6 ms·

> However, IMO, it will never happen because it needs a full artificial general intelligence. I think it will happen but only by making many expensive, intrus

• nathanaldensr 5y ago
  This problem is, this was never the marketed vision. The implicit and sometimes explicit message everyone seemed to swallow was "it's like human driving, but better!" when it's actually not. It's just another set of fundamentally-flawed algorithms running on binary computers that only know about zeroes and ones.
• jonplackett 5y ago
  I think we still must be missing something very fundamental with the way we’re doing AI. When you look at nature and see a tiny bee or fly navigating perfectly around all sorts of obstacles, including the newspaper I’m trying to swat it with, using just that teeny tiny brain running of mili-watts of power with just compound eyes to guide it. And in 3D space not a nice flat surface. But we still can’t make a car not drive into a massive concrete barrier? Something is off. But that gives me hope that there’s a discovery waiting to be made that can fix it.
  • wpietri 5y ago
    We surely are missing a lot. But nature has picked easier problems with a fly. They are small enough to be very robust; flying into things is no problem. They're also cheap to build and incredibly numerous. Flies, well, drop like flies. If we had a similar tolerance for car crashes, existing levels of automation would be fine.
    • wearywanderer 5y ago
      Even human brains, with all their capabilities, get the job done for 20 watts (or something in that order of magnitude.) Who even knows how much power we'd need for equivalent results from the best specialized silicon we have? I think you might burn a hundred gigawatts and still not get comparable results. Something is clearly wrong with our approach. It should be possible to do much more with much less, but there is some piece of the puzzle we're missing.
      • osmarks 5y ago
        The brain has hyperspecialized and hyperoptimized single-purpose hardware. Human AI systems run on more general-purpose machines with a few decades spent improving the hardware. Blaming the software is silly.
        • wearywanderer 5y ago
          I'm not talking about running general purpose CPUs. I'm talking about the most high end specialized silicon we have. Throw the best TPUs ever made at the problem and you still won't get anywhere even remotely close to what the squishy pink meat can do. The power gap is so huge, our software simply must be inadequate. We're talking about a power gap wider than the gap between my toaster oven and the Saturn V.
          • osmarks 5y ago
            I rechecked some random internet articles, and the brain contains about 10^15 synapses. They operate at about 10Hz (~10 PFLOPS). If we arbitrarily assume that each synapse operation is equivalent to 1 floating point operation on a computer, then this is about 3 orders of magnitude more than a good GPU (~10 TFLOPS). Which is actually a lot less than I thought. Still, the brain's basic structures have been optimized over ridiculous amounts of time, the training data those get while you exist is years of high-resolution images/sound/etc, and being a smaller in-skull device it has advantages of lower latency than, say, a cluster used to train ML models.
            • jonplackett 5y ago
              I think the link between 1 floating point operation and 1 synapse is probably a bit dubious.
    • jonplackett 5y ago
      I picked flies as an extreme example but really any small animal is doing an immense amount of computing. I just found this weird video of how a dragon flies brains act basically like a homing missile, using only a few dozen neurones: https://www.youtube.com/watch?v=Y0vRupFPw90 https://www.youtube.com/watch?v=Y0vRupFPw90
  • markkanof 5y ago
    I think your comment is interesting and generally agree, but to play devils advocate, there are certainly times when a fly might crash right into a window or something and then just gets up and keeps flying so there is also an aspect of resiliency built into a fly that we haven't (or maybe can't) built into cars.
    • jonplackett 5y ago
      As I mentioned in previous comment - flies crash into glass because they didn't evolve with it. They don't have the right sensors to see it. So it seems like an unfair thing to level at them!
  • mathstuf 5y ago
    [ Note: I'm a complete layperson in the AI field, so feel free to correct me. This is mostly based on my penchant for reading topics such as evolutionary biology, Hofstadter, and such. ] If we used genetic algorithms to design the algorithm, it'd probably be able to get something as efficient as that. However, you're also not going to be able to "fix this one thing" because it's more likely to be the result of emergent behavior from interactions more complicated than anyone can understand. I believe one could get something that works like that, but you're also going to have other behaviors akin to moths flying into lamps because they navigate by the moon which is recognized as "the brightest thing at night". We think we can make rules for everything and expect them to be followed without exception to perform these complicated tasks, but I think that's hubris. Anything that ends up doing it at that power scale is going to be as inscrutable as a brain. Asimov's robopsychology is then likely to be something real, but it's going to be dissecting neural networks because "fix this issue" on something that took multiple GW of energy to train in the first place will need fixing from that end versus "well, time to train it again". As an anecdote for this thread, I remember there was some setup where physical circuits were designed via genetic algorithms to do some task. There were results with unconnected resistors that actually influenced the behavior of the circuit. You're generating behavior which is sensitive to that level. Wish I could find that again…
    • deleted 5y ago
      [deleted]
    • deleted 5y ago
      [deleted]
  • gher-shyu3i 5y ago
    You're literally asking humans to create life. This is strictly the Creator's domain.
  • gmadsen 5y ago
    These are self inflicted problems by only using cameras. These are entirely avoidable problems using the sensors and methods every other company besides Tesla are using
    • jonplackett 5y ago
      If those cameras were hooked up to an AR helmet and a human had 360 view of the car through them, I bet they could drive just fine. The data is there. Sensors might be an alternate strategy though and a way to at least take vision processing out of the list of hard problems.
      • ketamine__ 5y ago
        Radar and Lidar would make the car safer than if a human was driving?
        • gmadsen 5y ago
          those are sensors. "safer than a human" is broad and not really applicable to talking about just sensors. but as an example, lidar has orders of magnitude faster detection of an object than human perception. so in that case, sure it is much safer.
  • AareyBaba 5y ago
    Organisms tuned by years of evolution can fail when confronted by novel environments. Think of a bee that wanders indoors and keeps hitting itself on a window pane trying to escape. A moth attracted to a light bulb. A cat chasing a laser pointer. Deer paralyzed by headlights.
    • jonplackett 5y ago
      Yes indeed - but luckily driving is a fairly narrow task by human standards. An AI trained specifically do this should be more like an animal's well known behaviours. If driverless cars were crashing because all of a sudden a giant sheet of glass appeared in the middle of the road, or a giant alien death ray shot up the tarmac, I think most people would have some sympathy.
  • osmarks 5y ago
    The fly has a really efficient specialized "computer" for the neural network thing it's running, while human ones are more generalized and don't have the benefit of hundreds of millions of years of power consumption optimization. The human software also has not been iterated on for those hundreds of millions of years.
  • Syonyk 5y ago
    > Something is off. Yes. The fundamental assumptions about how brains work are wrong. I see, far too often, the dismissive interpretation of brains as "A couple crappy cameras tied to a neural network" - which leads to the "Well, we have better cameras and we know how to do neural networks, so it can't be hard!" Throw in some dismissive statements about how awful humans are at driving and such, and you're set for the trap. Human/animal vision systems are way more optimized than that sort of handwaving dismissal. The "cameras" are well optimized for what's needed, and have some pretty darned impressive scanning features to make a very small central cone of resolution do everything that's needed - without flooding the brain with HD video in places that don't matter. It's an optimized system for making a fairly narrow feed cover everything that's needed. https://en.wikipedia.org/wiki/Saccade https://en.wikipedia.org/wiki/Saccade And, yes, there are some weird quirks of vision systems - optical illusions and such. But once you get past the eyes, the rest of the "Make sense of the 3D world around us" system is insanely optimized, and exceedingly power efficient. It works well enough and reliably enough to handle absolutely absurd changes in the operating environments. Humans did not come born with "supersonic low level flight" built into the system, yet... our brains can work with it. It just takes some learning and brain adjustments. And the whole rest of the system following is similarly impressive. There's a typically paired arrogance you also see: "We are like gods in the synthetic world of the internet, because we know code and manage 99.995% API success rates, therefore we can use code to solve reality." Reality is infinitely more creative at throwing wrenches into things than we are at solving them with code, and while it doesn't really matter on the internet, it very much does matter at 75mph. When you dismiss all that as "crappy cameras and a neural network, we know code, we can do that!" - you end up failing in the predictable ways we see with the self driving cars.
  • emkoemko 5y ago
    well can't we just clone a human brain maybe one from like a F1 driver and stick them in cars ? problem solved..
• bobthepanda 5y ago
  Which is why I’m so pessimistic about the likelihood of this. In the rich world it is not hard to find a potholed road with faded markings, so how can we expect our society to maintain and upkeep expensive infrastructure when we can barely manage paint and basic asphalt?
• simias 5y ago
  I agree that it could work. I'm not sure I'd want that because I expect that it would make those roads very hostile to pedestrians since you'd probably want to forbid them from crossing outside of designated areas and only when authorized. You'll probably need some dividing walls between the street and the sidewalk. In many countries it would be a huge culture shift, and IMO a step in the wrong direction. We don't need more urban real-estate devoted to cars.
• tibbydudeza 5y ago
  Yep that will be coming first - rail is a good example or a dedicated road for freight from say a factory complex to a port. NY to Jersey - nope.
• Syonyk 5y ago
  > I think it will happen but only by making many expensive, intrusive changes to our cities and roads to accommodate "self-driving" cars. We could put some metal guides in the ground so they can follow that path. We could then separate that path from other obstructions with barriers, maybe put some tunnels in the ground that keep other people out. And have signals that indicate when the "self driving" stuff is going to interfere with other roads, so nobody gets in the way! "Totally change cities to meet the requirements of self driving cars" sounds an awful lot like "Just put rails in and call it a train."