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I suspect some aspects of driving a car consumes a majority of a person's brain power, even if it doesn't feel like it. Ever get into a situation where there's

I suspect some aspects of driving a car consumes a majority of a person's brain power, even if it doesn't feel like it. Ever get into a situation where there's on-ramps and off-ramps on both sides, you've never been on that stretch of road before and there's a lot of traffic? Driver conversation stops. Driver paying attention to the audiobook or podcast playing stops. It takes all your attention. If that's the case, then maybe we won't get true self-driving until these systems have the processing power of a human brain...

256lie 6y ago
Not processing power but a better world model of physics and reasoning. Humans can understand other drivers intentions and when laws can be bent based on the context to avoid dangerous situations.
dstaley 6y ago
> Ever get into a situation where there's on-ramps and off-ramps on both sides, you've never been on that stretch of road before and there's a lot of traffic? One advantage cars with large sensor suites have over humans is that they can see and process information from all around them. In your specific example, the car can watch both on an off ramps at the same time, isn't phased by the "newness" of the road since other cars have navigated this section of road hundreds of times before it has, and can keep tabs on cars obscured by line of sight due to the car's ability to bounce signals off of vehicles.
- fnord77 6y ago
  ok - here's a better example - skillful drivers on a highway can predict when another driver might change lanes just from the "body language" of that car. It's pretty subtle and I don't think all human drivers can recognize it, much less SOA AI. Along the same vein, most drivers will become extra vigilant of another car that's driving in a way that's the least bit erratic, giving that car a wide berth.
samatman 6y ago
Yes and no. ENIAC exceeded the processing power of a human brain. Only for solving systems of equations, a task which humans find very difficult, and for which computers are naturally suited. But we would never have built it if this weren't the case. Chess fell to AI decades before Go did, because computers find Go more difficult, due to the much greater branching factor. Humans are more naturally suited to Go, we can "cheat" by training our built-in shape and pattern recognition subsystems. It's true that driving a car recruits many adaptive subsystems of a human brain. It's further along the spectrum of 'easy for humans, hard for computers'. But what I want to illustrate is that the 'processing power of a human brain' isn't very well-defined, and isn't the relevant factor for why self-driving has proven remarkably difficult. It's not clear to me that full self-driving, at the level where there's no steering wheel in the car, can be achieved without general AI. I don't even think it's a useful goal, since the really difficult tasks are things like "park your car in this particular place in a field when arriving at a wedding", rather than situations a human would have to suddenly take over for. But I have to employ my full concentration to add two five-digit numbers in my head, and while I once knew the trick for multiplication, today I'm quite incapable. Yet there's nothing more trivial for a computer.
rodgerd 6y ago
> I suspect some aspects of driving a car consumes a majority of a person's brain power, even if it doesn't feel like it. A decade or so ago I decided to get my motorcycle license, and one of the changes to the testing regime that had come about since I got my car license was that you are required to verbalise any risks you are seeing: drive along saying "oncoming traffic, pedestrian approaching the edge of the footpath, driveway" and so on. It's an interesting thing to do because it's remarkable to understand just how much background processing that you are doing, and how many subtle hints you might be getting - the direction a person is looking and other body language are influencing your assessment of whether someone is likely to wait at the edge of an intersection or just step out; if the lights on a car blink as a person walks towards it, they're probably about to get into it rather than cross the road, and so on.

256lie 6y ago

Not processing power but a better world model of physics and reasoning. Humans can understand other drivers intentions and when laws can be bent based on the context to avoid dangerous situations.

dstaley 6y ago

> Ever get into a situation where there's on-ramps and off-ramps on both sides, you've never been on that stretch of road before and there's a lot of traffic? One advantage cars with large sensor suites have over humans is that they can see and process information from all around them. In your specific example, the car can watch both on an off ramps at the same time, isn't phased by the "newness" of the road since other cars have navigated this section of road hundreds of times before it has, and can keep tabs on cars obscured by line of sight due to the car's ability to bounce signals off of vehicles.

fnord77 6y ago
ok - here's a better example - skillful drivers on a highway can predict when another driver might change lanes just from the "body language" of that car. It's pretty subtle and I don't think all human drivers can recognize it, much less SOA AI. Along the same vein, most drivers will become extra vigilant of another car that's driving in a way that's the least bit erratic, giving that car a wide berth.

samatman 6y ago

Yes and no. ENIAC exceeded the processing power of a human brain. Only for solving systems of equations, a task which humans find very difficult, and for which computers are naturally suited. But we would never have built it if this weren't the case. Chess fell to AI decades before Go did, because computers find Go more difficult, due to the much greater branching factor. Humans are more naturally suited to Go, we can "cheat" by training our built-in shape and pattern recognition subsystems. It's true that driving a car recruits many adaptive subsystems of a human brain. It's further along the spectrum of 'easy for humans, hard for computers'. But what I want to illustrate is that the 'processing power of a human brain' isn't very well-defined, and isn't the relevant factor for why self-driving has proven remarkably difficult. It's not clear to me that full self-driving, at the level where there's no steering wheel in the car, can be achieved without general AI. I don't even think it's a useful goal, since the really difficult tasks are things like "park your car in this particular place in a field when arriving at a wedding", rather than situations a human would have to suddenly take over for. But I have to employ my full concentration to add two five-digit numbers in my head, and while I once knew the trick for multiplication, today I'm quite incapable. Yet there's nothing more trivial for a computer.

rodgerd 6y ago

> I suspect some aspects of driving a car consumes a majority of a person's brain power, even if it doesn't feel like it. A decade or so ago I decided to get my motorcycle license, and one of the changes to the testing regime that had come about since I got my car license was that you are required to verbalise any risks you are seeing: drive along saying "oncoming traffic, pedestrian approaching the edge of the footpath, driveway" and so on. It's an interesting thing to do because it's remarkable to understand just how much background processing that you are doing, and how many subtle hints you might be getting - the direction a person is looking and other body language are influencing your assessment of whether someone is likely to wait at the edge of an intersection or just step out; if the lights on a car blink as a person walks towards it, they're probably about to get into it rather than cross the road, and so on.