On 1/31/2012 19:01, Craig Weinberg wrote:
On Jan 31, 12:45 pm, acw<a...@lavabit.com>  wrote:

A digital or analog camera would get similar amounts of noise as the
eye, actually probably less than the eye.

Why do you say that? Have you ever taken a photo with the lens cap on?
First, the eyes don't have a perfect lens cap, photons get through quite well. Second, no, but I've seen photos taken in almost (as was feasible to be) dark rooms, and there tends to be some noise, if you don't see it, try using some filters to better differentiate the pixels.
I just looked at my digital camera in my phone and blocked the lens
with my hand and there is no noise or snow whatsoever.
Check the pixel values directly then.
In an very dark room, a human might as well not perceive any noise as well. Noise is perceived when there's still a few photons here and there hitting the retina.

If I unplug the
monitor from my computer but leave it powered on - no snow.
That's normal if you have a DVI or HDMI digital display - if the data is transmitted digitally, that greatly reduces the chances of it getting damaged. The problem I was talking about wasn't as much about display and transmitting as much as of the limitation of an ideal photon detector. I've seen you mention Feynman and QED - surely that would have given you a decent understanding on the limitations of capture devices (and no, QM does not contradicted by COMP: COMP predicts the 1p indeterminacy which gives rise locally to some QM/observational laws).


  >  Closed-eye hallucinations and closed-eye visualizations (CEV) are a
distinct class of hallucination. These types of hallucinations generally
only occur when one's eyes are closed or when one is in a darkened room.
They are a form of phosphene.

Phosphene is nothing more than a name. Calling them hallucinations is
a loaded term. They are visual qualia, to me pretty obviously related
to the physical neurology of the optical system and not to any
computational interpretation software. You all can disagree, but I
know that what I see seems like analog 'respiration', not digital

I take it you didn't read the rest of the article? The noise is inherent in any accurate simulation of such systems, be they the eye, an ideal photon detector or some quantum systems. Sure, hallucinations is a term, but is it 'wrong'? If for some reason I've been very tired and my cognitive load is high, my brain could start making errors when recognizing certain patterns - I would be hallucinating as whatever it is I was perceiving wasn't the correct perception. Any such mismatches would be hallucinations. Feed just noise into a neural network and you'll be sure it'll be making errors, and thus "hallucinate" - how do you think dreaming works? If what you perceive is likely 3p correct, it's not a hallucination. OF course, 3p being an inference done from the 1p, you can only bet on what is real and what isn't, you cannot ever truly know, and with COMP, real is just sharable reality.

Also, you are very sure about your raw access to "analog" data, I wonder where you derive that confidence from. I have absolutely no way of knowing I have *direct* access to any analog data, actually I would be very skeptical of that, because of the implications it would have for local physics. Even with qualia, I don't see infinitely complex details - the only thing that I can communicate is that my view is coherent and unified.

  >  The noise probably originates from thermal noise exciting the
photoreceptor cells in the retina

That should be easy enough to test. The point though, is that it has
no business leaking into our visual software. No computer has
comparable thermal noise that leaks into the software, does it? You
can get RF interference, sure, but why would a program tuned precisely
to represent some things and not others include unfiltered noise in
it's representation? I know it's not evidence that contradicts comp,
but it's not supportive of it at all.

I'm sorry, but I don't understand what you mean by 'leaking'. If the data that I captured is noisy (such as visual data), the software will handle noisy data. Nothing more, nothing less. If I do some image recognition or filter or *dynamically reconstruct* the image, it may look much cleaner, which is not that much different from what our visual system is *sometimes* doing (when it was enough matching patterns).

Why don't we see clean images instead of a noisy convoluted mess during
our daily lives? Because we actually "see" patterns which also happen to
"correct" the input data (look at the hierarchical structure of the
cortex or read "On Intelligence" for some examples. I could also link
some PLoS articles about this, but I don't have them handy right now.) -
we don't usually see raw unfiltered inputs.

We shouldn't ever see raw unfiltered inputs, that's why the phosphene
doesn't make sense as a filtered process.

Why not? Well, we don't quite see, completely raw unfiltered inputs, but if the visual system can't recognize any high-level patterns, thus it cannot "fix" the image, I see no reason why noise/static shouldn't be experienced.

Static and noise can occur just as well within COMP - they are
incredibly common within the UD at various levels. Set up a system with
some random rules and you have a good chance of observing noise. Noise
is so damn easy to make... However, if considered from the COMP
perspective, even incompressible noise (Kolmogorov random) is very
common due to 1p indeterminacy. I think you must have the wrong
conception about what COMP really is.

Noise should either be unavoidable or absent, not present if we pay
attention to the front of our visual field and absent if we visualize
darkness. The fact that there is a difference for human vision behind
closed eyes and within the mind's eye would need to be explained.

Imagine you have this amazing piece of software, it can reconstruct images really well, if it can process enough to recognize high-level patterns, it will dynamically redraw the picture to better fit those high-level patterns... it'd be like having your own little master painter constantly improving and embellishing your dull captured noisy image to give you a perfect crystal-clear image - one which uses all the patterns that you could possibly know or recognize. It's all good when you feed it things which are usual and can be understood, but imagine you would be feeding it only noise (you're already feeding it noise, but plenty of information as well, but now it's devoid of information) - what happens now is that either your master painter mismatches ("hallucinates") some patterns, or it just fails to recognize anything and leaves your picture as it is - a mess, "garbage in - garbage out".
I don't know what people think I don't understand about COMP is. It
makes perfect sense to me, it just happens to be exactly wrong in the
real world. In a theoretical world, COMP is the way to go, definitely.

There are many details about COMP which you seem to miss, at least when I read your posts about COMP. Here, it seemed like you were surprised there would be noise in either the 1p indeterminacy of COMP or some non-COMP digital physics - there's absolutely no problem with there being noise in either, in one case you get free incompressible random noise, in the other you get compressible, but not easily humanly recognizable as compressible noise (that is, statistically random). I also have no clear idea about what your theory *actually is*. Some details are understandable, but the whole makes little sense to me, and whatever your thought processes about your theory - they seem opaque to me, and you don't seem to explain why should one theory be preferred over the other and how you got to some conclusion or another. What's worse, we use different terms and sometimes even when using the same terms, the semantics I have for some of the terms and the semantics you have for them are sometimes different.

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