5 ms·

Not sure if you have read the article, but it's actually about a company called WaveSense who claims to have developed ground-penetrating radar that can greatly

Not sure if you have read the article, but it's actually about a company called WaveSense who claims to have developed ground-penetrating radar that can greatly improve all weather autonomous driving. So yes, it's a daunting task but lot of people are working on it and progress is being made. I'd be interested to hear your counterargument.

gugagore 8y ago
That helps with localization only, right? Not with any other perceptual tasks?
YeGoblynQueenne 8y ago
>> I'd be interested to hear your counterargument. Not the OP, but like you say, the article is about a company who claims to have developed a technology that will solve self-driving cars' problems with rain. People in industry make claims all the time. People in the sciences do, too. Just because someone makes a claim, doesn't mean it's true. It's only a claim.
seibelj 8y ago
I’m not an expert in self driving car engineering. I have some experience with ML but not in a significant professional way. What I have is a decade of professional experience building all kinds of software and a skeptical eye. You have a problem that is unconstrained, with infinite variables, where even a simple mistake can have catastrophic outcomes. Society itself may object to self driving cars for a ton of reasons, from safety to simply driving like a grandma and slowing everything and everyone down. The cost to develop this technology, plus the added cost of hardware to each car, will be enormous and is not obviously a cost savings over a $15 per hour human. If the self driving car is doing anything other than getting from A to B, you still need a human (or a human-like robot) to handle the unloading / delivery / whatever at the end. Now, I’ve worked at companies with extremely talented and intelligent engineers, and something as constrained and seemingly simple as making a login form can take a long time to perfect - and no lives are at risk! Just imagine the challenges and requirements for building self driving cars. New hardware, software, real-time processing and analysis of tons of data, all to drive split-second decisions that can kill people if done incorrectly. Huge challenge - huge risks - huge money - uncertain payoff. This is not something that will appear suddenly. If there aren’t convoys of self driving trucks operating in desert highways overnight, where it’s dry and straight and flat and no one else is there, then we aren’t going to see city taxis for a very long time.
- bkirkby 8y ago
  But it doesn't have to be perfect, just has better than human drivers. That doesn't seem too difficult.
  - refurb 8y ago
    I think you’re underestimating the ability of even bad drivers to accurately process and react to new information while driving.
    - JibJabLab 8y ago
      I think you're also overestimating the abilities and self-restraint of drivers to not use their phones while driving, to look both ways, to not go too fast, etc.
  - seibelj 8y ago
    My thesis is that “better than human drivers” is an extremely difficult problem that even software professionals have massively underestimated the difficulty of. It may not even be possible to solve without something radical like banning human drivers or inserting electronic nodes directly into our roads and infrastructure to aid autonomous vehicles. The existence of human drivers might make the problem simply impossible to solve in a way acceptable to society.
    - klibertp 8y ago
      > even software professionals have massively underestimated the difficulty of. Software professionals are somewhat notorious for underestimating the difficulty of their projects. There's a massive amount of literature about that, proposing various techniques of mitigating this on a personal, team, or organization level. That being said, I think in this particular case the problem was more of an overestimation of what the ability to work with highly dimensional data (as in ML algorithms) can give you (and underestimating the practical problems of deploying the ML-based systems). Basically, people tried running 30+ years old algorithms on GPUs while feeding them the ungodly amounts of data and realized that, with sufficient horse-power, they can make them (finally) work (as in: do something genuinely useful). This built up a lot of hype, of which self-driving cars are just one offshoot, I think. Anyway, (if it's not evident from the above ;)) I find your arguments convincing and share your doubts. Self-driving cars are probably not impossible to achieve, but to get there we either need decades of research and progress or a couple of very high-profile breakthroughs in tech and theory. I won't hold my breath for neither :)
DoctorOetker 8y ago
I think it would be more succinct to describe WaveSense as ground penetrating radar for positioning purpouses. It's pretty orthogonal to autonomous driving which obviously would benefit from any extra position sensor, but it does not actually contribute autonomous driving.
rayiner 8y ago
The article supports his point. This is a press release for technology that may be many years from appearing in a production vehicle. It uses a sensor that isn’t included in the package of sensors used in other self driving vehicles, a package that’s already too expensive for consumer vehicles. Yet the technology seems to be necessary to handling a fairly common road condition.

gugagore 8y ago

That helps with localization only, right? Not with any other perceptual tasks?

YeGoblynQueenne 8y ago

>> I'd be interested to hear your counterargument. Not the OP, but like you say, the article is about a company who claims to have developed a technology that will solve self-driving cars' problems with rain. People in industry make claims all the time. People in the sciences do, too. Just because someone makes a claim, doesn't mean it's true. It's only a claim.

seibelj 8y ago

I’m not an expert in self driving car engineering. I have some experience with ML but not in a significant professional way. What I have is a decade of professional experience building all kinds of software and a skeptical eye. You have a problem that is unconstrained, with infinite variables, where even a simple mistake can have catastrophic outcomes. Society itself may object to self driving cars for a ton of reasons, from safety to simply driving like a grandma and slowing everything and everyone down. The cost to develop this technology, plus the added cost of hardware to each car, will be enormous and is not obviously a cost savings over a $15 per hour human. If the self driving car is doing anything other than getting from A to B, you still need a human (or a human-like robot) to handle the unloading / delivery / whatever at the end. Now, I’ve worked at companies with extremely talented and intelligent engineers, and something as constrained and seemingly simple as making a login form can take a long time to perfect - and no lives are at risk! Just imagine the challenges and requirements for building self driving cars. New hardware, software, real-time processing and analysis of tons of data, all to drive split-second decisions that can kill people if done incorrectly. Huge challenge - huge risks - huge money - uncertain payoff. This is not something that will appear suddenly. If there aren’t convoys of self driving trucks operating in desert highways overnight, where it’s dry and straight and flat and no one else is there, then we aren’t going to see city taxis for a very long time.

bkirkby 8y ago
But it doesn't have to be perfect, just has better than human drivers. That doesn't seem too difficult.
- refurb 8y ago
  I think you’re underestimating the ability of even bad drivers to accurately process and react to new information while driving.
  - JibJabLab 8y ago
    I think you're also overestimating the abilities and self-restraint of drivers to not use their phones while driving, to look both ways, to not go too fast, etc.
- seibelj 8y ago
  My thesis is that “better than human drivers” is an extremely difficult problem that even software professionals have massively underestimated the difficulty of. It may not even be possible to solve without something radical like banning human drivers or inserting electronic nodes directly into our roads and infrastructure to aid autonomous vehicles. The existence of human drivers might make the problem simply impossible to solve in a way acceptable to society.
  - klibertp 8y ago
    > even software professionals have massively underestimated the difficulty of. Software professionals are somewhat notorious for underestimating the difficulty of their projects. There's a massive amount of literature about that, proposing various techniques of mitigating this on a personal, team, or organization level. That being said, I think in this particular case the problem was more of an overestimation of what the ability to work with highly dimensional data (as in ML algorithms) can give you (and underestimating the practical problems of deploying the ML-based systems). Basically, people tried running 30+ years old algorithms on GPUs while feeding them the ungodly amounts of data and realized that, with sufficient horse-power, they can make them (finally) work (as in: do something genuinely useful). This built up a lot of hype, of which self-driving cars are just one offshoot, I think. Anyway, (if it's not evident from the above ;)) I find your arguments convincing and share your doubts. Self-driving cars are probably not impossible to achieve, but to get there we either need decades of research and progress or a couple of very high-profile breakthroughs in tech and theory. I won't hold my breath for neither :)

DoctorOetker 8y ago

I think it would be more succinct to describe WaveSense as ground penetrating radar for positioning purpouses. It's pretty orthogonal to autonomous driving which obviously would benefit from any extra position sensor, but it does not actually contribute autonomous driving.

rayiner 8y ago

The article supports his point. This is a press release for technology that may be many years from appearing in a production vehicle. It uses a sensor that isn’t included in the package of sensors used in other self driving vehicles, a package that’s already too expensive for consumer vehicles. Yet the technology seems to be necessary to handling a fairly common road condition.