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This author missed Musks point entierly. His argument is that to solve self-driving you need a deep understanding of your surrounding which you can only achieve

by loourr 7y ago

This author missed Musks point entierly. His argument is that to solve self-driving you need a deep understanding of your surrounding which you can only achieve with visible light spectrum video. That's the real hard problem to solve and you need cameras to solve that and if you solve it then lidar becomes unnecessary. The doomed part is because if companies are spending all of their energy on creating neural nets around lidar then they'll reach a local maximum where they never begin to tackle the much more difficult problem truly needed for self-driving.

threeseed 7y ago
Musk's argument was refuted by his own Data Scientists. They admitted their own models are far from perfect and will likely never be. The concerning one in particular was the "is this a large object" model which initially failed to identity objects such as car-carrying trucks, cranes etc. With Lidar you can certain at least that it will identity an obstacle.
AndrewBissell 7y ago
> His argument is that to solve self-driving you need a deep understanding of your surrounding which you can only achieve with visible light spectrum video. That's the real hard problem to solve Musk's argument is more that cameras should be sufficient because humans can drive using only two eyes to perceive the driving environment. He always neglects to mention that humans do this with a combination of sight and a brain capable of general intelligence. I'm sure it's true that if Tesla invents AGI, self-driving with just cameras will become tractable. But "real hard problem to solve" doesn't begin to capture the difficulty. In reality, since no one has yet invented a self-driving computer, it's impossible to say what components are necessary or even whether there may be more than one way to skin the cat. But one source we should probably take with a grain of salt on this issue is those (like Musk) with an intense commercial interest in one perspective.
- kjksf 7y ago
  You could have made the same argument about any hard problem before it was solved. "So this guy says a machine can outplay chess with just a CPU, some memory and a bit of code. He neglects to mention that humans have a brain capable of general intelligence". Year later, computer beats human in chess. "So this guy says you can teach a computer to play Go just by unsupervised training of neural networks. He neglects to mention that humans have a brain capable of general intelligence". Year later, computer beats human in Go. "So this guys says you can program neural network to play computer games competitively using vision and deep learning. He neglects to mention that humans have a brain capable of general intelligence". We don't need AGI for self driving. The difficulty of self driving is probably less than a dog walking on the street. No, a dog doesn't steer a car, because he doesn't have hands, but he's performing the same vision and planning tasks like a human (or AI) driving a car. He knows where he is, he knows where he wants to go and he uses vision and his non-AGI brain to plan a path to get there while also avoiding dynamic, unexpected obstacles.
  - AndrewBissell 7y ago
    Do you have any counterexamples which aren't finite games where all the potential moves and outcomes can (at least in theory) be exhaustively enumerated at any point in time?
    - marcinzm 7y ago
      You can approximate most everything in theory almost perfectly by a set of very large but finite moves. Driving a car can be approximated as a set of finite moves (ie: 0.001 degree changes in wheel position) done at finite intervals (say 10000 "frames" per second). That'd give you more precision and a finer time grain than even a human brain is capable of.
      - Dylan16807 7y ago
        And you don't need a 'very large' set of moves in the first place. 100 wheel positions are enough to give you 1-degree accuracy near neutral, and moderate but sufficient accuracy for strong turns. If you're looking at a delta from the previous position, 30 will do the job. Multiply that by 10 to 40 positions for the pedals, run the whole thing at 20Hz, and you're good to go.
- bob457 7y ago
  It seems to me that one of the difficulties we have with making robots is trying to model them too closely after ourselves. We don’t have a humanoid maid, but we do have a roomba; similarly for lots of industrial automation. Home automation doesn’t look like c3po walking around your house flipping light switches. It seems like maybe not the best reasoning to say “humans, do it this way, so that’s how my robot should do it.”
  - marcinzm 7y ago
    Except a Roomba is much more limited than a human maid even in the constrained task of vacuuming the floor. And for a self-driving car you do need human levels of performance. Nor can you cheat and redo the infrastructure to accommodate simpler system like with home automation (ie: replace light switches withe relays).
    - dawnim 7y ago
      Except that you could most definitely repurpose some infrastructure to better suit AD. Having a somewhat protected AD only lane in cities would allow, today even, autonomous transport to be utilized.
rhacker 7y ago
Even if that is his point, that's making a lot of assumptions. I don't know why Tesla autopilot keeps missing obvious impervious occlusive surfaces, and detecting obvious impervious occlusive surfaces is what Lidar excels at, it's kinda making the point for the other side.
cromwellian 7y ago
Seems to me that "deep understanding of surrounding" and "only achievable with visible spectrum" are contradictory. Visible light is readily attenuated, occluded, and reflected. The first time Tesla runs over a kid chasing a ball into the street because it couldn't see him between the cars, this will be readily apparent. Seems to me that Tesla is in the business of selling cars, other self driving companies are interested in AV for ride sharing or trucking. The latter have different requirements for styling and costs and the consumer case, so Musk has several limitations on the sensor suite he includes in a Tesla. What he's doing is trying to argue a $5k system with cheap cameras and crappy radar coverage is all that is needed, because a full no-blind-spot multi-spectrum system would both cost too much AND likely make the car look ugly. Two people have already been killed, and several injured, by Tesla autopilot due to blind spots.
- lolc 7y ago
  Exactly. Until a car with reliable object permanence is demonstrated Tesla must tone down their promises. This LIDAR controversy is just a sideshow. Though a car having it will be able to outperform a car without it in many scenarios. An improvement over baseline human perception is very welcome.
- davidgould 7y ago
  Can you explain how a lidar sees a child hidden between cars? I was under the impression that lidar was line of sight.
- moduspol 7y ago
  The things detectable in the visible spectrum are what humans use to drive. Will it be apparent how fundamentally problematic this is when a human runs over a kid chasing a ball into the street because it couldn't see him between the cars? How many people have been killed by human drivers due to blind spots?
Sean1708 7y ago
> a deep understanding of your surrounding which you can only achieve with visible light spectrum video Why can you only achieve that using visible light spectrum video?
KaiserPro 7y ago
> which you can only achieve with visible light spectrum video Well, no. RGB is really useful. But actually, you can get pretty good object recognition from a point cloud alone. I mean its better to have RGB as well. but infra-red works just as well. The problem that appears to escape a lot of the commentary is latency. Sure, you can have a rudimentary stereo camera setup and get _some_ depth information reasonably fast. But it won't be good enough to tell you if that blob that's 100m out is stationary or moving towards you. Lidar gives you high resolution long range 3d point cloud at 30hz (or faster). The best most reliable depth from monocular/stereo will have a latency of at least 150ms and will be a tiny resolution. The chances are that we will have sub $100 CCD based lidar before we have low noise/low latency/full resolution depth from monocular/stereo cameras. The other big issue is that to get decent high res depth from deep learning, you need to have decent segmentation. Segmentation comes for free with lidar (assuming you impose rgb over it.) > spending all of their energy on creating neural nets around lidar then they'll reach a local maximum where they never begin to tackle the much more difficult problem truly needed for self-driving. This does not make all that much sense. You don't just train on lidar, you feed in steering, acceleration, braking, gears, signs, radar, pretty much everything. The other important thing to note is that tesla's stuff is still level 2. volvo, BMW, and a few truck companies are all at least level 4. We are celebrating a "genius" who has yet to actually release a system that does what he claims it should.
- mc_blue 7y ago
  Can you give examples of specific vehicles from Volvo/BMW/truck companies that are at level 4?
JibJabDab 7y ago
Cameras also can't really see around objects (in front of car, for instance). Lidar can. With cameras, its as if the goal is "to mimic human vision". That's fine and all but why can't we make it "beyond human vision"?
- davidgould 7y ago
  I’m really curious to learn about how lidar can see around things? You’re the second person to make this claim in this thread and I’ve never heard of it. Please explain or provide a link or something.
  - Sean1708 7y ago
    https://www.youtube.com/watch?v=KnGQEzB9u_0 https://www.youtube.com/watch?v=KnGQEzB9u_0 maybe?
    - davidgould 7y ago
      Hey, thanks, that was interesting. It doesn't look like it will be widely available for a few years at least though.

by loourr 7y ago

threeseed 7y ago

Musk's argument was refuted by his own Data Scientists. They admitted their own models are far from perfect and will likely never be. The concerning one in particular was the "is this a large object" model which initially failed to identity objects such as car-carrying trucks, cranes etc. With Lidar you can certain at least that it will identity an obstacle.

AndrewBissell 7y ago

> His argument is that to solve self-driving you need a deep understanding of your surrounding which you can only achieve with visible light spectrum video. That's the real hard problem to solve Musk's argument is more that cameras should be sufficient because humans can drive using only two eyes to perceive the driving environment. He always neglects to mention that humans do this with a combination of sight and a brain capable of general intelligence. I'm sure it's true that if Tesla invents AGI, self-driving with just cameras will become tractable. But "real hard problem to solve" doesn't begin to capture the difficulty. In reality, since no one has yet invented a self-driving computer, it's impossible to say what components are necessary or even whether there may be more than one way to skin the cat. But one source we should probably take with a grain of salt on this issue is those (like Musk) with an intense commercial interest in one perspective.

kjksf 7y ago
You could have made the same argument about any hard problem before it was solved. "So this guy says a machine can outplay chess with just a CPU, some memory and a bit of code. He neglects to mention that humans have a brain capable of general intelligence". Year later, computer beats human in chess. "So this guy says you can teach a computer to play Go just by unsupervised training of neural networks. He neglects to mention that humans have a brain capable of general intelligence". Year later, computer beats human in Go. "So this guys says you can program neural network to play computer games competitively using vision and deep learning. He neglects to mention that humans have a brain capable of general intelligence". We don't need AGI for self driving. The difficulty of self driving is probably less than a dog walking on the street. No, a dog doesn't steer a car, because he doesn't have hands, but he's performing the same vision and planning tasks like a human (or AI) driving a car. He knows where he is, he knows where he wants to go and he uses vision and his non-AGI brain to plan a path to get there while also avoiding dynamic, unexpected obstacles.
- AndrewBissell 7y ago
  Do you have any counterexamples which aren't finite games where all the potential moves and outcomes can (at least in theory) be exhaustively enumerated at any point in time?
  - marcinzm 7y ago
    You can approximate most everything in theory almost perfectly by a set of very large but finite moves. Driving a car can be approximated as a set of finite moves (ie: 0.001 degree changes in wheel position) done at finite intervals (say 10000 "frames" per second). That'd give you more precision and a finer time grain than even a human brain is capable of.
    - Dylan16807 7y ago
      And you don't need a 'very large' set of moves in the first place. 100 wheel positions are enough to give you 1-degree accuracy near neutral, and moderate but sufficient accuracy for strong turns. If you're looking at a delta from the previous position, 30 will do the job. Multiply that by 10 to 40 positions for the pedals, run the whole thing at 20Hz, and you're good to go.
bob457 7y ago
It seems to me that one of the difficulties we have with making robots is trying to model them too closely after ourselves. We don’t have a humanoid maid, but we do have a roomba; similarly for lots of industrial automation. Home automation doesn’t look like c3po walking around your house flipping light switches. It seems like maybe not the best reasoning to say “humans, do it this way, so that’s how my robot should do it.”
- marcinzm 7y ago
  Except a Roomba is much more limited than a human maid even in the constrained task of vacuuming the floor. And for a self-driving car you do need human levels of performance. Nor can you cheat and redo the infrastructure to accommodate simpler system like with home automation (ie: replace light switches withe relays).
  - dawnim 7y ago
    Except that you could most definitely repurpose some infrastructure to better suit AD. Having a somewhat protected AD only lane in cities would allow, today even, autonomous transport to be utilized.

rhacker 7y ago

Even if that is his point, that's making a lot of assumptions. I don't know why Tesla autopilot keeps missing obvious impervious occlusive surfaces, and detecting obvious impervious occlusive surfaces is what Lidar excels at, it's kinda making the point for the other side.

cromwellian 7y ago

Seems to me that "deep understanding of surrounding" and "only achievable with visible spectrum" are contradictory. Visible light is readily attenuated, occluded, and reflected. The first time Tesla runs over a kid chasing a ball into the street because it couldn't see him between the cars, this will be readily apparent. Seems to me that Tesla is in the business of selling cars, other self driving companies are interested in AV for ride sharing or trucking. The latter have different requirements for styling and costs and the consumer case, so Musk has several limitations on the sensor suite he includes in a Tesla. What he's doing is trying to argue a $5k system with cheap cameras and crappy radar coverage is all that is needed, because a full no-blind-spot multi-spectrum system would both cost too much AND likely make the car look ugly. Two people have already been killed, and several injured, by Tesla autopilot due to blind spots.

lolc 7y ago
Exactly. Until a car with reliable object permanence is demonstrated Tesla must tone down their promises. This LIDAR controversy is just a sideshow. Though a car having it will be able to outperform a car without it in many scenarios. An improvement over baseline human perception is very welcome.
davidgould 7y ago
Can you explain how a lidar sees a child hidden between cars? I was under the impression that lidar was line of sight.
moduspol 7y ago
The things detectable in the visible spectrum are what humans use to drive. Will it be apparent how fundamentally problematic this is when a human runs over a kid chasing a ball into the street because it couldn't see him between the cars? How many people have been killed by human drivers due to blind spots?

Sean1708 7y ago

> a deep understanding of your surrounding which you can only achieve with visible light spectrum video Why can you only achieve that using visible light spectrum video?

KaiserPro 7y ago

> which you can only achieve with visible light spectrum video Well, no. RGB is really useful. But actually, you can get pretty good object recognition from a point cloud alone. I mean its better to have RGB as well. but infra-red works just as well. The problem that appears to escape a lot of the commentary is latency. Sure, you can have a rudimentary stereo camera setup and get _some_ depth information reasonably fast. But it won't be good enough to tell you if that blob that's 100m out is stationary or moving towards you. Lidar gives you high resolution long range 3d point cloud at 30hz (or faster). The best most reliable depth from monocular/stereo will have a latency of at least 150ms and will be a tiny resolution. The chances are that we will have sub $100 CCD based lidar before we have low noise/low latency/full resolution depth from monocular/stereo cameras. The other big issue is that to get decent high res depth from deep learning, you need to have decent segmentation. Segmentation comes for free with lidar (assuming you impose rgb over it.) > spending all of their energy on creating neural nets around lidar then they'll reach a local maximum where they never begin to tackle the much more difficult problem truly needed for self-driving. This does not make all that much sense. You don't just train on lidar, you feed in steering, acceleration, braking, gears, signs, radar, pretty much everything. The other important thing to note is that tesla's stuff is still level 2. volvo, BMW, and a few truck companies are all at least level 4. We are celebrating a "genius" who has yet to actually release a system that does what he claims it should.

mc_blue 7y ago
Can you give examples of specific vehicles from Volvo/BMW/truck companies that are at level 4?

JibJabDab 7y ago

Cameras also can't really see around objects (in front of car, for instance). Lidar can. With cameras, its as if the goal is "to mimic human vision". That's fine and all but why can't we make it "beyond human vision"?

davidgould 7y ago
I’m really curious to learn about how lidar can see around things? You’re the second person to make this claim in this thread and I’ve never heard of it. Please explain or provide a link or something.
- Sean1708 7y ago
  https://www.youtube.com/watch?v=KnGQEzB9u_0 https://www.youtube.com/watch?v=KnGQEzB9u_0 maybe?
  - davidgould 7y ago
    Hey, thanks, that was interesting. It doesn't look like it will be widely available for a few years at least though.