Re: topmind: ID is potentially testable
- From: "Zachriel" <angelmailSPAM@xxxxxxxxxxxx>
- Date: Wed, 3 May 2006 07:34:25 -0400
"topmind" <topmind@xxxxxxxxxxxxxxxx> wrote in message
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Zachriel wrote:
"topmind" <topmind@xxxxxxxxxxxxxxxx> wrote in message
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Zachriel wrote:
"topmind" <topmind@xxxxxxxxxxxxxxxx> wrote in message
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Zachriel wrote:
"topmind" <topmind@xxxxxxxxxxxxxxxx> wrote in message
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<snip>
If there was a bit-map of the Mona
Lisa within the human genome, there
is a very high probability it would have
been noticed because it would stick
out like a statistical sore thumb.
(Note the qualification to probability and to the specific encoding
scheme.)
Not all encryptions of an image would be detectable. There are
unlimited
numbers of methods of encoding and encryption, including
encryptions
unbreakable with current technology.
I realize that, but that is not the issue being raised here. Most
of
the algorithms listed by those guys appear to look for repeating
codon
sequences, perhaps with typical transpositions and mutuations as
found
in biology. However, those kinds of patterns would NOT be found in
typical bitmapped images (such as Mona).
"Most". What about the rest?
Perhaps all. If you have a favorite that WOULD HAVE detected Mona if in
those studies, by all means point the damned thing out. What are you
afraid of? Scrutity?
Generalized pattern recognition software has been used repeatedly by
genomic
researchers. Lilith provided you ample direction to understanding. But
it's
hard to see when you cover your eyes.
Other than the human mind, THERE IS NO SUCH THING as "Generalized
pattern recognition software".
Did I point out that the genome has been printed out in a variety of
formats
(sometimes in color) and people have visually scanned the pages?
Unless the scan lines are lined up properly (the line width is known),
most bitmapped images will not stand out from randomness to the human
eye, especially if the palette mapping is not known (which is the
likely case).
So, in other words, the human mind is not as generalized as you had
indicated.
That is why it is best to use a computer to try the
myriad scan-line widths that would need to be tested.
The human eye would be best left to evaluating the candidates
identified by automated processes, not the other way around.
You want to detect an image, specifically an image of the Mona Lisa, but you
don't even know what it means to be an image. More importantly, you don't
even care.
Did you know that the human mind is not completely generalized, but works
within a specific sensory and analytical framework?
I am not sure what your point is here.
Of course not.
This is part of the reason why humans
flip burgers for 7 dollars an hour instead of machines for 50-cents per
hour.
Yes, there are algorithms that detect snippets of exact matches or
nearly exact matches (codon sequences), but that is not what you need
for most images. I've studied the bitmaps of various images.
Tell, us. Where is your statistical analysis of the content of a bit-map
of
the Mona Lisa? Of generalized images?
Why is it my burden to show you? Youses are the ones who claimed that
stuff already tried would have found Mona (as a test case). You claim,
your prove.
You just claimed that you had "studied the bitmaps of various images". Was
this a lie?
topmind: "I've studied the bitmaps of various images."
"Good enough for Mona" is NOT the default.
Moving the goalposts and consistently ignoring evidence that is contrary to
your prejudice.
Recurrence time statistics: versatile tools for genomic DNA sequence
analysis.
Cao Y, Tung WW, Gao JB, Qi Y.
"Our method ... to extract all the repeat-related and periodic or
quasi-periodic features ... without any prior knowledge on the consensus
sequence of those features"
http://tinyurl.com/gs8vn
--
topmind: "Whether my victories are real or hallucinations, they are
satisfying either way."
Zachriel
http://zachriel.blogspot.com/
[snip]
Zachriel, angel that rules over memory, presides over the planet
Jupiter.
http://zachriel.blogspot.com/
-T-
.
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