Of course, this is guesswork.

My current calculations, based on the Novamente system, are: It would
be "easy" to do with a few tens of thousands of commodity PC's
networked together.  Doing it with merely hundreds of such machines
will require a lot of attention to be paid to various sorts of
optimization.  Doing it with merely dozens may or may not be possible.

-- Ben G

On  Sun, 27 Nov 2005 08:33:43 -600, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:
> Maybe someone can tell me what kind of processing power will it take to
> run an AI system, with reasonable responce.
>
> Dan Goe
>
> ----------------------------------------------------
> From : Ben Goertzel <[EMAIL PROTECTED]>
> To : agi@v2.listbox.com
> Subject : Re: [agi] /. [Unleashing the Power of the Cell Broadband
> Engine]
> Date : Sun, 27 Nov 2005 08:48:47 -0500
> > Eugen,
> >
> > Thanks for the interesting post.
> >
> > I am left wondering whether the Cell Broadband Engine could
> > potentially be effective for Genetic Programming learning.  (In
> > Novamente we use an evolutionary learning algorithm different from GP,
> > but it's similar enough that if the CBE can do GP, then it can do our
> > algorithm as well.)
> >
> > I am curious for the opinion of others who are more knowledgeable
> > about such things.  (I'm not really a hardware guy.)
> >
> > Looking over the article you referenced, it seems to me that the PPE
> > (the main processing unit, a PowerPC variant) could be used to run the
> > main GP algorithm, and then fitness evaluations could be carried out
> > on the 8 SPE's ("synergistic
> > processing units") in parallel.
> >
> > For Novamente-relevant cases (as opposed to mathematical optimization
> > problems) this would require what the above article calls a "Large
> > single-SPE programming model", meaning that the SPE would need to
> > access main memory to do its fitness evaluation.  (Because for
> > Novamente learning, fitness evaluation of evolved programs has to do
> > with comparison of programs against fairly large databases of
> > experientially and inferentially acquired knowledge.)
> >
> > A downside is that the Cell has only 256MB of RAM.  This doesn't seem
> > to be a fundamental obstacle but it means care would have to be taken
> > in coding/design....  In the application I envision, most of the RAM
> > would be taken up by the set of data against which the candidate
> > programs are compared during the fitness evaluation process.
> >
> > Of course, the basic idea is that if this worked it would be much
> > cheaper to buy PS3's than 8-processor PC's, so a much larger
> > evolutionary learning farm could be constructed at a relatively modest
> > budget.
> >
> > Thoughts?
> >
> > --- Ben Goertzel
> >
> >
> > On 11/27/05, Eugen Leitl <[EMAIL PROTECTED]> wrote:
> > >
> > > Link: http://slashdot.org/article.pl?sid=05/11/26/228247
> > > Posted by: ScuttleMonkey, on 2005-11-27 06:34:00
> > >
> > >   An anonymous reader writes "IBM DeveloperWorks is running a paper
> from
> > >   the MPR Fall Processor Forum 2005 explores [1]programming models for
> > >   the Cell Broadband Engine (CBE) Processor, from the simple to the
> > >   progressively more advanced. With nine cores on a single die,
> > >   programming for the CBE is like programming for no processor you've
> > >   ever met before."
> > >
> > > References
> > >
> > >   1.
> http://www.ibm.com/developerworks/power/library/pa-fpfunleashing/?ca=dgr-lnxw01CellUnleash
> > >
> > > ----- End forwarded message -----
> > > --
> > > Eugen* Leitl <a href="http://leitl.org";>leitl</a>
> > > ______________________________________________________________
> > > ICBM: 48.07100, 11.36820            http://www.leitl.org
> > > 8B29F6BE: 099D 78BA 2FD3 B014 B08A  7779 75B0 2443 8B29 F6BE
> > >
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> > > Version: GnuPG v1.4.1 (GNU/Linux)
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> > > CyDBYmPd1pszzeasRifNr+0=
> > > =nSh6
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> > >
> > >
> >
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