Well, everyone here thinks that algorithms are v. intelligent - if not
now,
then soon, with a little scaling and more sophisticated heuristics.
Just
a
bit more of the same, old.
I agree that they are only slavish routines (no matter how complex) and
will
never be more than a hyperspecialist form of low-level intelligence.
But
you
haven't persuaded me (or I suspect anyone else) that you're actually
offering anything different - not even *conceptually.* You *sound* like
Pei
who was - perhaps still is - offering a "non-algorithmic" form of
logic -
except that it turned out, when you pressed him, to be just another
algorithm after all.
Perhaps there are others like y'all, recognising the limits of algo's,
but
trying for magic sauce solutions.
--------------------------------------------------
From: "Sergio Pissanetzky" <[email protected]>
Sent: Monday, July 16, 2012 1:51 PM
To: "AGI" <[email protected]>
Subject: RE: [agi] Analog Computation
Alan,
That's nonsense. A camera, or a person, can look at a black and white
scene,
light-on or light-off. A person will still recognize the image. How?
You
can't tell. You can only write a monstruous program that will do
nothing
but
what you teach it to do. And you can't improve on that. Your robots
are
clumsy, and you can't improve on that. Your chess-playing machine
can't
play
checkers, and can't even learn how. You need a human to improve on
that.
You
can't do OO-analysis, you need a human to do that. Your semantic web
...
where is it? You can't integrate systems, you need a human to do that.
This
is an AGI blog, and writing program is not AGI, it is using human
slaves
to
row.
Sergio
-----Original Message-----
From: Alan Grimes [mailto:[email protected]]
Sent: Sunday, July 15, 2012 5:46 PM
To: AGI
Subject: Re: [agi] Analog Computation
Sergio Pissanetzky wrote:
I'll use a camera instead of the retina. When light hits a pixel in
that camera, an electric signal is produced and travels to the brain,
I mean the computer. That's it, that's the causal relation, light +
pixel (and the pixel has a position, which is how spatial information
gets encoded) cause signal. Multiply that by 1 million pixels, and
you
have a big causal set. From the signals alone, you can't tell that
the
camera is looking at your mother's face (in Hofstadter's words). But
if you display the signals on a screen, your brain will immediately
recognize the image. That's EI. I did it on a small scale on my PC,
and I now want to do it on a larger scale.
Do you have ANY idea how cameras work?
For every pixel, for every scan interval, the sensor will be affected
by
tens of thousands to millions of photons...
What you get is a number. Typically, in most applications between 0
and
255.
We can abstract that to some floating point value between 0 and 1
where
0
is
almost no light and 1 is sensor saturation.
You are given a matrix of these, We will assume perfect pixels that
are
vertically aligned and there are no sensor artifacts.
Your AI must find and encode the simplest possible theory of what
objects
must exist out in the world to have excited the sensors on your camera
in
such a way.
That is visual perception.
I'm getting sick and tired of reading this ignorant crap out of you. I
expect it from the list clown but you should be smarter than this,
that's
why I'm so disappointed in you. =(
--
E T F
N H E
D E D
Powers are not rights.
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