29 ms·

Nvidia and Audi aim to bring a self-driving AI car to market by 2020

215 points by t23 10y ago

dbcooper 10y ago
ZF's press release: http://www.zf.com/corporate/en_de/press/list/release/release_29147.html http://www.zf.com/corporate/en_de/press/list/release/release...
lucidrains 10y ago
Video: https://www.youtube.com/watch?v=7jS4AuPnmyg https://www.youtube.com/watch?v=7jS4AuPnmyg "Audi and NVIDIA developed an Audi Q7 piloted driving concept vehicle, which uses neural networks and end-to-end deep learning. Demo track at CES 2017 in Las Vegas."
- remir 10y ago
  I wonder how it compares to Tesla Vision.
  - deleted 10y ago
    [deleted]
  - dangrossman 10y ago
    They are one and the same, no? http://www.nvidia.com/object/tesla-and-nvidia.html http://www.nvidia.com/object/tesla-and-nvidia.html
    - remir 10y ago
      Tesla made their own software: The computer delivers more than 40 times the processing power of the previous system, running an Tesla-developed neural net for vision, sonar, and radar processing
      - dangrossman 10y ago
        Every customer of Nvidia's solution "develops their own neural net" by feeding their own set of sensor data into Nvidia's training platform, then using the resulting neural net on Nvidia's hardware in the cars. Did Tesla not do that, the same way Audi did here, and Nvidia themselves did for BB8? Everyone's going to be adding some software on top of that for the UI and UX they want to offer and such. Did Tesla do more than that? Your quote doesn't actually suggest they did.
        PeterisP 10y ago
        The neural net is 99% of the work - if all they share is a particular GPU model, but each have "their own" neural net made on their own training data, then you can pretty much treat it as a completely separate, different system. The quality and performance of the system is mostly determined by the data, not the raw computing power, so it's worth comparing them as they can be very different.
Hydraulix989 10y ago
The scary thing about non-ad hoc techniques is that deep net is a "black box" -- you really don't know how pathologies occurred nor do you know how to fix them. Not only that, there are _inherent_ pathologies associated with using deep nets in the first place.
- makecheck 10y ago
  It doesn’t have to be all or nothing. For instance, the network might only be used to decide among a series of actions, and those actions can still have limits (such as “car cannot travel faster than X” or “Y cannot change more than 3 times per minute”, or whatever). There is still an abundance of attention put into safety, as usual for the auto industry. It isn’t just a brain hooked up to an engine that is allowed to run rampant.
  - apk17 10y ago
    Depending on the context, 'turn the wheel left two degrees' can be a non-rampant, a very rampant, or a rampage-compensating action.
    - marcosdumay 10y ago
      "Keep the car in a straight line" or "turn right, 10°" are the kinds of operation that will always be more performant, take less engineering, and more reliable to create as an old-fashioned simple math function than by using machine learning. One would expect the output of the neural nets to be encoded in those.
      - Hydraulix989 10y ago
        It's the exceptional cases that get you: 1. "Keep the car in a straight line" => The road is closed or there is a detour, or the lane markers aren't visible (or incorrectly marked like on the Palo Alto stretch of the 101 where there are two sets of lane markers; one new (the "actual" markers) and another old but barely faded and still very visible. 2. "Turn right, 10 degree" => With what steering radius? What if the road is bumpy or sloped and the driver has to compensate with the wheel? etc. These corner cases are everyday occurrences and lend a necessity for something far more sophisticated than a mere ad hoc model to represent and control human-level driving behaviors with a finite set of rudimentary actions. Actuator inputs like steering and pedals are almost always represented using continuous values rather than discrete sets for these very reasons.
frik 10y ago
Tesla is using a modified Nvidia self-driving platform too for Autopilot v2, available in early 2017. Nvidia demonstrated their platform with many sensors like 10 cameras, ultra-sonic sensors and at least one LIDAR. Where as Tesla is using a sensor mix with radar, ultra-sonic sensors and like 7 cameras - the LIDAR is probably still too expensive even for a 70+k car (the big one you know from Google cars cost $70k, the smallest one cost at least 7k). It will be interesting to learn about Audi's sensor mix, and what LIDAR product they choose.
- lucidrains 10y ago
  250$ LIDAR is on the horizon http://driverless.wonderhowto.com/news/quanergys-new-250-solid-state-lidar-could-bring-self-driving-masses-0175790/ http://driverless.wonderhowto.com/news/quanergys-new-250-sol...
  - remir 10y ago
    Velodyne is working on a 50$ solid state LiDAR.
    - deepnotderp 10y ago
      The problem is that those solid state LiDARs have missed shipment targets many times and they also aren't equivalent to $60K lidar systems.
      - jayjay71 10y ago
        The smaller sensors aren't the same as the giant sensor that goes on top of the car, but ~10 of them can give you comparable coverage for self-driving purposes (assuming they work similar to other smaller LIDAR sensors such as what ibeo makes, hard to say before the product actually ships). And a few thousand dollars is easily affordable for luxury cars; think of it as a typical upgrade like consumers pay for navigation packages, stereos, leather interior, etc. With regards to the missed shipments - I agree, that is a red flag. And when a company gives a timeline, and then that passes and they change their answer to "soon" it's concerning. Of course, it's CES right now - maybe someone will make an announcement in a few days. Last year Quanergy hyped up their sensor, but when they were pressed it turns out their demo sensor was actually not solid state.
thinkloop 10y ago
Wonder how many more times this can get declared before the PR value works as a net loss.
- tsenkov 10y ago
  I think that's happening already, among engineers at least. There should be some healthy dose of inspiring "propaganda", but this got out of hand - everybody claims "they have it". I am so sick of this endless stream of lies, that I'm not even going to read the article. The next thing I am going to read on the topic would read something like "X has a viable self-driving car - it's hitting the market later this year.".
  - thinkloop 10y ago
    You'll still have to endure the definition-stretching phase. I'm going to start really paying attention when pedaless cars are declared.
    - ars 10y ago
      > when pedaless cars are declared. That won't happen till General AI. How would you do something as simple as drive the car onto a lift to change the oil without pedals and a steering wheel? Or there is a concert and you need to drive onto the grass to park?
      - TillE 10y ago
        Solving a couple tiny problems really doesn't require human-level general intelligence. At the very worst you'd have a touchscreen with simple overrides. People talk as if there's some infinite number of unique edge cases when driving a dang car, but there simply isn't that much you actually do with a vehicle. Real deal no-drivers-license-required automated vehicles are coming pretty soon; maybe not in 5 years, but definitely within 20.
        Piskvorrr 10y ago
ParadisoShlee 10y ago
I know lawyers and states need time to legalise the paperwork around driverless, but I feel like 2020 is simply to appease the auto companies and give them another few years to stall.
deleted 10y ago
[deleted]
nameisu 10y ago
lately every few weeks the trend in news is 1 tech company+1 car company
- seeekr 10y ago
  ... and soon the trend'll be 1 car company owned by a tech company. Wondering when the first tech companies are going to start buying car companies -- in the tried and true spirit of tech (software) eating the world.
  - chx 10y ago
    Maybe. Fiat Chrysler is a 16.44B company, nVidia is a 57.15B company. Any other car group I can think of is much larger than Fiat Chrysler.
k__ 10y ago
And all this because of gamers. You're welcome ;)
- visarga 10y ago
  And the guys with the NNs.
KKKKkkkk1 10y ago
The term "self-driving" in this context has no technical meaning behind it. Cruise control is also self-driving. And don't get me started on "AI". Jen-Hsun is saying that the car "was trained for four days". WTF? Mobileye has a team of 100s of annotators working 9-to-5 generating training data. It's as if this report is tailored to fool credulous readers who have a vision of HAL 9000 driving a car in their mind.
- jayjay71 10y ago
  The article specifies Level 4 autonomy, which means: The automated system can control the vehicle in all but a few environments such as severe weather. The driver must enable the automated system only when it is safe to do so. When enabled, driver attention is not required.
  - apk17 10y ago
    The last two sentences seem contradictory. If the system cannot detect by itself when it is safe to be used, the driver will as well have to react when it becomes unsafe to use?
    - marcosdumay 10y ago
      It means the system is constructed such that it won't get into a situation it can not handle. But it does not handle any random situation a human can put it in.
    - wyldfire 10y ago
      You're right, it should probably be a bit more muted. Perhaps "When enabled, [significantly less] driver attention is required." The driver can't go to sleep, for example, lest they miss the alert that indicates "oh no I can't figure it out anymore." Though the car would likely be designed to timeout on driver response and execute a safe deceleration/pull-aside maneuver.
  - notheguyouthink 10y ago
    On a sidenote, level 4 autonomy will be really interesting when it's all over the place. People are already "bad drivers" (in my opinion, and including myself), but not having to drive 75-90% of the time will mean we rob ourselves of the constant training that helps keep us somewhat competent at driving. How bad will the roads be when we have thousands of people all very unsure of their driving skills driving in conditions that are dangerous to begin with? Seems quite the interesting issue.
peteretep 10y ago
Random thought: the more deep learning is used in training, the less humans will be able to retroactively explain decisions; this surely has liability implications
- bobcostas55 10y ago
  Perhaps NNs need functionality to come up with fake rationalizations for their decisions just like the human brain does.
  - worldsayshi 10y ago
    I'm thinking that this idea about "fake rationalization" is a bit backwards. We say that many actions happen before we are aware of it or have a rationalization for them but becoming aware of why we did something after the fact doesn't mean that "you" weren't part of the decision. Aren't your reflexes a part of "you"?
    - bobcostas55 10y ago
      Of course, but nobody is going to say "my reflexes did it". We come up with stories, lines of argumentation, etc. Even though these are "ex post" we often manage to convince ourselves... In Homer's time the Greeks viewed the unconscious as an external (divine) force, the most famous example being Telemachus's sneeze. In a weird way this feels more intellectually honest than the thing we do.
      - peteretep 10y ago
        > we often manage to convince ourselves In this case, presumably the trick is to convince a jury.
- wavefunction 10y ago
  I don't see how this is true. With a machine system you would at least have the ability to log the mathematical operations and results, which would be complex, sure. But more complex than figuring out if another person is lying about a very nuanced and opaque decision they made?
joeyspn 10y ago
Bitcoin and cryptocurrencies, AI, self-driving cars... good (and profitable) times for GPU manufacturers. Nvidia stock (NASDAQ:NVDA) is x4 in the last year and probably will continue escalating..
- rrdharan 10y ago
  I thought all the bitcoin and crypto stuff had already moved past GPUs and on to custom ASIC units?
  - joeyspn 10y ago
    The only crypto that has transitioned from GPU to ASIC is bitcoin, but that comes after many years of GPU-based mining operations. Regarding the rest of cryptos, the vast majority is still being mined with GPUs, including Ethereum.
  - notheguyouthink 10y ago
    I know next to nothing about this but my buddy is big into Bitcoin. He runs a lot of ASIC machines for bitcoin, but he says there are a lot of reasons to dislike the ASIC compatible algorithms. He's experimenting with switching to GPUs, iirc he's mining Ethereum with them at the moment. I can't go into much detail as it's not my knowledge obviously, but i can say that GPUs are viable/required for some of the coins out there. Based on his word, at least.
slaunchwise 10y ago
Audi? I'd be happy if they could build a car with a damned USB port and a touch screen.
zxcvvcxz 10y ago
Why is everyone so damn cynical about self-driving cars? We know this is coming, and this technology will improve the lives of so many people in the long run. Maybe it's from Nvidia and Audi, maybe Tesla, Uber, Google, that dude who launched and failed and ran away to China, who knows? I'm excited to think about what opportunities will start to open up once humans don't need to spend 2+ hrs a day with their hands on the wheel :)
ilaksh 10y ago
I think that Tesla is basically saying 'F it' and releasing something like this either right now (version 2.0) or full version before end of 2017. But they have more-or-less been doing that the whole time. Its just now they have more sensors and deep learning so they are going to be autonomous a higher percentage of the time. So I think as soon as they start rolling it out more and more Tesla owner will have more common 100% autonomous trips with some exceptions for weird traffic or weather. I think this is risky in some ways but overall its more ethical than delaying because the only way to train/engineer for the exceptional situations is to get a lot of vehicles running the system and training on data. Waiting a few years means people die from human error and you're unlikely to see massive improvements to the system that would make up for that. One thing people will realize eventually is that we create a lot of driving situations that are structurally unsafe. For example, it is accepted to speed past pedestrians or bicyclists a few feet away on the sidewalk or bike lane. No level of AI advancement can prevent some random horrific accidents in that case. Could be as simple as a pedestrian crossingthe street a little early. People are not going to tolerate AIs going 5 mph anytime a pedestrian is nearby but thats the only way you could prevent fatalities in some situations. That is part of the 'low confidence situations' the nvidia guy mentioned. So actually we need laws to protect autonomous tech companies in those situations or that will delay situational deployment and lead to more human error deaths.

215 points by t23 10y ago

ZF's press release: http://www.zf.com/corporate/en_de/press/list/release/release_29147.html http://www.zf.com/corporate/en_de/press/list/release/release...

lucidrains 10y ago

Video: https://www.youtube.com/watch?v=7jS4AuPnmyg https://www.youtube.com/watch?v=7jS4AuPnmyg "Audi and NVIDIA developed an Audi Q7 piloted driving concept vehicle, which uses neural networks and end-to-end deep learning. Demo track at CES 2017 in Las Vegas."

remir 10y ago
I wonder how it compares to Tesla Vision.
- deleted 10y ago
  [deleted]
- dangrossman 10y ago
  They are one and the same, no? http://www.nvidia.com/object/tesla-and-nvidia.html http://www.nvidia.com/object/tesla-and-nvidia.html
  - remir 10y ago
    Tesla made their own software: The computer delivers more than 40 times the processing power of the previous system, running an Tesla-developed neural net for vision, sonar, and radar processing
    - dangrossman 10y ago
      Every customer of Nvidia's solution "develops their own neural net" by feeding their own set of sensor data into Nvidia's training platform, then using the resulting neural net on Nvidia's hardware in the cars. Did Tesla not do that, the same way Audi did here, and Nvidia themselves did for BB8? Everyone's going to be adding some software on top of that for the UI and UX they want to offer and such. Did Tesla do more than that? Your quote doesn't actually suggest they did.
      - PeterisP 10y ago
        The neural net is 99% of the work - if all they share is a particular GPU model, but each have "their own" neural net made on their own training data, then you can pretty much treat it as a completely separate, different system. The quality and performance of the system is mostly determined by the data, not the raw computing power, so it's worth comparing them as they can be very different.

Hydraulix989 10y ago

The scary thing about non-ad hoc techniques is that deep net is a "black box" -- you really don't know how pathologies occurred nor do you know how to fix them. Not only that, there are _inherent_ pathologies associated with using deep nets in the first place.

makecheck 10y ago
It doesn’t have to be all or nothing. For instance, the network might only be used to decide among a series of actions, and those actions can still have limits (such as “car cannot travel faster than X” or “Y cannot change more than 3 times per minute”, or whatever). There is still an abundance of attention put into safety, as usual for the auto industry. It isn’t just a brain hooked up to an engine that is allowed to run rampant.
- apk17 10y ago
  Depending on the context, 'turn the wheel left two degrees' can be a non-rampant, a very rampant, or a rampage-compensating action.
  - marcosdumay 10y ago
    "Keep the car in a straight line" or "turn right, 10°" are the kinds of operation that will always be more performant, take less engineering, and more reliable to create as an old-fashioned simple math function than by using machine learning. One would expect the output of the neural nets to be encoded in those.
    - Hydraulix989 10y ago
      It's the exceptional cases that get you: 1. "Keep the car in a straight line" => The road is closed or there is a detour, or the lane markers aren't visible (or incorrectly marked like on the Palo Alto stretch of the 101 where there are two sets of lane markers; one new (the "actual" markers) and another old but barely faded and still very visible. 2. "Turn right, 10 degree" => With what steering radius? What if the road is bumpy or sloped and the driver has to compensate with the wheel? etc. These corner cases are everyday occurrences and lend a necessity for something far more sophisticated than a mere ad hoc model to represent and control human-level driving behaviors with a finite set of rudimentary actions. Actuator inputs like steering and pedals are almost always represented using continuous values rather than discrete sets for these very reasons.

frik 10y ago

Tesla is using a modified Nvidia self-driving platform too for Autopilot v2, available in early 2017. Nvidia demonstrated their platform with many sensors like 10 cameras, ultra-sonic sensors and at least one LIDAR. Where as Tesla is using a sensor mix with radar, ultra-sonic sensors and like 7 cameras - the LIDAR is probably still too expensive even for a 70+k car (the big one you know from Google cars cost $70k, the smallest one cost at least 7k). It will be interesting to learn about Audi's sensor mix, and what LIDAR product they choose.

lucidrains 10y ago
250$ LIDAR is on the horizon http://driverless.wonderhowto.com/news/quanergys-new-250-solid-state-lidar-could-bring-self-driving-masses-0175790/ http://driverless.wonderhowto.com/news/quanergys-new-250-sol...
- remir 10y ago
  Velodyne is working on a 50$ solid state LiDAR.
  - deepnotderp 10y ago
    The problem is that those solid state LiDARs have missed shipment targets many times and they also aren't equivalent to $60K lidar systems.
    - jayjay71 10y ago
      The smaller sensors aren't the same as the giant sensor that goes on top of the car, but ~10 of them can give you comparable coverage for self-driving purposes (assuming they work similar to other smaller LIDAR sensors such as what ibeo makes, hard to say before the product actually ships). And a few thousand dollars is easily affordable for luxury cars; think of it as a typical upgrade like consumers pay for navigation packages, stereos, leather interior, etc. With regards to the missed shipments - I agree, that is a red flag. And when a company gives a timeline, and then that passes and they change their answer to "soon" it's concerning. Of course, it's CES right now - maybe someone will make an announcement in a few days. Last year Quanergy hyped up their sensor, but when they were pressed it turns out their demo sensor was actually not solid state.

thinkloop 10y ago

Wonder how many more times this can get declared before the PR value works as a net loss.

tsenkov 10y ago
I think that's happening already, among engineers at least. There should be some healthy dose of inspiring "propaganda", but this got out of hand - everybody claims "they have it". I am so sick of this endless stream of lies, that I'm not even going to read the article. The next thing I am going to read on the topic would read something like "X has a viable self-driving car - it's hitting the market later this year.".
- thinkloop 10y ago
  You'll still have to endure the definition-stretching phase. I'm going to start really paying attention when pedaless cars are declared.
  - ars 10y ago
    > when pedaless cars are declared. That won't happen till General AI. How would you do something as simple as drive the car onto a lift to change the oil without pedals and a steering wheel? Or there is a concert and you need to drive onto the grass to park?
    - TillE 10y ago
      Solving a couple tiny problems really doesn't require human-level general intelligence. At the very worst you'd have a touchscreen with simple overrides. People talk as if there's some infinite number of unique edge cases when driving a dang car, but there simply isn't that much you actually do with a vehicle. Real deal no-drivers-license-required automated vehicles are coming pretty soon; maybe not in 5 years, but definitely within 20.
      - Piskvorrr 10y ago

ParadisoShlee 10y ago

I know lawyers and states need time to legalise the paperwork around driverless, but I feel like 2020 is simply to appease the auto companies and give them another few years to stall.

deleted 10y ago

[deleted]

nameisu 10y ago

lately every few weeks the trend in news is 1 tech company+1 car company

seeekr 10y ago
... and soon the trend'll be 1 car company owned by a tech company. Wondering when the first tech companies are going to start buying car companies -- in the tried and true spirit of tech (software) eating the world.
- chx 10y ago
  Maybe. Fiat Chrysler is a 16.44B company, nVidia is a 57.15B company. Any other car group I can think of is much larger than Fiat Chrysler.

k__ 10y ago

And all this because of gamers. You're welcome ;)

visarga 10y ago
And the guys with the NNs.

KKKKkkkk1 10y ago

The term "self-driving" in this context has no technical meaning behind it. Cruise control is also self-driving. And don't get me started on "AI". Jen-Hsun is saying that the car "was trained for four days". WTF? Mobileye has a team of 100s of annotators working 9-to-5 generating training data. It's as if this report is tailored to fool credulous readers who have a vision of HAL 9000 driving a car in their mind.

jayjay71 10y ago
The article specifies Level 4 autonomy, which means: The automated system can control the vehicle in all but a few environments such as severe weather. The driver must enable the automated system only when it is safe to do so. When enabled, driver attention is not required.
- apk17 10y ago
  The last two sentences seem contradictory. If the system cannot detect by itself when it is safe to be used, the driver will as well have to react when it becomes unsafe to use?
  - marcosdumay 10y ago
    It means the system is constructed such that it won't get into a situation it can not handle. But it does not handle any random situation a human can put it in.
  - wyldfire 10y ago
    You're right, it should probably be a bit more muted. Perhaps "When enabled, [significantly less] driver attention is required." The driver can't go to sleep, for example, lest they miss the alert that indicates "oh no I can't figure it out anymore." Though the car would likely be designed to timeout on driver response and execute a safe deceleration/pull-aside maneuver.
- notheguyouthink 10y ago
  On a sidenote, level 4 autonomy will be really interesting when it's all over the place. People are already "bad drivers" (in my opinion, and including myself), but not having to drive 75-90% of the time will mean we rob ourselves of the constant training that helps keep us somewhat competent at driving. How bad will the roads be when we have thousands of people all very unsure of their driving skills driving in conditions that are dangerous to begin with? Seems quite the interesting issue.

peteretep 10y ago

Random thought: the more deep learning is used in training, the less humans will be able to retroactively explain decisions; this surely has liability implications

bobcostas55 10y ago
Perhaps NNs need functionality to come up with fake rationalizations for their decisions just like the human brain does.
- worldsayshi 10y ago
  I'm thinking that this idea about "fake rationalization" is a bit backwards. We say that many actions happen before we are aware of it or have a rationalization for them but becoming aware of why we did something after the fact doesn't mean that "you" weren't part of the decision. Aren't your reflexes a part of "you"?
  - bobcostas55 10y ago
    Of course, but nobody is going to say "my reflexes did it". We come up with stories, lines of argumentation, etc. Even though these are "ex post" we often manage to convince ourselves... In Homer's time the Greeks viewed the unconscious as an external (divine) force, the most famous example being Telemachus's sneeze. In a weird way this feels more intellectually honest than the thing we do.
    - peteretep 10y ago
      > we often manage to convince ourselves In this case, presumably the trick is to convince a jury.
wavefunction 10y ago
I don't see how this is true. With a machine system you would at least have the ability to log the mathematical operations and results, which would be complex, sure. But more complex than figuring out if another person is lying about a very nuanced and opaque decision they made?

joeyspn 10y ago

Bitcoin and cryptocurrencies, AI, self-driving cars... good (and profitable) times for GPU manufacturers. Nvidia stock (NASDAQ:NVDA) is x4 in the last year and probably will continue escalating..

rrdharan 10y ago
I thought all the bitcoin and crypto stuff had already moved past GPUs and on to custom ASIC units?
- joeyspn 10y ago
  The only crypto that has transitioned from GPU to ASIC is bitcoin, but that comes after many years of GPU-based mining operations. Regarding the rest of cryptos, the vast majority is still being mined with GPUs, including Ethereum.
- notheguyouthink 10y ago
  I know next to nothing about this but my buddy is big into Bitcoin. He runs a lot of ASIC machines for bitcoin, but he says there are a lot of reasons to dislike the ASIC compatible algorithms. He's experimenting with switching to GPUs, iirc he's mining Ethereum with them at the moment. I can't go into much detail as it's not my knowledge obviously, but i can say that GPUs are viable/required for some of the coins out there. Based on his word, at least.

slaunchwise 10y ago

Audi? I'd be happy if they could build a car with a damned USB port and a touch screen.

zxcvvcxz 10y ago

Why is everyone so damn cynical about self-driving cars? We know this is coming, and this technology will improve the lives of so many people in the long run. Maybe it's from Nvidia and Audi, maybe Tesla, Uber, Google, that dude who launched and failed and ran away to China, who knows? I'm excited to think about what opportunities will start to open up once humans don't need to spend 2+ hrs a day with their hands on the wheel :)

ilaksh 10y ago

I think that Tesla is basically saying 'F it' and releasing something like this either right now (version 2.0) or full version before end of 2017. But they have more-or-less been doing that the whole time. Its just now they have more sensors and deep learning so they are going to be autonomous a higher percentage of the time. So I think as soon as they start rolling it out more and more Tesla owner will have more common 100% autonomous trips with some exceptions for weird traffic or weather. I think this is risky in some ways but overall its more ethical than delaying because the only way to train/engineer for the exceptional situations is to get a lot of vehicles running the system and training on data. Waiting a few years means people die from human error and you're unlikely to see massive improvements to the system that would make up for that. One thing people will realize eventually is that we create a lot of driving situations that are structurally unsafe. For example, it is accepted to speed past pedestrians or bicyclists a few feet away on the sidewalk or bike lane. No level of AI advancement can prevent some random horrific accidents in that case. Could be as simple as a pedestrian crossingthe street a little early. People are not going to tolerate AIs going 5 mph anytime a pedestrian is nearby but thats the only way you could prevent fatalities in some situations. That is part of the 'low confidence situations' the nvidia guy mentioned. So actually we need laws to protect autonomous tech companies in those situations or that will delay situational deployment and lead to more human error deaths.