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

electrek.co

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

#161

Post by vidarh »

argonaut wrote: post #138
vidarh wrote: post #64

Earlier quoted context omitted.

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.

You need humans to label those "millions of experiences." The bottleneck is not raw video. You need humans to label that data. Otherwise it's useless.

No, you don't. You need to process enough of it to see how the majority of human drivers act in situations where the automated system currently would react substantially differently.

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

#162

Post by mikeash »

aetherson wrote: post #134
mikeash wrote: post #116

Earlier quoted context omitted.

A huge number of traffic deaths are due to alcohol. An autonomous system that's as safe as a sober human would improve safety by a factor of 2 or 3. Many of the other deaths are due to distraction, inattention, or slow reaction times. Get rid of those and you can probably see an order of magnitude improvement with something that is nominally "no better than a human driver."

Would you (while sober) get into a car driven by an autonomous system that was demonstrably more likely to get into a crash than the average sober, awake, healthy driver, but less likely to get into a crash than the average driver? Honest question. I don't think I would.

Good question. It would depend on the exact numbers, I'd say. I do sometimes ride in (or drive) non-autonomous cars more dangerous than the best drivers, after all.

I don't know how relevant it will be, though. I suspect that the fact that computers are always attentive, can react instantly, and follow the rules consistently will make them much safer very quickly. But we shall see!

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

#164

Post by emcq »

tim333 wrote: post #97

The PX 2 is kind of a cool computer. 8 teraflops, 250W, liquid cooled. I imagine it would run a good bit less than that most of the time. 8 teraflops is about 8% of Moravecs estimate of brain equivalence so assuming you use ~8% of your brain driving it may be about right.

The brain doesn't do floating point operations. You're trying to compare apples to oranges.

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

#165

Post by wool_gather »

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…

> The success criteria for self driving cars is that they can drive at least as well, in the common case, as the set of human drivers who are defined to be "good" drivers. And self driving is not invalidated by a computer's mishandling of an event that a good driver would also mishandle.

This comes with one important caveat: these are the engineering criteria. The criteria of public perception, unfortunately, may not allow for a computer driver that makes the same mistakes that a human "would have", because people tend to mis-estimate what they or another human "would have" done.

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

#166

Post by Animats »

unfamiliar wrote: post #159
2bitencryption wrote: post #149

Earlier quoted context omitted.

Let me make sure I get this: When a Tesla (or other non-LIDAR) vehicle is driving, it is not continuously building a 3D model of its environment. Instead, it is matching patterns on the road, and "understanding" based off what it sees in an otherwise flat image. Whereas LIDAR vehicles use the LIDAR technology to develop a map of the world around them, for additional understanding?

No. They're both building a map and trying to place themselves in it. Using LIDAR makes this much easier to do.

It's not clear whether Tesla has a local map. They've never shown pictures of one, unlike Google. The Mobileye unit definitely does not; you can buy a Mobileye aftermarket unit and watch it put rectangles around things that look like cars and people. Tesla's radar probably just returns targets and range, like most first-generation automotive radars. Tesla's system may be entirely reactive.

Google builds maps; they do path planning, so they have to.

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

#168

Post by argonaut »

2bitencryption wrote: post #149
argonaut wrote: post #142

Earlier quoted context omitted.

Driving has almost nothing to do with image classification. * Humans implicitly perform SLAM (simulataneous localization and mapping). What do I mean? Look around your room. Close your eyes. Visualize the room. As a human, you've built a rough 3D model of the room. And if you keep your eyes open and walk through the room, that map is pretty fine-grained/detailed too and humans can keep track of where they are in the…

Let me make sure I get this: When a Tesla (or other non-LIDAR) vehicle is driving, it is not continuously building a 3D model of its environment. Instead, it is matching patterns on the road, and "understanding" based off what it sees in an otherwise flat image. Whereas LIDAR vehicles use the LIDAR technology to develop a map of the world around them, for additional understanding?

It's unclear if Tesla is building a 3D model or not. For the cameras, at least looking at Mobileeye's demos, it appears not. But Tesla also is using radar - it's unclear whether they're using the radar for just collision detection, or for building a full 3D map.

LIDAR gives you a 3D map of the surroundings, yes.

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

#169

Post by argonaut »

georgespencer wrote: post #160
argonaut wrote: post #145

Earlier quoted context omitted.

Great. Now the problem you've posed is no longer image classification. It's more like video classification or zero-shot classification! (neither of which are close to solved)

It doesn't seem like zero-shot classification to me. It still seems like image classification. You said: > What if every time Ford/GM/Toyota substantially changes the look of their cars, your classifier no longer recognizes them My answer was probably incomplete, but I took the above to mean that cosmetic changes to vehicles mean that classifiers no longer identify them as cars, and this detrimentally modifies the be…

"it moves at the speed a car moves at, it's in the road, it's overtaking on the right hand lane" is video classification, which is not solved. In fact, at least how you described it (you could probably change the problem statement to avoid this), this would involve an ML model that must learn a model of physics - also unsolved.

You've just specified a manually hardcoded set of decision rules. This is not machine learning, and is incredibly brittle.

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

#170

Post by argonaut »

vidarh wrote: post #161
argonaut wrote: post #138

Earlier quoted context omitted.

You need humans to label those "millions of experiences." The bottleneck is not raw video. You need humans to label that data. Otherwise it's useless.

No, you don't. You need to process enough of it to see how the majority of human drivers act in situations where the automated system currently would react substantially differently.

You've just described end-to-end-learning (e.g. the data is raw video/camera/radar/sensor data, the labels are steering angles, etc.)

No autonomous vehicle manufacturer uses end-to-end learning. The only one to claim to use it was Comma.ai, and we all know how that went.

All the autonomous car companies will manually label the camera images - e.g. given an image, draw boxes around where all the cars are.

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