[email protected] said:
Yes, but as a public forum, in addition to its entertainment and social value, 
it obliges us to uphold high standards of work and homework, and it is doubtful 
the most frequent posters have been keeping these high standards. And those few 
here who have simple solutions and simple refutations would be better off 
delivering them but not too often, obviously repetition after a point is not a 
virtue, rather a low standard.
 
 
Me: The value that I get from these discussions is that every once in a while I 
get an idea that might be useful. I want to talk about programming as it might 
relate to an AGI project.  I personally think that petty remarks are the low 
water marks in these  groups, but I have to admit that I am amazed by 
conjectures that seem to be based on unattainable computational achievements as 
premises for their projects.  It does not make a lot of sense.   
 
sokratis.dk:
Now, can I "see" a mind without statistics (or equivalent generative code)? No, 
at least not until someone provides a deep and surprising explication of the 
normal distribution. Even if you start life with a statistics-free mind and 
just go out looking for resources, let's say looking for apples on apple trees, 
or water in water holes, you will stumble upon the normal distribution, first 
you walk into a couple of apple trees here and there, then into a cluster, you 
reach a plateau and then decline again. What could be simpler! It should come 
right after me Tarzan, you Jane!
 
 
Me: I may be misinterpreting what you said, but it looks like you said that 
since you can see distributions everywhere they should be used as the basis for 
AGI.  That kind of reasoning sounds like it might really go down with the 
statistics-based-AGIers but it does not seem particularly persuasive to me.  
 
 
sokratis.dk:
Now, we do have a substantial statistical toolbox that we have not really 
deployed towards AGI, the main reason being its difficulty capturing 
generative, recursive, self-similar models: the reason the word "models" 
appears in these two specific locations in this paragraph is not to be 
explained by a Gaussian mix or any other probabilistic tool, it is all grammar 
and syntax.
 
 
Me: I think you are saying that statistics has difficulty capturing 
computational syntax of generative, recursive and self-similar models.  You 
cannot use statistics to capture everything there is about a resource (in spite 
of what I am guessing is your unspoken fantasy that such a thing is 
theoretically attainable - given the propensity of people in this group to 
believe that unattainable computational achievements can stand as the sound 
premises for their AGI conjectures).  So if you actually wanted to use 
statistics to capture something about the generative, recursive and 
self-similar models you could do so if you just went ahead and did it.  But, 
even if the result of the effort was interesting it would not make your AGI 
project attainable.  There are many things that cannot be measured and the idea 
that by forcing a bunch of different kinds of measurements in with a bunch of 
estimates your going to get be able to use the smush to produce insight seems a 
little far-fetched to me.
 
 
 
My current theory in Simple AGI is that knowledge is based on structure and 
reasons.  Using the form of your argument I could say that, since you can see 
structure and reasons in everything it stands that this can be used as the 
basis for AGI.  (What could be simpler?)  Well that argument is not very 
strong, but the thing is that I can see structure and reasons in thought and 
that is why I believe that these components are so important in AGI.
 
You cannot readily find the reasons and the structures in every system of ideas 
just as you can't measure every part of an idea or even determine what a 
reasonable domain of measurement might be for every idea.  But you can find 
structure and reasons in thought even when you can't find statistics.  
 
Jim Bromer 

 
Subject: Re: [agi] A Very Simple AGI Project
From: [email protected]
Date: Wed, 31 Jul 2013 09:41:51 +0200
To: [email protected]

On 30.07.2013, at 02:18, Jim Bromer <[email protected]> wrote:




I am interested in discussing AGI, not because I have it all figured out, but 
because I don't.
 
You started to say: "Simple learning, statistics transcending..."



Yes, but as a public forum, in addition to its entertainment and social value, 
it obliges us to uphold high standards of work and homework, and it is doubtful 
the most frequent posters have been keeping these high standards. And those few 
here who have simple solutions and simple refutations would be better off 
delivering them but not too often, obviously repetition after a point is not a 
virtue, rather a low standard.
Now, can I "see" a mind without statistics (or equivalent generative code)? No, 
at least not until someone provides a deep and surprising explication of the 
normal distribution. Even if you start life with a statistics-free mind and 
just go out looking for resources, let's say looking for apples on apple trees, 
or water in water holes, you will stumble upon the normal distribution, first 
you walk into a couple of apple trees here and there, then into a cluster, you 
reach a plateau and then decline again. What could be simpler! It should come 
right after me Tarzan, you Jane!
It is telling how indispensable random number generators are in most kinds of 
scientific code. I have previously remarked that unpredictability is probably a 
desirable feature in complex cognitive and social systems, while someone here 
kind of missed the point and replied that unpredictability is merely the result 
of complexity. Now, we do have a substantial statistical toolbox that we have 
not really deployed towards AGI, the main reason being its difficulty capturing 
generative, recursive, self-similar models: the reason the word "models" 
appears in these two specific locations in this paragraph is not to be 
explained by a Gaussian mix or any other probabilistic tool, it is all grammar 
and syntax.
Bring it on!
AT


  
    
      
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