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> The power questions also aren't cut and dry: if you need extra in-vehicle GPUs to support the radar+camera approach, you may well be using more power than a l

• joshuamorton 7y ago
  > All current lidar-based approaches I'm aware of also supplement with radar+cameras. LIDAR isn't sufficient in isolation. GPUs consume way too much power, there's no way you can cavalierly just add more of them as a scaling solution. Yes, but they don't need to get point-cloud level spacial data from a suite of cameras. That takes more compute power to do at 60fps accurately with cameras than with a lidar. > Not even sure how to interpret such a statement. Let me rephrase: You don't need the vehicles to work in worst case conditions at all, if economically they're still a success if you don't allow them to run in those conditions. If Waymo or Cruise who whomever has self driving taxis in 2020 deployed in temperate cities, and Tesla doesn't have L4 autonomy until 2024, at which point it also works in a blizzard, it doesn't matter if they're cheaper and more effective them. Tesla will have already lost. > Custom ASICs for ML that Tesla is building is fairly well-understood tech at this point. This is one small piece of the puzzle. You also need algorithms that Tesla doesn't appear to have, and (camera) hardware that Tesla claims to have but others seem to agree can't support what they want.
  • DaiPlusPlus 7y ago
    > If Waymo or Cruise who whomever has self driving taxis in 2020 deployed in temperate cities, and Tesla doesn't have L4 autonomy until 2024, at which point it also works in a blizzard, it doesn't matter if they're cheaper and more effective them. Tesla will have already lost. If those self-driving taxis are not available for retail purchase and cost their operators over 6-figure sums to add to their fleet - and Tesla have it working in their promised $35k Model 3, then Tesla will win in the long-term. Also, remember the car industry moves very, very slowly (no pun intended). The Model 3 has been out for over a year now and has barely captured a fraction of its possible market. Consider that people will buy/lease a car for individual use for 3-5 years before replacing it: someone buys a normal car in 2021 because they need one at the time, but will still buy Tesla’s FSD car when it comes out. The “autonomous taxis will replace individual car ownership” trope only applies to hyper-urbanised environments where parking-spaces are luxury lifestyle accessories - and where people are already well-services by public-transit infrastructure. Finally: people who try an autonomous (but unaffordable for exclusive individual use) taxi service in 2020 might be so impressed with the experience that they vow to buy the first available individually purchasable autonomous car - even if that happens until Tesla’s 2024 models come out - Tesla still wins. By analogy, consider that Tesla is probably the /hottest/ car brand in the world today - and they did it without any traditional advertising - and they got started over 10 years ago. Enough people influenced by reviews and YouTube videos of the Roadster and 2012 Model S translated that into real money being spent on Model 3 buys today. That’s an anticipation gap of at least to 7 years - that’s impressive. Can you imagine people waiting 7 years for an “affordable” version of a luxury product? Why weren’t any of the other manufacturers doing anything to meet this clear demand for physically attractive EVs with over-hyped autonomous capabilities? (Disclaimer: I own a Tesla Model X)
    • close04 7y ago
      > only applies to hyper-urbanised environments That's where most of the population lives in western countries (both US and EU have ~10% of the population in the largest 10 cities and that's without the well connected metropolitan areas which probably at least double the numbers). So if the futuristic predictions of shared vehicles actually materialize the market for the "personal" vehicle would shrink and manufacturers will have less incentive for whatever they produce for the "personal car" slice of the market. Unless we also get a decentralization trend and people start leaving urban centers. > Why weren’t any of the other manufacturers doing anything to meet this clear demand for physically attractive EVs with over-hyped autonomous capabilities? While I agree with the "physically attractive EVs" (although for me it's more of a nice to have than a must), the second part is pretty cynical. You're asking why aren't manufacturers knowingly killing people to sell more cars. Well they are. Some promise you clean diesel, some promise you self driving. Both missed the mark a bit. And both of those promises sold lots of cars.
• kahnjw 7y ago
  >> I'll respond clearly: We're multiple computer vision leaps forward away from what Elon needs for success. They're easily half a decade behind Lidar based systems. And people die as a consequence of putting those systems on the road. >Custom ASICs for ML that Tesla is building is fairly well-understood tech at this point. High-end smartphones have used similar tech for years now joshuamorton is right and you didn't really address the point made. It isn't about understanding the hardware, it's about understanding the software. You point me to any individual who can tell you concretely how a specific convolutional neural network (CNN) arrives at a given solution and I'll take this all back. We know so little about how CNNs work, and plane old neural networks (NNs) for that matter, it's embarrassing. They're prone to adversarial attacks, not only that, you can successfully mount the same attack against _any_ NN that was trained on a common dataset. We don't know how to effectively defend against these yet in a white box setting. We have no idea what the solution space looks like. We barely understand why one of the most simple optimization algorithms outperforms almost all others on at these tasks. We barely understand why randomizing data visitation results in solutions that perform completely differently. The counter argument goes something like "we tested it on a big eval set and it aced it" Well I'm here to tell you that things change. Assumptions made in creating that eval set might not generalize to all real-world cases. And in this case bad assumptions result in death. As someone who has spent a good portion of my life working on this stuff I've learned that sometimes (most of the time) the best choice is the obvious, known, simple one. The fact that a good portion of cars may be controlled via something we know so little about should worry you. On a different note, I think you're also missing why Tesla have opted to invest in a percept suite that doesn't use LIDAR. That reason is cost. Tesla needs to sell cars now. They and their customers cannot afford to put LIDAR on their current platform. At the same time they need to move the metal and they know their customers want AEVs. I think their strategy is sound from a purely business cost/benefit analysis. It's a risk but from a financial perspective a good one, because if it works they hit pay dirt.
  • microtherion 7y ago
    > I think you're also missing why Tesla have opted to invest in a percept suite that doesn't use LIDAR. That reason is cost. Even beyond pure cost, one problem Tesla has is that they already SOLD tens of thousands of FSD option packages, predicated on NOT needing to retrofit the cars with LIDAR. So arguably, Tesla might be worse off if they deliver a LIDAR based FSD (and need to retrofit tens of thousands of cars, or pay off the owners), than if they just plod on with a camera based FSD that never quite works safely.