On 8/27/2013 3:55 PM, Chris de Morsella wrote:
*From:* John Clark <[email protected]>
*To:* [email protected]
*Sent:* Tuesday, August 27, 2013 10:08 AM
*Subject:* Re: When will a computer pass the Turing Test?
On Mon, Aug 26, 2013 Chris de Morsella <[email protected]
<mailto:[email protected]>> wrote:
> you cannot prove that things in the brain happen because of some proximate
definable and identifiable cause or otherwise they must therefore result by
a
completely random process.
>>Bullshit. Axioms don't need proof, and the most fundamental axiom in all of logic is
that X is Y or X is not Y. Everything else is built on top of that. And only somebody
who was absolutely desperate to prove the innate superiority of humans over computers
would try to deny it.
You seem confused... the brain is not an axiom... it is one of the most complex systems
we know about in the observed universe.
> In a system as layered, massively parallel and highly noisy as the brain
your
assumptions of how it works are naïve and border on the comical. The brain
is not a
based on a simple deterministic algorithm in which the chain of cause and
effect is
always clear.
>> Although reductionism has recently received a lot of bad press from supermarket
tabloids and new age gurus the fact remains that if you want to study something complex
you've got to break it into simpler parts and then see how the parts fit together. And
in the final analysis things happen for a reason or they don't happen for a reason; and
if they did then it's deterministic and if they didn't then it's random.
Perhaps your final analysis is a bit too shallow and self limiting. Why you cling so
tenaciously to this need for definitive causality chains (or else it must be complete
randomness) is amusing, but is not misguided. You cannot show definitive causality for
most of what goes on in most of the universe. You can hypothesize a causal relationship
perhaps, but you cannot prove one for all manner of phenomenon arising out of chaotic
systems. The brain is a noisy chaotic system and you are attempting to impose your
Newtonian order on it.
Your approach does not map well onto the problem domain. And what you say has no
predictive value; it does not help unravel how the brain works... or how the mind arises
within it.
It does help. There's no evidence that the brain can't be understood as a parallel
computer plus some randomness. The problem with John's formulation is he insists there is
either *a* reason or not *a* reason. Hardly anything can be thought of as having *a*
reason. In the case of human behavior, each instance almost certainly has many different
causes, some in memory, some in the immediate environment, and some which are random and
don't have an effective cause. I think of the person, brain/body/etc, plus immediate
environment narrow down the probable actions to a few, e.g. 1 to 20, and then some quantum
randomness realizes one of those. So it's not deterministic like Laplace's clockwork
world, but it's not anything-is-possible either.
Brent
> You can copy the symbols on a sheet of paper , but without understanding
Hungarian
you will never be impacted by the meaning or sensations that poem is
seeking to convey.
>>True but irrelevant. I never claimed we would someday understand how to make an AI
more intelligent than ourselves, I only said that someday such an AI would get made.
And how are you sure it has not already been achieved. To go by some of the recent DARPA
solicitations they are really hot on the trail of trying to develop/discover smart
algorithms modeled on the neocortext's own algorithms -- especially in the area of
pattern matching.
What I said about needing to understand that which you are studying in order to be able
to really be able to manipulate, extend, emulate, simulate etc. is not only true -- as
you admit -- but is also relevant. With no understanding of the symbol stream you have
no knowledge of what to do with the symbol stream passing across your view; you are
unable to operate with it in any kind of meaningful manner. It is like looking at DNA
sequences flashing by you... ACTG... with no insight into what they symbols mean, do or
control.
As I earlier agreed -- black box testing has its place and it is possible to discover
some aspects of a system through its external interface, but to really know a system and
to be able to describe it one must open it up and actually study it. A white box
methodology is required.
This applies to understanding the brain as well.. it is and will remain a mystery until
we go in and figure out its fine grained workings.
-Chris
>> John K Clark
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