Moravec's paradox • Hacker News Board

Re: Moravec's paradox

#21

Post by saulrh » Fri, Dec 14, 2012, 11:43 PM UTC

joe_the_user wrote: post #20

saulrh wrote: post #3

Roboticist here. This is actually a huge problem in robotics and causes all sorts of problems for real robots. For example, my current project is to teach robots how levers work.

Well, Teach as in "program", right? It seems like the problem is that computers and robots don't learn in same fashion as human and thus the process of "teaching" them things in their not learning concept X in same fashion as humans - ie, they don't learn generalizations such a way that are "ready at hand" to use when the appropriate situation arises.

That's one of the underlying causes of Moravec's Paradox, yes. Humans have a very difficult time with precision and regularity, which are exactly what current computer systems are best at. Computers, by contrast, have a hard time with generalization, and creativity and physically interacting with the real world are some of the the most general systems possible.

Re: Moravec's paradox

#22

Post by joe_the_user » Fri, Dec 14, 2012, 11:44 PM UTC

I would say that this is true only as long as this "adult intelligence" pretty much remains within a single "logical frame" (http://en.wikipedia.org/wiki/Frame_%28artificial_intelligenc...).

I would claim that while a single logical frame is easy to simulate on a digital computer, creating and balancing multiple, not-necessarily consistent frames is very difficult and requires as much computer activity or brain activity as the also difficult activities of raw input processing.

One might argue that neural system began as very different systems from digital computers but the evolution of the large human has allowed them emulate discreet, including a computer's digital logic while still doing the balancing of multitudes of environmental constraints which neural system have excelled at for millions of years. And letting "us" conceive-of and to even build computers perfecting this discreet logic. Pretty amazing.

Re: Moravec's paradox

#23

Post by ilaksh » Sat, Dec 15, 2012, 12:34 AM UTC

Sounds like people posting or contributing to an article like this are aiming at understanding artificial general intelligence. So just search for that. Artificial General Intelligence or AGI.

Re: Moravec's paradox

#24

Post by jerf » Sat, Dec 15, 2012, 12:40 AM UTC

tgflynn wrote: post #6

It's an interesting observation and certainly something one needs to be aware of in thinking about intelligent systems but I'm not convinced that the notion that perception is intrinsically harder than logic is quite true. I think the difficulty of a problem is highly dependent on the representations and models used. Computers were developed based on logical and mathematical principles so it makes sense that they are…

"I'm not convinced that the notion that perception is intrinsically harder than logic is quite true."

But... where's the room for doubt? This isn't an article from 1930 about theoretical possibilities of what may happen someday when we have a lot of computational power. This is an observation about how perception has proved to be much more complicated than more pure reasoning, one quite old, robust, and well-established. The question is more about why that is true than whether it is true.

In a further comment you reply about how you could not convince your neural net to play chess... but again, we are not theorizing that computers may be good at chess someday. We live in a world in which, if they are not already simply better than humans, we only a couple of years away. Certainly better than all but the absolute very best. Whereas we still get excited when we see a robot that can walk up or down a normal, rocky hill at all.

Also, it baffles me how you think that explaining why logic is easier than perceptual problems is somehow disproof of that very fact. It doesn't matter that it's "really" the programmer that knows how to play chess (even if I'd observe the machine is still doing it better) when we still can't hardly make machines walk at all, regardless of whether the programmer or the computer is the one "knowing", a concept that in this context comes perilously close to a tautological assertion that if a computer can do it it must not be true "knowing". If we were really good at both sensorimotor and logic, but with two radically different toolkits, that might be an interesting point, but that's not the world we live in.

Re: Moravec's paradox

#25

Post by tgflynn » Sat, Dec 15, 2012, 2:22 AM UTC

jerf wrote: post #24

tgflynn wrote: post #6

It's an interesting observation and certainly something one needs to be aware of in thinking about intelligent systems but I'm not convinced that the notion that perception is intrinsically harder than logic is quite true. I think the difficulty of a problem is highly dependent on the representations and models used. Computers were developed based on logical and mathematical principles so it makes sense that they are…

"I'm not convinced that the notion that perception is intrinsically harder than logic is quite true." But... where's the room for doubt? This isn't an article from 1930 about theoretical possibilities of what may happen someday when we have a lot of computational power. This is an observation about how perception has proved to be much more complicated than more pure reasoning, one quite old, robust, and well-establis…

The undeniable observation is that certain people spent a long time trying to do perception with a certain set of tools and found it to be very hard.

That does not necessarily imply that perception is intrinsically so much harder than logic, merely that it is using those tools.

It may turn out for example that there exist (in a mathematical sense) functions which are good at recognizing characters which are simpler than the simplest function which is good at playing chess. If that were the case it would make sense to say that chess is intrinsically harder than character recognition, even if humans have historically had a harder time discovering the recognition functions than the chess playing functions.

On your last paragraph there's a huge difference between a program discovering a good solution to a problem, which is what happens in machine learning, and a programmer discovering such a solution then creating a program to implement it. In the first case we may begin to consider the program to be showing signs of intelligence while in the later it's just a really fast calculator which isn't doing anything the programmer couldn't do.

Is there circularity here - yes because we can say the same thing of the learning program if we treat it at a lower level of abstraction and therein lies perhaps the core of the problem of understanding what we mean by intelligence.

Re: Moravec's paradox

#26

Post by treePhase » Sat, Dec 15, 2012, 2:59 AM UTC

tgflynn wrote: post #13

Breakthrough wrote: post #10

Earlier quoted context omitted.

There's also the difficult task of real-world interaction (or as the article puts it, low-level sensorimotor skills), although I suppose this is what you mean by perceptual problems. Most things humans create are based on rules (e.g. games, markets, governments), and rules can be easily taught to computers as they're just abstract logical ideas. Even for probabilistic problems, you can certainly teach a neural networ…

Well what I mean by "hard" is that I can train a neural network to do a reasonably good job of recognizing say handwritten characters given some amount of training data. My attempts to train similar networks to learn the rules of chess (just the rules, I'm not even talking about trying to win) have not led to good or steadily improving performance, despite the fact that there's effectively no limit to the amount of t…

You should also consider the possibility that the type of neural network you chose is not capable of learning the rules of chess, but may be sufficient for OCR.

Re: Moravec's paradox

#27

Post by cmccabe » Sat, Dec 15, 2012, 3:29 AM UTC

jerf wrote: post #24

tgflynn wrote: post #6

It's an interesting observation and certainly something one needs to be aware of in thinking about intelligent systems but I'm not convinced that the notion that perception is intrinsically harder than logic is quite true. I think the difficulty of a problem is highly dependent on the representations and models used. Computers were developed based on logical and mathematical principles so it makes sense that they are…

"I'm not convinced that the notion that perception is intrinsically harder than logic is quite true." But... where's the room for doubt? This isn't an article from 1930 about theoretical possibilities of what may happen someday when we have a lot of computational power. This is an observation about how perception has proved to be much more complicated than more pure reasoning, one quite old, robust, and well-establis…

Come up with an AI that can play the game of Go well. Then we'll talk.

Re: Moravec's paradox

#28

Post by simonster » Sat, Dec 15, 2012, 4:13 AM UTC

tgflynn wrote: post #13

Breakthrough wrote: post #10

Earlier quoted context omitted.

There's also the difficult task of real-world interaction (or as the article puts it, low-level sensorimotor skills), although I suppose this is what you mean by perceptual problems. Most things humans create are based on rules (e.g. games, markets, governments), and rules can be easily taught to computers as they're just abstract logical ideas. Even for probabilistic problems, you can certainly teach a neural networ…

Well what I mean by "hard" is that I can train a neural network to do a reasonably good job of recognizing say handwritten characters given some amount of training data. My attempts to train similar networks to learn the rules of chess (just the rules, I'm not even talking about trying to win) have not led to good or steadily improving performance, despite the fact that there's effectively no limit to the amount of t…

I would bet heavily on (1). Non-human primates, with ~10 billion neurons (~3 billion neocortical), also cannot learn the rules of chess. Nearly all neural networks have far fewer.

Re: Moravec's paradox

#29

Post by jerf » Sat, Dec 15, 2012, 4:14 AM UTC

tgflynn wrote: post #25

jerf wrote: post #24

Earlier quoted context omitted.

"I'm not convinced that the notion that perception is intrinsically harder than logic is quite true." But... where's the room for doubt? This isn't an article from 1930 about theoretical possibilities of what may happen someday when we have a lot of computational power. This is an observation about how perception has proved to be much more complicated than more pure reasoning, one quite old, robust, and well-establis…

The undeniable observation is that certain people spent a long time trying to do perception with a certain set of tools and found it to be very hard. That does not necessarily imply that perception is intrinsically so much harder than logic, merely that it is using those tools. It may turn out for example that there exist (in a mathematical sense) functions which are good at recognizing characters which are simpler t…

"That does not necessarily imply that perception is intrinsically so much harder than logic, merely that it is using those tools."

Again, this might follow if, say, nobody had ever tried to come up with such tools, and we were going to try for the first time this year. But people have been trying, and failing, and failing. Of course it will be easier when the tools exist; robot.walk_to(grocery_store) is as easy as any other function to call, but it is obviously much harder to implement.

In the "mathematical sense" I can simply assert the existence of "recognize_character(image_matrix)". In reality, the complexity of such a function is obviously much higher than, say, a Prolog implementation.

You keep retreating into theory, but again, that's not the world we live in. The world we live in is one in which the problem of sensorimotor perception and manipulation has received immense work on it, and remains in a state in which it is still wildly less capable than my dog in most ways, whereas we were knocking out things like SAT solvers that blow humans away (which are notably incapable of holding very many symbols in their heads at once) decades ago. It doesn't matter if you can theorize a world in which perceptual problems are easier than sensory problems; we don't live there.

Re: Moravec's paradox

#30

Post by jerf » Sat, Dec 15, 2012, 4:21 AM UTC

cmccabe wrote: post #27

jerf wrote: post #24

Earlier quoted context omitted.

"I'm not convinced that the notion that perception is intrinsically harder than logic is quite true." But... where's the room for doubt? This isn't an article from 1930 about theoretical possibilities of what may happen someday when we have a lot of computational power. This is an observation about how perception has proved to be much more complicated than more pure reasoning, one quite old, robust, and well-establis…

Come up with an AI that can play the game of Go well. Then we'll talk.

That's just a snide comment, not a useful one. The difficulty of symbolic/logic problems can be made unboundedly great by construction. Nobody ever denied that. The point is that something like crossing a room and picking up a pencil seemed easy, and to this day is still a significant achievement for robotics, still requiring fairly controlled circumstances.

It can be difficult to understand this from our present-day perspective where we have so thoroughly internalized this idea that it has apparently passed into invisibility for some of us. Go back and read Asimov's robots work, in which he has robots walking, talking, socially interacting with humans, even pondering great ethical conundrums, while at the same time it requires massive resources to attain the raw numerical computational power available to a Commodore 64.