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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 pr

by 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.

by tomp 1y ago

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.