4 ms·
Yeah-- they are qualitatively different. I didn't want to cloud the question with this point, but data from a machine driver mistake can be used to train every
by fattire 8y ago
Yeah-- they are qualitatively different.
I didn't want to cloud the question with this point, but data from a machine driver mistake can be used to train every other machine driver and make it better. While much can till be learned from the mistake made by a human driver, the error is not as likely to be minimized across the 'fleet' in the same way as it is for a machine driver, if that makes sense.
Also it's probably important to keep in mind-- if my undestanding is correct-- companies like Tesla are only using neural nets for situational awareness-- to understand the car's position in space and in relation to the identified objects, paths, and obstacles around it. The actual logic related to the car's operation/behavior within that space is via traditional programming. So it's not quite a black box in terms of understanding why the car decided to act in a particular way-- it may be that something in the world was miscategorized or otherwise sensed incorrectly, which could be addressed (via better training/validation, etc.). Or it could be that it understood the world around it but took the wrong action, which could also be addressed (via traditional programming).
If I'm wrong about that, I'm sure someone will chime in. (please do!)
- magduf 8y ago>While much can till be learned from the mistake made by a human driver, the error is not as likely to be minimized across the 'fleet' in the same way as it is for a machine driver, if that makes sense. This is some serious whitewashing here. It's not "unlikely", it's simply not going to happen at all. People have been killing innocents by drunk driving for decades now, so they obviously still haven't learned. They continually make the same mistakes, over and over. No, human drivers do not learn at all from each other's mistakes in any significant fashion. This could be changed, if we as a society wanted it to. We could mandate serious driver training (like what they do in Germany), and also periodic retraining. Putting people in simulators and test tracks and teaching them how to handle various situations, using the latest findings, would save a lot of lives. But we choose not to do this because it's expensive and we just don't care that much; we think that driving is some kind of inherent human right and it's very hard for people to lose that privilege in this country. And it doesn't help that not being able to drive equates to being very difficult to survive in much of the US thanks to a lack of public transit options.
- imtringued 8y ago>They continually make the same mistakes, over and over. No, human drivers do not learn at all from each other's mistakes in any significant fashion. Why do you assume that drivers have to learn from each other's mistakes? A drunk driver learning from his own mistakes is already significantly ahead of what a self driving car does which potentially just repeats the same mistake over and over again. The correlated risk may even cause accidents in bursts. 10 self driving cars all doing the same mistake at the same time will cause even more damage than just a single one.
- magduf 8y ago>Why do you assume that drivers have to learn from each other's mistakes? Because that's what computers do: we can program them to avoid a mistake once we know about it, and then ALL cars will never make that mistake again. The same isn't true with humans: they keep making the same stupid mistakes. >A drunk driver learning from his own mistakes is already significantly ahead of what a self driving car does which potentially just repeats the same mistake over and over again Why do you think this? You're assuming the car's software will never be updated, which is completely nonsensical. >10 self driving cars all doing the same mistake at the same time will cause even more damage than just a single one. Only in the short term. As soon as they're updated to avoid that mistake, it never happens again. Hum