

Full employment theorem - profquail
http://en.wikipedia.org/wiki/Full_employment_theorem

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rndmcnlly0
On a meta-note: I deeply enjoy that linking to Wikipedia articles is part of
HN culture. If that which is timely cannot be timeless, then it is of supreme
importance that what is News to us, individually, consists of more than what
is New at the time of posting.

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Miky
There isn't anything that sufficiently complex algorithms can't find out that
humans can, so this doesn't seen to be a terribly useful conclusion.

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iwwr
It's unclear what this has to do with A.I. Even humans are limited by the
halting problem or other undecidable questions.

So why is this called a "theorem"? There is yet no proof that there are
classes of problems inherently better solvable by the human mind. Or
otherwise, that the human is something _extra_ , computationally-wise, than a
Turing machine.

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baddox
I think the point is that, for some problems, no computation can perform
better than human beings. A strong AI would perform _equally as well_ as
humans on these problems, but not better.

Of course, a "strong AI" in this usage would probably have to not only be
computationally equivalent to the human mind, but also be provided with the
same insanely complex and chaotic input that the human mind operates on.

To truly mimic human "creativity," this strong AI would probably need all the
qualitative experience and memories that human beings have. It would probably
need to undergo development in a dynamic social environment, or at least have
the memory of doing so.

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memetichazard
It doesn't seem like this is really an AI vs. Humans issue. Rather, it's
saying, regardless if you have some optimal algorithm X for a class of "Full
Employment" problems, it is always possible to have an algorithm that performs
better for a specific case at the cost of worse performance for other cases.

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alain94040
The trick is that perfection is usually overrated. Just like human experts,
you can be the best at what you do, but you don't need to be the best ever
(especially considering future experts).

That's also the key difference between science and engineering. In
engineering, you need a good-enough solution, but you are not so concerned
with proving that there is possible better implementation.

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VMG
Isn't this like saying that AI is impossible?

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alextgordon
Quite the opposite, it's saying there are some jobs which are AI-complete.

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endtime
I agree, but the wording is poor. "no algorithm can optimally perform a
particular task done by some class of professionals" implies that general
intelligence is not an algorithm.

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eru
Go forth and improve that article.

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known
Computer/algorithms cannot tell who is hot, if the input is photo of Marilyn
Monroe versus Scarlett Johansson

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Dilpil
Whenever you claim no algorithm can do something that a human can, you must
ask yourself: what does the computer lack that a human might posses?

In this case, there are indeed machine learning algorithms that can do this
task.

[http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5533...](http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5533684)

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known
Computer algorithm cannot tell who is hotter, Marilyn Monroe or Scarlett
Johansson

