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The counter argument is a bitter lesson that Tesla is learning from Waymo and the lesson might be bitter enough to tank the company. Waymo's approach to self dr

by typon 2y ago

The counter argument is a bitter lesson that Tesla is learning from Waymo and the lesson might be bitter enough to tank the company. Waymo's approach to self driving isn't end to end - they have classical control combined with tons of deep learning, creating a final product that actually works in the real world, meanwhile the purely data driving approach from Tesla has failed to deliver a working product.

ModernMech 2y ago
The lesson from Tesla is that AI is not just a magic box where you can put in data and get out intelligence. There are more to working systems than compute, and when they operate in the real world, data isn't enough. The key problem with Tesla cars that keep them from succeeding is not that they don't have enough data, but they have no idea what to do with it. Even if they had infinite compute and all the driving videos in the world, it wouldn't be enough to overcome the limitations of their sensors.
- dangus 2y ago
  Tesla is a poor counterargument because it is no longer a market leader. It has poor management compared to 10 years ago and seems to be unable to attract top talent (poor labor relations). Tesla is being leapfrogged by competitors across the auto industry. All it has is first mover status (charging network). Tesla purposefully limits the capabilities of its self driving by refusing to implement it with sensors that go beyond smartphone cameras. My belief is that Tesla doesn’t want to actually deliver a car that can drive itself because the end result of Waymo is that fewer people will need to own a car and fleets of short term rental self-driving cars won’t spend frivolous money on prestige and luxury like consumer car buyers. They won’t lease a car and replace it every 2-3 years like some car owners do just because they like having a new car. Fleet vehicle operators purchase cars with razor thin margins and make decisions based solely on economics, as well as having a lot more purchasing leverage over car manufacturers. I don’t think Tesla ever wants self driving to work, they just want to sell the idea of the software.
  - immibis 2y ago
    Tesla removed the LIDAR and thought advances in AI would be able to do without one. They were wrong.
    - _ea1k 2y ago
      Tesla didn't remove LIDAR, they never had it. So far, that bet is looking pretty reasonable. It seems evident at the moment that the most formidable competitors in this space could build a solid FSD product with cameras alone, with the biggest variable being time.
      - dangus 2y ago
        Is that evident? The only level 3 certified drive system available in the US (Mercedes) utilizes LIDAR. The only operating robotaxi service also uses it. I would say it’s the opposite of evident that cameras are enough.
        _ea1k 2y ago
        While Mobileye has focused on using lidar+cameras with each effectively serving as a form of "backup", they have also demonstrated a full city drive using nothing but cameras. I've seen enough from Waymo to see that they could easily do the same thing. I expect both to keep radar and lidar for quite a few years, but I think its usage will consistently decline to zero or near zero over the next 10 years.
        ModernMech 2y ago
        The problem with this prediction is.... why? Camera doesn't actually replace LiDAR, even if we solve getting depth maps from camera 100%. The recent test in which the car ran over a child hidden in a smoke screen is evidence of this. If they purpose of driverless cars is to be better than humans, we should be aiming for them to have super human sensing with camera+lidar+radar etc, instead of human-level sensing with just cameras.
- xg15 2y ago
  > The key problem with Tesla cars that keep them from succeeding is not that they don't have enough data, but they have no idea what to do with it. Even if they had infinite compute and all the driving videos in the world, it wouldn't be enough to overcome the limitations of their sensors. Isn't this effectively a refutation of the "bitter lesson"?
_ea1k 2y ago
I'd argue that bitter lesson might be the other way around. Waymo has been experimenting with more end-to-end approaches and is likely to end up with something that looks more like that than a "classical control" approach, though maybe not quite the same approach as Tesla's current setup. IMO, this is the best public description of the current state of the art: https://www.youtube.com/watch?v=92e5zD_-xDw https://www.youtube.com/watch?v=92e5zD_-xDw I expect Waymo to continue to evolve in a similar direction.
imtringued 2y ago
Tesla is actually an example of relying too much on human domain knowledge. Wayno is brute forcing the problem with hardware. They use Lidar. Elon Musk's argument against Lidar is that humans only need two eyes and therefore stereoscopic vision is enough. "Human drivers use two eyes, therefore self driving cars need two eyes." is exactly the type of thing the bitter lesson is warning against if you stretch the analogy to hardware.
grbsh 2y ago
Tesla / Waymo is a perfect illustration of the point, but the Bitter Lesson doesn’t allow us to pick a winner here. The Bitter Lesson tells us that the Tesla approach (fully end to end, minimizing hand coded features / logic) will _ultimately_ win out. The Bitter Lesson does not tell us that this approach has to economically justify itself 1 year in, 5 years in, or that the approach when the technology is immature will allow a company to avoid bankrupting itself in the meantime while they wait for the data and compute to scale. In other words, just because we know that ultimately (possibly in 20+ years) the Tesla compute-only approach will be simpler and more effective, Tesla might not survive to see this happen. Instead, manual feature engineering and hacking can always give temporary gains over data and compute driven approaches. The bitter lesson was clear about this. I suspect Waymo will win, and at some point in the future once they are out of their growth at all costs stage, they will transition into their maximum value extraction stage, in which vision will make significantly more economic sense than LiDAR. But once they win, they’ll have plenty of time to see the bitter lesson through its ultimate consequences. Elon is right, but he’s probably too early.
- typon 2y ago
  That's religion, not a predictive theory. The Bitter Lesson has held up in a lot of domains where injecting human inductive bias was detrimental. Adding LIDAR for example is not inductive bias - it's a strictly superior form of sensing. You won't call a wolf's sense of smell "hand engineered features" or a cat's reflexes a failure of evolution to extract more signal from an inferior sensory input. Waymo will win because they want to make a product that works and not be ideological about it - that's ultimately what matters.

by typon 2y ago

ModernMech 2y ago

The lesson from Tesla is that AI is not just a magic box where you can put in data and get out intelligence. There are more to working systems than compute, and when they operate in the real world, data isn't enough. The key problem with Tesla cars that keep them from succeeding is not that they don't have enough data, but they have no idea what to do with it. Even if they had infinite compute and all the driving videos in the world, it wouldn't be enough to overcome the limitations of their sensors.

dangus 2y ago
Tesla is a poor counterargument because it is no longer a market leader. It has poor management compared to 10 years ago and seems to be unable to attract top talent (poor labor relations). Tesla is being leapfrogged by competitors across the auto industry. All it has is first mover status (charging network). Tesla purposefully limits the capabilities of its self driving by refusing to implement it with sensors that go beyond smartphone cameras. My belief is that Tesla doesn’t want to actually deliver a car that can drive itself because the end result of Waymo is that fewer people will need to own a car and fleets of short term rental self-driving cars won’t spend frivolous money on prestige and luxury like consumer car buyers. They won’t lease a car and replace it every 2-3 years like some car owners do just because they like having a new car. Fleet vehicle operators purchase cars with razor thin margins and make decisions based solely on economics, as well as having a lot more purchasing leverage over car manufacturers. I don’t think Tesla ever wants self driving to work, they just want to sell the idea of the software.
- immibis 2y ago
  Tesla removed the LIDAR and thought advances in AI would be able to do without one. They were wrong.
  - _ea1k 2y ago
    Tesla didn't remove LIDAR, they never had it. So far, that bet is looking pretty reasonable. It seems evident at the moment that the most formidable competitors in this space could build a solid FSD product with cameras alone, with the biggest variable being time.
    - dangus 2y ago
      Is that evident? The only level 3 certified drive system available in the US (Mercedes) utilizes LIDAR. The only operating robotaxi service also uses it. I would say it’s the opposite of evident that cameras are enough.
      - _ea1k 2y ago
        While Mobileye has focused on using lidar+cameras with each effectively serving as a form of "backup", they have also demonstrated a full city drive using nothing but cameras. I've seen enough from Waymo to see that they could easily do the same thing. I expect both to keep radar and lidar for quite a few years, but I think its usage will consistently decline to zero or near zero over the next 10 years.
        ModernMech 2y ago
        The problem with this prediction is.... why? Camera doesn't actually replace LiDAR, even if we solve getting depth maps from camera 100%. The recent test in which the car ran over a child hidden in a smoke screen is evidence of this. If they purpose of driverless cars is to be better than humans, we should be aiming for them to have super human sensing with camera+lidar+radar etc, instead of human-level sensing with just cameras.
xg15 2y ago
> The key problem with Tesla cars that keep them from succeeding is not that they don't have enough data, but they have no idea what to do with it. Even if they had infinite compute and all the driving videos in the world, it wouldn't be enough to overcome the limitations of their sensors. Isn't this effectively a refutation of the "bitter lesson"?

_ea1k 2y ago

I'd argue that bitter lesson might be the other way around. Waymo has been experimenting with more end-to-end approaches and is likely to end up with something that looks more like that than a "classical control" approach, though maybe not quite the same approach as Tesla's current setup. IMO, this is the best public description of the current state of the art: https://www.youtube.com/watch?v=92e5zD_-xDw https://www.youtube.com/watch?v=92e5zD_-xDw I expect Waymo to continue to evolve in a similar direction.

imtringued 2y ago

Tesla is actually an example of relying too much on human domain knowledge. Wayno is brute forcing the problem with hardware. They use Lidar. Elon Musk's argument against Lidar is that humans only need two eyes and therefore stereoscopic vision is enough. "Human drivers use two eyes, therefore self driving cars need two eyes." is exactly the type of thing the bitter lesson is warning against if you stretch the analogy to hardware.

grbsh 2y ago

Tesla / Waymo is a perfect illustration of the point, but the Bitter Lesson doesn’t allow us to pick a winner here. The Bitter Lesson tells us that the Tesla approach (fully end to end, minimizing hand coded features / logic) will _ultimately_ win out. The Bitter Lesson does not tell us that this approach has to economically justify itself 1 year in, 5 years in, or that the approach when the technology is immature will allow a company to avoid bankrupting itself in the meantime while they wait for the data and compute to scale. In other words, just because we know that ultimately (possibly in 20+ years) the Tesla compute-only approach will be simpler and more effective, Tesla might not survive to see this happen. Instead, manual feature engineering and hacking can always give temporary gains over data and compute driven approaches. The bitter lesson was clear about this. I suspect Waymo will win, and at some point in the future once they are out of their growth at all costs stage, they will transition into their maximum value extraction stage, in which vision will make significantly more economic sense than LiDAR. But once they win, they’ll have plenty of time to see the bitter lesson through its ultimate consequences. Elon is right, but he’s probably too early.

typon 2y ago
That's religion, not a predictive theory. The Bitter Lesson has held up in a lot of domains where injecting human inductive bias was detrimental. Adding LIDAR for example is not inductive bias - it's a strictly superior form of sensing. You won't call a wolf's sense of smell "hand engineered features" or a cat's reflexes a failure of evolution to extract more signal from an inferior sensory input. Waymo will win because they want to make a product that works and not be ideological about it - that's ultimately what matters.