On 2/1/2011 11:11 PM, Stathis Papaioannou wrote:
On Wed, Feb 2, 2011 at 9:53 AM, Colin Hales
<c.ha...@pgrad.unimelb.edu.au> wrote:
In relation to Stathis' request:
If you model a natural environment presenting some problem to a human
within that environment, the simulated human will arrive at the same
solution as the real human would have. If intelligence is
problem-solving behaviour, there is therefore no difference between
the natural world and the model provided that the model is in fact a
good one. Your claim that computers cannot replicate human
intelligence is thus equivalent to a claim that there is some process
in the human brain which is not Turing emulable. What process do you
No. This is just plain wrong. You cannot model an observation of something
that you have no idea of the evidence of .i.e. You cannot model the unknown.
If you could then you'd already know it (the observer and the relationship
of the observer to everything else. If you want to get at unknowns, then you
have to model a modeller of the unknown ... and then _assume_ that
everything in a model captures the reality you are modelling, during the
process.
Of course you can model the unknown: there would be no point to
computer models otherwise. You include in the model the rules
determining the system's behaviour, run it, and prepare to be
surprised.
The non-Turing emulable part of the natural world is the relationship
between every little bit X and every other bit of it that is NOT directly
related to X. A product of massive parallelism created by a massive
collection of the entities of which we are actually made, which is best
assumed not to be abstract numbers if you want to understand it. This is
something we inherit by 'being' in the world. Something that cannot be
simulated. Something that a Turing Machine (computer), totally different to
us physically, does not get in its program.
By way of example, I have attached a video of a simulated neuron firing.
It's from a paper I have in review at the moment. The video depicts the
currents originating the biologically realistic EM fields around a neuron
due to the ion channels involed in an action potential. It was produce by
the package NEURON. In it you will see a pair of red/blue interfaces
travelling away from the soma. These interfaces are virtual evanescent
current-dipoles. They are mathematically describable, but form no part of
the mathematical description that generated them. THAT is what is missing.
These are the virtual relationships not accessed by the mathematics of a
Turing machine. No matter what is going on in a Turing machine, NONE of this
kind of phenomenon are accessed by it.
If the NEURON model is good enough then you can use it to simulate a
collection of neurons such as the human brain. This would allow you to
simulate the motor output of a brain when it is presented with sensory
input: in other words, when your model is presented with a problem it
will process the data and present you with a solution, the same
solution as a biological brain would have. The proviso is, of course,
that the model is good enough. Do you think that there is some aspect
of neuronal biochemistry that cannot be modelled at all by a computer?
I think it very likely that the brain can be so modeled. But the
meaning that simulated brain, as expressed in it's output decisions
relative to inputs is dependent on the rest of the world, or at least of
it with which the brain will interact - including the past evoutionary
history which led up to the brain. Its computations have no canonical
interpretation in themselves.
Brent
The question is 'what is it like to BE those fields'. It cannot be claimed
to be like the mathematical description that represents them, nor can it be
claimed to be 'like' being the computer running the simulation.
We can agree that the simulation of the fields or the ion channels or
whatever is not the same thing as the original, but simply predicts
how the original will behave. That's sufficient for intelligence.
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