6 ms·

Everybody wants to jump straight to 4, because 3 is actually dangerous and likely to cause deaths as people are lulled into a false sense of safety. The questi

Everybody wants to jump straight to 4, because 3 is actually dangerous and likely to cause deaths as people are lulled into a false sense of safety. The question is how long will it take? Some people say 2 years, some people say 20.

puranjay 10y ago
How much has the recent interest and investment in self-driving cars impacted this estimate? 5 years ago, I would have said that level 4 automation is 20 years away. With all these billions pouring in, I'd cut that projection in less than half. I'm certain that I won't be driving a car ever in 2030
- jayjay71 10y ago
  I think it actually doesn't make that much difference. The problem, I believe, is that people are used to rapid advances in software. Lots of small iterations can take you a long way, but sometimes you just reach a hurdle which requires a breakthrough. A fully self-driving car would need a huge breakthrough in perception (which most people categorize under AI) in order to work. Computer vision actually started out in the 60's because how hard could it be to classify objects in images? Well, decades later and it's still a hugely unsolved problem. Robotics can be broken into 3 main categories: perception, planning, and controls. Perception is always the weak point. Robots just cannot see and understand their environments like people can. When you put a robot in a dynamic environment, they fail spectacularly. To give some idea of this, look at videos of robots falling down at the DARPA Robotics Challenge - and keep in mind those were made by teams of top roboticists with millions of dollars in a highly constrained environment (it's hard to say that obstacle course was "real"). I really, really doubt it's going to happen in a few years. I would love to be wrong though.
  - deleted 10y ago
    [deleted]
  - adrianN 10y ago
    Last time I checked Google's self driving car was doing pretty well already without major breakthroughs. I suppose there still are problems when the weather conditions are less than ideal, but you can't compare it to /r/shittyrobots.
    - fweespeech 10y ago
      Many places have "less than ideal weather conditions" for 100+ days a year.
    - fucking_tragedy 10y ago
      The car's performance on a relatively small stretch of road in California is hardly indicative of its potential performance on millions of miles of varied roadways, terrain and climate that make up the rest of the world.
    - serge2k 10y ago
      How does it do in a snowstorm? Heavy rain?
  - vasilipupkin 10y ago
    well, hasn't google driven around actual city streets for many millions of miles? I could be wrong, but driving a car doesn't actually require breakthroughs in perception beyond current technology, The issue is that it just isn't economical for individual car ownership at this stage, but it could very well make economic sense for a fleet of taxis. Note, those taxis don't have to have the ability to go just anywhere, they could have predefined routes
  - majewsky 10y ago
    > how hard could it be to classify objects in images? Well, decades later and it's still a hugely unsolved problem. AFAIK Google's cars rely on radar to identify the position of objects, which I would think is vastly easier. Of course, there's still the interesting challenge of classifying objects into traffic partipicants and obstacles.
  - kamaal 10y ago
    >>sometimes you just reach a hurdle which requires a breakthrough. When there are billions of $'s to be made. Generally there is way. I understand from where you are coming. But if the trend grows, and one companies sees the billions coming. Others are forced to innovate. Also a whole new ecosystem is born. See pre iPhone and post iPhone mobile industry. Sometimes you need one company to do something insane to drive others down the same path.
- Shivetya 10y ago
  Same view here, current solutions are nothing more than Sunday drivers to me. They work well in good to near perfect conditions only where we actually need the least amount of self driving. Wheel less driving, first show me it drives in the pouring rain at night when the roads aren't lit. Show it having the ability to obey posted speed limits, adjust to construction, and the like. I am still surprised at how much current systems love to tail gate let alone don't suggest obeying posted limits.
  - rwmj 10y ago
    Give me a car which self-drives for 4 months of the year, and requires me to drive it the other 8 months. That's still a massive advantage over the car I currently own.
    - kalleboo 10y ago
      Indeed but the context here are all the futuristic predictions starting with mass-unemployment of taxi and truck drivers (indeed that's what Uber is selling their market valuation on). If drivers are still needed 60% of the time, they're going nowhere. The hype right now is so great that even if the reality is amazing it will be disappointing.
      - stale2002 10y ago
        The disruptive effects still happen even if we don't get to 100%. For example, a train of self driving trucks can be led by 1 in the front. Yes, I know, REAL trains exist, but they don't go everywhere. A train of self driving trucks could save a lot of money. If self driving Taxis don't work in the rain, then Uber can just NOT drive them when it is raining! For example, Maybe the penetration rate will be very low in Seattle, but very high in Texas. Disrupting 20% of the Taxi market by eliminating drivers is still a very big deal.
        falafel_muncher 10y ago
        They still have to work in the rain before gov't allows them on the road though..
- kalleboo 10y ago
  How many billions have been poured into speech recognition? I don't anyone here would trust controlling a car with Siri or Google Voice lest it misinterpret something you said.
  - tcoppi 10y ago
    Have you used Google Voice in the past ~year? I have a standard american accent so I might be the best case scenario for it but I haven't seen it miss a word I've said anytime I can remember in a year or two. I mostly use it in the car to reply and send texts, works even with the radio and ventilation on. I've used an Amazon Echo and that is right 99% of the time too. Now, interpreting the words I say is a different matter, but as far as transcription I'd say we are at basically 100% right now and have been for a while.
    - gambiting 10y ago
      Well, the thing is, English is not the only language in the world. Google's voice recognition in my native language, Polish, is absolutely abysmal.
      - tcoppi 10y ago
        I feel like that is more a product of the fact that the effort put into most other languages is greatly lower at this point relative to English, rather than English is particularly easy or other languages are particularly hard. It will all come in time.
        Nadya 10y ago
        Not effort - but data. A large amount of the dictation learning was done through users using and correcting the software. If you have 40,000,000 English users but only 80,000 Polish users you can immediately see why the software may not be up to par. Google Voice to Text, from my experiences, is bloody amazing for Chinese. My Chinese is abysmal (think "never gets the tone right") and for short phrases/sentences I've never had Google fail on me. Maybe it fails on larger sentences but it would be difficult for me to believe. Japanese is another language it does very well in. I can only count on one hand how many times it has made a mistake - and usually repeating myself a tad slower and with less slurring and it will pick it up just fine.
- gambiting 10y ago
  And interestingly, seeing challenges ahead, I don't think we will have 100% autonomous cars before 2050, if not later. 50 years ago, we were certain that perfect image recognition is just few months of work away, or at least enough money poured into it will solve the problem. It's 2016 and our best of the best image recognition algorithms can't even tell a zebra and a sofa in a zebra print apart. Since automatic cars are trying to solve the same problem I can't believe that in 2030 anyone will make 100% autonomous car, not a chance. Super advanced cruise control, like Tesla's autopilot, but better - sure, absolutely. But a car without a steering wheel? nope.
  - eric_cc 10y ago
    People like you are the best because it really adds to the enjoyment of great achievements when there are a healthy amount of naysayers to point out. Thank you, naysayer.
  - dlubarov 10y ago
    > It's 2016 and our best of the best image recognition algorithms can't even tell a zebra and a sofa in a zebra print apart. State of the art offline CNNs have been doing classification quite well recently, arguably better than humans. See the Inception-v3 paper: http://arxiv.org/pdf/1512.00567v3.pdf http://arxiv.org/pdf/1512.00567v3.pdf
    - argonaut 10y ago
      None of that changes the fact that they're easy to fool and have some pathological cases (that gambiting alludes to) that most humans consider quite dumb.
Fricken 10y ago
Both 2 years and 20 years are good estimates, depending on whether you're talking about a robocab that ferries people from their suburban homes to the train station when the weather is nice, or a vehicle that drive empty across the country in a snowstorm.
ethbro 10y ago
I think the bigger question is how you get straight to 4. Ford has resources, but I feel like they're betting against history here w/ regards to ML successes. Practical, reliable ML stems from enormous data sets. And I can't see a way of obtaining the necessary data volume other than sitting in Level 3 for a product cycle...
- rhino369 10y ago
  I think the evolution will be using self driving features as a pure backup safety feature until they get good enough to go fulltime on their own.
Animats 10y ago
NHTSA Level 3 ("Limited Self-Driving: Vehicles at this level of automation enable the driver to cede full control of all safety-critical functions under certain traffic or environmental conditions and in those conditions to rely heavily on the vehicle to monitor for changes in those conditions requiring transition back to driver control. The driver is expected to be available for occasional control, but with sufficiently comfortable transition time. The Google car is an example of limited self-driving automation.") is OK. That means that the self-driving system can recognize situations it can't handle (snow, potholes, crowds in streets) and come to a safe stop if the driver doesn't take over. It's Level 2 ("adaptive cruise control in combination with lane centering") that's the problem. Therein lies the deadly valley - good enough that the driver can tune out, but not good enough to handle trouble. That's where Tesla is. Level 2 with strongly enforced hands-on-wheel seems to be OK, but don't let the driver take their hands off for long periods.

puranjay 10y ago

How much has the recent interest and investment in self-driving cars impacted this estimate? 5 years ago, I would have said that level 4 automation is 20 years away. With all these billions pouring in, I'd cut that projection in less than half. I'm certain that I won't be driving a car ever in 2030

jayjay71 10y ago
I think it actually doesn't make that much difference. The problem, I believe, is that people are used to rapid advances in software. Lots of small iterations can take you a long way, but sometimes you just reach a hurdle which requires a breakthrough. A fully self-driving car would need a huge breakthrough in perception (which most people categorize under AI) in order to work. Computer vision actually started out in the 60's because how hard could it be to classify objects in images? Well, decades later and it's still a hugely unsolved problem. Robotics can be broken into 3 main categories: perception, planning, and controls. Perception is always the weak point. Robots just cannot see and understand their environments like people can. When you put a robot in a dynamic environment, they fail spectacularly. To give some idea of this, look at videos of robots falling down at the DARPA Robotics Challenge - and keep in mind those were made by teams of top roboticists with millions of dollars in a highly constrained environment (it's hard to say that obstacle course was "real"). I really, really doubt it's going to happen in a few years. I would love to be wrong though.
- deleted 10y ago
  [deleted]
- adrianN 10y ago
  Last time I checked Google's self driving car was doing pretty well already without major breakthroughs. I suppose there still are problems when the weather conditions are less than ideal, but you can't compare it to /r/shittyrobots.
  - fweespeech 10y ago
    Many places have "less than ideal weather conditions" for 100+ days a year.
  - fucking_tragedy 10y ago
    The car's performance on a relatively small stretch of road in California is hardly indicative of its potential performance on millions of miles of varied roadways, terrain and climate that make up the rest of the world.
  - serge2k 10y ago
    How does it do in a snowstorm? Heavy rain?
- vasilipupkin 10y ago
  well, hasn't google driven around actual city streets for many millions of miles? I could be wrong, but driving a car doesn't actually require breakthroughs in perception beyond current technology, The issue is that it just isn't economical for individual car ownership at this stage, but it could very well make economic sense for a fleet of taxis. Note, those taxis don't have to have the ability to go just anywhere, they could have predefined routes
- majewsky 10y ago
  > how hard could it be to classify objects in images? Well, decades later and it's still a hugely unsolved problem. AFAIK Google's cars rely on radar to identify the position of objects, which I would think is vastly easier. Of course, there's still the interesting challenge of classifying objects into traffic partipicants and obstacles.
- kamaal 10y ago
  >>sometimes you just reach a hurdle which requires a breakthrough. When there are billions of $'s to be made. Generally there is way. I understand from where you are coming. But if the trend grows, and one companies sees the billions coming. Others are forced to innovate. Also a whole new ecosystem is born. See pre iPhone and post iPhone mobile industry. Sometimes you need one company to do something insane to drive others down the same path.
Shivetya 10y ago
Same view here, current solutions are nothing more than Sunday drivers to me. They work well in good to near perfect conditions only where we actually need the least amount of self driving. Wheel less driving, first show me it drives in the pouring rain at night when the roads aren't lit. Show it having the ability to obey posted speed limits, adjust to construction, and the like. I am still surprised at how much current systems love to tail gate let alone don't suggest obeying posted limits.
- rwmj 10y ago
  Give me a car which self-drives for 4 months of the year, and requires me to drive it the other 8 months. That's still a massive advantage over the car I currently own.
  - kalleboo 10y ago
    Indeed but the context here are all the futuristic predictions starting with mass-unemployment of taxi and truck drivers (indeed that's what Uber is selling their market valuation on). If drivers are still needed 60% of the time, they're going nowhere. The hype right now is so great that even if the reality is amazing it will be disappointing.
    - stale2002 10y ago
      The disruptive effects still happen even if we don't get to 100%. For example, a train of self driving trucks can be led by 1 in the front. Yes, I know, REAL trains exist, but they don't go everywhere. A train of self driving trucks could save a lot of money. If self driving Taxis don't work in the rain, then Uber can just NOT drive them when it is raining! For example, Maybe the penetration rate will be very low in Seattle, but very high in Texas. Disrupting 20% of the Taxi market by eliminating drivers is still a very big deal.
      - falafel_muncher 10y ago
        They still have to work in the rain before gov't allows them on the road though..
kalleboo 10y ago
How many billions have been poured into speech recognition? I don't anyone here would trust controlling a car with Siri or Google Voice lest it misinterpret something you said.
- tcoppi 10y ago
  Have you used Google Voice in the past ~year? I have a standard american accent so I might be the best case scenario for it but I haven't seen it miss a word I've said anytime I can remember in a year or two. I mostly use it in the car to reply and send texts, works even with the radio and ventilation on. I've used an Amazon Echo and that is right 99% of the time too. Now, interpreting the words I say is a different matter, but as far as transcription I'd say we are at basically 100% right now and have been for a while.
  - gambiting 10y ago
    Well, the thing is, English is not the only language in the world. Google's voice recognition in my native language, Polish, is absolutely abysmal.
    - tcoppi 10y ago
      I feel like that is more a product of the fact that the effort put into most other languages is greatly lower at this point relative to English, rather than English is particularly easy or other languages are particularly hard. It will all come in time.
      - Nadya 10y ago
        Not effort - but data. A large amount of the dictation learning was done through users using and correcting the software. If you have 40,000,000 English users but only 80,000 Polish users you can immediately see why the software may not be up to par. Google Voice to Text, from my experiences, is bloody amazing for Chinese. My Chinese is abysmal (think "never gets the tone right") and for short phrases/sentences I've never had Google fail on me. Maybe it fails on larger sentences but it would be difficult for me to believe. Japanese is another language it does very well in. I can only count on one hand how many times it has made a mistake - and usually repeating myself a tad slower and with less slurring and it will pick it up just fine.
gambiting 10y ago
And interestingly, seeing challenges ahead, I don't think we will have 100% autonomous cars before 2050, if not later. 50 years ago, we were certain that perfect image recognition is just few months of work away, or at least enough money poured into it will solve the problem. It's 2016 and our best of the best image recognition algorithms can't even tell a zebra and a sofa in a zebra print apart. Since automatic cars are trying to solve the same problem I can't believe that in 2030 anyone will make 100% autonomous car, not a chance. Super advanced cruise control, like Tesla's autopilot, but better - sure, absolutely. But a car without a steering wheel? nope.
- eric_cc 10y ago
  People like you are the best because it really adds to the enjoyment of great achievements when there are a healthy amount of naysayers to point out. Thank you, naysayer.
- dlubarov 10y ago
  > It's 2016 and our best of the best image recognition algorithms can't even tell a zebra and a sofa in a zebra print apart. State of the art offline CNNs have been doing classification quite well recently, arguably better than humans. See the Inception-v3 paper: http://arxiv.org/pdf/1512.00567v3.pdf http://arxiv.org/pdf/1512.00567v3.pdf
  - argonaut 10y ago
    None of that changes the fact that they're easy to fool and have some pathological cases (that gambiting alludes to) that most humans consider quite dumb.

Fricken 10y ago

Both 2 years and 20 years are good estimates, depending on whether you're talking about a robocab that ferries people from their suburban homes to the train station when the weather is nice, or a vehicle that drive empty across the country in a snowstorm.

ethbro 10y ago

I think the bigger question is how you get straight to 4. Ford has resources, but I feel like they're betting against history here w/ regards to ML successes. Practical, reliable ML stems from enormous data sets. And I can't see a way of obtaining the necessary data volume other than sitting in Level 3 for a product cycle...

rhino369 10y ago
I think the evolution will be using self driving features as a pure backup safety feature until they get good enough to go fulltime on their own.

Animats 10y ago

NHTSA Level 3 ("Limited Self-Driving: Vehicles at this level of automation enable the driver to cede full control of all safety-critical functions under certain traffic or environmental conditions and in those conditions to rely heavily on the vehicle to monitor for changes in those conditions requiring transition back to driver control. The driver is expected to be available for occasional control, but with sufficiently comfortable transition time. The Google car is an example of limited self-driving automation.") is OK. That means that the self-driving system can recognize situations it can't handle (snow, potholes, crowds in streets) and come to a safe stop if the driver doesn't take over. It's Level 2 ("adaptive cruise control in combination with lane centering") that's the problem. Therein lies the deadly valley - good enough that the driver can tune out, but not good enough to handle trouble. That's where Tesla is. Level 2 with strongly enforced hands-on-wheel seems to be OK, but don't let the driver take their hands off for long periods.