>
>
> What I am trying to debunk is the perceived risk of a fast takeoff
> singularity launched by the first AI to achieve superhuman intelligence. In
> this scenario, a scientist with an IQ of 180 produces an artificial
> scientist with an IQ of 200, which produces an artificial scientist with an
> IQ of 250, and so on. I argue it can't happen because human level
> intelligence is the wrong threshold. There is currently a global brain (the
> world economy) with an IQ of around 10^10, and approaching 10^12. THAT is
> the threshold we must cross. And that seed was already planted 3 billion
> years ago.
>
> To argue this point, I need to discredit certain alternative proposals,
> such as intelligent agents making random variations of itself and then
> testing the children with puzzles of the parent's choosing. My paper proves
> that proposals of this form cannot work.



Your paper does **not** prove anything whatsoever about real-world
situations.

Among other reasons: Because, in the real world, the scientist with an IQ of
200 is **not** a brain in a vat with the inability to learn from the
external world.

Rather, he is able to run experiments in the external world (which has a far
higher algorithmic information than him, by the way), which give him **new
information** about how to go about making the scientist with an IQ of 220.

Limitations on the rate of self-improvement of scientists who are brains in
vats, are not really that interesting

(And this is separate from the other critique I made, which is that using
algorithmic information as a proxy for IQ is a very poor choice, given the
critical importance of runtime complexity in intelligence.  As an aside,
note there are correlations between human intelligence and speed of neural
processing!)

-- Ben G



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agi
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