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Karpathy is great at presenting executive-101. However self-driving is much much more than image classification. You have a time component, you need to integra

Karpathy is great at presenting executive-101. However self-driving is much much more than image classification. You have a time component, you need to integrate information as it comes in to meaningful state (aka SLAM) and make sequential decisions that has potential to kill people. This is still unsolved research problem unlike punny ImageNet classification. Karpathy could have easily spent entire day talking about current state of the art and how they have improved on it but instead we got Deep Learning 101. I hope he didn't intentionally used this tactic to avoid talking about the elephant in the room. It seems they are hell bent on vision-based end-to-end learning which vast majority of experts would agree that is far away in the future. So this whole thing is quite bold and if they really make this happen in 1yr3mo then I'd say you should dump your entire 401K in buying Tesla stock. Collecting data is actually more trivial part of this problem.

p1esk 8y ago
This is still unsolved research problem Luckily, Karpathy is pretty good at solving research problems. Karpathy could have easily spent entire day talking about current state of the art and how they have improved on it Why would he do that? To help Uber? Collecting data is actually more trivial part of this problem. For Tesla, yes. For all others that’s the hardest part.
- eanzenberg 8y ago
  Maybe when Tesla cars stop driving into medians at full speed...
- adrianmonk 8y ago
  When they say that collecting data is the trivial part, they mean that (in comparison to the other parts of the problem) it is easy for everyone to solve. In other words, they are saying Tesla has an advantage in area that doesn't matter.
  - tomp 8y ago
    It’s “easy” in the sense that reusable rockets are “easy” - they’re possible, but noone else is working on them. Musk was way ahead of time, again.
- Upvoter33 8y ago
  > Luckily, Karpathy is pretty good at solving research problems. Oh come on - there are a lot of people good at solving research problems, but hard problems remain unsolved. To pretend driving autonomously in the real world is anything but very very hard is naive.
alyx 8y ago
Good overview, I share your opinion. Tesla is betting BIG on NNs. In the presentation they say that we have NNs in our brain. Which is why we can look at one photo of a dog, and distill enough identifying information in order to spot the breed from then on. Training sample of 1. Curiously though, they than say that NNs don't work like our brains do, and require A LOT of training data from all angles, etc. Training sample of N. The presentation doesn't actually show, how they plan to train a single NN to encompass all the knowledge for self driving. In particular, the looooooong tail. But maybe they'll have independent models, say based on "observed" conditions, which swap in and out ... based on more NN logic. But at the end of the day, there is no known (to me) examples, of NNs even approaching human ability. Tesla is bascially hoping we will believe, they will be the first to show this capability of NNs. Let's wait and see, 2020 is not that far away.
- monk_e_boy 8y ago
  > require A LOT of training data from all angles Also, we learn things outside of our cars. I ride a bike, this gives me insight into what bike riders will do on the road. I have kids, so I know a kid on the pavement will be more risky / unpredictable than an adult. I drove down a single track road today and met another car coming towards me. We stopped, then he started to reverse, there was a passing place behind him. Another car pulled up behind him, so I then reversed back into a field to let the cars past. This sort of thing happened maybe six times today as I drove around. Not at all surprising, not even noteworthy enough for any of the drivers to acknowledge even a flick of the finger in thanks. Just part of driving here.
  - xkcd-sucks 8y ago
    Hmm maybe the problem is actually interacting with humans naturally, on the road, so self-driving is really human-style general AI
    - threeseed 8y ago
      This is actually the aspect that really doesn't get discussed enough. Imagine these scenarios: a) Roadworks and a guy tells you to stop or waves you through. Or asks you to drive slowly. Or points to a direction that he wants you to go. b) Woman on the side of the road is waving their arms about because her small child is crawling on the road trying to chase a toy. If self driving cars can't look another person in the eye and identity their intent then there are going to be a lot of unforeseen problems.
deleted 8y ago
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p1esk 8y ago

This is still unsolved research problem Luckily, Karpathy is pretty good at solving research problems. Karpathy could have easily spent entire day talking about current state of the art and how they have improved on it Why would he do that? To help Uber? Collecting data is actually more trivial part of this problem. For Tesla, yes. For all others that’s the hardest part.

eanzenberg 8y ago
Maybe when Tesla cars stop driving into medians at full speed...
adrianmonk 8y ago
When they say that collecting data is the trivial part, they mean that (in comparison to the other parts of the problem) it is easy for everyone to solve. In other words, they are saying Tesla has an advantage in area that doesn't matter.
- tomp 8y ago
  It’s “easy” in the sense that reusable rockets are “easy” - they’re possible, but noone else is working on them. Musk was way ahead of time, again.
Upvoter33 8y ago
> Luckily, Karpathy is pretty good at solving research problems. Oh come on - there are a lot of people good at solving research problems, but hard problems remain unsolved. To pretend driving autonomously in the real world is anything but very very hard is naive.

alyx 8y ago

Good overview, I share your opinion. Tesla is betting BIG on NNs. In the presentation they say that we have NNs in our brain. Which is why we can look at one photo of a dog, and distill enough identifying information in order to spot the breed from then on. Training sample of 1. Curiously though, they than say that NNs don't work like our brains do, and require A LOT of training data from all angles, etc. Training sample of N. The presentation doesn't actually show, how they plan to train a single NN to encompass all the knowledge for self driving. In particular, the looooooong tail. But maybe they'll have independent models, say based on "observed" conditions, which swap in and out ... based on more NN logic. But at the end of the day, there is no known (to me) examples, of NNs even approaching human ability. Tesla is bascially hoping we will believe, they will be the first to show this capability of NNs. Let's wait and see, 2020 is not that far away.

monk_e_boy 8y ago
> require A LOT of training data from all angles Also, we learn things outside of our cars. I ride a bike, this gives me insight into what bike riders will do on the road. I have kids, so I know a kid on the pavement will be more risky / unpredictable than an adult. I drove down a single track road today and met another car coming towards me. We stopped, then he started to reverse, there was a passing place behind him. Another car pulled up behind him, so I then reversed back into a field to let the cars past. This sort of thing happened maybe six times today as I drove around. Not at all surprising, not even noteworthy enough for any of the drivers to acknowledge even a flick of the finger in thanks. Just part of driving here.
- xkcd-sucks 8y ago
  Hmm maybe the problem is actually interacting with humans naturally, on the road, so self-driving is really human-style general AI
  - threeseed 8y ago
    This is actually the aspect that really doesn't get discussed enough. Imagine these scenarios: a) Roadworks and a guy tells you to stop or waves you through. Or asks you to drive slowly. Or points to a direction that he wants you to go. b) Woman on the side of the road is waving their arms about because her small child is crawling on the road trying to chase a toy. If self driving cars can't look another person in the eye and identity their intent then there are going to be a lot of unforeseen problems.

deleted 8y ago

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