3 ms·

1 hour of video is a lot of bytes. But 1 hour of driving doesn’t contain much of the total experiential set possible when driving. Generative AI only really can

1 hour of video is a lot of bytes. But 1 hour of driving doesn’t contain much of the total experiential set possible when driving. Generative AI only really can interpolate between things it has been trained on, it can’t extrapolate. This feels like an infinitesimal amount of driving data. That said, a POC doesn’t have to be production worthy. In the hands of a major automobile company perhaps this tech is profoundly powerful. Or perhaps it’s a single model in an ensemble. Regardless it’s going to be interesting where this goes.

XorNot 3y ago
Generative AI can absolutely extrapolate, that's the whole reason it works. The whole point of machine learning is to derive the underlying rules relating your input data. Extrapolation is just extending where you follow those "curves" beyond bounds of known data points.
- fnordpiglet 3y ago
  Oh but it can’t, but with a sufficiently complex vector space it can seem like it can. What seems like extrapolation is an interpolation in the semantic vector space, particularly in the transformer / attention model. This is a key difference between human intelligence and current AI, it’s not able to “create” and see beyond what it’s been trained on. Any approximation of that is simply indicative of a very complete training set, and it is sufficiently powerful enough to fool people with its expectation based inference - but when you dig into the details of cutting edge stuff you’re an expert in and ask it conceptual questions that extend beyond the semantic corpus embedded in its vector space, it will hallucinate, or if well fine tuned admit lack of knowledge, because the best it can do is interpolate within its own semantic vector space. But listen, I’m a big buyer of generative AI, what it does is incredible. But it’s useful to not ascribe more power to a tool than the math allows. And there are very few machine learning algorithms that do extrapolation at all with any precision. Generally they project an expectation,often of some complex highly dimensional non linear system, which is amazing, but when they are confronted with a novel input pattern they are thrown off. The issue is they’re at their core probabilistic systems, and if the data experiences a regime change that’s unexpected the model will misbehave and output garbage.
  - sillysaurusx 3y ago
    By this metric, a large number of humans can’t extrapolate either. In fact if you imagine your first paragraph were written about humans, it lines up pretty well.
    - uoaei 3y ago
      Don't be a dick, you know what is meant.
      - sillysaurusx 3y ago
        Huh? I disagree with the premise, and explained why. Reading over your comments for the last few days, you seem consistently aggressive. If you need to vent to someone about something, you can DM me. Happy to just listen.
        uoaei 3y ago
        If you mean when people who are being dicks make obvious glaring mistakes and can't handle when they're pointed out, I think the word you're looking for is "impatient". This community's standards are higher than the way you're participating. Have some dignity and bring your best side forward, not this petty sass. You know they're talking about the fundamental differences in learning between advanced and specialized biological systems (humans) and relatively rudimentary digital ones (LLMs). You're not explaining your disagreements you're just demonstrating your disdain for some implied lower-quality humans. That's called "being a dick".
        sillysaurusx 3y ago
        What on earth are you on about? You seem to have unilaterally declared that I was being sassy, when in fact this exists nowhere other than your own head. Then you run around like a sheriff on a power trip ranting about protecting the community from us sassy brats. Brass tacks: you need to stop what you’re doing, or you’re going to get yourself penalized by the mods. They have a duty to protect the intellectual curiosity of the site. Trust me when I say it’s no fun to be in the penalty box. You can start by re-reading the guidelines and paying particular attention to "don’t cross examine," along with realizing that it’s not okay to be calling people a dick multiple times when they’re engaging in good faith. Your call. Either way, I wash my hands of you and this conversation.
- dartos 3y ago
  It can to a point, but it can’t to the extent that humans can with sufficiently complex problems. Deep learning models like this can theoretically approximate pretty much any problem that can be expressed as a function. It’s entirely possible that there just doesn’t exist a function from visual data (maybe even including LIDAR and RADAR etc) to correct driver decisions. Humans can also intuit the behavior of other humans to an extent, even while driving (knowing that someone who is driving erratically is probably fucked up and will be dangerous to stay near). Kind of like a really shitty gossip protocol.
  - fnordpiglet 3y ago
    It can only approximate any function for which it’s seen data in the local feature spaces of the function. For anything it’s not seen features for it will do some maladapted interpolation through the feature space it has been trained on. It can’t be creative or synthesize a novel technique based on some more abstract reasoning over the new regime - it literally must attempt to fit its past observations as best it can to the new regime. Humans certainly do that too, but they are also able to step back and synthesize completely new behaviors given completely new data that isn’t just adapting old behavior based on some optimization function telling it that behavior is most appropriate in the new situation. People are confused because interpolation is actually fairly powerful and is often entirely sufficient. Especially with the GPT4 model it’s so well trained with such a large and varied corpus that it is able to handle many things well, even unexpected things, and seems like it is extrapolating at times. But it still hallucinates, and these are the most obvious symptoms of its inability to extrapolate. It’s just fitting within its trained vector space as best it can.
candiodari 3y ago
But ... all this goes for humans too! Is the argument that we should just outlaw driving alltogether, all possible forms? One famous example of that is how to react correctly when the car starts to slip due to speed, braking, or driving on water, mud, sand, snow or ice. I think everyone knows people's reflexes are to floor the brakes, and start wildly turning the steering wheel, which only results in total loss of control over the vehicle. Is anyone demanding drivers learn to correctly handle cars or other vehicles under these circumnstances? There are only very minimal efforts, because it is completely impractical to teach many humans better driving practices. So we just accept the flaws ... and the constant stream of victims this generates. Reality: Yes, a driving AI is not ready for all possible situations. It just isn't. It will never be. Is that a problem? Also reality: Humans drive drunk. Humans drive while under the influence of drugs. Humans drive trucks near kids when they're so tired they can't keep their head lifted up. And roads are full of dead cats, squirrels, mice, ... Also also reality: AI driving software can, after an accident, be taught to handle the situation that caused the accident, and the result of this learning process can then be uploaded to all instances of this software. Humans will keep making the same mistakes, with the same consequences, over and over and over again. Perhaps there is very slow improvement (mostly by modifying roads), but it takes decades. Practical view: I have driven around in Mountain View next to self-driving cars. One thing's for sure: self-driving cars behave much better than human drivers. Including me. It's very irritating how good they behave on the road. If the roads have many self-driving cars, I'm pretty damn sure it'll result in much fewer accidents and lower transit times. Never mind that self-driving cars of course solve the parking problem. I don't get why people hate them. And I hate this goalpost moving where AIs are compared to multiple top-performing humans, that you see everywhere. Of course, there are now cases where AIs have actually beaten groups of top-performing humans (translation, chess, Go, robot control, ...)
- moe_sc 3y ago
  Your arguments don't really fit, what was previously said. There was nothing said against driving AI in general, just that 4700h of videos seems low. I also get that humans are pretty bad drivers, but isn't that exactly why we shouldn't use them as the baseline for AIs to compare to? We are now at a point where we can set high standards for AI, so we get a best possible result, because while it isn't feasible to have everyone learn driving over a couple of years, a good AI has to be trained once and can be used by many, so we have the time. And sure, it can be updated, but should we really trust companies to keep innovating once they are already allowed to have the AI in use? The incentive to do so is far bigger if they have to do so before they got any money out of it.

XorNot 3y ago

Generative AI can absolutely extrapolate, that's the whole reason it works. The whole point of machine learning is to derive the underlying rules relating your input data. Extrapolation is just extending where you follow those "curves" beyond bounds of known data points.

fnordpiglet 3y ago
Oh but it can’t, but with a sufficiently complex vector space it can seem like it can. What seems like extrapolation is an interpolation in the semantic vector space, particularly in the transformer / attention model. This is a key difference between human intelligence and current AI, it’s not able to “create” and see beyond what it’s been trained on. Any approximation of that is simply indicative of a very complete training set, and it is sufficiently powerful enough to fool people with its expectation based inference - but when you dig into the details of cutting edge stuff you’re an expert in and ask it conceptual questions that extend beyond the semantic corpus embedded in its vector space, it will hallucinate, or if well fine tuned admit lack of knowledge, because the best it can do is interpolate within its own semantic vector space. But listen, I’m a big buyer of generative AI, what it does is incredible. But it’s useful to not ascribe more power to a tool than the math allows. And there are very few machine learning algorithms that do extrapolation at all with any precision. Generally they project an expectation,often of some complex highly dimensional non linear system, which is amazing, but when they are confronted with a novel input pattern they are thrown off. The issue is they’re at their core probabilistic systems, and if the data experiences a regime change that’s unexpected the model will misbehave and output garbage.
- sillysaurusx 3y ago
  By this metric, a large number of humans can’t extrapolate either. In fact if you imagine your first paragraph were written about humans, it lines up pretty well.
  - uoaei 3y ago
    Don't be a dick, you know what is meant.
    - sillysaurusx 3y ago
      Huh? I disagree with the premise, and explained why. Reading over your comments for the last few days, you seem consistently aggressive. If you need to vent to someone about something, you can DM me. Happy to just listen.
      - uoaei 3y ago
        If you mean when people who are being dicks make obvious glaring mistakes and can't handle when they're pointed out, I think the word you're looking for is "impatient". This community's standards are higher than the way you're participating. Have some dignity and bring your best side forward, not this petty sass. You know they're talking about the fundamental differences in learning between advanced and specialized biological systems (humans) and relatively rudimentary digital ones (LLMs). You're not explaining your disagreements you're just demonstrating your disdain for some implied lower-quality humans. That's called "being a dick".
        sillysaurusx 3y ago
        What on earth are you on about? You seem to have unilaterally declared that I was being sassy, when in fact this exists nowhere other than your own head. Then you run around like a sheriff on a power trip ranting about protecting the community from us sassy brats. Brass tacks: you need to stop what you’re doing, or you’re going to get yourself penalized by the mods. They have a duty to protect the intellectual curiosity of the site. Trust me when I say it’s no fun to be in the penalty box. You can start by re-reading the guidelines and paying particular attention to "don’t cross examine," along with realizing that it’s not okay to be calling people a dick multiple times when they’re engaging in good faith. Your call. Either way, I wash my hands of you and this conversation.
dartos 3y ago
It can to a point, but it can’t to the extent that humans can with sufficiently complex problems. Deep learning models like this can theoretically approximate pretty much any problem that can be expressed as a function. It’s entirely possible that there just doesn’t exist a function from visual data (maybe even including LIDAR and RADAR etc) to correct driver decisions. Humans can also intuit the behavior of other humans to an extent, even while driving (knowing that someone who is driving erratically is probably fucked up and will be dangerous to stay near). Kind of like a really shitty gossip protocol.
- fnordpiglet 3y ago
  It can only approximate any function for which it’s seen data in the local feature spaces of the function. For anything it’s not seen features for it will do some maladapted interpolation through the feature space it has been trained on. It can’t be creative or synthesize a novel technique based on some more abstract reasoning over the new regime - it literally must attempt to fit its past observations as best it can to the new regime. Humans certainly do that too, but they are also able to step back and synthesize completely new behaviors given completely new data that isn’t just adapting old behavior based on some optimization function telling it that behavior is most appropriate in the new situation. People are confused because interpolation is actually fairly powerful and is often entirely sufficient. Especially with the GPT4 model it’s so well trained with such a large and varied corpus that it is able to handle many things well, even unexpected things, and seems like it is extrapolating at times. But it still hallucinates, and these are the most obvious symptoms of its inability to extrapolate. It’s just fitting within its trained vector space as best it can.

candiodari 3y ago

But ... all this goes for humans too! Is the argument that we should just outlaw driving alltogether, all possible forms? One famous example of that is how to react correctly when the car starts to slip due to speed, braking, or driving on water, mud, sand, snow or ice. I think everyone knows people's reflexes are to floor the brakes, and start wildly turning the steering wheel, which only results in total loss of control over the vehicle. Is anyone demanding drivers learn to correctly handle cars or other vehicles under these circumnstances? There are only very minimal efforts, because it is completely impractical to teach many humans better driving practices. So we just accept the flaws ... and the constant stream of victims this generates. Reality: Yes, a driving AI is not ready for all possible situations. It just isn't. It will never be. Is that a problem? Also reality: Humans drive drunk. Humans drive while under the influence of drugs. Humans drive trucks near kids when they're so tired they can't keep their head lifted up. And roads are full of dead cats, squirrels, mice, ... Also also reality: AI driving software can, after an accident, be taught to handle the situation that caused the accident, and the result of this learning process can then be uploaded to all instances of this software. Humans will keep making the same mistakes, with the same consequences, over and over and over again. Perhaps there is very slow improvement (mostly by modifying roads), but it takes decades. Practical view: I have driven around in Mountain View next to self-driving cars. One thing's for sure: self-driving cars behave much better than human drivers. Including me. It's very irritating how good they behave on the road. If the roads have many self-driving cars, I'm pretty damn sure it'll result in much fewer accidents and lower transit times. Never mind that self-driving cars of course solve the parking problem. I don't get why people hate them. And I hate this goalpost moving where AIs are compared to multiple top-performing humans, that you see everywhere. Of course, there are now cases where AIs have actually beaten groups of top-performing humans (translation, chess, Go, robot control, ...)

moe_sc 3y ago
Your arguments don't really fit, what was previously said. There was nothing said against driving AI in general, just that 4700h of videos seems low. I also get that humans are pretty bad drivers, but isn't that exactly why we shouldn't use them as the baseline for AIs to compare to? We are now at a point where we can set high standards for AI, so we get a best possible result, because while it isn't feasible to have everyone learn driving over a couple of years, a good AI has to be trained once and can be used by many, so we have the time. And sure, it can be updated, but should we really trust companies to keep innovating once they are already allowed to have the AI in use? The incentive to do so is far bigger if they have to do so before they got any money out of it.