6 ms·

I think the argument is that if a human with two eyeballs can do it, a computer with a bunch of cameras should be able to as well. I can drive in the snow.

perardi 6y ago
That’s…a supposition more than an argument.
- fastball 6y ago
  How is that not an argument? A human can drive in the snow, and has a sensing package which effectively consists of two cameras. The hard part (when you only have two cameras) is that the processor needs to be exceedingly sophisticated, e.g. a human brain. People like Waymo have decided the best way to decrease the brain requirement is to add more sophisticated sensing that humans are fundamentally incapable of. Tesla's strategy is more to just build a better digital driving brain with machine learning + lots of miles, because arguably all sensing mechanisms have their shortcomings. That being said, they still have a lot more than two cameras in their FSD package – just not LIDAR. They still have radar and other things as well. Only time will tell which approach is better. Probably in the end the best approach will be to combine the two: a brain that is sophisticated enough it can drive with just cameras, but you throw LIDAR and such in their too to go the extra mile.
  - Skunkleton 6y ago
    > A human can drive in the snow, and has a sensing package which effectively consists of two cameras. Two cameras, and a huge amount of mostly not understood wetware interpreting their signals. Our current approaches to ML may be a local maxima. The true path to AGI be somewhere as yet undiscovered. Lidar certainly seems like a good tool to use given our current ML capabilities.
    - fastball 6y ago
      Our current ML capabilities involve throwing as much training data at the problem as humanly possible. No LIDAR means more training data, as has been made clear by the amount of miles driven by Waymo vehicles vs Teslas in Autopilot.
  - Barrin92 6y ago
    it's a strange philosophy. Isn't the point of building machines that they can do things that humans can't? It's like building drones for warfare and turning the heat-seeking off because humans don't have that capacity. A generally intelligent driving system is going to benefit from better sensory inputs just like a human would, it's not like that makes the system dumber. The whole dichotomy between sensory inputs and processing seems strange to begin with, there's not necessary a clear line, or a reason why one should be prioritized over the other.
    - fastball 6y ago
      We are not talking about generally intelligent driving systems though. You have to realize that most SOTA self-driving systems are using a lot of NNs. NNs in turn want lots of training data. That training is not fully generic – in other words, if you train a NN using only cameras, giving LIDAR to that trained network (i.e. for inference) will not really do anything. Having large LIDAR arrays on the top of vehicles is expensive and slow to deploy, which directly translates to being able to generate less training data. So if your goal is to have the best possible self-driving vehicles 100 years from now, absolutely you should be using as much sophisticated sensing equipment you can get your hands on, and slowly train your nets for the next century. If your goal is to get out something that is better than a human driver as fast as possible, then it is not clear that requiring all vehicles to have LIDAR on them is the best way to go.
    - mewpmewp2 6y ago
      Not necessarily. Usually machines are built to do mundane tasks that humans have to do. In most cases they are built to replace what a human can do. The argument for having a lidar vs not having a lidar is different. They chose to go without lidar because it should be cheaper and faster to get started, and the fact that people are capable of doing driving without lidar makes it seem possible that a machine could do it without lidar.
hilbertseries 6y ago
This is a terrible argument. You’re basically saying that computers can do anything humans can, which so far has not been the case.
- jsight 6y ago
  Saying that computer vision can view the world with snow present is hardly the same as claiming that computers can do literally anything a human can. On the contrary, having computer vision capable of handling snow is a necessary precondition for self-driving, regardless of what other sensors are present.
- Dylan16807 6y ago
  Not "anything". Just taking noisy camera data and turning it into a de-noised picture.
  - tylerhou 6y ago
    > Just taking noisy camera data and turning it into a de-noised picture. I think this is a huge simplification of the actual problem. Not only do you have to denoise the data, you have to use the data to generate models of 3D objects in space. Maybe you could argue that exact 3D models are not necessary, but IMO any neural network that can drive at Level 4/5 needs to approximate 3D space in some layer. This is incredibly difficult; we have an entire region of the brain dedicated to for this exact purpose (the visual cortex). This region has the benefit of millions of years of evolution. We also have the advantage that we can predict 3D models based on everyday experience; we don't know how to encode that knowledge into a neural network efficiently. That's not even mentioning the latency requirements that driving in the real world would impose on such a network.
    - Dylan16807 6y ago
      You have to do all that hard stuff with or without snow. The difficulty imposed by snowfall itself is just de-noising.
- Sohcahtoa82 6y ago
grumple 6y ago
Humans certainly do drive in the snow, but not well. I've driven without being able to see the road (very slowly). This is not a safe situation. This is actually a case where I think computers (with LIDAR or other advanced sensors) will be able to outperform humans and it won't be close. I agree with the posters that say the anti-LIDAR stance is not going to work out in the long run.
- AlotOfReading 6y ago
  Musk is not only anti-LIDAR, he's anti-HD mapping. Imagine if you had a centimeter-accurate map overlaid on your windscreen. You'd probably be able to operate the vehicle right up to the limits of the conditions. It definitely won't be close in many situations.
alacombe 6y ago
> I can drive in the snow More often than not, snow driving is CHALLENGING. And it's not for a lack of experience, as I'm doing multiple roadtrips through the BC Coquihalla Highway. More often than now, it's more of a matter of best attempt at driving in the path made by other car disregarding lines on the road than driving by the book. The utter HELL being driving at night with a blizzard, this is a level-up experience for sure.
- ghaff 6y ago
  And before anyone says, well don't do that: 1. Many people have no choice but to drive in bad snow conditions for any number of reasons including that they're emergency workers. 2.) Winter conditions catch you. Even though I don't commute and basically do everything to avoid bad winter weather conditions, I've still been caught in pretty bad conditions a couple times over the past few years.
  - alacombe 6y ago
    > And before anyone says, well don't do that: Fuck them... Is that how much a pussy society we have become ? Avoid dangerous conditions because "it might be dangerous" ? If a freaking Tesla can't handle what my 06 SUV can handle without issue, and what people were handling ~forever, ... just as much as an Apple laptop can't handle what a then-IBM was handling, then the damn "car"/"laptop" is nothing but a piece of shit. Urbanus homo sapiens sapiens is really a pussy...
    - mewpmewp2 6y ago
      That's a ridiculous statement. Having a self driving car that works in only certain conditions can still be a benefit for the society. It won't benefit you, but it will benefit thousands of others.
      - alacombe 6y ago
        In the mean time, every Texan EV owner is stuck because their brand new 50k Tesla can drive in the snow.

perardi 6y ago

That’s…a supposition more than an argument.

fastball 6y ago
How is that not an argument? A human can drive in the snow, and has a sensing package which effectively consists of two cameras. The hard part (when you only have two cameras) is that the processor needs to be exceedingly sophisticated, e.g. a human brain. People like Waymo have decided the best way to decrease the brain requirement is to add more sophisticated sensing that humans are fundamentally incapable of. Tesla's strategy is more to just build a better digital driving brain with machine learning + lots of miles, because arguably all sensing mechanisms have their shortcomings. That being said, they still have a lot more than two cameras in their FSD package – just not LIDAR. They still have radar and other things as well. Only time will tell which approach is better. Probably in the end the best approach will be to combine the two: a brain that is sophisticated enough it can drive with just cameras, but you throw LIDAR and such in their too to go the extra mile.
- Skunkleton 6y ago
  > A human can drive in the snow, and has a sensing package which effectively consists of two cameras. Two cameras, and a huge amount of mostly not understood wetware interpreting their signals. Our current approaches to ML may be a local maxima. The true path to AGI be somewhere as yet undiscovered. Lidar certainly seems like a good tool to use given our current ML capabilities.
  - fastball 6y ago
    Our current ML capabilities involve throwing as much training data at the problem as humanly possible. No LIDAR means more training data, as has been made clear by the amount of miles driven by Waymo vehicles vs Teslas in Autopilot.
- Barrin92 6y ago
  it's a strange philosophy. Isn't the point of building machines that they can do things that humans can't? It's like building drones for warfare and turning the heat-seeking off because humans don't have that capacity. A generally intelligent driving system is going to benefit from better sensory inputs just like a human would, it's not like that makes the system dumber. The whole dichotomy between sensory inputs and processing seems strange to begin with, there's not necessary a clear line, or a reason why one should be prioritized over the other.
  - fastball 6y ago
    We are not talking about generally intelligent driving systems though. You have to realize that most SOTA self-driving systems are using a lot of NNs. NNs in turn want lots of training data. That training is not fully generic – in other words, if you train a NN using only cameras, giving LIDAR to that trained network (i.e. for inference) will not really do anything. Having large LIDAR arrays on the top of vehicles is expensive and slow to deploy, which directly translates to being able to generate less training data. So if your goal is to have the best possible self-driving vehicles 100 years from now, absolutely you should be using as much sophisticated sensing equipment you can get your hands on, and slowly train your nets for the next century. If your goal is to get out something that is better than a human driver as fast as possible, then it is not clear that requiring all vehicles to have LIDAR on them is the best way to go.
  - mewpmewp2 6y ago
    Not necessarily. Usually machines are built to do mundane tasks that humans have to do. In most cases they are built to replace what a human can do. The argument for having a lidar vs not having a lidar is different. They chose to go without lidar because it should be cheaper and faster to get started, and the fact that people are capable of doing driving without lidar makes it seem possible that a machine could do it without lidar.

hilbertseries 6y ago

This is a terrible argument. You’re basically saying that computers can do anything humans can, which so far has not been the case.

jsight 6y ago
Saying that computer vision can view the world with snow present is hardly the same as claiming that computers can do literally anything a human can. On the contrary, having computer vision capable of handling snow is a necessary precondition for self-driving, regardless of what other sensors are present.
Dylan16807 6y ago
Not "anything". Just taking noisy camera data and turning it into a de-noised picture.
- tylerhou 6y ago
  > Just taking noisy camera data and turning it into a de-noised picture. I think this is a huge simplification of the actual problem. Not only do you have to denoise the data, you have to use the data to generate models of 3D objects in space. Maybe you could argue that exact 3D models are not necessary, but IMO any neural network that can drive at Level 4/5 needs to approximate 3D space in some layer. This is incredibly difficult; we have an entire region of the brain dedicated to for this exact purpose (the visual cortex). This region has the benefit of millions of years of evolution. We also have the advantage that we can predict 3D models based on everyday experience; we don't know how to encode that knowledge into a neural network efficiently. That's not even mentioning the latency requirements that driving in the real world would impose on such a network.
  - Dylan16807 6y ago
    You have to do all that hard stuff with or without snow. The difficulty imposed by snowfall itself is just de-noising.
Sohcahtoa82 6y ago

grumple 6y ago

Humans certainly do drive in the snow, but not well. I've driven without being able to see the road (very slowly). This is not a safe situation. This is actually a case where I think computers (with LIDAR or other advanced sensors) will be able to outperform humans and it won't be close. I agree with the posters that say the anti-LIDAR stance is not going to work out in the long run.

AlotOfReading 6y ago
Musk is not only anti-LIDAR, he's anti-HD mapping. Imagine if you had a centimeter-accurate map overlaid on your windscreen. You'd probably be able to operate the vehicle right up to the limits of the conditions. It definitely won't be close in many situations.

alacombe 6y ago

> I can drive in the snow More often than not, snow driving is CHALLENGING. And it's not for a lack of experience, as I'm doing multiple roadtrips through the BC Coquihalla Highway. More often than now, it's more of a matter of best attempt at driving in the path made by other car disregarding lines on the road than driving by the book. The utter HELL being driving at night with a blizzard, this is a level-up experience for sure.

ghaff 6y ago
And before anyone says, well don't do that: 1. Many people have no choice but to drive in bad snow conditions for any number of reasons including that they're emergency workers. 2.) Winter conditions catch you. Even though I don't commute and basically do everything to avoid bad winter weather conditions, I've still been caught in pretty bad conditions a couple times over the past few years.
- alacombe 6y ago
  > And before anyone says, well don't do that: Fuck them... Is that how much a pussy society we have become ? Avoid dangerous conditions because "it might be dangerous" ? If a freaking Tesla can't handle what my 06 SUV can handle without issue, and what people were handling ~forever, ... just as much as an Apple laptop can't handle what a then-IBM was handling, then the damn "car"/"laptop" is nothing but a piece of shit. Urbanus homo sapiens sapiens is really a pussy...
  - mewpmewp2 6y ago
    That's a ridiculous statement. Having a self driving car that works in only certain conditions can still be a benefit for the society. It won't benefit you, but it will benefit thousands of others.
    - alacombe 6y ago
      In the mean time, every Texan EV owner is stuck because their brand new 50k Tesla can drive in the snow.