Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

electrek.co

Post reply on HN
Print view View original

71–80 of 174 posts

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#71

Post by Houshalter »

tedunangst wrote: post #50
ChuckMcM wrote: post #45

Earlier quoted context omitted.

The argument reasoning I've heard goes like this; People drive reasonably well using vision primarily and with imperfect visibility of their environment. Computer learning networks can classify imagery at least as accurately as humans and sometimes more so. A computer using imagery that is well classified from an array of visual sensors with near perfect visibility should be able to drive as well, or better, than a h…

ML seems pretty bad at classifying things it hasn't seen before though. There are quite a few examples where an input outside the training data resulted in misclassification. Humans may not always see a white truck in a snowstorm, but is computer vision going to see it either? Or will it pattern match the few visible parts as something else entirely? Or dismiss the truck entirely as noise?

Classification is not the right metric to use here. Lidar doesn't classify the objects it's looking it, it just tells you the direction and distance.

Cameras can also gauge distance pretty effectively from parallax. Either using multiple cameras, or from the motion of the vehicle itself, or both. From this it should be possible to gauge where obstacles are and drive safely.

But NNs give the possibility of gathering much more information from recognizing objects. Information that Lidar systems don't have.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#72

Post by dogma1138 »

mattnewton wrote: post #59
dogma1138 wrote: post #53

Earlier quoted context omitted.

>I'm not a big fan of $150K high-end servers filled with $5000 GPUs that can be bested with clever code on a $25K server fill with $1200 consumer GPUs. But I am a huge fan of charging what you can while you are unopposed. It's just that I think that state is temporary. There is virtually not a single "enterprise" grade product which can't be made at least 50% cheaper (or sometimes 10 times...) with off the shelf cons…

I don't understand your argument, so maybe this is off base, but if you are saying people in industry aren't replacing their supercomputers with commodity gpu's, you're wrong; both apple and google have massive purchase orders for commodity nvidia gpus because they aren't just cheaper, they are better at this application. And I imagine other companies are as well. Edit: "replace" is probably not the right word, this…

They aren't buying consumer GPU's they aren't buying the NVIDIA dedicated servers, but they aren't running Geforce chips either.

If nothing else is that because you cannot virtualize Geforce line GPU's, there is no CUDA Direct or NVLINK support etc.

If you are telling me that Google is buying Geforce GPU's and flashing the bios with a custom bios ripped off a Quadro card so they can do PCIe passthrough in a hypervisor and initialize the cards then sorry not buying it.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#73

Post by visarga »

tedunangst wrote: post #50
ChuckMcM wrote: post #45

Earlier quoted context omitted.

The argument reasoning I've heard goes like this; People drive reasonably well using vision primarily and with imperfect visibility of their environment. Computer learning networks can classify imagery at least as accurately as humans and sometimes more so. A computer using imagery that is well classified from an array of visual sensors with near perfect visibility should be able to drive as well, or better, than a h…

ML seems pretty bad at classifying things it hasn't seen before though. There are quite a few examples where an input outside the training data resulted in misclassification. Humans may not always see a white truck in a snowstorm, but is computer vision going to see it either? Or will it pattern match the few visible parts as something else entirely? Or dismiss the truck entirely as noise?

> Humans may not always see a white truck in a snowstorm, but is computer vision going to see it either?

So you put in your training and test dataset a bunch of such situations. At some point you've covered enough cases to extrapolate the rest.

Good testing is going to hunt for these blind spots and fix them. Fact is that it's already safer than humans, even with all its hidden imperfections.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#74

Post by visarga »

ChuckMcM wrote: post #55
tedunangst wrote: post #50

Earlier quoted context omitted.

ML seems pretty bad at classifying things it hasn't seen before though. There are quite a few examples where an input outside the training data resulted in misclassification. Humans may not always see a white truck in a snowstorm, but is computer vision going to see it either? Or will it pattern match the few visible parts as something else entirely? Or dismiss the truck entirely as noise?

I don't disagree, both humans and ML are bad at classifying things they haven't seen before[1]. However that reasoning doesn't disqualify either vision only auto driving systems or machine learning. Both statements are true: "Computer driven cars may crash, even fatally, when they encounter a situation that they do not recognize." and "People driving cars may crash, even fatally, when they encounter a situation that…

There is a difference though - humans understand the surrounding state, computer vision is not quite there. It can recognize things, and in NVIDIA's case directly generates steering commands without going through the intermediate step of building a model.

Humans build models of the world, and such models allow us to predict the future to a little extent, and explain the reasons behind a situation. Humans can intuit the intentions of other drivers and the behavior of other objects. AI can't do that quite as well.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#75

Post by k_lander »

ChuckMcM wrote: post #45
Animats wrote: post #20

I'm still not happy with self-driving on vision alone, or vision augmented with radar. There are too many hard cases for vision. Everybody who has good self-driving right now - Google, Otto, Volvo, GM - uses LIDAR. Self-driving is coming to the first end users in 2017, in Volvo's test of 100 vehicles. Volvo has multiple LIDARs, multiple radars, multiple cameras, redundant computers, and redundant actuators. They're b…

The argument reasoning I've heard goes like this; People drive reasonably well using vision primarily and with imperfect visibility of their environment. Computer learning networks can classify imagery at least as accurately as humans and sometimes more so. A computer using imagery that is well classified from an array of visual sensors with near perfect visibility should be able to drive as well, or better, than a h…

article from yesterday:

http://spectrum.ieee.org/cars-that-think/transportation/sens...

hopefully this will make LIDAR more economically practical

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#76

Post by visarga »

ChuckMcM wrote: post #63
mattnewton wrote: post #58

Earlier quoted context omitted.

Why not shoot for better than human performance and "cheat" any way possible along the way? To paraphrase a quote I can't remember by who, do we care if a submarine "swims"? Besides, with even with lidar, the problem is hard enough.

I agree, being better than human is a sales point that I expect to see in brochures. One of the ways I would expect that plays out is self driving transport cars for high value targets like world leaders and drug lords. "This car will respond faster, and more accurately, to get you to safety before a human driver even knew there was a problem." That said, John stated that without LIDAR you couldn't adequately meet th…

> One way to evaluate how far the image processing pipeline has come is to look at research on how well it can classify images. And in that space, in the research, it is doing better than humans.

Well, computer vision is doing better than humans on the ImageNet dataset, that does not mean it is better than human on a driving image dataset.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#78

Post by philjohn »

ChuckMcM wrote: post #45
Animats wrote: post #20

I'm still not happy with self-driving on vision alone, or vision augmented with radar. There are too many hard cases for vision. Everybody who has good self-driving right now - Google, Otto, Volvo, GM - uses LIDAR. Self-driving is coming to the first end users in 2017, in Volvo's test of 100 vehicles. Volvo has multiple LIDARs, multiple radars, multiple cameras, redundant computers, and redundant actuators. They're b…

The argument reasoning I've heard goes like this; People drive reasonably well using vision primarily and with imperfect visibility of their environment. Computer learning networks can classify imagery at least as accurately as humans and sometimes more so. A computer using imagery that is well classified from an array of visual sensors with near perfect visibility should be able to drive as well, or better, than a h…

One of the central tenets of autonomous vehicles should be that they are BETTER than any human driver could be. Relying on vision because, well, it works OK for humans doesn't cut it in my book.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#79

Post by philjohn »

visarga wrote: post #74
ChuckMcM wrote: post #55

Earlier quoted context omitted.

I don't disagree, both humans and ML are bad at classifying things they haven't seen before[1]. However that reasoning doesn't disqualify either vision only auto driving systems or machine learning. Both statements are true: "Computer driven cars may crash, even fatally, when they encounter a situation that they do not recognize." and "People driving cars may crash, even fatally, when they encounter a situation that…

There is a difference though - humans understand the surrounding state, computer vision is not quite there. It can recognize things, and in NVIDIA's case directly generates steering commands without going through the intermediate step of building a model. Humans build models of the world, and such models allow us to predict the future to a little extent, and explain the reasons behind a situation. Humans can intuit t…

Also, making eye contact and being waved through. Humans are excellent at reading cues such as this.

Re: Nvidia on new self-driving system: “basically 5 years ahead and coming in 2017”

#80

Post by jaffa214525 »

vidarh wrote: post #64
tedunangst wrote: post #50

Earlier quoted context omitted.

ML seems pretty bad at classifying things it hasn't seen before though. There are quite a few examples where an input outside the training data resulted in misclassification. Humans may not always see a white truck in a snowstorm, but is computer vision going to see it either? Or will it pattern match the few visible parts as something else entirely? Or dismiss the truck entirely as noise?

But the computer vision systems can be endlessly improved and merge experience from millions of cars, while human drivers accumulate experience from a single driver, age, and are eventually replaced by younger, inexperienced drivers. Soon enough these systems will have data from encounters with far more varied situations than any single human will ever be physically able to encounter in a lifetime.

Not sure I see how that would work when there is no 3G signal. If a computer on-board a vehicle sees something it does not recognize when it's not connected to the Tesla HQ, what should it do? And even if it is connected, uploading video over 3G is too slow for the real-time classification needs. Right?
Post reply on HN