You still don’t understand.

The problem of AGI is for a machine to be able to deal with *new* unpredictable 
elements – as humans can – the endless unpredictable things that can crop up in 
any field from a street to a text – AND to be able to proactively produce new 
elements – to independently explore the world, and move down new paths and into 
new fields, and seek out new objects.

So you don’t need a program that can produce an endless variety of *patterns.* 
Patterns can’t produce new elements OR altogether  new patterns other than 
themselves. A machine that could produce an endless diversification of 
patchworks would however be AGI- although that’s not at all a natural entrance 
point for AGI.

P.S. There is only one way,. broadly, to actively incorporate new elements – 
and that is for a robot to reach out and grab new objects. And there is only 
one way broadly to find new ways of reacting to new objects/obstacles, and that 
is for a robot to reach out and grope for new lines of movement for its body.,  
 There is no way for a boxed in recipe/algorithm by itself to incorporate new 
elements. Since you don’t believe in robotics – basically because you’re lazy 
and unwilling to incorporate any new technologies in your thinking - you will 
never be able to deal with AGI, and will continue to think like other AGI-ers 
forever inside rather than outside the box/algo/formula/pattern.

From: Jim Bromer 
Sent: Tuesday, November 20, 2012 1:26 PM
To: AGI 
Subject: Re: [agi] Randomness: Mathematics as Perceptual Bias

Well, I can't provide an example of an AGI program -that actually works - 
because it is still beyond the fringes of science. However, we have seen 
expected milestones go by: chess programs that can beat almost all human 
players, Watson who can beat all human Jeopardy players (so far), cars that 
drive themselves, toy helicopters that can learn to fly upside down and do 
other stunts while going through small windows and so on. 
The problem of finding "an example" of a generalization of all generalizations 
is a philosophical conundrum. (It cannot be done.)  And finding examples that 
produce an endless variety of transformations is really not the problem we are 
interested in. We want to find a computer program that is capable of learning 
-like human beings-. Since this is well beyond our abilities we are looking for 
ways to get them to display some human-like capabilities of thought. But, while 
I don't have an example of an AGI program that actually works, I can think 
about things like a program that can draw a massive variety of types or a 
program that can output a massive variety of patterns. While the theoretical 
question was interesting to me (you need to use variable length data fields for 
the characteristics that you want to use) it is not AI because these "examples" 
would not be responding to Input Output. So I would not expect anyone to be 
very interested in an actual program to output a massive variety of visual 
patterns. I am not going to spend the time to make an example of something 
which no one would be interested in.
Once you change the challenge so that it is becomes: write a program that will 
create an uncountable variety of patterns based on Input, you have taken the 
program nearer to AGI because now, part of the challenge is to get it to react 
to Input-Output in a rational way.  The problem is not whether a computer 
program can potentially create (or model) more patterns then anyone could 
imagine count or keep track of, but whether or not such a potential could be 
harnessed to demonstrate reasoned intelligence.

The challenge is interesting.  For instance, could I write a program that could 
create an uncountable variety of patterns based only on images of garbage.  
Well, if the input images were constrained to images of garbage then yes I 
could.  If the input was unconstrained then no I couldn't because it requires 
intelligence to identify images of garbage.

So I am in an odd situation.  I believe I could write a program that produced 
an uncountable variety of patterns but so what?  No one would be interested.  
It is an interesting challenge because there are some theoretical problems that 
few people are even aware of, but I am pretty sure that I could do it. 

Maybe I should try it sometime just to make sure I did figure it out.
Jim Bromer


On Tue, Nov 20, 2012 at 4:44 AM, Mike Tintner <[email protected]> wrote:

  Jim: The idea is that we are arguing is that computers have a potential to 
'represent' an astounding variety of things and relations.
  You seem quite incapable of distinguishing between “computers” and “programs” 
*Computers* currently have billions of apps and programs - potentially if not 
actually indeed representing all things. Programs – algorithmic programs – are 
just complex recipes with an extremely limited stock of a few ingredients, and 
zero new elements.
  You seem equally incapable of understanding the problem of AGI, which can be 
expressed as the incapacity of programs to incorporate any new elements. 
Patterns- algorithms – formulae – recipes – all only apply to a limited stock 
of elements.
  But in your wild imagination they are already all-knowing and 
all-encompassing and have already solved the problem of AGI.
  You are confusing the recipe with the chef - AGI is about creating a chef 
that can create any dish, and mix any new elements into dishes – – unlike 
algorithms and patterns which self-evidently have only a very limited set of 
elements – and even then run into problems of combinatorial complexity – the 
purely narrow AI problem that obsesses you.
  Examples, specifics, Jim, and not just waffle – of these all-growing, 
all-new-element-producing patterns, and these all-knowing, all-encompassing 
algorithms.
  You guys are really maintaining absolute nonsense – and you can’t produce a 
single example to back up your arguments.
  From: Jim Bromer 
  Sent: Tuesday, November 20, 2012 8:28 AM
  To: AGI
  Subject: Re: [agi] Randomness: Mathematics as Perceptual Bias
  I guess Mike was saying that the variety of patterns that he provided a link 
to were, "unlike natural evolution, in which new elements, like eyes, limbs, 
opposable thumbs, voiceboxes, etc emerge..."
  But again, he is declaring that complex arrangements of cells are "elements" 
so even if I misunderstood how he was using the references to the images of 
patterns, I am still left with sense that he is not basing his argument on the 
idea that there are an infinite number of 'elements' but on the idea that an 
infinite number of complexes can emerge.
  No one is saying that a computer can truly represent an infinite variety of 
anything, no more than we are we saying that a single computer can know 
everything. No human being knows everything that human beings have ever known. 
The idea is that we are arguing is that computers have a potential to 
'represent' an astounding variety of things and relations.
  Jim Bromer



  On Tue, Nov 20, 2012 at 3:13 AM, Jim Bromer <[email protected]> wrote:

    On Mon, Nov 19, 2012 at 8:31 PM, Mike Tintner <[email protected]> 
wrote:

      A specific pattern – Mandelbrot, Fourier transform, cellular automaton 
no. 30 etc.. specific. 
      Examples are specific, Aaron, not general.
      And the “pattern of neuronal firings in your brain” is a fictional 
product of your imagination.
      Specifics. Evidence. e.g.
      
https://www.google.com/search?num=10&hl=en&safe=off&site=imghp&tbm=isch&source=hp&biw=1340&bih=690&q=patterns&oq=patterns&gs_l=img.3..0l10.1679.2746.0.3037.8.7.0.1.1.0.159.516.5j2.7.0...0.0...1ac.1.hHfKyrSHq4M
      And here are “evolving patterns”, except that they don’t truly evolve 
with new elements – they aren’t truly “emergent”
    Mike's idea of a "patchwork" is just a fictional product of his 
imagination, if that is the attitude that he wants to take. And Mike's 
reference of the patterns in the images he provides the links to are truly 
formed from non changing elements of pixels of computer imagery. If his 
argument can be exemplified by the seemingly infinite variety of different 
patterns that can be found by searching on Google then that proves that the 
unchanging elements of pixlation can indeed represent the variety of different 
kinds of patterns that Mike is talking about. This seems like a contradiction 
of his basic argument since the question seems to hinge on whether computers 
can potentially -represent- a massive variety of patterns.
    Jim Bromer

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