassenger 5y ago

> I think Tesla is right that to solve it for real you need to solve the general case which can’t rely on high resolution maps. But they do relay on maps. You cannot use FSD without latest, high resolution maps.