Why Ray Kurzweil's Google Project May Be Doomed To Fail 354
moon_unit2 writes "An AI researcher at MIT suggests that Ray Kurzweil's ambitious plan to build a super-smart personal assistant at Google may be fundamentally flawed. Kurzweil's idea, as put forward in his book How to Build a Mind, is to combine a simple model of the brain with enormous computing power and vast amounts of data, to construct a much more sophisticated AI. Boris Katz, who works on machines designed to understand language, says this misses a key facet of human intelligence: that it is built on a lifetime of experiencing the world rather than simply processing raw information."
Ah! (Score:5, Informative)
The old `Chinese Room` again.
The Complete 1 Atlantic Recordings 1956-1961
It's Penrose vs Hofstadter! (Seriously, haven't we done this before?)
Re:Ah! (Score:5, Informative)
Oops! That second line should of course have been:
http://en.wikipedia.org/wiki/Chinese_room [wikipedia.org]
(That'll teach me to post to Slashdot when I'm sorting out my Mingus!)
Re:It may be flawed, but that doesn't sound like i (Score:5, Informative)
But I'm curious why you think a mind is necessarily a neural network. Are you saying there is no other possible way to construct a mind? As far as I can tell, there are lots of other designs, many of them far superior to neural networks, especially for such basic things as representing knowledge.
Cyc vs. bottom up (Score:5, Informative)
We've heard this before from the top-down AI crowd. I went through Stanford CS in the 1980s when that crowd was running things, so I got the full pitch. The Cyc project [wikipedia.org] is, amazingly, still going on after 29 years. The classic disease of the academic AI community was acting like strong AI was just one good idea away. It's harder than that.
On the other hand, it's quite likely that Google can come up with something that answers a large fraction of the questions people want to ask Google. Especially if they don't actually have to answer them, just display reasonably relevant information. They'll probably get a usable Siri/Wolfram Alpha competitor.
The long slog to AI up from the bottom is going reasonably well. We're through the "AI Winter". Optical character recognition works quite well. Face recognition works. Automatic driving works. (DARPA Grand Challenge) Legged locomotion works. (BigDog). This is real progress over a decade ago.
Scene understanding and manipulation in uncontrolled environments, not so much. Willow Garage has towel-folding working, and can now match and fold socks. The DARPA ARM program [darpa.mil] is making progress very slowly. Watch their videos to see really good robot hardware struggling to slowly perform very simple manipulation tasks. DARPA is funding the DARPA Humanoid Challenge to kick some academic ass on this. (The DARPA challenges have a carrot and a stick component. The prizes get the attention, but what motivates major schools to devote massive efforts to these projects are threats of a funding cutoff if they can't get results. Since DARPA started doing this under Tony Tether, there's been a lot more progress.)
Slowly, the list of tasks robots can do increases. More rapidly, the cost of the hardware decreases, which means more commercial applications. The Age of Robots isn't here yet, but it's coming. Not all that fast. Robots haven't reached the level of even the original Apple II in utility and acceptance. Right now, I think we're at the level of the early military computer systems, approaching the SAGE prototype [wikipedia.org] stage. (SAGE was an 1950s air defense system. It had real time computers, data communication links, interactive graphics, light guns, and control of remote hardware. The SAGE prototype was the first system to have all that. Now, everybody has all that on their phone. It took half a century to get here from there.)
a much better article (Score:4, Informative)
The crappy little superficial one-page MIT Technology Review article has a link to another, similarly crappy article on the same site, but if you click through one more layer you actually get to this [newyorker.com] much more substantial piece in the New Yorker.