From: Bodie (mclarkc@essex.ac.uk)
Date: Wed Jun 12 2002 - 18:07:02 MDT
I was at that as well, thought it was quite good, but I spent most of the
day either at the pub or on the london 2600 stall setting up lots of
random stuff including BBC micros imitating bird songs :) I saw freeman
dyson, always been a big fan of his. I've looked into this problem a bit
in the past and I've always concluded that the machines we have at the
moment are pretty primitive compared to a human brain, and to try to get
anywhere near mirroring the function of the brain we need computers that
are a good 30 - 40 years away. Like with your problem, the hardware is
just too slow to cope at the moment.
There is certainly a bit possibility that one day we may learn enough
about intelligence to recreate it to a reasonable accuracy, but that day
is a long way off yet
On Wed, 12 Jun 2002, Andy Brice wrote:
> I went to The Festival of Inappropriate Technology (XCOM2002) on Sunday. It
> was rather chaotic (especially with the inaudible PA system for the first
> hour or so), but quite interesting. I got to ask a question of Freeman Dyson
> and have a quick chat with him at the book signing afterwards. Subsequent
> attempts at name-dropping have been frustrated by the fact that none of my
> friends or work colleagues have heard of him!
>
> Anyway an interesting question came up that touched an issue raised here by
> the Hermit. Can computers be programmed to create machine intelligence, for
> example using genetic algorithms? I think there are some problems with this
> approach:
> * Genetic algorithms allow us to search a space of possible solutions, but
> its up to us to define that space. At present I don't think we even know
> enough about the problem to describe the problem space when it comes to
> intelligence.
> * Genetic algorithms are computationally very inefficient - they quickly
> choke on large problems and are usually regarded as a method of last resort
> for optimisation problems. Evolution took billions of years to evolve
> intelligence on earth using a degree of parallelism we may never be able to
> approach, and as far as we know this may have been a fluke.
> * Genetic algorithms work well (at present) where the problem space is not
> too large and we can quickly decide whether a solution is good, neither of
> these apply to the problem of creating intelligence.
> * Genetic algorithms need a reasonable pool of starting solutions if you
> want a good end result. At present I think we have no idea how to even
> create a reasonable starting population.
>
> A colleague and I wrote a genetic algorithm based program to lay-out
> chemical plant schematics according to various aesthetic criteria (minimum
> line crossings etc). The time response was approx n^2. It choked on any
> problem much bigger than 20 nodes. I set it the London underground as a
> 'stress test' - it still had nothing like a good solution 24 hours later.
>
> Andy Brice
>
>
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