>> Why are images almost always more powerful than the corresponding symbols? 
>> Why do they communicate so much faster?

Um . . . . dude . . . . it's just a bandwidth thing.

Think about images vs. visual symbols vs. word descriptions vs. names.

It's a spectrum from high-bandwidth information transfer to almost pure 
reference tags.

If it's something you've never run across before, images are best -- high 
bandwidth but then you end up with high mental processing costs.

For familiar items, word descriptions (or better yet, single word names) 
require little bandwidth and little in the way of subsequent processing costs.

  ----- Original Message ----- 
  From: Mike Tintner 
  To: agi@v2.listbox.com 
  Sent: Sunday, March 30, 2008 4:02 PM
  Subject: Re: [agi] Symbols


  In this & surrounding discussions, everyone seems deeply confused - & it's 
nothing personal, so is our entire culture - about the difference between

  SYMBOLS

  1.  "Derek Zahn"  "curly hair" "big jaw"  "intelligent eyes"  ..... etc. etc

  and 

  IMAGES

  2. http://robot-club.com/teamtoad/nerc/h2-derek-sunflower.JPG

  I suggest that everytime you want to think about this area, you all put 
symbols besides the corresponding images, and slowly it will start to become 
clear that each does things the other CAN'T do, period.

  We are all next to illiterate - and I mean, mind-blowingly ignorant - about 
how images function. What, for example, does an image of D.Z. or any person, 
do, that no amount of symbols - whether words, numbers, algebraic formulae, or 
logical propositions -  could ever do?

  Why are images almost always more powerful than the corresponding symbols? 
Why do they communicate so much faster?

    Derek:

    Related obliquely to the discussion about pattern discovery algorithms.... 
What is a symbol?
     
    I am not sure that I am using the words in this post in exactly the same 
way they are normally used by cognitive scientists; to the extent that causes 
confusion, I'm sorry.  I'd rather use words in their strict conventional sense 
but I do not fully understand what that is.  These thoughts are fuzzier than 
I'd like; if I was better at de-fuzzifying them I might be a pro instead of an 
amateur!
     
    Proposition:  a "symbol" is a token with both denotative and 
model-theoretic semantics.
     
    The denotative semantacs are what makes a symbol refer to something or "be 
about" something.  The model-theoretic semantics allow symbol processing 
operations to occur (such as reasoning).
     
    I believe this is a somewhat more restrictive use of the word "symbol" than 
is necessarily implied by Newell and Simon in the Physical Symbol System 
Hypothesis, but my aim is engineering rather than philosophy.
     
    I'm actually somewhat skeptical that human beings use symbols in this sense 
for much of our cognition.  We appear to be a million times better at it than 
any other animal, and that is the special thing that makes us so great, but we 
still aren't very good at it.  However, most of the things we want to build AGI 
*for* require us to greatly expand the symbol processing capabilities of mere 
humans.  I think we're mostly interested in building artificial scientists and 
engineers rather than artificial musicians.  Since computer programs, 
engineering drawings, and physics theories are explicitly symbolic constructs, 
we're more interested in effectively creating symbols than in the totality of 
the murky "subsymbolic" world supporting it.  To what extent can we separate 
them?  I wish I knew.
     
    In this view, "subsymbolic" simply refers to tokens that lack some of the 
features of symbols.  For example, a representation of a pixel from a camera 
has clear denotational semantics but it is not elaborated as well as a better 
symbol would be ("the light coming from direction A at time B" is not as useful 
as "the light reflecting off of Fred's pinky fingernail").  Similarly, and more 
importantly, subsymbolic products of sensory systems lack useful 
model-theoretic semantics.  The "origin of symbols" problem involves how those 
semantics arise -- and to me it's the most interesting piece of the AGI puzzle.
     
    Is anybody else interested in this kind of question, or am I simply 
inventing issues that are not meaningful and useful?



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