[ExI] Immeasurable hubris

[Tomaz Kristan]

Anders!

The term/logism "pharaonic tasks" is just great! I'll use it in the future
whenever I'll need to. :-)

10 years ago I contemplated and co-wrote an algorithm evolver, you can
download it here:

http//www.critticall.com/Setup_Critticall137.exe

It can do quite non-trivial things.

Evolving algorithm isn't that time consuming anymore as it used to be - say
a decade ago. Still, we are far from doing something pharaonic.









On Sun, Sep 7, 2014 at 12:21 PM, Anders Sandberg <anders at aleph.se> wrote:

> Tomaz Kristan <protokol2020 at gmail.com> , 7/9/2014 10:30 AM:
>
> What one has to do, to conquer the at least nearby Universe, is to write
> down and run some computer code, perhaps not a very long code at all. And
> then just wait and watch all of the above happening automatically.
>
> Light speed and slower probes permutating everything, from your body to
> rocks.
>
> What code? I don't know, just as the majority is clueless about any
> complex code I am pretty clueless  about that one.
>
> Except that it must be possible and that it is likely in our grasp.
>
>
> Yes. Except that finding the code might be very non-trivial.
>
> In his "Constructor theory" paper (http://arxiv.org/abs/1210.7439) David
> Deutsch talks about "pharaonic tasks" where you build the tools or
> resources needed to build the tools to do something (potentially in many
> layers).
>
> Something we at FHI have been trying to figure out is how much we can
> bound the efficiency of pharaonic tasks: in a sense making a
> superintelligent AI is just a matter of randomly generating code and
> running it, since in the long run you will hit jackpot. But it is not
> efficient at all. Similarly simple mammals can colonize space by evolving
> into intelligent creatures with culture and technology - but it is not
> efficient (each trial takes millions of years and requires an entire
> planet). Intelligence means you are better at zooming in on more efficient
> approaches, but this only works in domains where there is information your
> intelligence can use to optimize. So what do we really know about the
> domain of writing smart code?
>
> Some pieces we have learned: many everyday tasks are far harder than
> abstract tasks, big data machine learning approaches do fairly well in
> messy domains, the structure of problem-space is complex (check out Moore
> and Mertens book!), self-improving systems are not naturally exponential in
> the domains we have tried (genetic programming/alife, Eurisco)...
>
>
> Anders Sandberg, Future of Humanity Institute Philosophy Faculty of Oxford
> University
>
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