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Full self driving is either a hard problem - requiring advanced sensors and algorithms; or an easy problem - solvable with cameras and neural nets. If it's har

by ddalex 1y ago

Full self driving is either a hard problem - requiring advanced sensors and algorithms; or an easy problem - solvable with cameras and neural nets. If it's hard, Waymo has an insurmountable lead. If it is easy, everyone can replicate easily what Tesla is doing. I'm not seeing any strategic moat on Tesla's side

rcxdude 1y ago
The notional moat is that it's easy given enough training data, which Tesla has a significant hoard of. I'm skeptical of this (they've been in that situation for a long time now), but that's the argument.
- Zigurd 1y ago
  Tesla has imagery from lo-res cameras. If it turns out that LIDAR and/or radar is needed for AVs, the value of that data is questionable.
tomp 1y ago
You simply have no idea how AI works. The key ingredient is data - the bitter lesson. It's not about better algorithms, but simply about algorithms that can process more data efficiently (e.g. transformers). Tesla is one of the few companies that have a data flywheel - a fleet of (non-self-driving) cars collecting real-world data worldwide all the time at massive scale! Now that is an insourmountable lead. (Along with good engineering, which, believe it or not, is still a competitive advantage - see e.g. German car companies unable to launch a single useful on-board computer, let alone a software-defined self-driving car.) Google is one of the few companies that could compete, even without Waymo, because of YouTube.
- dboreham 1y ago
  It will turn out there isn't a linear relationship between data volumes and successful self driving. There will be a wall somewhere that prevents it from being achieved regardless of data (assuming current AI techniques and hardware available in the foreseeable future). So what will happen is Musk and co will demand that roads be redesigned to accommodate their tech (e.g. cars network and human drivers are banned from major highways).
  - tomp 1y ago
    Maybe, but so far we don't really have any examples of good AI (or even barely working AI like GPT4o) that wasn't trained on massive amounts of data. Is data enough? Maybe not, there's a lot of progress on RL now that can do wonders without even more data. Is data necessary? No evidence to the contrary, yet.
  - testing22321 1y ago
    > what will happen is Musk and co will demand that roads be redesigned to accommodate their tech Every road, in every country on earth? No, that is never going to happen.
- aatd86 1y ago
  How would youtube help with driving?
  - tomp 1y ago
    Massive amount of "world" data - enough for Google to successfully train Veo3, a "video generation" model that is extremely good, and evidently includes a decent "world model" i.e. a model that can generate or, more accurately, predict the (short-term) "future" - like "what happens if you let go of an apple" (it falls down) etc. This kind of "world models" that can understand physics enough to be able to predict short term future (like humans can) are crucial for any kind of real-world AI (i.e. robotics, including self-driving), because they constitute what could be termed as "physical common sense" (that humans have, but also animals, to some degree). Is it enough for self-driving? No, you also need to understand road rules, communicate with humans (pedestrians and fellow drivers), etc. but it's a good, possibly necessary, step - it allows you to better handle many unpredictable (tail of distribution) situations: https://www.reddit.com/r/SelfDrivingCars/comments/1g75ftb/waymo_meets_water_fountain/ https://www.reddit.com/r/SelfDrivingCars/comments/1g75ftb/wa... https://www.youtube.com/watch?v=-tJH8hED11I https://www.youtube.com/watch?v=-tJH8hED11I
  - christophilus 1y ago
    My guess is he means they have lots of car-cam videos like this: https://m.youtube.com/watch?v=MejbOFk7H6c&pp=ygUJb2sgZ28gY2Fy https://m.youtube.com/watch?v=MejbOFk7H6c&pp=ygUJb2sgZ28gY2F...
- Spooky23 1y ago
  That’s the Muskophile babble. Cool story, where is it? Reality is the Tesla product in this space hasn’t advanced in a decade. They hit a wall. They have promised that the next big thing is just over the next hill, but like the Roadster, hasn’t quite arrived yet.
  - infecto 1y ago
    I think the person you are responding too has too much hype but you are equally too negative. Without a doubt Musk overpromises and under delivers constantly, would never trust him or his words. Teslas FSD has been improving nicely especially over the last 3 years. To say it’s stalled for a decade is wrong.
    - philistine 1y ago
      The overall point is that automated driving limited to cameras can still improve, but that the threshold is probably very close to the quality, in terms of accident and mistakes, of human driving. The point is that automated driving with a fleet of sensors can be an order of magnitude safer than just using cameras. The current slow improvements at Tesla do not correlate to an unlimited amount of improvements.
      - infecto 1y ago
        “The point” is the original statement I replied to is wrong. FSD has improved significantly in the past few years. Does that mean I think it’s the future or they have won? Nope, not at all. I don’t like Musk but I also don’t let me feelings for him cloud the discussion.
    - ModernMech 1y ago
      Tesla has been getting closer to FSD the same way climbing up a ladder gets you closer to the moon. They can keep going the direction they're going, but at this point it's clear there's a pretty hard limit to how close they're going to get without significantly rethinking their sensor strategy.
- ricardobayes 1y ago
  It's not that car companies are unable, but rather, margins on new cars are pretty thin so they are trying to save every last penny. The key ingredient is indeed data, and also, depending on the stack, hardware. If "true" level 5 self-driving is only possible with LIDAR and up-to-date HD maps, then it won't happen for some time. I foresee that unbounded "full" self-driving will either never happen or with severe boundary conditions only.
- rsfern 1y ago
  This is sort of a misguided take IMO - as if LiDAR and other sensor streams are somehow not large scale data while video is The bitter lesson isn’t fundamentally even about data. the key ingredient is computation (which does scale with data in modern deep learning). There’s even a whole theme on search outperforming learning - until learning methods changed to leverage computation! I think in a lot of applications, richer data yields better scaling performance. So the bet for self driving is that the complexity of multiple sensor fusion gives a much better constant factor or exponent in the power law scaling of performance with data and compute
  - steveBK123 1y ago
    Right this is why we periodically see Tesla's in FSD go absolutely bezerk in ways more sensor-laden competitors do not appear to. https://electrek.co/2025/05/23/tesla-full-self-driving-veers-off-road-flips-car-scary-crash-driver-couldnt-prevent/ https://electrek.co/2025/05/23/tesla-full-self-driving-veers... This was literally 2 months ago, so miss me with the "you're wrong, the latest FSD solved it all this time bro, for real, trust me (the 100th time I've heard this)".
    - adwn 1y ago
      From the article: > Despite its name, Full Self-Driving (FSD) is still considered a level 2 driver assist system and is not fully self-driving. How the hell has Tesla not been sued into the ground by now?
      - deleted 1y ago
        [deleted]
    - birn559 1y ago
      Will we be able mid-term to rely on LLMs not hallucinating and causing crashes? Even if the probability is low, the thought that the AI might do something crazy because it's hallucinating is terrifying, so that might be a barrier for adoption. For the same reason, will a (fully) LLM driven car ever be allowed on Western streets? I have serious doubts regarding Europe, at least.
- brk 1y ago
  Almost every vehicle has multiple cameras in it today, plus cellular connectivity. Tesla doesn't have a major advantage here. Plus, the data isn't immediately valuable on its own, it needs to be labelled and fed back into the training. This is all very far from a data flywheel analogy. Musk equates machine vision to human vision, but that is an over simplification, and the best MV algorithms and methods are still miles away from human capabilities. FSD is very reliant on depth perception, which is much easier to solve with sensors other than stereo vision. I also don't get your German car company statement, Mercedes has been a technology leader in the automotive space across a number of fronts for quite a while.
- fsh 1y ago
  Transformer LLMs are good at generating text since they were trained on huge volumes of high quality texts. There is no reason to assume that feeding a neural net with unlabeled garbage data (i.e. video recordings from random cars) is going to lead to anything.
jillesvangurp 1y ago
I agree with you on the moat side. Tesla is very late to this market. But, I would also argue that Waymo's moat isn't that wide either. Waymo is probably behind their Chinese counterparts that are already operating at a larger scale. More rides. Larger cities. And more of them. Waymo isn't the only player in the market and unlike Tesla and their Chinese competitors, they aren't really structured as a manufacturing operation. They are modifying consumer cars made by others, probably at great cost. That raises the question about how they are going to scale. Waymo is so far not a scalable operation. They can manage thousands of cars. But can they handle millions? Or make a profit. Chinese manufacturers, like Tesla, have a ready answer to that by virtue of their proven manufacturing skills. And it seems they so far don't need Waymo's software to get their cars to drive themselves. Tesla is late. But they can build cars at scale. So, I'm not ready to claim they are too late yet. I think Waymo might have a bright future ahead licensing their platform to manufacturers that are, so far, not showing many signs of having their own version of this. As for whether this is technically possible or not, I think it's hard to argue that it's not from the back of a self driving taxi. I've not had that pleasure yet (none around near where I live) but I've seen enough to not be that foolish.
- jonstewart 1y ago
  I wonder how long a Chinese FSD car would last on the BWI parkway coping with Maryland drivers before it pulled over for a good cry.
  - gcr 1y ago
    Who would you trust more: an FSD that’s learned to survive Xi’an rush hour and Wenzhou’s interpretive traffic balet, or one that’s learned to panic brake in Palo Alto? America doesn’t have a monopoly on challenging driving situations, y’know. :-)
    - op00to 1y ago
      Is it still the case in China that it's cheaper to kill a pedestrian you hit with your car than it is to pay out damages? This might be propaganda! If so, I wonder if or how that affects the algorithms for pedestrian avoidance. :)
steveBK123 1y ago
I had a Tesla 2018-2022, and switched to a competing EV brand at that point. The fact that Tesla has removed sensors since then while competitors have added says a lot. My car doesn't even have LIDAR but it has 5 radar sensors (corners & forward) so it can do all sorts of neat stuff. For example, it has actual working adjacent lane blindspot detection, which Tesla never dialed in. It also can warn you about oncoming cars at intersections or when backing out of parking spots. It even flashes lights on the doors if you try to open a door when a car is coming in the adjacent lane. None of that is full self driving but it leaves me wondering what Tesla can ever accomplish with cameras-only.
- rimunroe 1y ago
  > For example, it has actual working adjacent lane blindspot detection Is this not standard? I don’t think my Hyundai Ioniq 5’s blind spot detection has ever failed to warn me about a car in my blind spot
  - steveBK123 1y ago
    Tesla literally didn't have it in 2018, and slowly added a poor implementation of it over time. Recall the card hardware had no light not he mirror or in the window sill to alert you, so their early version required looking at the screen. Current Teslas at least actually have some sort of light in the sill, but again its using cameras only, no radar, sonar, whatever.
    - gcr 1y ago
      That’s really surprising. Whenever I rent a car, I’ve relied on that feature as standard issue for modern vehicles. It’s like selling a Tesla without an air conditioner.
      - philistine 1y ago
        Tesla's were ahead of the curve on most things when they first came out. Tesla has refused to join the year model model, so their changes have been haphazard, often regressive, and ultimately very slow. They still are ahead on some technologies, with the Cybertruck's one and only interesting technology its drive-by-wire system, but the industry has caught up and overtaken Tesla with the relentless progress of the year model.
onlyrealcuzzo 1y ago
How hard the problem is may depend on how successful you are at lobbying politicians to force your solution down the public's throat...
boshalfoshal 1y ago
You are thinking about "hard" and "easy" in the wrong frame of mind. What Tesla does is not "easy" either. Their moat is manufacturing and the R&D they've spent on codesigning their HW and SW stack, and their insane supply chain. Ford does not suddenly have several million cars with 8-9 cameras to tap into for training data, nor does it have the infrastructure/talent to train models with the data it may get. I think you are underselling the Tesla moat. Its the same reason why there are only 3-4 "frontier" AI labs, and the rest are just playing catchup, despite a lot of LLM improvements being pretty well researched and open in papers.

by ddalex 1y ago

rcxdude 1y ago

The notional moat is that it's easy given enough training data, which Tesla has a significant hoard of. I'm skeptical of this (they've been in that situation for a long time now), but that's the argument.

Zigurd 1y ago
Tesla has imagery from lo-res cameras. If it turns out that LIDAR and/or radar is needed for AVs, the value of that data is questionable.

tomp 1y ago

You simply have no idea how AI works. The key ingredient is data - the bitter lesson. It's not about better algorithms, but simply about algorithms that can process more data efficiently (e.g. transformers). Tesla is one of the few companies that have a data flywheel - a fleet of (non-self-driving) cars collecting real-world data worldwide all the time at massive scale! Now that is an insourmountable lead. (Along with good engineering, which, believe it or not, is still a competitive advantage - see e.g. German car companies unable to launch a single useful on-board computer, let alone a software-defined self-driving car.) Google is one of the few companies that could compete, even without Waymo, because of YouTube.

dboreham 1y ago
It will turn out there isn't a linear relationship between data volumes and successful self driving. There will be a wall somewhere that prevents it from being achieved regardless of data (assuming current AI techniques and hardware available in the foreseeable future). So what will happen is Musk and co will demand that roads be redesigned to accommodate their tech (e.g. cars network and human drivers are banned from major highways).
- tomp 1y ago
  Maybe, but so far we don't really have any examples of good AI (or even barely working AI like GPT4o) that wasn't trained on massive amounts of data. Is data enough? Maybe not, there's a lot of progress on RL now that can do wonders without even more data. Is data necessary? No evidence to the contrary, yet.
- testing22321 1y ago
  > what will happen is Musk and co will demand that roads be redesigned to accommodate their tech Every road, in every country on earth? No, that is never going to happen.
aatd86 1y ago
How would youtube help with driving?
- tomp 1y ago
  Massive amount of "world" data - enough for Google to successfully train Veo3, a "video generation" model that is extremely good, and evidently includes a decent "world model" i.e. a model that can generate or, more accurately, predict the (short-term) "future" - like "what happens if you let go of an apple" (it falls down) etc. This kind of "world models" that can understand physics enough to be able to predict short term future (like humans can) are crucial for any kind of real-world AI (i.e. robotics, including self-driving), because they constitute what could be termed as "physical common sense" (that humans have, but also animals, to some degree). Is it enough for self-driving? No, you also need to understand road rules, communicate with humans (pedestrians and fellow drivers), etc. but it's a good, possibly necessary, step - it allows you to better handle many unpredictable (tail of distribution) situations: https://www.reddit.com/r/SelfDrivingCars/comments/1g75ftb/waymo_meets_water_fountain/ https://www.reddit.com/r/SelfDrivingCars/comments/1g75ftb/wa... https://www.youtube.com/watch?v=-tJH8hED11I https://www.youtube.com/watch?v=-tJH8hED11I
- christophilus 1y ago
  My guess is he means they have lots of car-cam videos like this: https://m.youtube.com/watch?v=MejbOFk7H6c&pp=ygUJb2sgZ28gY2Fy https://m.youtube.com/watch?v=MejbOFk7H6c&pp=ygUJb2sgZ28gY2F...
Spooky23 1y ago
That’s the Muskophile babble. Cool story, where is it? Reality is the Tesla product in this space hasn’t advanced in a decade. They hit a wall. They have promised that the next big thing is just over the next hill, but like the Roadster, hasn’t quite arrived yet.
- infecto 1y ago
  I think the person you are responding too has too much hype but you are equally too negative. Without a doubt Musk overpromises and under delivers constantly, would never trust him or his words. Teslas FSD has been improving nicely especially over the last 3 years. To say it’s stalled for a decade is wrong.
  - philistine 1y ago
    The overall point is that automated driving limited to cameras can still improve, but that the threshold is probably very close to the quality, in terms of accident and mistakes, of human driving. The point is that automated driving with a fleet of sensors can be an order of magnitude safer than just using cameras. The current slow improvements at Tesla do not correlate to an unlimited amount of improvements.
    - infecto 1y ago
      “The point” is the original statement I replied to is wrong. FSD has improved significantly in the past few years. Does that mean I think it’s the future or they have won? Nope, not at all. I don’t like Musk but I also don’t let me feelings for him cloud the discussion.
  - ModernMech 1y ago
    Tesla has been getting closer to FSD the same way climbing up a ladder gets you closer to the moon. They can keep going the direction they're going, but at this point it's clear there's a pretty hard limit to how close they're going to get without significantly rethinking their sensor strategy.
ricardobayes 1y ago
It's not that car companies are unable, but rather, margins on new cars are pretty thin so they are trying to save every last penny. The key ingredient is indeed data, and also, depending on the stack, hardware. If "true" level 5 self-driving is only possible with LIDAR and up-to-date HD maps, then it won't happen for some time. I foresee that unbounded "full" self-driving will either never happen or with severe boundary conditions only.
rsfern 1y ago
This is sort of a misguided take IMO - as if LiDAR and other sensor streams are somehow not large scale data while video is The bitter lesson isn’t fundamentally even about data. the key ingredient is computation (which does scale with data in modern deep learning). There’s even a whole theme on search outperforming learning - until learning methods changed to leverage computation! I think in a lot of applications, richer data yields better scaling performance. So the bet for self driving is that the complexity of multiple sensor fusion gives a much better constant factor or exponent in the power law scaling of performance with data and compute
- steveBK123 1y ago
  Right this is why we periodically see Tesla's in FSD go absolutely bezerk in ways more sensor-laden competitors do not appear to. https://electrek.co/2025/05/23/tesla-full-self-driving-veers-off-road-flips-car-scary-crash-driver-couldnt-prevent/ https://electrek.co/2025/05/23/tesla-full-self-driving-veers... This was literally 2 months ago, so miss me with the "you're wrong, the latest FSD solved it all this time bro, for real, trust me (the 100th time I've heard this)".
  - adwn 1y ago
    From the article: > Despite its name, Full Self-Driving (FSD) is still considered a level 2 driver assist system and is not fully self-driving. How the hell has Tesla not been sued into the ground by now?
    - deleted 1y ago
      [deleted]
  - birn559 1y ago
    Will we be able mid-term to rely on LLMs not hallucinating and causing crashes? Even if the probability is low, the thought that the AI might do something crazy because it's hallucinating is terrifying, so that might be a barrier for adoption. For the same reason, will a (fully) LLM driven car ever be allowed on Western streets? I have serious doubts regarding Europe, at least.
brk 1y ago
Almost every vehicle has multiple cameras in it today, plus cellular connectivity. Tesla doesn't have a major advantage here. Plus, the data isn't immediately valuable on its own, it needs to be labelled and fed back into the training. This is all very far from a data flywheel analogy. Musk equates machine vision to human vision, but that is an over simplification, and the best MV algorithms and methods are still miles away from human capabilities. FSD is very reliant on depth perception, which is much easier to solve with sensors other than stereo vision. I also don't get your German car company statement, Mercedes has been a technology leader in the automotive space across a number of fronts for quite a while.
fsh 1y ago
Transformer LLMs are good at generating text since they were trained on huge volumes of high quality texts. There is no reason to assume that feeding a neural net with unlabeled garbage data (i.e. video recordings from random cars) is going to lead to anything.

jillesvangurp 1y ago

I agree with you on the moat side. Tesla is very late to this market. But, I would also argue that Waymo's moat isn't that wide either. Waymo is probably behind their Chinese counterparts that are already operating at a larger scale. More rides. Larger cities. And more of them. Waymo isn't the only player in the market and unlike Tesla and their Chinese competitors, they aren't really structured as a manufacturing operation. They are modifying consumer cars made by others, probably at great cost. That raises the question about how they are going to scale. Waymo is so far not a scalable operation. They can manage thousands of cars. But can they handle millions? Or make a profit. Chinese manufacturers, like Tesla, have a ready answer to that by virtue of their proven manufacturing skills. And it seems they so far don't need Waymo's software to get their cars to drive themselves. Tesla is late. But they can build cars at scale. So, I'm not ready to claim they are too late yet. I think Waymo might have a bright future ahead licensing their platform to manufacturers that are, so far, not showing many signs of having their own version of this. As for whether this is technically possible or not, I think it's hard to argue that it's not from the back of a self driving taxi. I've not had that pleasure yet (none around near where I live) but I've seen enough to not be that foolish.

jonstewart 1y ago
I wonder how long a Chinese FSD car would last on the BWI parkway coping with Maryland drivers before it pulled over for a good cry.
- gcr 1y ago
  Who would you trust more: an FSD that’s learned to survive Xi’an rush hour and Wenzhou’s interpretive traffic balet, or one that’s learned to panic brake in Palo Alto? America doesn’t have a monopoly on challenging driving situations, y’know. :-)
  - op00to 1y ago
    Is it still the case in China that it's cheaper to kill a pedestrian you hit with your car than it is to pay out damages? This might be propaganda! If so, I wonder if or how that affects the algorithms for pedestrian avoidance. :)

steveBK123 1y ago

I had a Tesla 2018-2022, and switched to a competing EV brand at that point. The fact that Tesla has removed sensors since then while competitors have added says a lot. My car doesn't even have LIDAR but it has 5 radar sensors (corners & forward) so it can do all sorts of neat stuff. For example, it has actual working adjacent lane blindspot detection, which Tesla never dialed in. It also can warn you about oncoming cars at intersections or when backing out of parking spots. It even flashes lights on the doors if you try to open a door when a car is coming in the adjacent lane. None of that is full self driving but it leaves me wondering what Tesla can ever accomplish with cameras-only.

rimunroe 1y ago
> For example, it has actual working adjacent lane blindspot detection Is this not standard? I don’t think my Hyundai Ioniq 5’s blind spot detection has ever failed to warn me about a car in my blind spot
- steveBK123 1y ago
  Tesla literally didn't have it in 2018, and slowly added a poor implementation of it over time. Recall the card hardware had no light not he mirror or in the window sill to alert you, so their early version required looking at the screen. Current Teslas at least actually have some sort of light in the sill, but again its using cameras only, no radar, sonar, whatever.
  - gcr 1y ago
    That’s really surprising. Whenever I rent a car, I’ve relied on that feature as standard issue for modern vehicles. It’s like selling a Tesla without an air conditioner.
    - philistine 1y ago
      Tesla's were ahead of the curve on most things when they first came out. Tesla has refused to join the year model model, so their changes have been haphazard, often regressive, and ultimately very slow. They still are ahead on some technologies, with the Cybertruck's one and only interesting technology its drive-by-wire system, but the industry has caught up and overtaken Tesla with the relentless progress of the year model.

onlyrealcuzzo 1y ago

How hard the problem is may depend on how successful you are at lobbying politicians to force your solution down the public's throat...

boshalfoshal 1y ago

You are thinking about "hard" and "easy" in the wrong frame of mind. What Tesla does is not "easy" either. Their moat is manufacturing and the R&D they've spent on codesigning their HW and SW stack, and their insane supply chain. Ford does not suddenly have several million cars with 8-9 cameras to tap into for training data, nor does it have the infrastructure/talent to train models with the data it may get. I think you are underselling the Tesla moat. Its the same reason why there are only 3-4 "frontier" AI labs, and the rest are just playing catchup, despite a lot of LLM improvements being pretty well researched and open in papers.