7 ms·

I didn't find his answers particularly convincing. His answer focused on costs mainly, and how "the best part is no part". We have already seen multiple acciden

I didn't find his answers particularly convincing. His answer focused on costs mainly, and how "the best part is no part". We have already seen multiple accidents caused by camera's limitations [1] which would not have happened if Tesla used Lidars. Cameras have poor dynamic range and can be easily blinded by bright surfaces. While it is true that humans do fine with only eyes, our eyes are significantly better than cameras. More importantly, expectations are higher when an automated system is driving the car. It is not sufficient if, in aggregate, self-driving cars have fewer accidents. If you lose a loved one in an accident where the accident could have been easily avoided if a human was driving, then you're not going to be mollified to hear that in aggregate, fewer people are being killed by self-driving cars! You'd be outraged to hear such a justification! The expectation therefore is that in each individual injury accident a human clearly could not have handled the situation any better. Self-driving cars have to be significantly better than humans to be accepted by society, and that means it has to have better-than-human levels of vision (which lidars provide). [1] https://www.youtube.com/watch?v=X3hrKnv0dPQ https://www.youtube.com/watch?v=X3hrKnv0dPQ

bergenty 4y ago
Not to mention waymo works well with LiDAR, cameras and radars. If you’re argument is it’s too hard to deal with that much data, it’s definitely the wrong answer.
Nomentatus 4y ago
You're right to note the advantages of lidar and (narrow range of) contrast problem for cameras (they arent eyes.) This is why the Uber human driver shouldn't have trusted the machine at night, in particular. But you still have to address his system argument, which was that adding geegaws that added little would actually increase overall risks along the supply chain (plus maintenance) while distracting the team and adding more risk that way, for very little apparent (but only apparent) gain. The team does believe that they'll get to better than human driving, and do that without lidar.
- Marazan 4y ago
  They cannot actually believe that.
  - mensetmanusman 4y ago
    LiDAR has its own false positives that haven’t been solved, so it’s possible they believe that. I certainly was skeptical until alphago and alphafold happened.
    - freejazz 4y ago
      That's especially amusing considering how if you view Go as a visual problem, it's beyond trivial compared to what is required to safely operate a motor vehicle (even just visually).
      - Nomentatus 4y ago
        Yikes. I'd be a lot better Go player if it was just a matter of seeing the board.
        freejazz 4y ago
        It is yikes - what's shocking is that you seem to be advocating for that same exact perspective for... driving a car???
        Nomentatus 4y ago
        Nope. There's definitely mapping, and then, much, much more. You're stuffing words in my mouth.
        freejazz 4y ago
        Not sure if I'm stuffing so much as removing the bluster
lostsock 4y ago
That video is from 2020, but Tesla didn't remove radar until 2021. Meaning that the crash occurred with radar still active, which I feel just backs up what Karpathy was saying.
- petilon 4y ago
  Well, the car may have had radar hardware but there are questions as to whether the software was using it: https://www.nytimes.com/2021/07/05/business/tesla-autopilot-lawsuits-safety.html https://www.nytimes.com/2021/07/05/business/tesla-autopilot-... Excerpt: Mr. Rajkumar of Carnegie Mellon, who reviewed the video and data at the request of The Times, said Autopilot might have failed to brake for the Explorer because the Tesla’s cameras were facing the sun or were confused by the truck ahead of the Explorer. The Tesla was also equipped with a radar sensor, but it appears not to have helped. “A radar would have detected the pickup truck, and it would have prevented the collision,” Mr. Rajkumar said in an email. “So the radar outputs were likely not being used.” https://www.nytimes.com/2021/12/06/technology/tesla-autopilot-elon-musk.html https://www.nytimes.com/2021/12/06/technology/tesla-autopilo... Excerpt: Tesla later said that during the crash, Autopilot’s camera could not distinguish between the white truck and the bright sky. Tesla has never publicly explained why the radar did not prevent the accident.
  - lostsock 4y ago
    Because radar is not good at picking up stationary objects and/or has to filter them out: https://www.wired.com/story/tesla-autopilot-why-crash-radar/ https://www.wired.com/story/tesla-autopilot-why-crash-radar/
  - dmix 4y ago
    > Autopilot’s camera could not distinguish between the white truck and the bright sky. Is this a hard limitation to vision systems? Or are they saying in that particular early version it couldn't? (And yes I understand LIDAR wouldnt be limited by the color and would see the objects)
akira2501 4y ago
> While it is true that humans do fine with only eyes, our eyes are significantly better than cameras. They also have better failure modes and a really sophisticated error management system. They are susceptible to optical illusions, though. > It is not sufficient if, in aggregate, self-driving cars have fewer accidents. This is the incorrect analysis anyways. This was always going to be true because a large portion of accidents are single vehicle accidents where the driver was at fault for the crash. Usually due to speeding, alcohol, youth, or a combination of them. If they didn't have fewer accidents then something is very very wrong with the entire idea. Which may very well be the outcome here. Looking at multi-vehicle accidents where there was no fault of the driver who died, it's not clear that an automated system driving the car would have saved them. Roads are built right next to cliffs and bodies of water. Semi trucks can completely destroy your vehicle in an instant. Large accidents on snowy or foggy highways happen. Drunk drivers exist and sometimes literally do come out of nowhere, a pickup truck moving at 60mph has enough energy to knock a firetruck onto it's side if you hit it side-on and freeway ramps dump out right onto residential streets. Parts fail, floormats get stuck, people don't wear their seatbelts, and you can get a license to ride on a motorcycle if you want. It's a guess based on the research I've done, but my expectation is around 20% of fatal accidents can in some way be prevented by automation. You'd honestly prevent more fatalities by putting an ignition interlock on everyone's vehicle or building real barriers between traffic and pedestrians.
- BurningFrog 4y ago
  > a large portion of accidents are single vehicle accidents where the driver was at fault for the crash. Usually due to speeding, alcohol, youth, or a combination of them. Also plenty of suicides in that group, which confuses the stats. We really need SDCs to have fewer accidents than human drivers, excluding the suicides.
- oldgradstudent 4y ago
  > but my expectation is around 20% of fatal accidents can in some way be prevented by automation. Assuming, of course, that automation does not introduce its own failure modes. That's a strong assumption.
watwut 4y ago
> It is not sufficient if, in aggregate, self-driving cars have fewer accidents It would be sufficient if it would be the case. With actual proof. Reality is that in limited abstract situations, self driving card maybe have some advantages. But, that is all that we can claim. And when self driving fails, somehow human is always the cause.
- bumby 4y ago
  I disagree, but mainly because of the way humans perceive risk. From a public standpoint I don’t think it’s sufficient because there’s inherent trust lacking in an automated system. With ape-driven systems we have a certain amount of trust because we can more accurately intuit what the other ape is reasonably thinking. This is not the case with autonomous driving which leads to a wider amount of uncertainty. Not unlike how we are intuitively less trusting of someone who is legitimately “crazy” even if statistically we don’ can’t say they are shown to be more dangerous.
  - paulryanrogers 4y ago
    AI cars can also get a software update at any moment. Human drivers won't change behavior en masse overnight.
    - bumby 4y ago
      You’re right, but that still misses the point. More frequently updated software doesn’t make people intuitively trust it more. For some, it can do the opposite by making them question why it needs to be updated so much to begin with. Humans don’t generally measure risks statistically. They do so emotionally and with lots of cognitive biases. You don’t alleviate that with more and more facts, unfortunately.
      - paulryanrogers 4y ago
        Sorry if I was unclear. Software is more unpredictable in my view, both because of fleet updates and it being so fundamentally different than humans. (On the whole, I realize AI and ML could work similar to some human processes.)
amelius 4y ago
The problem with self-driving is that it is based on data, but the environment may change. See e.g. the case where Tesla thinks that firetrucks are roads. So if fashion changes, pedestrians may suddenly look like road too, as just an example. Another problem is that state-of-the-art classification networks have an accuracy in the 90% range. Given that a car has to take hundreds of decisions in a single ride, then even if the accuracy was 99%, you see that error rate simply gets too high.
- martindbp 4y ago
  > state-of-the-art classification networks have an accuracy in the 90% range. If you're referring to ImageNet SOTA, is has 20000 different classes, including 120 different dog breeds [1]. This is a vastly different task than reliably detecting pedestrians where Tesla can actively curate a dataset of hard examples (from their fleet), whereas ImageNet is fixed, sometimes with low quality labels and as few as a couple of hundred examples. Tesla can also pick a point on the ROC curve to give higher recall but more false positives (which is important for VRUs specifically). Another big factor is that Tesla is using video, not still images, which makes predictions even more robust. And that's just for pedestrians, Tesla are also using a general ViDAR (visual LiDAR) which is trained to detect obstacles that do not have a specific class. The ViDAR again operates on image sequences, not a single image, and can thus pick out structure from motion. [1] https://en.wikipedia.org/wiki/ImageNet https://en.wikipedia.org/wiki/ImageNet
aeternum 4y ago
The dynamic range is the reason Tesla know counts photons rather than use traditional camera processing. They basically remove the concept of exposure entirely and simply pass the sensor photon counts to the neural net. This approach not only simpler as it removes photo processing/encoding but the result is that the NN can operate with a very high dynamic range similar to the human eye and in many cases can be sensitive on the single-photon level.
- petilon 4y ago
  But it doesn't appear to be helping. Here's an example accident where depth data from Lidar would have helped: "Tesla later said that during the crash, Autopilot’s camera could not distinguish between the white truck and the bright sky." https://www.nytimes.com/2021/12/06/technology/tesla-autopilot-elon-musk.html https://www.nytimes.com/2021/12/06/technology/tesla-autopilo...
  - mensetmanusman 4y ago
    Humanity doesn’t know how to solve this yet, so it’s hard to say whether it is helping or not.
    - Gigachad 4y ago
      We already have the solution. LiDAR.
      - ALittleLight 4y ago
        If you could use LiDAR well enough then it would solve the problem. Of course, if you could use vision well enough it would solve the problem too.
        touch_abs 4y ago
        The big limits of LiDAR are cost, more than anything. There have been dozens of public driving trials where from a functionality level the answer has been positive (apart from traffic lights, the bastards), but nobody wants to buy a solution with a six figure BOM, before integration.
mensetmanusman 4y ago
I have some experience with LiDAR, they fail easily if a water droplet is on the cover or if signs are too bright. It’s a whole different technology challenge.
- imglorp 4y ago
  Why is LiDAR still expensive enough for the cost to be a problem for anyone? Why have large numbers not driven these down to commodity devices at this point? Or maybe similar tech at another frequency like spread spectrum microwave with phased array semiconductor antennae?
  - petilon 4y ago
    It is now cheap enough for GM and Volkswagen: https://www.bloomberg.com/news/articles/2022-10-25/lidar-sensor-price-plunge-leads-to-orders-from-gm-volkswagen https://www.bloomberg.com/news/articles/2022-10-25/lidar-sen...
  - hwillis 4y ago
    > Why is LiDAR still expensive enough for the cost to be a problem for anyone? Because economy of scale is not the only reason things are expensive. Lidar with 2cm distance resolution has to detect light and measure time to less than 60 picoseconds. It requires sophisticated, expensive sensors like avalanche diodes and complex and extremely fast circuitry. Consider what a single pixel of a lidar device is doing. It's operating 8 orders of magnitude faster than a normal camera pixel. It's detecting an incredibly small amount of light; the spot of a weak laser on a questionable surface from tens of meters away. Its doing that in the presence of light that is tens or hundreds of thousands of times more powerful than the reflection it's actually looking for. Much of that reflection is even at the same wavelength of the laser! Even the mechanics of the device are critical. Pixels are gathered sequentially, unlike in a camera, so any vibration makes the data uselessly fuzzy. Vibration in a camera is correlated extremely tightly between millions of pixels. In lidar its correlated with dozens to hundreds. Any high frequency vibration has large negative impacts on the data. > Or maybe similar tech at another frequency like spread spectrum microwave with phased array semiconductor antennae? ...that's just radar. Literally. Microwaves are 300 Mhz to 300 GHz. Automotive radar is like, 80 GHz, +/=5 GHz (mostly). It uses phased arrays. It uses highly integrated devices. They don't use semiconductor antennas, because the area on a silicon die is far, far to valuable to use for an antenna, but the antennas are incredibly cheap. Radar and lidar are just pretty different.
jandrese 4y ago
> While it is true that humans do fine with only eyes We do not. Humans are terrible at driving. Traffic accidents are one of the leading causes of death in the developed world. Billions of dollars of property damage occur every year because humans are not up to the task. A self driving system that is as safe as an average human driver would be an absolute failure.
- paulcole 4y ago
  > Traffic accidents are one of the leading causes of death in the developed world. Perhaps leading cause of premature death or leading cause of accidental death or leading cause in demographics who are otherwise unlikely to die, but they are nowhere close to the top of the overall list.
- croes 4y ago
  >We do not. But not because of a lack of visual information. Most of the time it's a la k of concentration or an overestimation of one's own driving abilities.
  - freejazz 4y ago
    Here is some shocking news for you. It's not your eyes driving the car... its your brain.
    - croes 4y ago
      That's exactly my point. Unless Teslas have something similar to the human brain cameras are not enough.
- rootusrootus 4y ago
  > Traffic accidents are one of the leading causes of death in the developed world. Not even close, really. A bit under 1%. You are more likely to die from an overdose, or suicide. And much, much, much more likely to die from cancer or heart disease. And that is without getting into the trade-offs. Cars at least have a significant utility value, which is not true of suicide, opiate addiction, cancer, or heart disease. We should try to reduce traffic deaths, but we should not lose perspective.
masswerk 4y ago
Having seen their AI Day, I supposed this was all about a unified, pseudo-visual voxel representation – and especially about generating scenarios. Apparently these have become a crucial part of the system and generating a broader variety of sensor data would be a considerable liability.
whiddershins 4y ago
He's not talking about costs - money. He's talking about costs - engineering. It's about more information is not always better. It can instead muddy the waters. It can create confusion.

bergenty 4y ago

Not to mention waymo works well with LiDAR, cameras and radars. If you’re argument is it’s too hard to deal with that much data, it’s definitely the wrong answer.

Nomentatus 4y ago

You're right to note the advantages of lidar and (narrow range of) contrast problem for cameras (they arent eyes.) This is why the Uber human driver shouldn't have trusted the machine at night, in particular. But you still have to address his system argument, which was that adding geegaws that added little would actually increase overall risks along the supply chain (plus maintenance) while distracting the team and adding more risk that way, for very little apparent (but only apparent) gain. The team does believe that they'll get to better than human driving, and do that without lidar.

Marazan 4y ago
They cannot actually believe that.
- mensetmanusman 4y ago
  LiDAR has its own false positives that haven’t been solved, so it’s possible they believe that. I certainly was skeptical until alphago and alphafold happened.
  - freejazz 4y ago
    That's especially amusing considering how if you view Go as a visual problem, it's beyond trivial compared to what is required to safely operate a motor vehicle (even just visually).
    - Nomentatus 4y ago
      Yikes. I'd be a lot better Go player if it was just a matter of seeing the board.
      - freejazz 4y ago
        It is yikes - what's shocking is that you seem to be advocating for that same exact perspective for... driving a car???
        Nomentatus 4y ago
        Nope. There's definitely mapping, and then, much, much more. You're stuffing words in my mouth.
        freejazz 4y ago
        Not sure if I'm stuffing so much as removing the bluster

lostsock 4y ago

That video is from 2020, but Tesla didn't remove radar until 2021. Meaning that the crash occurred with radar still active, which I feel just backs up what Karpathy was saying.

petilon 4y ago
Well, the car may have had radar hardware but there are questions as to whether the software was using it: https://www.nytimes.com/2021/07/05/business/tesla-autopilot-lawsuits-safety.html https://www.nytimes.com/2021/07/05/business/tesla-autopilot-... Excerpt: Mr. Rajkumar of Carnegie Mellon, who reviewed the video and data at the request of The Times, said Autopilot might have failed to brake for the Explorer because the Tesla’s cameras were facing the sun or were confused by the truck ahead of the Explorer. The Tesla was also equipped with a radar sensor, but it appears not to have helped. “A radar would have detected the pickup truck, and it would have prevented the collision,” Mr. Rajkumar said in an email. “So the radar outputs were likely not being used.” https://www.nytimes.com/2021/12/06/technology/tesla-autopilot-elon-musk.html https://www.nytimes.com/2021/12/06/technology/tesla-autopilo... Excerpt: Tesla later said that during the crash, Autopilot’s camera could not distinguish between the white truck and the bright sky. Tesla has never publicly explained why the radar did not prevent the accident.
- lostsock 4y ago
  Because radar is not good at picking up stationary objects and/or has to filter them out: https://www.wired.com/story/tesla-autopilot-why-crash-radar/ https://www.wired.com/story/tesla-autopilot-why-crash-radar/
- dmix 4y ago
  > Autopilot’s camera could not distinguish between the white truck and the bright sky. Is this a hard limitation to vision systems? Or are they saying in that particular early version it couldn't? (And yes I understand LIDAR wouldnt be limited by the color and would see the objects)

akira2501 4y ago

> While it is true that humans do fine with only eyes, our eyes are significantly better than cameras. They also have better failure modes and a really sophisticated error management system. They are susceptible to optical illusions, though. > It is not sufficient if, in aggregate, self-driving cars have fewer accidents. This is the incorrect analysis anyways. This was always going to be true because a large portion of accidents are single vehicle accidents where the driver was at fault for the crash. Usually due to speeding, alcohol, youth, or a combination of them. If they didn't have fewer accidents then something is very very wrong with the entire idea. Which may very well be the outcome here. Looking at multi-vehicle accidents where there was no fault of the driver who died, it's not clear that an automated system driving the car would have saved them. Roads are built right next to cliffs and bodies of water. Semi trucks can completely destroy your vehicle in an instant. Large accidents on snowy or foggy highways happen. Drunk drivers exist and sometimes literally do come out of nowhere, a pickup truck moving at 60mph has enough energy to knock a firetruck onto it's side if you hit it side-on and freeway ramps dump out right onto residential streets. Parts fail, floormats get stuck, people don't wear their seatbelts, and you can get a license to ride on a motorcycle if you want. It's a guess based on the research I've done, but my expectation is around 20% of fatal accidents can in some way be prevented by automation. You'd honestly prevent more fatalities by putting an ignition interlock on everyone's vehicle or building real barriers between traffic and pedestrians.

BurningFrog 4y ago
> a large portion of accidents are single vehicle accidents where the driver was at fault for the crash. Usually due to speeding, alcohol, youth, or a combination of them. Also plenty of suicides in that group, which confuses the stats. We really need SDCs to have fewer accidents than human drivers, excluding the suicides.
oldgradstudent 4y ago
> but my expectation is around 20% of fatal accidents can in some way be prevented by automation. Assuming, of course, that automation does not introduce its own failure modes. That's a strong assumption.

watwut 4y ago

> It is not sufficient if, in aggregate, self-driving cars have fewer accidents It would be sufficient if it would be the case. With actual proof. Reality is that in limited abstract situations, self driving card maybe have some advantages. But, that is all that we can claim. And when self driving fails, somehow human is always the cause.

bumby 4y ago
I disagree, but mainly because of the way humans perceive risk. From a public standpoint I don’t think it’s sufficient because there’s inherent trust lacking in an automated system. With ape-driven systems we have a certain amount of trust because we can more accurately intuit what the other ape is reasonably thinking. This is not the case with autonomous driving which leads to a wider amount of uncertainty. Not unlike how we are intuitively less trusting of someone who is legitimately “crazy” even if statistically we don’ can’t say they are shown to be more dangerous.
- paulryanrogers 4y ago
  AI cars can also get a software update at any moment. Human drivers won't change behavior en masse overnight.
  - bumby 4y ago
    You’re right, but that still misses the point. More frequently updated software doesn’t make people intuitively trust it more. For some, it can do the opposite by making them question why it needs to be updated so much to begin with. Humans don’t generally measure risks statistically. They do so emotionally and with lots of cognitive biases. You don’t alleviate that with more and more facts, unfortunately.
    - paulryanrogers 4y ago
      Sorry if I was unclear. Software is more unpredictable in my view, both because of fleet updates and it being so fundamentally different than humans. (On the whole, I realize AI and ML could work similar to some human processes.)

amelius 4y ago

The problem with self-driving is that it is based on data, but the environment may change. See e.g. the case where Tesla thinks that firetrucks are roads. So if fashion changes, pedestrians may suddenly look like road too, as just an example. Another problem is that state-of-the-art classification networks have an accuracy in the 90% range. Given that a car has to take hundreds of decisions in a single ride, then even if the accuracy was 99%, you see that error rate simply gets too high.

martindbp 4y ago
> state-of-the-art classification networks have an accuracy in the 90% range. If you're referring to ImageNet SOTA, is has 20000 different classes, including 120 different dog breeds [1]. This is a vastly different task than reliably detecting pedestrians where Tesla can actively curate a dataset of hard examples (from their fleet), whereas ImageNet is fixed, sometimes with low quality labels and as few as a couple of hundred examples. Tesla can also pick a point on the ROC curve to give higher recall but more false positives (which is important for VRUs specifically). Another big factor is that Tesla is using video, not still images, which makes predictions even more robust. And that's just for pedestrians, Tesla are also using a general ViDAR (visual LiDAR) which is trained to detect obstacles that do not have a specific class. The ViDAR again operates on image sequences, not a single image, and can thus pick out structure from motion. [1] https://en.wikipedia.org/wiki/ImageNet https://en.wikipedia.org/wiki/ImageNet

aeternum 4y ago

The dynamic range is the reason Tesla know counts photons rather than use traditional camera processing. They basically remove the concept of exposure entirely and simply pass the sensor photon counts to the neural net. This approach not only simpler as it removes photo processing/encoding but the result is that the NN can operate with a very high dynamic range similar to the human eye and in many cases can be sensitive on the single-photon level.

petilon 4y ago
But it doesn't appear to be helping. Here's an example accident where depth data from Lidar would have helped: "Tesla later said that during the crash, Autopilot’s camera could not distinguish between the white truck and the bright sky." https://www.nytimes.com/2021/12/06/technology/tesla-autopilot-elon-musk.html https://www.nytimes.com/2021/12/06/technology/tesla-autopilo...
- mensetmanusman 4y ago
  Humanity doesn’t know how to solve this yet, so it’s hard to say whether it is helping or not.
  - Gigachad 4y ago
    We already have the solution. LiDAR.
    - ALittleLight 4y ago
      If you could use LiDAR well enough then it would solve the problem. Of course, if you could use vision well enough it would solve the problem too.
      - touch_abs 4y ago
        The big limits of LiDAR are cost, more than anything. There have been dozens of public driving trials where from a functionality level the answer has been positive (apart from traffic lights, the bastards), but nobody wants to buy a solution with a six figure BOM, before integration.

mensetmanusman 4y ago

I have some experience with LiDAR, they fail easily if a water droplet is on the cover or if signs are too bright. It’s a whole different technology challenge.

imglorp 4y ago
Why is LiDAR still expensive enough for the cost to be a problem for anyone? Why have large numbers not driven these down to commodity devices at this point? Or maybe similar tech at another frequency like spread spectrum microwave with phased array semiconductor antennae?
- petilon 4y ago
  It is now cheap enough for GM and Volkswagen: https://www.bloomberg.com/news/articles/2022-10-25/lidar-sensor-price-plunge-leads-to-orders-from-gm-volkswagen https://www.bloomberg.com/news/articles/2022-10-25/lidar-sen...
- hwillis 4y ago
  > Why is LiDAR still expensive enough for the cost to be a problem for anyone? Because economy of scale is not the only reason things are expensive. Lidar with 2cm distance resolution has to detect light and measure time to less than 60 picoseconds. It requires sophisticated, expensive sensors like avalanche diodes and complex and extremely fast circuitry. Consider what a single pixel of a lidar device is doing. It's operating 8 orders of magnitude faster than a normal camera pixel. It's detecting an incredibly small amount of light; the spot of a weak laser on a questionable surface from tens of meters away. Its doing that in the presence of light that is tens or hundreds of thousands of times more powerful than the reflection it's actually looking for. Much of that reflection is even at the same wavelength of the laser! Even the mechanics of the device are critical. Pixels are gathered sequentially, unlike in a camera, so any vibration makes the data uselessly fuzzy. Vibration in a camera is correlated extremely tightly between millions of pixels. In lidar its correlated with dozens to hundreds. Any high frequency vibration has large negative impacts on the data. > Or maybe similar tech at another frequency like spread spectrum microwave with phased array semiconductor antennae? ...that's just radar. Literally. Microwaves are 300 Mhz to 300 GHz. Automotive radar is like, 80 GHz, +/=5 GHz (mostly). It uses phased arrays. It uses highly integrated devices. They don't use semiconductor antennas, because the area on a silicon die is far, far to valuable to use for an antenna, but the antennas are incredibly cheap. Radar and lidar are just pretty different.

jandrese 4y ago

> While it is true that humans do fine with only eyes We do not. Humans are terrible at driving. Traffic accidents are one of the leading causes of death in the developed world. Billions of dollars of property damage occur every year because humans are not up to the task. A self driving system that is as safe as an average human driver would be an absolute failure.

paulcole 4y ago
> Traffic accidents are one of the leading causes of death in the developed world. Perhaps leading cause of premature death or leading cause of accidental death or leading cause in demographics who are otherwise unlikely to die, but they are nowhere close to the top of the overall list.
croes 4y ago
>We do not. But not because of a lack of visual information. Most of the time it's a la k of concentration or an overestimation of one's own driving abilities.
- freejazz 4y ago
  Here is some shocking news for you. It's not your eyes driving the car... its your brain.
  - croes 4y ago
    That's exactly my point. Unless Teslas have something similar to the human brain cameras are not enough.
rootusrootus 4y ago
> Traffic accidents are one of the leading causes of death in the developed world. Not even close, really. A bit under 1%. You are more likely to die from an overdose, or suicide. And much, much, much more likely to die from cancer or heart disease. And that is without getting into the trade-offs. Cars at least have a significant utility value, which is not true of suicide, opiate addiction, cancer, or heart disease. We should try to reduce traffic deaths, but we should not lose perspective.

masswerk 4y ago

Having seen their AI Day, I supposed this was all about a unified, pseudo-visual voxel representation – and especially about generating scenarios. Apparently these have become a crucial part of the system and generating a broader variety of sensor data would be a considerable liability.

whiddershins 4y ago

He's not talking about costs - money. He's talking about costs - engineering. It's about more information is not always better. It can instead muddy the waters. It can create confusion.