From: Tim Duyzer (firstname.lastname@example.org)
Date: Tue May 06 2003 - 17:57:07 MDT
I realize that there is a lot of subconscious information people have,
process, and use. But a super AI, given access to something like the
Internet, would probably have access to all of the raw information it would
need. If it was taught how to process that information, there'd be little
need to train it further - it could teach itself. That's because the net
contains ridiculous amounts of information (and myriad examples, unintended
and otherwise) about things like social relationships, interactions, and the
like. An SAI should be able to do a far better job than a research team
could in learning how to deal with people if it was just given a basic
framework that it could color in itself.
Or maybe I am just naive. I just like reading this list, I haven't much
education as far as cognitive science goes :)
----- Original Message -----
From: "Ben Goertzel" <email@example.com>
Sent: Tuesday, May 06, 2003 7:20 PM
Subject: RE: Hardware Progress: $212/GFlop/s
> In my view, your perspective is a bit naive in terms of cognitive science.
> To explain why fully would take more than a single e-mail. But the main
> point is that most of the knowledge that a mind requires is not of the
> that can easily be articulated in a file to be loaded into an AI system.
> Most human knowledge is:
> a) highly detailed tacit/implicit declarative knowledge about familiar
> things, usually unconscious in humans
> b) procedural knowledge, detailed knowledge about how to do particular
> things in particular contexts, nearly always unconscious in humans [how to
> prove a theorem... how to talk to a girl.. how to walk down the street ..
> how to phrase a sentence based on the education level of the listener ..
> etc. etc.]
> This kind of knowledge has got to be learned -- at least, until we figure
> out how to read detailed knowledge out of human brains. Or until we
> the FIRST real AI system, then we can copy it with variations ;)
> The well-known Cyc project is an attempt to encode all human knowledge in
> explicit form, to be loaded into an AI brain. Many AI experts, myself
> included, think this is doomed to fail, for the reasons stated above
> it may fail interstingly, and may lead to valuable results short of Real
> AI). However, we do have on this list Stephen Reed, one of the leaders of
> the Cyc project, who is of a different opinion!
> -- Ben Goertzel (www.goertzel.org, www.agiri.org)
> > -----Original Message-----
> > From: firstname.lastname@example.org [mailto:email@example.com]On Behalf Of Tim
> > Duyzer
> > Sent: Tuesday, May 06, 2003 6:49 PM
> > To: firstname.lastname@example.org
> > Subject: Re: Hardware Progress: $212/GFlop/s
> > I don't see machines needing 2.5 years to train. Training time
> > for humans is
> > a mix of social training and education. Unlike machines, though, we
> > simply load data into a brain. Give a superintelligent machine access to
> > resource such as the Internet (which by then would likely be far more
> > extensive and powerful than it is today, perhaps completely
> > unrecognizeable
> > at all) and it would take very little time for it to become adept
> > at social
> > interaction as well as extremely knowledgeable - it would have the
> > to assimilate and process information on many more levels than a human.
> > the end, there'd really be no need for any kind of AI training - just
> > it in.
> > Tim
> > > The processing power to run a human-level AI is
> > > unknown, but is estimated to be in the range of
> > > 100 - 100,000 TFlop/s. Assume the most powerful
> > > machine available for AI work is in the $3 M price
> > > range. Then the expected date of a human-level
> > > machine is 2008-2025. The expected date for
> > > superintelligent machines is 7.5 years later. This
> > > is calculated from a human taking about 20 years
> > > to train. A machine 8 times faster than a human
> > > is expected 5 years after a human-equivalent, and
> > > it would be expected to train in 20/8 = 2.5 years.
> > >
> > > Daniel
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