> 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, intrusive changes to our cities and roads to accommodate "self-driving" cars.
I think it will happen but only by making many expensive, intrusive changes to our cities and roads to accommodate "self-driving" cars.
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.
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.
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
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…
These are entirely avoidable problems using the sensors and methods every other company besides Tesla are using
Sensors might be an alternate strategy though and a way to at least take vision processing out of the list of hard problems.
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.
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
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.
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."
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.
NY to Jersey - nope.
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?