43 ms·

Andrej Karpathy (Tesla): CVPR 2021 Workshop on Autonomous Vehicles [video]

189 points by vpj 5y ago

sam_goody 5y ago
tldr: Tesla uses vision alone, and has dropped radar and the other sensor. He makes a very decent argument why. (Surprisingly, he basically ignores night driving.)
- nickik 5y ago
  The list of triggers contains things like 'motorcycles at night', so it seems its all in that dataset.
- dogma1138 5y ago
  Ironically this is what Tesla criticized Mobileye for. I still think that this is far the best demonstration of autonomous driving to date https://youtu.be/A1qNdHPyHu4 https://youtu.be/A1qNdHPyHu4
  - marricks 5y ago
    Wow that demo has it all. - car stalled in it's lane - complicated intersections - people exiting cars in it's lane - car going over into it's lane If I had an hour of driving that I'd be stressed.
    - halotrope 5y ago
      Wait until you see the Jerusalem 40 minute video. Munich traffic is tame in comparison: https://youtu.be/kJD5R_yQ9aw https://youtu.be/kJD5R_yQ9aw I really don’t understand why mobileye gets so little recognition. They might be quietly winning the self driving race.
  - aimkey 5y ago
    The 11 minute mark is terrifying: 1) The car fails to accelerate to beat the truck as it merges (the safest option given the scenario, even with the yield sign) 2) The car almost collides with the trailer of the truck and it stops with its nose sticking out into the merge lane 3) The car sits there with its nose in the merge lane as other cars go by 4) When the car finally has an opportunity to merge after having done everything wrong up to this point, it sheepishly merges and takes forever to get up to speed. This is basically the least safe thing it can do when yield-merging into a high speed lane. LOL. This is the best the autonomous driving world has to offer? 80% of this driving is an immediate failure for a teenage driver taking their road course. I think I can take pretty much any random 2 minute sample from that video and find more than a few inputs/maneuvers that would lead to failure in a driver's license test. Why would ANYONE with a brain put their life into the hands of this system? OH, and do you want to know a little industry secret about these "unedited" long videos? Yes, the video is uncut. But guess what? They drove that route hundreds of times and only showed the best run. And they got laser-HD maps of the route that they won't have globally. This is what Zoox did for their infamous demo that got them bought out by Amazon. And it's what Tesla did for their "Full Self-Driving" video on YouTube that shows driving ability that their cars cannot match even today. Shhh, you didn't hear it from me.
    - watt 5y ago
      Sorry at (1) yield means yield. Maybe it shouldn't have stuck the nose so far out, but yeah you have to wait until proper gap in the traffic. The non-accelerating to highway speed is the real bug though.
      - aimkey 5y ago
        There WAS a proper gap in traffic if the car used its accelerator on the ramp. The car would not have impeded the truck at all if it drove the ramp faster. This is an incredibly common issue with autonomous systems: anticipation of other vehicles with an awkward angle of attack, which is common while merging or while other cars are merging. Also, autonomous systems also tend to be way too cautious, which is incredibly dangerous in merging scenarios. A good driver accelerates on that ramp on beats the truck by 2-3 car lengths and merges at speed. Yield does not mean stop. A cautious driver slows before the merge point, maintains a roll, then mashes the accelerator to merge safely at next opportunity. A terrible driver (Mobileye) stop abruptly at the end of the merge junction, almost hits a truck, leaves its front end sticking out into the oncoming traffic, then dangerously merges sheepishly without accelerating fast enough. You can even see how much this freaks out the human passenger. He thought he was going to get hit!
        nexuist 5y ago
        > A good driver accelerates on that ramp on beats the truck by 2-3 car lengths and merges at speed No. A good driver stops at the yield sign if an approaching vehicle is 2-3 car lengths away. It is dangerous to play guessing games with your car's engine and another driver's attention. If anything goes wrong (tire puncture, engine dies, slippery road, truck driver slams the gas) you have successfully managed to put yourself into the direct path of a speeding brick wall 5x as heavy as you. There is never a safe merging scenario where the right choice is to slam the gas pedal to beat another driver to the punch, especially not when merging onto an active freeway. If there is a yield sign at the end of the onramp, that means prepare to yield. If there is not a yield sign, then the expectation is to keep merging. There wouldn't be a point to the yield sign if everyone treated it as if it didn't exist. > leaves its front end sticking out into the oncoming traffic, I also agree with you but this may be a byproduct of the camera's perspective and maybe it would look normal in the driver's seat. We don't really have a great view but the truck could also have been hugging the curb which would have brought it closer to the car than it should be. > dangerously merges sheepishly without accelerating fast enough Fully agree here. If you merge you have to commit to matching the speed of nearby vehicles or else you're creating a dangerous situation. Mobileye should have sped up much faster than it did. I'm not a neural network, fwiw.
- 01100011 5y ago
  Not a fan of TSLA, but isn't night driving just a special case of daytime driving if you use IR and/or hyperspectral cameras?
  - tedk-42 5y ago
    I imagine it's far more tricky due to the lower image quality and increased noise on the sensors (less light/energy hitting them). Loss of colours in your visual imput as well is a bit of an issue...
childintime 5y ago
The video: https://youtu.be/NSDTZQdo6H8 https://youtu.be/NSDTZQdo6H8
- dang 5y ago
  Thanks! Maybe it's best if we change the URL to that from https://twitter.com/vpj/status/1407000737423368197 https://twitter.com/vpj/status/1407000737423368197.
  - ejdyksen 5y ago
    That video is a screen capture from another video (which was screen capped from a livestream), but the original has much better audio quality. Here's a direct link: https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28293s https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28293s
    - dang 5y ago
      Ok, I've switched to that link above (from https://www.youtube.com/watch?v=NSDTZQdo6H8 https://www.youtube.com/watch?v=NSDTZQdo6H8). Thanks!
nickik 5y ago
I resonantly had an argument on here where somebody insistent that breaking because of over-passes were issues with vision system. Seem pretty clear that it is the resolution of the radar, not the shadow of the bridge that causes the issue. Good to get some more insight into this. This is the right thing to focus on, as it is by far the largest issue with Autopilot on the highway. Multiple people who do testing of these system that false positives on some highway overpasses are the biggest usability issue.
- pokerhobo 5y ago
  The video directly addresses this…
andyxor 5y ago
I like Andrej from his PhD research days and awesome blog posts but this is a series of disasters in the making, that is until FTC steps in after more people die from “self-driving” accidents under interesting and unexpected circumstances. The whole vision vs. LIDAR stuff is a distraction as long as Tesla “AI” doesn’t have common sense. It literally doesn’t know what it’s doing, and the tail of edge cases to "fit" the models is infinitely long. ANNs are fundamentally backwards looking and cannot adapt to unforeseen or even slightly unusual combination of circumstances. It will go fine for n miles and will dramatically fail at mile n+1 where a new situation requires understanding of ones surroundings, and n is arbitrary number. It would be more honest to show the cases where it missed, thankfully there is no lack of them in “FSD beta“ videos on YouTube.
- option 5y ago
  There are two fundamental reasons, in principle, vision alone can do it: 1) Humans do it with vision alone 2) You can actually predict lidar’s output with vision alone. So many systems out there actually use lidar to generate more labeled data to make lidar unnecessary
  - andyxor 5y ago
    besides vision, humans also have this thing called brain, and reasoning, and instincts, and being able to tell if the object in front of them is e.g. a roof of an overturned truck vs. empty space, etc, etc. the key word is "etc" which expands into infinite tail, which no big data training on farms of GPUs would ever help with. Humans and other animals have an ability to understand the scene and generalize from prior experiences to infinite set of new and unexpected circumstances, the "common sense" these dumb curve-fitting models are fundamentally lacking.
    - darknavi 5y ago
      > humans also have this thing called brain, and reasoning, and instincts, and being able to tell if the object in front of them is e.g. a roof of an overturned truck vs. empty space, etc, etc. Assuming the car is reasonably good at this, it has the advantage that it can see in every direction at once. I don't think self-driving cars will ever be perfect, but I think they will quickly become less-lethal than the average human.
nightski 5y ago
It's interesting that an academic conference now feels like a marketing op for industrial research labs more than anything. His claims about how accurate their vision system is and how it is exceeding other sensors is not verifiable in any way to the public. Given how well qualified he is I am sure he is not wrong! Andrej is brilliant. But this is an academic conference right? This isn't open science, it's a discussion about an engineered system. I'm afraid this is the future of ML research (which CV is so heavily dependent on now). Long gone are the days of reading a paper and understanding the approach. Now you need the data and model which may not even be computationally feasible without millions of dollars in hardware. This isn't Tesla's fault or anything, it just makes me sad.
- aeternum 5y ago
  In the talk, he gave clear examples with detailed position + velocity graphs where the vision system detected obstacles sooner and with less jitter than the radar system. Specifically the overpass where radar triggers erroneous braking, and the pulled over truck where radar detects the obstacle significantly slower.
  - stefan_ 5y ago
    That's a strawman. No one is looking to build FSD with radar sensors that have shipped on cars for 20 years now for things like adaptive cruise control. LIDAR is what vision only is compared to.
    - nickik 5y ago
      Radar is the technology that is actually shipping in millions of cars. Lidar is future tech that is not practically to deploy in millions of cars as of now. There is absolutely 0 chance they could just 'put in lidar' from now on so for what he has to do its not relevant.
      - deleted 5y ago
        [deleted]
ketamine__ 5y ago
I've read claims that they are desperately trying to hire. https://mobile.twitter.com/TaylorOgan/status/1407051918317395968 https://mobile.twitter.com/TaylorOgan/status/140705191831739...
- DSingularity 5y ago
  Maybe it’s an unfortunate side effect of their success. Almost all early members of the team are now multi millionaires if they held their stock.
- jowday 5y ago
  Anecdata but both of the people I know that worked on Autopilot quit within 18 months of starting, citing extreme overwork and Musk micromanaging things. This lines up with that.
  - nickik 5y ago
    People have been claiming the same thing about SpaceX and Tesla for 20+ years now doesn't seem to stop them. Having a small sample size theater about people you personally know isn't really representative.
- karpathy 5y ago
  For the record these are some blatant & false FUD attempts.
  - darknavi 5y ago
    Good to hear it from the source! Great talk by the way. As someone in the CS field but with no knowledge of CV/NN I still find these presentations very insightful.
  - revscat 5y ago
    There is a lot of that on HN whenever Tesla is the subject.
    - 5y ago
Robotbeat 5y ago
He made a very good argument for vision-only, but it seems like training actually uses radar data to help calibrate vision measurements, so it seems to me there’s value in making some vehicles still contain radar (say, one out of 10) even if it’s not used for controlling the vehicle directly at drive time. Also, the sensor resolution issue he mentioned could be addressed by using a higher resolution radar sensor. I find the list of 221 triggers to be interesting. In principle, the NHTSA or NTSB could help contribute lists of triggers to companies to validate their training sets on. Every time there is a fatal airliner accident, the NTSB does a safety investigation and airliners get a little bit safer each time. In the same way, each fatal accident in a vehicle with this kind of autonomy could end up being captured by these triggers, improving safety over time in a sort of mixture between expert human analysis and ML. (Nobody does this for all regular car crashes because fatal car crashes happen every day! And you’re not going to retrain human drivers about some new edge case every day, although you can for vehicles like this.)
- avs733 5y ago
  Most fatal car crashes are investigated, but by the police not engineering experts. The invetigational motivation is legal and liability focused not improvement focused. You sparked a happy delusion in my mind...training drivers to the same level we train pilots. Can you imagine drivers having regular check rides?
  - eddanger 5y ago
    I would love to see re-certification of "professional" drivers. Almost daily I encounter taxi or semi-truck operators driving at the limit of what is acceptable.
- osipov 5y ago
  > so it seems to me there’s value in making some vehicles still contain radar (say, one out of 10) even if it’s not used for controlling the vehicle directly at drive time. That's not how neural networks work. You start by training them with a radar, then you deploy them without the radar. Neural nets make the radar irrelevant post-training. This is the entire point of Karpathy's pitch.
bluepanda928752 5y ago
Tesla's decision not to use the LIDAR as a safety feature (i.e. having reliable high-resolution data about things the car can collide with) is so incredibly indefensible, since solving the last 1% of this using only vision likely requires a general artificial intelligence Prediction: Tesla will be the last of all major auto manufacturers to get to L5 autonomy. Time interval between when Tesla L5 FSD is finally available and when humanity is destroyed by the general AI it runs on will be very awesome and also very short
- soheil 5y ago
  > is so incredibly indefensible How can you make such a strong statement when you simply don't know how to achieve full autonomy? This reminds of the teapot orbiting the Sun argument [0]. You and people defending Lidar by their teeth don't sound too different from religious zealots who've "seen the light". [0] https://en.wikipedia.org/wiki/Russell%27s_teapot https://en.wikipedia.org/wiki/Russell%27s_teapot
- SheinhardtWigCo 5y ago
  They’re betting that they can use a massive feedback loop to train a set of neural networks to the point where they are as accurate as LiDAR without actually firing any lasers. Even if you believe this goal is possible to achieve at some point in the future, I think the argument falls apart when you consider that it will take years, probably decades, for a pure vision approach to catch up to where Waymo is today in terms of safety. (They have cameras too.) That Tesla can’t afford to fit expensive LiDAR sensors to all of the cars it sells is Tesla’s problem. Regulators won’t give a shit that pure vision is “better” in theory. They will simply compare Tesla’s crash rate in autonomous mode with that of Waymo and other AV operators, and act accordingly.
  - DSingularity 5y ago
    Definitely. Especially with car companies like NIO strapping in LIDAR to their upcoming models.
  - bluepanda928752 5y ago
aiddun 5y ago
Per "it's unscalable to get HD 3D maps of all the roads on earth", it's interesting to consider that Google/Waymo has been growing this for years with street view and the sensors on each car. Curious to see how that plays out
- nickik 5y ago
  HD 3D maps need to be way more accurate and be enriched with massive amounts of detail. Like where lights are, what lights are relevant for what lanes and so on. You can't just pull out your street view footage from 3 years ago.
  - aiddun 5y ago
    Good point. Street view cars since 2017 have had high def Lidar sensors on them[0], and they have some prowess in extracting features [1], but I'm not sure if that's enough detail. [0] https://www.geoweeknews.com/blogs/google-putting-lidar-new-street-view-cars https://www.geoweeknews.com/blogs/google-putting-lidar-new-s... [1] https://www.androidpolice.com/2021/01/16/google-maps-is-rolling-out-incredibly-accurate-street-level-details-in-these-4-cities/ https://www.androidpolice.com/2021/01/16/google-maps-is-roll...
aimkey 5y ago
What an annoying charlatan. Karpathy is a brilliant computer vision engineer, but he has let his expertise in that subfield cloud his judgement on achieving the overall goal of autonomous driving. Musk and Karpathy have been dead wrong about LIDAR for years. Remember Musk making the absurd claim of a million Tesla robotaxis by 2020? I think most hilarious is that both Karpathy and Musk claim the LIDAR systems are too expensive. Yet, in the same 2019 Autonomy Day they simultaneously claimed that Teslas would be able to drive themselves and operate as robotaxis, earning their owners passive income and therefore justifying significantly increased MSRPs. So, the $7k LIDAR system (that accelerates safe autonomous driving) is not worth the cost, yet stumbling towards autonomy on vision only is? If the car becomes an money-earner, you should use all of the systems available. The 2019 Autonomy Day was an utter embarrassment. I'm sure 2021 will be more of the same. So now it seems that they've realized their folly in logic. So what's the solution? Well, you can't just complain about COST of non-vision perception systems. Because, as noted above, that doesn't make sense if you're going to simultaneously claim that your car will be able to earn you money (augmenting any extra hardware cost that gets you to that point faster). No, now you have to smear all non-vision perception systems. You have to say that their data is worthless and detrimental to the overall effort. The entire claim from the 2019 Autonomy Day that "vision is what humans use to drive" is also completely bogus. Humans use many senses to drive. They feel the pedals and steering wheel. They use their equilibrio sense to sense motion. And they use their hearing to hear other vehicles, sirens, and issues with their own car (driving with headphones in is illegal for a reason). Any modern car, even a Tesla, is also using far more than just vision when attempting autonomy. Forget about radar and LIDAR for a moment. There are endless sensors in the drivetrain. Steering angle sensors and multiple IMUs for the electronic stability control. Brake and wheel sensors for the ABS. Temperature sensors everywhere. And countless other ECUs. The notion that vision is getting you there exclusively is nonsense. There's no good argument against LIDAR today other than perpetuating a lie to sell cars that are cheaper to produce. And, Karpathy has a massive professional conflict of interest in making CV the main player -- he's a CV expert. He was never a fusion expert before his hire. If CV is the pathway forward, he's gets to remain "the guy". It certainly behooves HIM to make that claim. Autonomous driving will not be achieved in this decade. Perhaps ever. Ask yourself honestly: if you were tasked with building an autonomous commercial aircraft OR an autonomous car, which would you choose? Most would say aircraft -- nothing to really hit in the air, fully mapped airport and runway systems, and far fewer variables. Yet autonomous aircraft still do not exist. Perhaps the edge cases always rule the roost. Ask yourself why driving would be any different...
accurrent 5y ago
I see a lot of people here are stuck on the perception side of things. There's a lot more to self driving than just the sensor suite and perception. There's a lot of work that needs to be done in the planning and controls department prior to the time we get full vehicle autonomy. Andrej's work is impressive, but I wish we'd see more research into the latter. Then again this is CVPR so...
deleted 5y ago
[deleted]
babesh 5y ago
I think the more interesting question is how much human context is necessary in decreasing accident rates. The signal question and tunnel answer hinted at that. Some context is very local and some context is general at the level of humans. Examples: human eyes will have trouble adjusting to the sudden darkness of tunnels so some people will tend to brake suddenly; that person looks old and will probably have slower reaction times so watch out for the upcoming sharp turn; that person looks like they are on their phone and may cross the lane suddenly; watch out for this intersection because young humans cross it after school without looking so slow down below the speed limit. This human understanding doesn’t seem to be directly represented by the system without explicit architecting on their part. A more general intelligence would begin to automatically learn these. A human intelligence would automatically model these or learn from experience or read about it. As mentioned, the current system has some advantages over humans: more eyes, doesn’t get tired or distracted, faster reaction time. I guess we shall see when these advantages cover up the disadvantages.
- fpgaminer 5y ago
  I agree, though I think there's an obvious path towards that higher order understanding of the road that humans have. Suppose they eventually have this current system dialed in and they get really good, accurate bounding boxes around all interesting objects on the road. So now, in addition to their 10 second samples of video data they're collecting, they start collecting 10 second samples of scene representations. These samples of scene representations are time series of how various objects in the scene are moving and behaving over time. Many examples of just what you describe: cars with older drivers having slower reaction times; cars with distracted drivers driving recklessly; etc. Now you train a model on all that data, asking it to make predictions through time. It's going to quickly pick up on the same or similar cues that humans do. It sees an older person in a car and says that slower, cautious paths through the scene are more likely for that vehicle. They see a large, lifted truck and assume a 90% probability of a "cut off every car possible" path through the scene. Etc. So I see what Karpathy is building now as a foundation upon which they can build the higher order stuff.
  - babesh 5y ago
villgax 5y ago
Even if FSD takes longer, I sure am glad about the active safety features to prevent dumb incidents. Hope that trickles to every other manufacturer petrol/electric
- rpmisms 5y ago
  There's clip after clip of AP yanking people out of situations where they had no idea they were in danger. Wife and I are planning on kids soon, and we won't consider anything except a Tesla due to those safety features.

189 points by vpj 5y ago

tldr: Tesla uses vision alone, and has dropped radar and the other sensor. He makes a very decent argument why. (Surprisingly, he basically ignores night driving.)

nickik 5y ago
The list of triggers contains things like 'motorcycles at night', so it seems its all in that dataset.
dogma1138 5y ago
Ironically this is what Tesla criticized Mobileye for. I still think that this is far the best demonstration of autonomous driving to date https://youtu.be/A1qNdHPyHu4 https://youtu.be/A1qNdHPyHu4
- marricks 5y ago
  Wow that demo has it all. - car stalled in it's lane - complicated intersections - people exiting cars in it's lane - car going over into it's lane If I had an hour of driving that I'd be stressed.
  - halotrope 5y ago
    Wait until you see the Jerusalem 40 minute video. Munich traffic is tame in comparison: https://youtu.be/kJD5R_yQ9aw https://youtu.be/kJD5R_yQ9aw I really don’t understand why mobileye gets so little recognition. They might be quietly winning the self driving race.
- aimkey 5y ago
  The 11 minute mark is terrifying: 1) The car fails to accelerate to beat the truck as it merges (the safest option given the scenario, even with the yield sign) 2) The car almost collides with the trailer of the truck and it stops with its nose sticking out into the merge lane 3) The car sits there with its nose in the merge lane as other cars go by 4) When the car finally has an opportunity to merge after having done everything wrong up to this point, it sheepishly merges and takes forever to get up to speed. This is basically the least safe thing it can do when yield-merging into a high speed lane. LOL. This is the best the autonomous driving world has to offer? 80% of this driving is an immediate failure for a teenage driver taking their road course. I think I can take pretty much any random 2 minute sample from that video and find more than a few inputs/maneuvers that would lead to failure in a driver's license test. Why would ANYONE with a brain put their life into the hands of this system? OH, and do you want to know a little industry secret about these "unedited" long videos? Yes, the video is uncut. But guess what? They drove that route hundreds of times and only showed the best run. And they got laser-HD maps of the route that they won't have globally. This is what Zoox did for their infamous demo that got them bought out by Amazon. And it's what Tesla did for their "Full Self-Driving" video on YouTube that shows driving ability that their cars cannot match even today. Shhh, you didn't hear it from me.
  - watt 5y ago
    Sorry at (1) yield means yield. Maybe it shouldn't have stuck the nose so far out, but yeah you have to wait until proper gap in the traffic. The non-accelerating to highway speed is the real bug though.
    - aimkey 5y ago
      There WAS a proper gap in traffic if the car used its accelerator on the ramp. The car would not have impeded the truck at all if it drove the ramp faster. This is an incredibly common issue with autonomous systems: anticipation of other vehicles with an awkward angle of attack, which is common while merging or while other cars are merging. Also, autonomous systems also tend to be way too cautious, which is incredibly dangerous in merging scenarios. A good driver accelerates on that ramp on beats the truck by 2-3 car lengths and merges at speed. Yield does not mean stop. A cautious driver slows before the merge point, maintains a roll, then mashes the accelerator to merge safely at next opportunity. A terrible driver (Mobileye) stop abruptly at the end of the merge junction, almost hits a truck, leaves its front end sticking out into the oncoming traffic, then dangerously merges sheepishly without accelerating fast enough. You can even see how much this freaks out the human passenger. He thought he was going to get hit!
      - nexuist 5y ago
        > A good driver accelerates on that ramp on beats the truck by 2-3 car lengths and merges at speed No. A good driver stops at the yield sign if an approaching vehicle is 2-3 car lengths away. It is dangerous to play guessing games with your car's engine and another driver's attention. If anything goes wrong (tire puncture, engine dies, slippery road, truck driver slams the gas) you have successfully managed to put yourself into the direct path of a speeding brick wall 5x as heavy as you. There is never a safe merging scenario where the right choice is to slam the gas pedal to beat another driver to the punch, especially not when merging onto an active freeway. If there is a yield sign at the end of the onramp, that means prepare to yield. If there is not a yield sign, then the expectation is to keep merging. There wouldn't be a point to the yield sign if everyone treated it as if it didn't exist. > leaves its front end sticking out into the oncoming traffic, I also agree with you but this may be a byproduct of the camera's perspective and maybe it would look normal in the driver's seat. We don't really have a great view but the truck could also have been hugging the curb which would have brought it closer to the car than it should be. > dangerously merges sheepishly without accelerating fast enough Fully agree here. If you merge you have to commit to matching the speed of nearby vehicles or else you're creating a dangerous situation. Mobileye should have sped up much faster than it did. I'm not a neural network, fwiw.
01100011 5y ago
Not a fan of TSLA, but isn't night driving just a special case of daytime driving if you use IR and/or hyperspectral cameras?
- tedk-42 5y ago
  I imagine it's far more tricky due to the lower image quality and increased noise on the sensors (less light/energy hitting them). Loss of colours in your visual imput as well is a bit of an issue...

childintime 5y ago

The video: https://youtu.be/NSDTZQdo6H8 https://youtu.be/NSDTZQdo6H8

dang 5y ago
Thanks! Maybe it's best if we change the URL to that from https://twitter.com/vpj/status/1407000737423368197 https://twitter.com/vpj/status/1407000737423368197.
- ejdyksen 5y ago
  That video is a screen capture from another video (which was screen capped from a livestream), but the original has much better audio quality. Here's a direct link: https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28293s https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28293s
  - dang 5y ago
    Ok, I've switched to that link above (from https://www.youtube.com/watch?v=NSDTZQdo6H8 https://www.youtube.com/watch?v=NSDTZQdo6H8). Thanks!

nickik 5y ago

I resonantly had an argument on here where somebody insistent that breaking because of over-passes were issues with vision system. Seem pretty clear that it is the resolution of the radar, not the shadow of the bridge that causes the issue. Good to get some more insight into this. This is the right thing to focus on, as it is by far the largest issue with Autopilot on the highway. Multiple people who do testing of these system that false positives on some highway overpasses are the biggest usability issue.

pokerhobo 5y ago
The video directly addresses this…

andyxor 5y ago

I like Andrej from his PhD research days and awesome blog posts but this is a series of disasters in the making, that is until FTC steps in after more people die from “self-driving” accidents under interesting and unexpected circumstances. The whole vision vs. LIDAR stuff is a distraction as long as Tesla “AI” doesn’t have common sense. It literally doesn’t know what it’s doing, and the tail of edge cases to "fit" the models is infinitely long. ANNs are fundamentally backwards looking and cannot adapt to unforeseen or even slightly unusual combination of circumstances. It will go fine for n miles and will dramatically fail at mile n+1 where a new situation requires understanding of ones surroundings, and n is arbitrary number. It would be more honest to show the cases where it missed, thankfully there is no lack of them in “FSD beta“ videos on YouTube.

option 5y ago
There are two fundamental reasons, in principle, vision alone can do it: 1) Humans do it with vision alone 2) You can actually predict lidar’s output with vision alone. So many systems out there actually use lidar to generate more labeled data to make lidar unnecessary
- andyxor 5y ago
  besides vision, humans also have this thing called brain, and reasoning, and instincts, and being able to tell if the object in front of them is e.g. a roof of an overturned truck vs. empty space, etc, etc. the key word is "etc" which expands into infinite tail, which no big data training on farms of GPUs would ever help with. Humans and other animals have an ability to understand the scene and generalize from prior experiences to infinite set of new and unexpected circumstances, the "common sense" these dumb curve-fitting models are fundamentally lacking.
  - darknavi 5y ago
    > humans also have this thing called brain, and reasoning, and instincts, and being able to tell if the object in front of them is e.g. a roof of an overturned truck vs. empty space, etc, etc. Assuming the car is reasonably good at this, it has the advantage that it can see in every direction at once. I don't think self-driving cars will ever be perfect, but I think they will quickly become less-lethal than the average human.

nightski 5y ago

It's interesting that an academic conference now feels like a marketing op for industrial research labs more than anything. His claims about how accurate their vision system is and how it is exceeding other sensors is not verifiable in any way to the public. Given how well qualified he is I am sure he is not wrong! Andrej is brilliant. But this is an academic conference right? This isn't open science, it's a discussion about an engineered system. I'm afraid this is the future of ML research (which CV is so heavily dependent on now). Long gone are the days of reading a paper and understanding the approach. Now you need the data and model which may not even be computationally feasible without millions of dollars in hardware. This isn't Tesla's fault or anything, it just makes me sad.

aeternum 5y ago
In the talk, he gave clear examples with detailed position + velocity graphs where the vision system detected obstacles sooner and with less jitter than the radar system. Specifically the overpass where radar triggers erroneous braking, and the pulled over truck where radar detects the obstacle significantly slower.
- stefan_ 5y ago
  That's a strawman. No one is looking to build FSD with radar sensors that have shipped on cars for 20 years now for things like adaptive cruise control. LIDAR is what vision only is compared to.
  - nickik 5y ago
    Radar is the technology that is actually shipping in millions of cars. Lidar is future tech that is not practically to deploy in millions of cars as of now. There is absolutely 0 chance they could just 'put in lidar' from now on so for what he has to do its not relevant.
    - deleted 5y ago
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ketamine__ 5y ago

I've read claims that they are desperately trying to hire. https://mobile.twitter.com/TaylorOgan/status/1407051918317395968 https://mobile.twitter.com/TaylorOgan/status/140705191831739...

DSingularity 5y ago
Maybe it’s an unfortunate side effect of their success. Almost all early members of the team are now multi millionaires if they held their stock.
jowday 5y ago
Anecdata but both of the people I know that worked on Autopilot quit within 18 months of starting, citing extreme overwork and Musk micromanaging things. This lines up with that.
- nickik 5y ago
  People have been claiming the same thing about SpaceX and Tesla for 20+ years now doesn't seem to stop them. Having a small sample size theater about people you personally know isn't really representative.
karpathy 5y ago
For the record these are some blatant & false FUD attempts.
- darknavi 5y ago
  Good to hear it from the source! Great talk by the way. As someone in the CS field but with no knowledge of CV/NN I still find these presentations very insightful.
- revscat 5y ago
  There is a lot of that on HN whenever Tesla is the subject.
  - 5y ago

Robotbeat 5y ago

He made a very good argument for vision-only, but it seems like training actually uses radar data to help calibrate vision measurements, so it seems to me there’s value in making some vehicles still contain radar (say, one out of 10) even if it’s not used for controlling the vehicle directly at drive time. Also, the sensor resolution issue he mentioned could be addressed by using a higher resolution radar sensor. I find the list of 221 triggers to be interesting. In principle, the NHTSA or NTSB could help contribute lists of triggers to companies to validate their training sets on. Every time there is a fatal airliner accident, the NTSB does a safety investigation and airliners get a little bit safer each time. In the same way, each fatal accident in a vehicle with this kind of autonomy could end up being captured by these triggers, improving safety over time in a sort of mixture between expert human analysis and ML. (Nobody does this for all regular car crashes because fatal car crashes happen every day! And you’re not going to retrain human drivers about some new edge case every day, although you can for vehicles like this.)

avs733 5y ago
Most fatal car crashes are investigated, but by the police not engineering experts. The invetigational motivation is legal and liability focused not improvement focused. You sparked a happy delusion in my mind...training drivers to the same level we train pilots. Can you imagine drivers having regular check rides?
- eddanger 5y ago
  I would love to see re-certification of "professional" drivers. Almost daily I encounter taxi or semi-truck operators driving at the limit of what is acceptable.
osipov 5y ago
> so it seems to me there’s value in making some vehicles still contain radar (say, one out of 10) even if it’s not used for controlling the vehicle directly at drive time. That's not how neural networks work. You start by training them with a radar, then you deploy them without the radar. Neural nets make the radar irrelevant post-training. This is the entire point of Karpathy's pitch.

bluepanda928752 5y ago

Tesla's decision not to use the LIDAR as a safety feature (i.e. having reliable high-resolution data about things the car can collide with) is so incredibly indefensible, since solving the last 1% of this using only vision likely requires a general artificial intelligence Prediction: Tesla will be the last of all major auto manufacturers to get to L5 autonomy. Time interval between when Tesla L5 FSD is finally available and when humanity is destroyed by the general AI it runs on will be very awesome and also very short

soheil 5y ago
> is so incredibly indefensible How can you make such a strong statement when you simply don't know how to achieve full autonomy? This reminds of the teapot orbiting the Sun argument [0]. You and people defending Lidar by their teeth don't sound too different from religious zealots who've "seen the light". [0] https://en.wikipedia.org/wiki/Russell%27s_teapot https://en.wikipedia.org/wiki/Russell%27s_teapot
SheinhardtWigCo 5y ago
They’re betting that they can use a massive feedback loop to train a set of neural networks to the point where they are as accurate as LiDAR without actually firing any lasers. Even if you believe this goal is possible to achieve at some point in the future, I think the argument falls apart when you consider that it will take years, probably decades, for a pure vision approach to catch up to where Waymo is today in terms of safety. (They have cameras too.) That Tesla can’t afford to fit expensive LiDAR sensors to all of the cars it sells is Tesla’s problem. Regulators won’t give a shit that pure vision is “better” in theory. They will simply compare Tesla’s crash rate in autonomous mode with that of Waymo and other AV operators, and act accordingly.
- DSingularity 5y ago
  Definitely. Especially with car companies like NIO strapping in LIDAR to their upcoming models.
- bluepanda928752 5y ago

aiddun 5y ago

Per "it's unscalable to get HD 3D maps of all the roads on earth", it's interesting to consider that Google/Waymo has been growing this for years with street view and the sensors on each car. Curious to see how that plays out

nickik 5y ago
HD 3D maps need to be way more accurate and be enriched with massive amounts of detail. Like where lights are, what lights are relevant for what lanes and so on. You can't just pull out your street view footage from 3 years ago.
- aiddun 5y ago
  Good point. Street view cars since 2017 have had high def Lidar sensors on them[0], and they have some prowess in extracting features [1], but I'm not sure if that's enough detail. [0] https://www.geoweeknews.com/blogs/google-putting-lidar-new-street-view-cars https://www.geoweeknews.com/blogs/google-putting-lidar-new-s... [1] https://www.androidpolice.com/2021/01/16/google-maps-is-rolling-out-incredibly-accurate-street-level-details-in-these-4-cities/ https://www.androidpolice.com/2021/01/16/google-maps-is-roll...

aimkey 5y ago

What an annoying charlatan. Karpathy is a brilliant computer vision engineer, but he has let his expertise in that subfield cloud his judgement on achieving the overall goal of autonomous driving. Musk and Karpathy have been dead wrong about LIDAR for years. Remember Musk making the absurd claim of a million Tesla robotaxis by 2020? I think most hilarious is that both Karpathy and Musk claim the LIDAR systems are too expensive. Yet, in the same 2019 Autonomy Day they simultaneously claimed that Teslas would be able to drive themselves and operate as robotaxis, earning their owners passive income and therefore justifying significantly increased MSRPs. So, the $7k LIDAR system (that accelerates safe autonomous driving) is not worth the cost, yet stumbling towards autonomy on vision only is? If the car becomes an money-earner, you should use all of the systems available. The 2019 Autonomy Day was an utter embarrassment. I'm sure 2021 will be more of the same. So now it seems that they've realized their folly in logic. So what's the solution? Well, you can't just complain about COST of non-vision perception systems. Because, as noted above, that doesn't make sense if you're going to simultaneously claim that your car will be able to earn you money (augmenting any extra hardware cost that gets you to that point faster). No, now you have to smear all non-vision perception systems. You have to say that their data is worthless and detrimental to the overall effort. The entire claim from the 2019 Autonomy Day that "vision is what humans use to drive" is also completely bogus. Humans use many senses to drive. They feel the pedals and steering wheel. They use their equilibrio sense to sense motion. And they use their hearing to hear other vehicles, sirens, and issues with their own car (driving with headphones in is illegal for a reason). Any modern car, even a Tesla, is also using far more than just vision when attempting autonomy. Forget about radar and LIDAR for a moment. There are endless sensors in the drivetrain. Steering angle sensors and multiple IMUs for the electronic stability control. Brake and wheel sensors for the ABS. Temperature sensors everywhere. And countless other ECUs. The notion that vision is getting you there exclusively is nonsense. There's no good argument against LIDAR today other than perpetuating a lie to sell cars that are cheaper to produce. And, Karpathy has a massive professional conflict of interest in making CV the main player -- he's a CV expert. He was never a fusion expert before his hire. If CV is the pathway forward, he's gets to remain "the guy". It certainly behooves HIM to make that claim. Autonomous driving will not be achieved in this decade. Perhaps ever. Ask yourself honestly: if you were tasked with building an autonomous commercial aircraft OR an autonomous car, which would you choose? Most would say aircraft -- nothing to really hit in the air, fully mapped airport and runway systems, and far fewer variables. Yet autonomous aircraft still do not exist. Perhaps the edge cases always rule the roost. Ask yourself why driving would be any different...

accurrent 5y ago

I see a lot of people here are stuck on the perception side of things. There's a lot more to self driving than just the sensor suite and perception. There's a lot of work that needs to be done in the planning and controls department prior to the time we get full vehicle autonomy. Andrej's work is impressive, but I wish we'd see more research into the latter. Then again this is CVPR so...

deleted 5y ago

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babesh 5y ago

I think the more interesting question is how much human context is necessary in decreasing accident rates. The signal question and tunnel answer hinted at that. Some context is very local and some context is general at the level of humans. Examples: human eyes will have trouble adjusting to the sudden darkness of tunnels so some people will tend to brake suddenly; that person looks old and will probably have slower reaction times so watch out for the upcoming sharp turn; that person looks like they are on their phone and may cross the lane suddenly; watch out for this intersection because young humans cross it after school without looking so slow down below the speed limit. This human understanding doesn’t seem to be directly represented by the system without explicit architecting on their part. A more general intelligence would begin to automatically learn these. A human intelligence would automatically model these or learn from experience or read about it. As mentioned, the current system has some advantages over humans: more eyes, doesn’t get tired or distracted, faster reaction time. I guess we shall see when these advantages cover up the disadvantages.

fpgaminer 5y ago
I agree, though I think there's an obvious path towards that higher order understanding of the road that humans have. Suppose they eventually have this current system dialed in and they get really good, accurate bounding boxes around all interesting objects on the road. So now, in addition to their 10 second samples of video data they're collecting, they start collecting 10 second samples of scene representations. These samples of scene representations are time series of how various objects in the scene are moving and behaving over time. Many examples of just what you describe: cars with older drivers having slower reaction times; cars with distracted drivers driving recklessly; etc. Now you train a model on all that data, asking it to make predictions through time. It's going to quickly pick up on the same or similar cues that humans do. It sees an older person in a car and says that slower, cautious paths through the scene are more likely for that vehicle. They see a large, lifted truck and assume a 90% probability of a "cut off every car possible" path through the scene. Etc. So I see what Karpathy is building now as a foundation upon which they can build the higher order stuff.
- babesh 5y ago

villgax 5y ago

Even if FSD takes longer, I sure am glad about the active safety features to prevent dumb incidents. Hope that trickles to every other manufacturer petrol/electric

rpmisms 5y ago
There's clip after clip of AP yanking people out of situations where they had no idea they were in danger. Wife and I are planning on kids soon, and we won't consider anything except a Tesla due to those safety features.