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George’s insights on self-driving cars remind me of when you get the rare exceptional engineer in your company who knows 100% what he or she is talking about do

George’s insights on self-driving cars remind me of when you get the rare exceptional engineer in your company who knows 100% what he or she is talking about down to the exact implementation level and all of the alternatives, and leadership totally ignores them because they foolhardily believe this kid can’t possibly be right—without asking engineering questions to test to see if they’re right about the engineer being wrong or having not considered something. Except George seems to have been right to the tune of others spending billions of dollars while this dude hacked on free and open source software. His biggest bootstrap expenses were probably commodity hardware, before dealing with business purchase orders. I find that hilarious and extremely gratifying.

ra7 4y ago
His insights on self driving cars are total fluff once you realize he was only working on problems several orders of magnitude smaller in scope than the ones spending billions are attempting to solve. Autonomous driving is more than just making lane-keep on highways work with a camera mounted to the windshield and requires more than just "hacking". His insights do indicate one thing: that he doesn't understand the rigor required to engineer safety-critical systems.
- andrewmcwatters 4y ago
  I mean you can say that all you want, but the proof of the self-driving pudding is in the driving, and SAE Level 2 is the most practical self-driving we are ever going to get. I don't think there's anything wrong with trying to refine that approach as much as openpilot did, and honestly if there was fruit in SAE Level 3 and above, I feel like we would have seen it by now, but we haven't. I have no idea what you mean by "problems several orders of magnitude." Driving is driving. Your hardware and software can do it, or it can't. What do billions of dollars have to do with anything? Should people remind you Meta spent billions of dollars on a less popular Second Life? How would you explain to shareholders that your solution can't compete with openpilot?
  - mwint 4y ago
    > SAE Level 2 is the most practical self-driving we are ever going to get. So… how much would you bet on this?
    - andrewmcwatters 4y ago
      $10,000 USD in 2022 dollars that SAE Level 4 is not available in standard economy cars in the next 10 years. My 2022 Corolla LE, a base model compact car, drives itself just fine (SAE Level 2) even on city streets. It would do it better with openpilot, though. It makes Tesla Full Self Driving look like a joke, in my opinion.
      - kajecounterhack 4y ago
        > SAE Level 2 is the most practical self-driving we are ever going to get. The bet is on this though -- what's impractical about having L4 fleets in major cities that replace Uber/Lyft? Just because you can't personally own one doesn't mean that in 10 years they can't be pretty ubiquitous and practical, particularly for city dwellers, which is most people. I'd bet that your statement is wrong on this basis. L4 cars already exist and are being used in large portions of San Francisco today. And this is to say nothing of trucking & delivery, where self driving is in some ways easier to solve and a lot of progress is being made.
        andrewmcwatters 4y ago
        Well, not everyone lives in San Francisco, and no one wants to take an Uber literally everywhere. So, like most people, I want to own my self-driving car. And I personally don't think the industry is mature enough to accept the realities and limitations of the technology we work with to just say, "Hey, actually, we can let attentive drivers basically be hands-free for 80+% of their drives." And to me, that would be great.
        kajecounterhack 4y ago
- hatware 4y ago
  > he was only working on problems several orders of magnitude smaller in scope Isn't that kind of the point? Tesla would have L4 if the architecture was built right, but it wasn't, and now they're scrambling. I think George made it very clear that the architecture is what these companies spending billions are getting wrong. Tech debt is more expensive than you think at the cutting edge. You know what is total fluff? Tesla FSD. Disgusting. At least comma is honest about their hardware, and that's about all it comes down to.
  - ra7 4y ago
    > I think George made it very clear that the architecture is what these companies spending billions are getting wrong. Tech debt is more expensive than you think at the cutting edge. And yet the architectures he disapproves are the only ones who have shown fully autonomous driving is possible. There are driverless robotaxis running now, albeit in small areas but expanding. > You know what is total fluff? Tesla FSD. Disgusting. At least comma is honest about their hardware, and that's about all it comes down to. I fully agree.
    - Kbelicius 4y ago
      > And yet the architectures he disapproves are the only ones who have shown fully autonomous driving is possible. They did not. > There are driverless robotaxis running now, albeit in small areas but expanding. Running in small areas shows that they can drive in small mapped out areas under specific conditions. Not that we have fully autonomous self driving.
      - ra7 4y ago
        > Running in small areas shows that they can drive in small mapped out areas under specific conditions. That is fully autonomous driving. It's just classified as Level 4. Geofences and operating conditions can be extended to provide a real, useful taxi service to a lot of people.
        adhendo 4y ago
taeric 4y ago
I'm curious what his insights were? Are those collected somewhere? Asking as someone that has largely not been following the field. Not challenging, genuinely curious.
- ra7 4y ago
  https://blog.comma.ai/a-100x-investment-part-1/ https://blog.comma.ai/a-100x-investment-part-1/ https://blog.comma.ai/a-100x-investment-part-2/ https://blog.comma.ai/a-100x-investment-part-2/ It's basically a bunch of apples-to-oranges comparisons that don't make sense.
  - taeric 4y ago
    I'm not entirely clear I get those blogs. :( If you are saying that the blogs are a bunch of apples-to-oranges comparisons that don't make sense, I think I fully agree on that.
- another_kel 4y ago
  Here's a rough summary: 1. There is no point in making human understandable layer between perception and planning. Mapping your surrounding with AI and then feeding it to handwritten planner isn't going to achieve real selfdriving. 2. To make AI you need big data, which means big fleet. Therefore you can only succeed if you have customers that are wiling to pay for you current version, because this way you gain money for each extra car in your fleet, instead of losing it. 3. Robotaxis are bad business. From a customer standpoint taxi with a driver is a selfdriving car, replacing driver with AI will make drive longer and more expensive. The path for self-driving company is to make driver assist and go from there to L5. 4. Vision only, AI powerful enough to be level 5 is powerful enough to retrieve depth from image.
  - throw__2sdfw 4y ago
    On the first point it looks like Tesla's approach to fixing bugs is much easier compared to Georges approach to fix bugs which is to modify and retrain the model until there are no regressions. I don't understand how this can cover every possible scenario. I am not in to ML and Tesla's approach seems more sense to me. Can anyone in the ML field comment on why George's approach might work.
bombcar 4y ago
> spending billions of dollars This is usually the problem; once you're in the many millions of dollars you find that other things are way more important than actually being right or even delivering a product. Time and time again the story is told.
deleted 4y ago
[deleted]

ra7 4y ago

His insights on self driving cars are total fluff once you realize he was only working on problems several orders of magnitude smaller in scope than the ones spending billions are attempting to solve. Autonomous driving is more than just making lane-keep on highways work with a camera mounted to the windshield and requires more than just "hacking". His insights do indicate one thing: that he doesn't understand the rigor required to engineer safety-critical systems.

andrewmcwatters 4y ago
I mean you can say that all you want, but the proof of the self-driving pudding is in the driving, and SAE Level 2 is the most practical self-driving we are ever going to get. I don't think there's anything wrong with trying to refine that approach as much as openpilot did, and honestly if there was fruit in SAE Level 3 and above, I feel like we would have seen it by now, but we haven't. I have no idea what you mean by "problems several orders of magnitude." Driving is driving. Your hardware and software can do it, or it can't. What do billions of dollars have to do with anything? Should people remind you Meta spent billions of dollars on a less popular Second Life? How would you explain to shareholders that your solution can't compete with openpilot?
- mwint 4y ago
  > SAE Level 2 is the most practical self-driving we are ever going to get. So… how much would you bet on this?
  - andrewmcwatters 4y ago
    $10,000 USD in 2022 dollars that SAE Level 4 is not available in standard economy cars in the next 10 years. My 2022 Corolla LE, a base model compact car, drives itself just fine (SAE Level 2) even on city streets. It would do it better with openpilot, though. It makes Tesla Full Self Driving look like a joke, in my opinion.
    - kajecounterhack 4y ago
      > SAE Level 2 is the most practical self-driving we are ever going to get. The bet is on this though -- what's impractical about having L4 fleets in major cities that replace Uber/Lyft? Just because you can't personally own one doesn't mean that in 10 years they can't be pretty ubiquitous and practical, particularly for city dwellers, which is most people. I'd bet that your statement is wrong on this basis. L4 cars already exist and are being used in large portions of San Francisco today. And this is to say nothing of trucking & delivery, where self driving is in some ways easier to solve and a lot of progress is being made.
      - andrewmcwatters 4y ago
        Well, not everyone lives in San Francisco, and no one wants to take an Uber literally everywhere. So, like most people, I want to own my self-driving car. And I personally don't think the industry is mature enough to accept the realities and limitations of the technology we work with to just say, "Hey, actually, we can let attentive drivers basically be hands-free for 80+% of their drives." And to me, that would be great.
        kajecounterhack 4y ago
hatware 4y ago
> he was only working on problems several orders of magnitude smaller in scope Isn't that kind of the point? Tesla would have L4 if the architecture was built right, but it wasn't, and now they're scrambling. I think George made it very clear that the architecture is what these companies spending billions are getting wrong. Tech debt is more expensive than you think at the cutting edge. You know what is total fluff? Tesla FSD. Disgusting. At least comma is honest about their hardware, and that's about all it comes down to.
- ra7 4y ago
  > I think George made it very clear that the architecture is what these companies spending billions are getting wrong. Tech debt is more expensive than you think at the cutting edge. And yet the architectures he disapproves are the only ones who have shown fully autonomous driving is possible. There are driverless robotaxis running now, albeit in small areas but expanding. > You know what is total fluff? Tesla FSD. Disgusting. At least comma is honest about their hardware, and that's about all it comes down to. I fully agree.
  - Kbelicius 4y ago
    > And yet the architectures he disapproves are the only ones who have shown fully autonomous driving is possible. They did not. > There are driverless robotaxis running now, albeit in small areas but expanding. Running in small areas shows that they can drive in small mapped out areas under specific conditions. Not that we have fully autonomous self driving.
    - ra7 4y ago
      > Running in small areas shows that they can drive in small mapped out areas under specific conditions. That is fully autonomous driving. It's just classified as Level 4. Geofences and operating conditions can be extended to provide a real, useful taxi service to a lot of people.
      - adhendo 4y ago

taeric 4y ago

I'm curious what his insights were? Are those collected somewhere? Asking as someone that has largely not been following the field. Not challenging, genuinely curious.

ra7 4y ago
https://blog.comma.ai/a-100x-investment-part-1/ https://blog.comma.ai/a-100x-investment-part-1/ https://blog.comma.ai/a-100x-investment-part-2/ https://blog.comma.ai/a-100x-investment-part-2/ It's basically a bunch of apples-to-oranges comparisons that don't make sense.
- taeric 4y ago
  I'm not entirely clear I get those blogs. :( If you are saying that the blogs are a bunch of apples-to-oranges comparisons that don't make sense, I think I fully agree on that.
another_kel 4y ago
Here's a rough summary: 1. There is no point in making human understandable layer between perception and planning. Mapping your surrounding with AI and then feeding it to handwritten planner isn't going to achieve real selfdriving. 2. To make AI you need big data, which means big fleet. Therefore you can only succeed if you have customers that are wiling to pay for you current version, because this way you gain money for each extra car in your fleet, instead of losing it. 3. Robotaxis are bad business. From a customer standpoint taxi with a driver is a selfdriving car, replacing driver with AI will make drive longer and more expensive. The path for self-driving company is to make driver assist and go from there to L5. 4. Vision only, AI powerful enough to be level 5 is powerful enough to retrieve depth from image.
- throw__2sdfw 4y ago
  On the first point it looks like Tesla's approach to fixing bugs is much easier compared to Georges approach to fix bugs which is to modify and retrain the model until there are no regressions. I don't understand how this can cover every possible scenario. I am not in to ML and Tesla's approach seems more sense to me. Can anyone in the ML field comment on why George's approach might work.

bombcar 4y ago

> spending billions of dollars This is usually the problem; once you're in the many millions of dollars you find that other things are way more important than actually being right or even delivering a product. Time and time again the story is told.

deleted 4y ago

[deleted]