On Thursday 04 September 2008, Mike Tintner wrote:
Bryan,
How do you know the brain has a code? Why can't it be entirely
impression-istic - a system for literally forming, storing and
associating sensory impressions (including abstracted, simplified,
hierarchical impressions of other
OK, then the observable universe has a finite description length. We don't
need to describe anything else to model it, so by universe I mean only the
observable part.
But, what good is it to only have finite description of the observable
part, since new portions of the universe enter the
our observable
universe.
-- Matt Mahoney, [EMAIL PROTECTED]
--- On Thu, 9/4/08, Abram Demski [EMAIL PROTECTED] wrote:
From: Abram Demski [EMAIL PROTECTED]
Subject: Re: Computation as an explanation of the universe (was Re: [agi]
Recursive self-change: some definitions)
To: agi@v2
On Thu, Sep 4, 2008 at 10:53 AM, Matt Mahoney [EMAIL PROTECTED] wrote:
To clarify what I mean by observable universe, I am including any part that
could be observed in the future, and therefore must be modeled to make
accurate predictions. For example, if our universe is computed by one of an
--- On Thu, 9/4/08, Abram Demski [EMAIL PROTECTED] wrote:
So, my only remaining objection is that while the universe
*could* be
computable, it seems unwise to me to totally rule out the
alternative.
You're right. We cannot prove that the universe is computable. We have evidence
like Occam's
On Wednesday 03 September 2008, Mike Tintner wrote:
I think this is a good important point. I've been groping confusedly
here. It seems to me computation necessarily involves the idea of
using a code (?). But the nervous system seems to me something
capable of functioning without a code -
Bryan,
How do you know the brain has a code? Why can't it be entirely
impression-istic - a system for literally forming, storing and associating
sensory impressions (including abstracted, simplified, hierarchical
impressions of other impressions)?
1). FWIW some comments from a cortically
of your work - at worst,
it will shed some needed light on the subject. At best... well, you know that
part. :-]
Terren
--- On Tue, 9/2/08, Ben Goertzel [EMAIL PROTECTED] wrote:
From: Ben Goertzel [EMAIL PROTECTED]
Subject: Re: [agi] Recursive self-change: some definitions
To: agi@v2.listbox.com
2008/9/2 Ben Goertzel [EMAIL PROTECTED]:
Yes, I agree that your Turing machine approach can model the same
situations, but the different formalisms seem to lend themselves to
different kinds of analysis more naturally...
I guess it all depends on what kinds of theorems you want to
hi,
What I am interested in is if someone gives me a computer system that
changes its state is some fashion, can I state how powerful that
method of change is likely to be? That is what the exact difference
between a traditional learning algorithm and the way I envisage AGIs
changing their
]
Subject: Re: [agi] Recursive self-change: some definitions
To: agi@v2.listbox.com
Date: Wednesday, September 3, 2008, 4:17 PM
Hi Ben,
My own feeling is that computation is just the latest in a series of technical
metaphors that we apply in service of understanding how the universe works.
Like
Terren:My own feeling is that computation is just the latest in a series of
technical metaphors that we apply in service of understanding how the universe
works. Like the others before it, it captures some valuable aspects and leaves
out others. It leaves me wondering: what future metaphors
] wrote:
From: Terren Suydam [EMAIL PROTECTED]
Subject: Re: [agi] Recursive self-change: some definitions
To: agi@v2.listbox.com
Date: Wednesday, September 3, 2008, 4:17 PM
Hi Ben,
My own feeling is that computation is just the latest in a series of
technical metaphors that we apply in service
] wrote:
From: Mike Tintner [EMAIL PROTECTED]
Subject: Re: [agi] Recursive self-change: some definitions
To: agi@v2.listbox.com
Date: Wednesday, September 3, 2008, 7:02 PM
Terren:My own
feeling is that computation is just the latest in a series of technical
metaphors that we apply
--- On Wed, 9/3/08, Abram Demski [EMAIL PROTECTED] wrote:
From: Abram Demski [EMAIL PROTECTED]
Subject: Re: Computation as an explanation of the universe (was Re: [agi]
Recursive self-change: some definitions)
To: agi@v2.listbox.com
Date: Wednesday, September 3, 2008, 7:35 PM
Matt, I have
I've put up a short fairly dense un-referenced paper (basically an
email but in a pdf to allow for maths) here.
http://codesoup.sourceforge.net/RSC.pdf
Any thoughts/ feed back welcomed. I'll try and make it more accessible
at some point, but I don't want to spend too much time on it at the
Hmmm..
Rather, I would prefer to model a self-modifying AGI system as something
like
F(t+1) = (F(t))( F(t), E(t) )
where E(t) is the environment at time t and F(t) is the system at time t
This is a hyperset equation, but it seems to nicely and directly capture the
fact that the system is
2008/9/2 Ben Goertzel [EMAIL PROTECTED]:
Hmmm..
Rather, I would prefer to model a self-modifying AGI system as something
like
F(t+1) = (F(t))( F(t), E(t) )
where E(t) is the environment at time t and F(t) is the system at time t
Are you assuming the system knows the environment totally?
I don't understand how mimicry in specific occurs without some kind of
turing-complete GA spawning a huge number of possible paths. I'm
thinking of humanoid robots mapping the movements of a human trainer
onto their motor cortex. I've certainly heard somewhere that this is
one way to do it and I
I really see a number of algorithmic breakthroughs as necessary for
the development of strong general AI but it seems like an imminent
event to me regardless. Nonetheless much of what we learn about the
brain in the meantime may be nonsense until we fundamentally grok the
mind.
On Tue, Sep 2, 2008 at 3:00 PM, William Pearson [EMAIL PROTECTED]wrote:
2008/9/2 Ben Goertzel [EMAIL PROTECTED]:
Hmmm..
Rather, I would prefer to model a self-modifying AGI system as something
like
F(t+1) = (F(t))( F(t), E(t) )
where E(t) is the environment at time t and F(t)
On Tue, Sep 2, 2008 at 4:43 PM, Eric Burton [EMAIL PROTECTED] wrote:
I really see a number of algorithmic breakthroughs as necessary for
the development of strong general AI
I hear that a lot, yet I never hear any convincing arguments in that
regard...
So, hypothetically (and I hope not
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