Why Ray Kurzweil's Google Project May Be Doomed To Fail

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."

Comments

Re:Mr. Grandiose

[Iamthecheese]

That "circus magic" showed enough intelligence to parse natural language. I understand you want to believe there's something special about a brain but there really isn't. The laws of physics are universal and apply equally to your brain, a computer, and a rock.

You should know after all science has created that "we don't know" doesn't mean "it's impossible" nor does it mean "this isn't the right method"

Re:You have to start somewhere.

[MichaelSmith]

My wife is putting our son through these horrible cram school things. Kumon and others. I was so glad when he found ways to cheat, now his marks are better, he gets yelled at less and he actually learned something.

Re:You have to start somewhere.

[bmo]

Modern AI involves having some system, which ranges from statistical learning algorithms all the way to biological neurons growing on a plate, learn through presentation of input. The same way people learn, except often faster.

Biological neurons on a plate learning faster than neurons inside one's head? They are both biological and work at the same "clock speed" (there isn't a clock speed).

Besides, we do this every day. It's called making babies.

The argument that I'm trying to get across is that the evangelists of AI like Kurzweil promote the idea that AI is somehow able to bypass experience, aka "learning by doing" and "common sense." This is tough enough teaching to systems that have been the result of the past 4.5 billion years of MomNature's bioengineering. I'm willing to bet that AI is doomed to fail (to be severely limited compared to the lofty goals of the AI community and the fevered imaginations of the Colossus/Lawnmower Man/Skynet/Matrix fearmongers) and that MomNature has already pointed the way to actual useful intelligence, as flawed as we are.

Penrose was right, and will continue to be right.

--
BMO

Re:You have to start somewhere.

[ridgecritter]

This interests me. As a nonexpert in AI, it has always seemed to me that a critical missing aspect of attempts to generate 'strong' AI (which I guess means AI that performs at a human level or better) is a process in which the AI formulates questions, gets feedback from humans (right, wrong, senseless - try again), coupled with modification by the AI of its responses and further feedback from humans...lather, rinse, repeat...until we get responses that pass the Turing test. This is basically just the evolutionary process. This is what made us.

I don't think we need to know how a mind works to make one. After all, hydrogen and time have led to this forum post, and I doubt the primordial hydrogen atoms were intelligent. So we know that with biochemical systems, it's possible to come up with strong I given enough time and evolution. Since evolution requires only variation, selection, and heritabillity, it's hard for me to believe we can't do that with computational systems. Is it so difficult to write a learning system that assimilates data about the world, asks questions, and changes its assumptions and conclusions on the basis of feedback from humans?

And it's probably already been tried, and I haven't heard about it. If it has, I'd like to know. If not, I'd like to know why not.