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>Not only you can't do this with just cameras and radar Humans do it really well with just two cameras. It's not a hardware problem; it is entirely software. W

>Not only you can't do this with just cameras and radar Humans do it really well with just two cameras. It's not a hardware problem; it is entirely software. Whether self driving is possible or not with current AI techniques is debatable, but we're not waiting on any advances in hardware to do it.

Animats 7y ago
As the article points out, machine learning has its limits. It can do some things reasonably well, but it does max out. It's easy to get to 90% accuracy, hard to get to 98%, and 99.9% is out of reach.
qchris 7y ago
> Humans do it really well with just two cameras. If you don't mind, I think I'm going to steal that quote. It makes a really good point very succinctly.
- MegaButts 7y ago
  It's true, but it ignores the fact that human eyes have orders of magnitude more dynamic range than even very expensive specialized cameras, and it obviously ignores the fact that we haven't invented general AI yet. It's a pithy response that undermines the challenge of a problem nobody has been able to solve even with years of effort and billions of dollars.
  - qchris 7y ago
    I agree that human eyes do have benefits over your typical camera, but I don't think the phrase ignores that GAI hasn't been created yet; rather, it concisely points that out and makes it clear how difficult it is to do. As the OP said, "it's not a hardware problem," in that the quality or number of cameras, sensors, etc. isn't the bottleneck to solving this problem.
  - aphextron 7y ago
    >It's true, but it ignores the fact that human eyes have orders of magnitude more dynamic range than even very expensive specialized cameras, and it obviously ignores the fact that we haven't invented general AI yet. That level of resolution doesn't matter at all for driving. People can drive just as well through a video feed, like Starsky was doing. Yes general AI does not exist yet, but my point is simply that the parent made a comment about the need for hardware which is simply not true.
    - MegaButts 7y ago
      > That level of resolution doesn't matter at all for driving. People can drive just as well through a video feed, like Starsky was doing. I can tell you from experience this is false. It usually works, but when it doesn't you're fucked. People wildly underestimate, by orders of magnitude, how many and how complicated the edge-cases are for self-driving.
  - llsf 7y ago
    My husband is an optometrist. There are lots of people who are driving with poor vision. We do not need (although it is obviously better) perfect vision to drive a vehicle. We can drive in fog or heavy rain, with limited vision. I am not sure that image quality is a big factor here. But we do have a good spacial sense (distance) + object recognition (mass/speed) + psychology/habits. I can tell at glance if an object is able/supposed to move, and adjust (i.e. watch/sample it for few more milliseconds) to estimate it current speed. I estimate its mass and deduce inertia (can it stop if need to). I make eye contact with driver, to acknowledge that he saw me, etc. Not saying that those things cannot be learnt and used by a software. I do agree that we do well with just two cameras, and we make up for it. BTW, from our senses, one that I rarely see mentioned is the hearing (used to label and spatially locate). I do use it while driving (e.g. motorbike approaching, but not seeing it yet, or emergency vehicle).
- legolas2412 7y ago
  Humans also have our brains backing up the eyes. Has Elon musk invented artificial general intelligence? If not, the point isn't a good one at all.
jschwartzi 7y ago
And the problem with current approaches is entirely that while we can "train" a NN to produce specific emergent behavior associated with the training data to a great degree of accuracy, we're totally unable to demonstrate that these systems have perfectly(100% accurate) predictable behaviors. This is because we're totally unable to come up with a coherent model for why the emergent behavior occurs given the input data and NN training. We know how individual elements of the NN work, and we can describe how the training system works. But the whole notion of repeatedly letting perturbations in a control value or control values dictate the entirety of the performance of a system is nuts. The only way to determine how a NN will perform in a given situation outside of the training set is to actually feed it the stimulus and check the outputs. Given the amount of stimulus that we as drivers routinely get, it's impossible to say with any degree of certainty that a self-driving car that is built on an NN classifying engine will accurately classify everything in all situations and lighting conditions, because it's impossible to feed it a training set large enough to encompass those situations. That leaves the question of making a classifier that is better than humans. And whether an NN is better than a human depends very much on the situation. We could make some statistical arguments, but when you're gambling with peoples' lives here it becomes difficult to tolerate such arguments. It's easy to be blase about it until it's your child chasing a ball in front of an AV, at which point any discussion of the statistics is academic.
- stefan8r 7y ago
  Some large teams have tried to overcome this by making up every such scenario, coding it into simulation, and testing their system. What makes this challenging is that there are more such scenarios that might occur than there are grains of sand, or stars in the universe. Those teams end up thinking they did all the necessary work and then go test, just to find out that there's a new edge case. At Starsky we called it Safety Theatre
  - jschwartzi 7y ago
    I had a mentor at my last job who would repeatedly say "You can't test safety into a product." As in you have to actually do the work to understand and limit how the product behaves, and only then can you call it safe. If you build a product without thinking of safety, then try to test the safety into the finished product, you just end up covering all the known sharp edges with foam. Software products have limitless sharp edges.
m0zg 7y ago
> Humans do it really well with just two cameras _and general intelligence_ FTFY. You can thank me later.
sifar 7y ago
>> Humans do it really well with just two cameras. It's not a hardware problem; it is entirely software We don't fully know how the human hardware works either. Or rather, we don't fully know how the human hardware + software works.
deleted 7y ago
[deleted]

Animats 7y ago

As the article points out, machine learning has its limits. It can do some things reasonably well, but it does max out. It's easy to get to 90% accuracy, hard to get to 98%, and 99.9% is out of reach.

qchris 7y ago

> Humans do it really well with just two cameras. If you don't mind, I think I'm going to steal that quote. It makes a really good point very succinctly.

MegaButts 7y ago
It's true, but it ignores the fact that human eyes have orders of magnitude more dynamic range than even very expensive specialized cameras, and it obviously ignores the fact that we haven't invented general AI yet. It's a pithy response that undermines the challenge of a problem nobody has been able to solve even with years of effort and billions of dollars.
- qchris 7y ago
  I agree that human eyes do have benefits over your typical camera, but I don't think the phrase ignores that GAI hasn't been created yet; rather, it concisely points that out and makes it clear how difficult it is to do. As the OP said, "it's not a hardware problem," in that the quality or number of cameras, sensors, etc. isn't the bottleneck to solving this problem.
- aphextron 7y ago
  >It's true, but it ignores the fact that human eyes have orders of magnitude more dynamic range than even very expensive specialized cameras, and it obviously ignores the fact that we haven't invented general AI yet. That level of resolution doesn't matter at all for driving. People can drive just as well through a video feed, like Starsky was doing. Yes general AI does not exist yet, but my point is simply that the parent made a comment about the need for hardware which is simply not true.
  - MegaButts 7y ago
    > That level of resolution doesn't matter at all for driving. People can drive just as well through a video feed, like Starsky was doing. I can tell you from experience this is false. It usually works, but when it doesn't you're fucked. People wildly underestimate, by orders of magnitude, how many and how complicated the edge-cases are for self-driving.
- llsf 7y ago
  My husband is an optometrist. There are lots of people who are driving with poor vision. We do not need (although it is obviously better) perfect vision to drive a vehicle. We can drive in fog or heavy rain, with limited vision. I am not sure that image quality is a big factor here. But we do have a good spacial sense (distance) + object recognition (mass/speed) + psychology/habits. I can tell at glance if an object is able/supposed to move, and adjust (i.e. watch/sample it for few more milliseconds) to estimate it current speed. I estimate its mass and deduce inertia (can it stop if need to). I make eye contact with driver, to acknowledge that he saw me, etc. Not saying that those things cannot be learnt and used by a software. I do agree that we do well with just two cameras, and we make up for it. BTW, from our senses, one that I rarely see mentioned is the hearing (used to label and spatially locate). I do use it while driving (e.g. motorbike approaching, but not seeing it yet, or emergency vehicle).
legolas2412 7y ago
Humans also have our brains backing up the eyes. Has Elon musk invented artificial general intelligence? If not, the point isn't a good one at all.

jschwartzi 7y ago

And the problem with current approaches is entirely that while we can "train" a NN to produce specific emergent behavior associated with the training data to a great degree of accuracy, we're totally unable to demonstrate that these systems have perfectly(100% accurate) predictable behaviors. This is because we're totally unable to come up with a coherent model for why the emergent behavior occurs given the input data and NN training. We know how individual elements of the NN work, and we can describe how the training system works. But the whole notion of repeatedly letting perturbations in a control value or control values dictate the entirety of the performance of a system is nuts. The only way to determine how a NN will perform in a given situation outside of the training set is to actually feed it the stimulus and check the outputs. Given the amount of stimulus that we as drivers routinely get, it's impossible to say with any degree of certainty that a self-driving car that is built on an NN classifying engine will accurately classify everything in all situations and lighting conditions, because it's impossible to feed it a training set large enough to encompass those situations. That leaves the question of making a classifier that is better than humans. And whether an NN is better than a human depends very much on the situation. We could make some statistical arguments, but when you're gambling with peoples' lives here it becomes difficult to tolerate such arguments. It's easy to be blase about it until it's your child chasing a ball in front of an AV, at which point any discussion of the statistics is academic.

stefan8r 7y ago
Some large teams have tried to overcome this by making up every such scenario, coding it into simulation, and testing their system. What makes this challenging is that there are more such scenarios that might occur than there are grains of sand, or stars in the universe. Those teams end up thinking they did all the necessary work and then go test, just to find out that there's a new edge case. At Starsky we called it Safety Theatre
- jschwartzi 7y ago
  I had a mentor at my last job who would repeatedly say "You can't test safety into a product." As in you have to actually do the work to understand and limit how the product behaves, and only then can you call it safe. If you build a product without thinking of safety, then try to test the safety into the finished product, you just end up covering all the known sharp edges with foam. Software products have limitless sharp edges.

m0zg 7y ago

> Humans do it really well with just two cameras _and general intelligence_ FTFY. You can thank me later.

sifar 7y ago

>> Humans do it really well with just two cameras. It's not a hardware problem; it is entirely software We don't fully know how the human hardware works either. Or rather, we don't fully know how the human hardware + software works.

deleted 7y ago

[deleted]