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Your comment is just random hopeful assertions though... >It's why so much human labour has been automated. But how much human labour that is as complicated a

Your comment is just random hopeful assertions though... >It's why so much human labour has been automated. But how much human labour that is as complicated as driving has been automated? As far as I can tell automation is very, very bad when it needs to interact with humans who may behave unexpectedly. >b) we've gone from self-driving vehicles being a gleam in someone's eye to actual self-driving vehicles on public roads in less than 10 years. Inclement weather won't take another 10 years. >It's like you're completely ignoring the clear evidence of rapid advancement just because you think it's a hard problem, while the experts actually building these systems expect fully automated transportation fleets within 15 years. Actually plenty of experts within the field disagree with you. “I tell adult audiences not to expect it in their lifetimes. And I say the same thing to students,” he says. “Merely dealing with lighting conditions, weather conditions, and traffic conditions is immensely complicated. The software requirements are extremely daunting. Nobody even has the ability to verify and validate the software. I estimate that the challenge of fully automated cars is 10 orders of magnitude more complicated than [fully automated] commercial aviation.” Steve Shladover, transportation researcher at the University of California, Berkeley http://www.automobilemag.com/news/the-hurdles-facing-autonomous-vehicles/ http://www.automobilemag.com/news/the-hurdles-facing-autonom... With autonomous cars, you see these videos from Google and Uber showing a car driving around, but people have not taken it past 80 percent. It's one of those problems where it's easy to get to the first 80 percent, but it's incredibly difficult to solve the last 20 percent. If you have a good GPS, nicely marked roads like in California, and nice weather without snow or rain, it's actually not that hard. But guess what? To solve the real problem, for you or me to buy a car that can drive autonomously from point A to point B—it's not even close. There are fundamental problems that need to be solved. Herman Herman, Director of the National Robotics Engineering Center @ CMU https://motherboard.vice.com/en_us/article/d7y49y/robotics-lab-uber-gutted-says-driving-cars-are-not-even-close-carnegie-mellon-nrec https://motherboard.vice.com/en_us/article/d7y49y/robotics-l...

naasking 9y ago
> But how much human labour that is as complicated as driving has been automated? Driving is not complicated at its core. Travel along vectors that intersect at well-defined angles. Stop to avoid obstacles whose vectors intersect with yours. Sometimes those obstacles will intersect with your vector faster than you can stop, which is probably what happened to this woman. As long as the autonomous car was following the prescribed laws, then it's not at fault, and a human definitely would not have been able to stop either. > Merely dealing with lighting conditions, weather conditions, and traffic conditions is immensely complicated. The software requirements are extremely daunting. Which is why self-driving cars don't depend on visual light, and why prototypes are being tested in regions without inclement weather. Being on HN, I'm sure you're well familiar with the product development cycle: start with the easiest problem that does something useful, then generalize as needed. > With autonomous cars, you see these videos from Google and Uber showing a car driving around, but people have not taken it past 80 percent. It's one of those problems where it's easy to get to the first 80 percent, but it's incredibly difficult to solve the last 20 percent. If you have a good GPS, nicely marked roads like in California, and nice weather without snow or rain, it's actually not that hard. Right, so the experts agree with me that the problem the pilot projects are addressing is readily solvable, and that general deployment will take a number of years of further research, but isn't beyond our reach. This past year I've already read about sensors that can peer through ice and snow. 15 years is not at all out of the question.
- rohit2412 9y ago
  Driving isn't just travel along a vector. Maybe trains, but not urban roads. urban roads are full of people and animals. If a ball bounces in front of me, I slow down expecting a dog or a child running after it. No self driving car now, and in 30 years is going to be able to infer that. Driving is essentially interacting with the environment, reading hand signals from people, understanding intent of pedestrians, bicycles and other drivers. No way any AI can do that now.
  - naasking 9y ago
    > Driving isn't just travel along a vector. Maybe trains, but not urban roads. Trains travel along a straight line, not a vector in 2D space. > If a ball bounces in front of me, I slow down expecting a dog or a child running after it. No self driving car now, and in 30 years is going to be able to infer that. Incorrect. I don't know why you think humans are so special that they're the only system capable of inferring such correlations.
kamaal 9y ago
>>But how much human labour that is as complicated as driving has been automated? Quite a lot actually. These days you can produce food for several thousands of people using a few hundred people and plenty of machines. Part of the reason why we haven't yet reached a Malthusian catastrophe is this.
- carlmr 9y ago
  Automated food production is very much simpler, because you're usually only producing one food item at large scale. That's the super easy stuff to automate. Automated driving is more like a fully automated chef, that can create new dishes from what his clients tell him they like. Without the clients being able to properly express themselves. That's a lot more complicated than following a recipe. Difficulty of automation goes roughly trains < planes << cars. Automated trains are simple, but don't provide much value. Automating planes provided value because it's safer than just with human pilots. Automated cars are a different league of complexity.

naasking 9y ago

> But how much human labour that is as complicated as driving has been automated? Driving is not complicated at its core. Travel along vectors that intersect at well-defined angles. Stop to avoid obstacles whose vectors intersect with yours. Sometimes those obstacles will intersect with your vector faster than you can stop, which is probably what happened to this woman. As long as the autonomous car was following the prescribed laws, then it's not at fault, and a human definitely would not have been able to stop either. > Merely dealing with lighting conditions, weather conditions, and traffic conditions is immensely complicated. The software requirements are extremely daunting. Which is why self-driving cars don't depend on visual light, and why prototypes are being tested in regions without inclement weather. Being on HN, I'm sure you're well familiar with the product development cycle: start with the easiest problem that does something useful, then generalize as needed. > With autonomous cars, you see these videos from Google and Uber showing a car driving around, but people have not taken it past 80 percent. It's one of those problems where it's easy to get to the first 80 percent, but it's incredibly difficult to solve the last 20 percent. If you have a good GPS, nicely marked roads like in California, and nice weather without snow or rain, it's actually not that hard. Right, so the experts agree with me that the problem the pilot projects are addressing is readily solvable, and that general deployment will take a number of years of further research, but isn't beyond our reach. This past year I've already read about sensors that can peer through ice and snow. 15 years is not at all out of the question.

rohit2412 9y ago
Driving isn't just travel along a vector. Maybe trains, but not urban roads. urban roads are full of people and animals. If a ball bounces in front of me, I slow down expecting a dog or a child running after it. No self driving car now, and in 30 years is going to be able to infer that. Driving is essentially interacting with the environment, reading hand signals from people, understanding intent of pedestrians, bicycles and other drivers. No way any AI can do that now.
- naasking 9y ago
  > Driving isn't just travel along a vector. Maybe trains, but not urban roads. Trains travel along a straight line, not a vector in 2D space. > If a ball bounces in front of me, I slow down expecting a dog or a child running after it. No self driving car now, and in 30 years is going to be able to infer that. Incorrect. I don't know why you think humans are so special that they're the only system capable of inferring such correlations.

kamaal 9y ago

>>But how much human labour that is as complicated as driving has been automated? Quite a lot actually. These days you can produce food for several thousands of people using a few hundred people and plenty of machines. Part of the reason why we haven't yet reached a Malthusian catastrophe is this.

carlmr 9y ago
Automated food production is very much simpler, because you're usually only producing one food item at large scale. That's the super easy stuff to automate. Automated driving is more like a fully automated chef, that can create new dishes from what his clients tell him they like. Without the clients being able to properly express themselves. That's a lot more complicated than following a recipe. Difficulty of automation goes roughly trains < planes << cars. Automated trains are simple, but don't provide much value. Automating planes provided value because it's safer than just with human pilots. Automated cars are a different league of complexity.