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You’re defining solid-engineering funny. You need a mass amount of data to train on. How do you get that? Its an engineering or a business problem, depending h

You’re defining solid-engineering funny. You need a mass amount of data to train on. How do you get that? Its an engineering or a business problem, depending how how you look at it - how do you get a ton of people driving for you? Tesla has the better business model here. That leads to more data, which is the most important factor in training. Now, google is orders of magnitude bigger and had a huge head start, perhaps they brute force their way to the lead. But being more conservative != better engineering. You could philosophically disagree with many things Tesla is doing, but in terms of solving self driving cars I think they have the better strategy that gives their engineers the data they need. Tesla is in the real world recording every car they sell through vastly more dynamic scenario/terrain. That’s smart engineering.

sumedh 6y ago
> But being more conservative != better engineering. Isn't being conservative better when your technology can kill people?
- nwienert 6y ago
  Sure, but that’s a moral problem not an engineering one.
  - _se 6y ago
    Yeah... Real engineers would call that an engineering problem. Like the kind who have stamps that can cost or preserve lives. You're just showcasing the immaturity of most software "engineers", yourself included.
    - nwienert 6y ago
      Oh boy, a real engineer is here to tell the immature ones what’s what. First, you made a huge assumption. I never said I approve of how they are doing it. Engineering at the highest level encompasses morality, obviously. But you wooshed real hard on the context of this thread in your rush to get that sweet feeling of moral superiority. I’ll rewind it for you. I was replying to someone claiming they hope Google delivers self-driving first because they see them as executing better at the engineering portion of doing so. Do you see now? If they had said they see them as engineering more ethically and so they hope they win, fine. But they didn’t. Read it again. The context is: is Google’s engineering strategy going to deliver self-driving first? I replied to that. I even called out that you can totally disagree on moral grounds, and I do disagree with much of what they do, so it’s funny to call me out on something I was leaving purposely open as a further topic to discuss. But the context was who would deliver self-driving faster, due strictly to their engineering strategy, I made the case that real world data trumps artificial data. And it does.
  - CharlesW 6y ago
    > Sure, but that’s a moral problem not an engineering one. I'm pretty sure "don't kill user" is not only an engineering requirement, but the most important one.
    - deleted 6y ago
      [deleted]
  - heavyset_go 6y ago
    When a civil engineer designs a structure that fails and kills people, not only are they held liable for the deaths, they stand to lose their licenses. In civil engineering, there is a culture of ensuring it never happens again after engineers design something that kills. Who at Tesla was held liable for designing a system that failed and resulted in death? Who at Tesla lost their licenses in the wake of deaths caused by their self-driving systems? Where is the culture of ensuring that their cars don't kill anyone again?
    - nwienert 6y ago
      These are great questions and I’m glad you’re bringing ethics in. But the parent posters context was that the “solid engineering” by google === faster delivery. I think that’s backwards. If you are an advocate of being more conservative with engineering to be safer - then you can’t have your cake and eat it too, you should hope it goes slowly. That’s literally the whole point. I’ll be the first to criticize Tesla for the shoddy, dangerously worded rollout of Autopilot. Totally. Has it saved more lives than lost? Who knows. But to argue that googles more conservative approach should somehow deliver FSD faster is just a contradiction. Perhaps they brute force it like I said already. But the fast rollout by Tesla == more dangerous == more data. If you’re talking engineering delivery time, then yea Tesla is taking a calculated risk of getting much more data much faster. They should be able to deliver faster, engineering-wise.
- Retric 6y ago
  Self driving can and likely will eventually save lives. The medical world deals with the same basic issue constantly and neither reckless behavior or extreme caution is the answer. At best you can model how much of a reduction in the 1.35 million people die in road accidents worldwide every year / 3,700 deaths a day offsets moving more quickly. If we are talking an eventual 10% reduction waiting just 1 year costs ~130,000 lives. On the other hand if mistakes slows long term adoption that’s also harmful. PS: Adoption curves etc are also import, but that’s what I mean by mistakes slowing adoption.
  - heavyset_go 6y ago
    > Self driving can and likely will eventually save lives. And yet there is no evidence of these assertions other than wishful thinking. There is no evidence that self-driving systems are safer than humans, so there is no reason to treat them as if they are. In fact, compared to other luxury vehicles, Tesla vehicles are involved in more accidents. The medical world is extremely conservative. The FDA has incredibly high standards to meet, thankfully, and demands ample scientific evidence for the medicines and treatments it approves. "Move fast and break things" doesn't exist in the medical world, but it does exist outside of it in the form of unregulated supplements and illegal procedures and distribution of medication. People are routinely made into victims of this market just so someone can make a quick buck.
    - Retric 6y ago
      If we knew the results it wouldn’t be research. Medical research is dealing with potential future solutions to known problems. The risk is from a drug that’s either useless or actively harmful. Saying we don’t know if self driving cars are eventually going to be better is therefore no different than considering a new vaccine. Anyway, move fast and break things is ingrained into the core of the medical profession when there is an unmet medical need. The FDA for example has: Accelerated Approval, Fast track designation, Breakthrough therapy designation, and Priority Review all designed to speed things up when the benefits are significant. They don’t apply for new pain medication because the risk vs reward is very different. 2014: https://www.fda.gov/media/94063/download https://www.fda.gov/media/94063/download PS: I think we can agree that in terms of car safety there is clearly a large unmet need. That’s not to say self driving is the solution, just that it’s a serious contender.
lern_too_spel 6y ago
Is Tesla really sending all that camera data off the cars? That doesn't sound plausible.
- jayd16 6y ago
  In theory they could train the model in a distributed way on the cars themselves.
  - mlindner 6y ago
    No this isn't really possible. The computation required for training is extensive compared to the computation required for simply running the system.
    - etaioinshrdlu 6y ago
      I disagree, federated learning is a very valid approach. The cars have a ton of computational power especially with HW3. (Although I think they don't have high precision floating point - the chips are for inference) Federated learning is a lot like distributed training of a neural network. The trouble with distributed training is that it's not as fast to converge as simply running more training steps. It is basically like increasing the batch size. Also, it sounds like a general hassle for Tesla to use federated learning. I believe they need to be carefully auditing and labelling their training data for almost all their tasks. Perhaps some like depth-estimation don't require labelled data.
      - Gravityloss 6y ago
        You could train and exchange data while charging. "You are the product."
- mlindner 6y ago
  It's not live streaming all the data. They have an independently running AI that looks for events/problems and streams problematic areas. The cars do this by default.
etaioinshrdlu 6y ago
I don't think it is completely a foregone conclusion that self-driving is even that much of an ML problem. It might be possible to handle steering, navigation, obstacle and accident avoidance purely with non-ML approaches. Then ML could be left to less safety critical features such as predicting the types of obstacles surrounding it, and their likely next moves. LIDAR (gasp!) might even help make the problem much easier. So no, I don't think that just saying you have more data is the end of the story. It's certainly AN approach, and maybe a good one, but I don't think you can conclude their engineering is better because of it.
- mlindner 6y ago
  Tesla used to have non-ML approaches for most of their systems but they've been gradually replacing all their non-ML systems with ML systems.
gamblor956 6y ago
As ML has demonstrated, more data doesn't mean better data. Tesla wins got having the most data about driving in the Bay Area. And not so much for driving anywhere else, or in bad weather, or on bad roads, or on highways where trucks may cross both lanes of traffic.
- deleted 6y ago
  [deleted]
- nwienert 6y ago
  Tesla’s are all over the world, how are you claiming they only operate in the Bay Area? It’s Google who is far less spread out.
deleted 6y ago
[deleted]

sumedh 6y ago

> But being more conservative != better engineering. Isn't being conservative better when your technology can kill people?

nwienert 6y ago
Sure, but that’s a moral problem not an engineering one.
- _se 6y ago
  Yeah... Real engineers would call that an engineering problem. Like the kind who have stamps that can cost or preserve lives. You're just showcasing the immaturity of most software "engineers", yourself included.
  - nwienert 6y ago
    Oh boy, a real engineer is here to tell the immature ones what’s what. First, you made a huge assumption. I never said I approve of how they are doing it. Engineering at the highest level encompasses morality, obviously. But you wooshed real hard on the context of this thread in your rush to get that sweet feeling of moral superiority. I’ll rewind it for you. I was replying to someone claiming they hope Google delivers self-driving first because they see them as executing better at the engineering portion of doing so. Do you see now? If they had said they see them as engineering more ethically and so they hope they win, fine. But they didn’t. Read it again. The context is: is Google’s engineering strategy going to deliver self-driving first? I replied to that. I even called out that you can totally disagree on moral grounds, and I do disagree with much of what they do, so it’s funny to call me out on something I was leaving purposely open as a further topic to discuss. But the context was who would deliver self-driving faster, due strictly to their engineering strategy, I made the case that real world data trumps artificial data. And it does.
- CharlesW 6y ago
  > Sure, but that’s a moral problem not an engineering one. I'm pretty sure "don't kill user" is not only an engineering requirement, but the most important one.
  - deleted 6y ago
    [deleted]
- heavyset_go 6y ago
  When a civil engineer designs a structure that fails and kills people, not only are they held liable for the deaths, they stand to lose their licenses. In civil engineering, there is a culture of ensuring it never happens again after engineers design something that kills. Who at Tesla was held liable for designing a system that failed and resulted in death? Who at Tesla lost their licenses in the wake of deaths caused by their self-driving systems? Where is the culture of ensuring that their cars don't kill anyone again?
  - nwienert 6y ago
    These are great questions and I’m glad you’re bringing ethics in. But the parent posters context was that the “solid engineering” by google === faster delivery. I think that’s backwards. If you are an advocate of being more conservative with engineering to be safer - then you can’t have your cake and eat it too, you should hope it goes slowly. That’s literally the whole point. I’ll be the first to criticize Tesla for the shoddy, dangerously worded rollout of Autopilot. Totally. Has it saved more lives than lost? Who knows. But to argue that googles more conservative approach should somehow deliver FSD faster is just a contradiction. Perhaps they brute force it like I said already. But the fast rollout by Tesla == more dangerous == more data. If you’re talking engineering delivery time, then yea Tesla is taking a calculated risk of getting much more data much faster. They should be able to deliver faster, engineering-wise.
Retric 6y ago
Self driving can and likely will eventually save lives. The medical world deals with the same basic issue constantly and neither reckless behavior or extreme caution is the answer. At best you can model how much of a reduction in the 1.35 million people die in road accidents worldwide every year / 3,700 deaths a day offsets moving more quickly. If we are talking an eventual 10% reduction waiting just 1 year costs ~130,000 lives. On the other hand if mistakes slows long term adoption that’s also harmful. PS: Adoption curves etc are also import, but that’s what I mean by mistakes slowing adoption.
- heavyset_go 6y ago
  > Self driving can and likely will eventually save lives. And yet there is no evidence of these assertions other than wishful thinking. There is no evidence that self-driving systems are safer than humans, so there is no reason to treat them as if they are. In fact, compared to other luxury vehicles, Tesla vehicles are involved in more accidents. The medical world is extremely conservative. The FDA has incredibly high standards to meet, thankfully, and demands ample scientific evidence for the medicines and treatments it approves. "Move fast and break things" doesn't exist in the medical world, but it does exist outside of it in the form of unregulated supplements and illegal procedures and distribution of medication. People are routinely made into victims of this market just so someone can make a quick buck.
  - Retric 6y ago
    If we knew the results it wouldn’t be research. Medical research is dealing with potential future solutions to known problems. The risk is from a drug that’s either useless or actively harmful. Saying we don’t know if self driving cars are eventually going to be better is therefore no different than considering a new vaccine. Anyway, move fast and break things is ingrained into the core of the medical profession when there is an unmet medical need. The FDA for example has: Accelerated Approval, Fast track designation, Breakthrough therapy designation, and Priority Review all designed to speed things up when the benefits are significant. They don’t apply for new pain medication because the risk vs reward is very different. 2014: https://www.fda.gov/media/94063/download https://www.fda.gov/media/94063/download PS: I think we can agree that in terms of car safety there is clearly a large unmet need. That’s not to say self driving is the solution, just that it’s a serious contender.

lern_too_spel 6y ago

Is Tesla really sending all that camera data off the cars? That doesn't sound plausible.

jayd16 6y ago
In theory they could train the model in a distributed way on the cars themselves.
- mlindner 6y ago
  No this isn't really possible. The computation required for training is extensive compared to the computation required for simply running the system.
  - etaioinshrdlu 6y ago
    I disagree, federated learning is a very valid approach. The cars have a ton of computational power especially with HW3. (Although I think they don't have high precision floating point - the chips are for inference) Federated learning is a lot like distributed training of a neural network. The trouble with distributed training is that it's not as fast to converge as simply running more training steps. It is basically like increasing the batch size. Also, it sounds like a general hassle for Tesla to use federated learning. I believe they need to be carefully auditing and labelling their training data for almost all their tasks. Perhaps some like depth-estimation don't require labelled data.
    - Gravityloss 6y ago
      You could train and exchange data while charging. "You are the product."
mlindner 6y ago
It's not live streaming all the data. They have an independently running AI that looks for events/problems and streams problematic areas. The cars do this by default.

etaioinshrdlu 6y ago

I don't think it is completely a foregone conclusion that self-driving is even that much of an ML problem. It might be possible to handle steering, navigation, obstacle and accident avoidance purely with non-ML approaches. Then ML could be left to less safety critical features such as predicting the types of obstacles surrounding it, and their likely next moves. LIDAR (gasp!) might even help make the problem much easier. So no, I don't think that just saying you have more data is the end of the story. It's certainly AN approach, and maybe a good one, but I don't think you can conclude their engineering is better because of it.

mlindner 6y ago
Tesla used to have non-ML approaches for most of their systems but they've been gradually replacing all their non-ML systems with ML systems.

gamblor956 6y ago

As ML has demonstrated, more data doesn't mean better data. Tesla wins got having the most data about driving in the Bay Area. And not so much for driving anywhere else, or in bad weather, or on bad roads, or on highways where trucks may cross both lanes of traffic.

deleted 6y ago
[deleted]
nwienert 6y ago
Tesla’s are all over the world, how are you claiming they only operate in the Bay Area? It’s Google who is far less spread out.

deleted 6y ago

[deleted]