--- On Wed, 1/7/09, Ben Goertzel b...@goertzel.org wrote:
if proving Fermat's Last theorem was just a matter of doing math, it would
have been done 150 years ago ;-p
obviously, all hard problems that can be solved have already been solved...
???
In theory, FLT could be solved by brute force
Matt: Logic has not solved AGI because logic is a poor model of the way
people think.
Neural networks have not solved AGI because you would need about 10^15
bits of memory and 10^16 OPS to simulate a human brain sized network.
Genetic algorithms have not solved AGI because the
PS I should have said the fundamental deficiencies of the PURELY
logicomathematical form of thinking. It's not deficient in itself - only if
you think like so many AGIers that it's the only form of thinking, or able
to accommodate the entirety of human thinking.
--- On Thu, 1/8/09, Mike Tintner tint...@blueyonder.co.uk wrote:
What then do you see as the way people *do* think? You
surprise me, Matt, because both the details of your answer
here and your thinking generally strike me as *very*
logicomathematical - with lots of emphasis on numbers and
[I second this recommendation elsewhere from Colin Hales - IMO, although it
may not appear at first obvious, the scientific study of the self, as of
mirror neurons, will have a profound effect on conceptions of AGI (and why
these two things are essential for intelligence) - and this is not
Matt,
Thanks. But how do you see these:
Pattern recognition in parallel, and hierarchical learning of increasingly
complex patterns by classical conditioning (association), clustering in
context space (feature creation), and reinforcement learning to meet evolved
goals.
as fundamentally
In response to Jim Bromer's post of Wed 1/7/2009 8:24 PM
=Jim Bromer==
All of the major AI paradigms, including those that are capable of learning,
are flat according to my definition. What makes them flat is that the
method of decision making is minimally-structured and they
IFrom: Jim Bromer [mailto:jimbro...@gmail.com]
Sent: Wednesday, January 07, 2009 8:24 PM
All of the major AI paradigms, including those that are capable of
learning, are flat according to my definition. What makes them flat
is that the method of decision making is minimally-structured
On Jan 8, 2009, at 10:29 AM, Ronald C. Blue wrote:
...Noise is not noise...
Speaking of noise, was that ghastly HTML formatting really necessary?
It made the email nearly unreadable.
J. Andrew Rogers
---
agi
Archives:
--- On Thu, 1/8/09, Mike Tintner tint...@blueyonder.co.uk wrote:
Matt,
Thanks. But how do you see these:
Pattern recognition in parallel, and hierarchical
learning of increasingly complex patterns by classical
conditioning (association), clustering in context space
(feature creation),
Matt:Free association is the basic way of recalling memories. If you
experience A followed by B, then the next time you experience A you will
think of (or predict) B. Pavlov demonstrated this type of learning in
animals in 1927.
Matt,
You're not thinking your argument through. Look carefully
That email had really nice images, but I don't know why gmail viewed
them automatically!
On 1/8/09, Mike Tintner tint...@blueyonder.co.uk wrote:
Matt:Free association is the basic way of recalling memories. If you
experience A followed by B, then the next time you experience A you will
think
Mike,
Your own thought processes only seem mysterious because you can't predict what
you will think without actually thinking it. It's not just a property of the
human brain, but of all Turing machines. No program can non-trivially model
itself. (By model, I mean that P models Q if for any
A picture is like an instant 1000 words and you will remind a picture almost
70 years but not 1000 words.
-Original Message-
From: J. Andrew Rogers and...@ceruleansystems.com
To: agi@v2.listbox.com
Sent: 1/8/09 1:59 PM
Subject: Re: [agi] The Smushaby of Flatway.
On Jan 8, 2009, at
On Fri, Jan 9, 2009 at 12:19 AM, Matt Mahoney matmaho...@yahoo.com wrote:
Mike,
Your own thought processes only seem mysterious because you can't predict
what you will think without actually thinking it. It's not just a property of
the human brain, but of all Turing machines. No program can
Ronald C. Blue wrote:
[snip]
[snip] ... chaos stimulation because ... correlational wavelet opponent
processing machine ... globally entangled ... Paul rf trap ... parallel
modulating string pulses ... a relative zero energy value or
opponent process ... phase locked ... parallel
Abram,
On 1/7/09, Abram Demski abramdem...@gmail.com wrote:
Steve,
Dp/dt methods do not fundamentally change the space of possible models
(if your initial mathematical claim of equivalence is true).
The claim is that a given neuron performs the same transformation, whether
on object
--- On Thu, 1/8/09, Vladimir Nesov robot...@gmail.com wrote:
On Fri, Jan 9, 2009 at 12:19 AM, Matt Mahoney
matmaho...@yahoo.com wrote:
Mike,
Your own thought processes only seem mysterious
because you can't predict what you will think without
actually thinking it. It's not just a
On Fri, Jan 9, 2009 at 6:04 AM, Matt Mahoney matmaho...@yahoo.com wrote:
Your earlier counterexample was a trivial simulation. It simulated itself but
did
nothing else. If P did something that Q didn't, then Q would not be
simulating P.
My counterexample also bragged, outside the input
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