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Moravec's paradox

en.wikipedia.org

31–40 of 44 posts

Re: Moravec's paradox

#31
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 agree hugely that computers are based on hard logic and this makes them poor tools to deal with tasks like 'perception'. I'd also add that most people working in the field of AI are trained in hard logic, and not at all in the subtleties of the perceptual world (not that there's a university course for this), which probably doesn't help.

I'm not so sure you start a good argument though. 'Harder' is all about the tools at hand. If you have the right tools, everything is easy. So to me this is all semantics. To me all the wikipedia page basically says is 'we haven't invented a good artificial tool for generalized, fast perception'.

Of course the other way to think about it is that humans and other animals devote generally much larger amounts of physical space (in the brain and otherwise) to subconscious things like perception and subconscious memory than they do to conscious things like logic...

Re: Moravec's paradox

#32
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 agree hugely that computers are based on hard logic and this makes them poor tools to deal with tasks like 'perception'. I'd also add that most people working in the field of AI are trained in hard logic, and not at all in the subtleties of the perceptual world (not that there's a university course for this), which probably doesn't help. I'm not so sure you start a good argument though. 'Harder' is all about the to…

>'Harder' is all about the tools at hand. If you have the right tools, everything is easy. >So to me this is all semantics. To me all the wikipedia page basically says is 'we haven't invented >a good artificial tool for generalized, fast perception'

Ok I'll rephrase. "After 30+ years of intense research it has hard to develop the tools to generalised fast perception". Whereas in that time we have developed tools that make higher level reasoning computationally cheap in comparison. But as you yourself say that's just semantics.

If you try to do something for over 30 years and make little progress, compared to another area of activity were many of the hard problems are solved in just a few years and the solutions to harder problems keep on coming, that's pretty good evidence that the first problem area is a hard one, however you try to finesse the description of the problems.

Re: Moravec's paradox

#33
post #27
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.

Some Go programs already play at professional level on 9x9 boards, and amateur mid-dan level on 19x19. That's "playing well" on my book: many people play go for years without reaching that level.

Yes, it's still far from the level computer chess was 15 years ago (beating top pros), but they're getting there. And I don't think it will take any major breakthrough in AI itself.

Re: Moravec's paradox

#34
post #29
post #25

Earlier quoted context omitted.

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 an…

I'm not sure I agree with your temporal notion of difficulty. One thing is not harder than another simply because the latter took less time to figure out. So what if many people have failed?* If someone with great insight like Ramanujan comes around and proves a bunch of new mathematical theorems, the fact that we now know those theorems does not imply that they are easier (or harder) to understand or make use of compared to some theorem which was not proved for another seventy years (there are examples here that go both ways.)

So why is robot.walk_to(...) "obviously harder to implement"? How could we know that simpler implementations will never be discovered? What you call "immense work" is not even a century's worth. In hundreds of years, making a robot walk convincingly might be no more difficult than implementing an effective chess AI.

I suppose I'm getting at a concept of minimality (like Komolgorov complexity). Just having a solution does not mean it's a minimal solution. We know enough to say perception is harder right now but not enough to say perception is intrinsically harder. We can't know that new breakthroughs (or just lots of gradual development) won't make these problems simple ones.

(*Actually, I do agree that lots of smart people failing at a problem is probably a good indicator that the problem is hard. This is still no guarantee though.)

Re: Moravec's paradox

#35
post #34
post #29

Earlier quoted context omitted.

"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 an…

I'm not sure I agree with your temporal notion of difficulty. One thing is not harder than another simply because the latter took less time to figure out. So what if many people have failed?* If someone with great insight like Ramanujan comes around and proves a bunch of new mathematical theorems, the fact that we now know those theorems does not imply that they are easier (or harder) to understand or make use of com…

Your definition falls down when faced with real world problems. I can write a 'perfect' chess program in less than a day that could easily run on a PC, however it's run time would make it useless in the real world. Crossing the Atlantic is an easy problem now, but that does not mean it was easy 500 years ago even though mathematically nothing has changed. And in 500 years computer vision is probably going to be considered a vary easy problem often done as a high school level project, but that does not mean it's easy now.

Re: Moravec's paradox

#36
This is exactly the kind of flawed behaviorist centric thinking that has held AI back for the past 50 year. Until AI researchers get over their obsession with mathematical constructs with no foundation in biology, like symbolic AI and bayesian networks, we will never have true AI. Once you realize this, you see that this “paradox” isn't really a paradox at all.

The brain is not anything like the Von Neumann architecture of a CPU. It is a massively parallel prediction machine. High level thought occurs in cerebral cortex whose base functional unit is Hierarchical Temporal Memory composed of about 100 neurons. Once we have figured out how these units are wired in the brain, “difficult” problems like pattern recognition will be trivial, and “trival” problems like playing checkers will require many hours of training and many HTM units just like in a real human brain.

For anyone interested in this, I highly recommend Jeff Hawkins' book, “On Intelligence”. http://books.google.com/books?isbn=0805078533

Re: Moravec's paradox

#37
post #36

This is exactly the kind of flawed behaviorist centric thinking that has held AI back for the past 50 year. Until AI researchers get over their obsession with mathematical constructs with no foundation in biology, like symbolic AI and bayesian networks, we will never have true AI. Once you realize this, you see that this “paradox” isn't really a paradox at all. The brain is not anything like the Von Neumann architect…

This is insulting to AI researchers in the extreme.

They know they are not making as good progress on "true AI" as they would like. But many researchers have tried very hard in many directions.

If you are so sure true AI is fairly trivial, why not do it? Even small amounts of progress would make you very famous.

Re: Moravec's paradox

#39
post #32

Earlier quoted context omitted.

I agree hugely that computers are based on hard logic and this makes them poor tools to deal with tasks like 'perception'. I'd also add that most people working in the field of AI are trained in hard logic, and not at all in the subtleties of the perceptual world (not that there's a university course for this), which probably doesn't help. I'm not so sure you start a good argument though. 'Harder' is all about the to…

>'Harder' is all about the tools at hand. If you have the right tools, everything is easy. >So to me this is all semantics. To me all the wikipedia page basically says is 'we haven't invented >a good artificial tool for generalized, fast perception' Ok I'll rephrase. "After 30+ years of intense research it has hard to develop the tools to generalised fast perception". Whereas in that time we have developed tools that…

You skew my words. What I was saying is that you can't say anything is hard if you have the right tools to do it. Not that this hasn't proved hard with our current technology/approach.

This was in response to the above post using phrases like "intrinsically harder" and "highly dependent on the representations and models used".

Apart from that I agree with you...

Re: Moravec's paradox

#40
post #36

This is exactly the kind of flawed behaviorist centric thinking that has held AI back for the past 50 year. Until AI researchers get over their obsession with mathematical constructs with no foundation in biology, like symbolic AI and bayesian networks, we will never have true AI. Once you realize this, you see that this “paradox” isn't really a paradox at all. The brain is not anything like the Von Neumann architect…

This is insulting to AI researchers in the extreme. They know they are not making as good progress on "true AI" as they would like. But many researchers have tried very hard in many directions. If you are so sure true AI is fairly trivial, why not do it? Even small amounts of progress would make you very famous.

"This is insulting to AI researchers in the extreme."

Well, yes and no. If you want the entire book "On Intelligence" (which I highly recommend too) is insulting to AI researchers.

The book basically explains why we're on the wrong track.

To me AI is about reasoning and creativity and none of the stuff we currently have comes anywhere close to that.

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