<div dir="ltr">AI color training. Different hierarchies (not qualia???), patterns represent the colors, and so on....<br><br><a href="https://openaccess.thecvf.com/content_CVPRW_2020/papers/w26/Hickey_Hierarchical_Color_Learning_in_Convolutional_Neural_Networks_CVPRW_2020_paper.pdf">https://openaccess.thecvf.com/content_CVPRW_2020/papers/w26/Hickey_Hierarchical_Color_Learning_in_Convolutional_Neural_Networks_CVPRW_2020_paper.pdf</a><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, Apr 11, 2023 at 1:50 AM Giovanni Santostasi <<a href="mailto:gsantostasi@gmail.com">gsantostasi@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">See, without even knowing this field at all but having worked in neuroscience I correctly predicted how a neuroscientist would talk about this business of colors. It is all about how the neural patterns happen, in which sequence, which brain regions are involved and so and on. Not one single word as "quality" appears anywhere. <br><br><img src="cid:ii_lgc0vb9g0" alt="image.png" width="283" height="440"><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, Apr 11, 2023 at 1:45 AM Giovanni Santostasi <<a href="mailto:gsantostasi@gmail.com" target="_blank">gsantostasi@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><span style="color:rgb(0,0,0);font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:14px">The visual system encodes color by means of a distributed representation: the activity of many neurons preferring different colors, but with broad and overlapping tuning curves. This means that similar colors evoke similar patterns of activity, and neural representations of color can be characterized by low-dimensional “neural color spaces” in which the positions of colors capture similarities between corresponding patterns of activity (</span><a id="m_-1742041201382698336m_618771671313263954gmail-xref-ref-5-1" href="https://www.jneurosci.org/content/33/39/15454#ref-5" aria-describedby="qtip-2" style="margin:0px;padding:0px;border:0px;outline:0px;vertical-align:baseline;font-variant-numeric:inherit;font-variant-east-asian:inherit;font-variant-alternates:inherit;font-weight:700;font-stretch:inherit;font-size:14px;line-height:inherit;font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-kerning:inherit;font-feature-settings:inherit;text-decoration-line:none;color:rgb(0,119,192)" target="_blank">Brouwer and Heeger, 2009</a><span style="color:rgb(0,0,0);font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:14px">).<br></span><h1 id="m_-1742041201382698336m_618771671313263954gmail-page-title" style="margin:0px 0px 20px;padding:10px 0px 0px;border:0px;outline:0px;vertical-align:baseline;font-variant-numeric:normal;font-variant-east-asian:normal;font-variant-alternates:normal;font-kerning:auto;font-feature-settings:normal;font-weight:400;font-stretch:normal;line-height:1.22em;font-family:Helvetica,Arial,sans-serif;letter-spacing:-0.03em;color:rgb(10,77,122)"><font size="2">Categorical Clustering of the Neural Representation of Color</font></h1><a href="https://www.jneurosci.org/content/33/39/15454" target="_blank">https://www.jneurosci.org/content/33/39/15454</a><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, Apr 11, 2023 at 1:37 AM Giovanni Santostasi <<a href="mailto:gsantostasi@gmail.com" target="_blank">gsantostasi@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">Another important paper. The AI actually came up with the idea of color in an emergent way. Patterns is all what there is. <br><h1 style="box-sizing:border-box;margin:0.375rem 0px 0.75rem;font-family:"Noto Sans",Arial,Helvetica,sans-serif;line-height:1.33333;color:rgb(33,33,33)"><font size="2">Emergent color categorization in a neural network trained for object recognition</font></h1><a href="https://elifesciences.org/articles/76472" target="_blank">https://elifesciences.org/articles/76472</a><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, Apr 11, 2023 at 1:22 AM Giovanni Santostasi <<a href="mailto:gsantostasi@gmail.com" target="_blank">gsantostasi@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">Ok here is a paper that should clarify a lot on this topic of color perception. <br>Let's read it and see what we get from it. It seems to me that again they simply used fMRI (so basically brain pattern) to deduce all what there is to deduce about redness and the similar. <br><h1 style="box-sizing:border-box;margin:0px;line-height:3rem;color:rgb(11,11,11);font-family:Montserrat,serif;padding:0.1rem 0px 0.5rem"><font size="2">Neural representations of perceptual color experience in the human ventral visual pathway</font></h1><a href="https://www.pnas.org/doi/10.1073/pnas.1911041117" target="_blank">https://www.pnas.org/doi/10.1073/pnas.1911041117</a><br><div><br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, Apr 10, 2023 at 4:48 PM Jason Resch via extropy-chat <<a href="mailto:extropy-chat@lists.extropy.org" target="_blank">extropy-chat@lists.extropy.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="auto"><div><br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, Apr 10, 2023, 7:08 PM Brent Allsop via extropy-chat <<a href="mailto:extropy-chat@lists.extropy.org" target="_blank">extropy-chat@lists.extropy.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, Apr 10, 2023 at 11:11 AM Jason Resch via extropy-chat <<a href="mailto:extropy-chat@lists.extropy.org" rel="noreferrer" target="_blank">extropy-chat@lists.extropy.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr">On Sun, Apr 9, 2023 at 5:20 PM Giovanni Santostasi via extropy-chat <<a href="mailto:extropy-chat@lists.extropy.org" rel="noreferrer" target="_blank">extropy-chat@lists.extropy.org</a>> wrote:<br></div><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">If this doesn't destroy completely anybody illusion that the a brain made of meat (and particular stuff like glutamate) I don't know what else it could. These people will always believe that meat brains are necessary because God made them so. No amound of science would convince them. <br></div></blockquote><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">2) You can train an AI to recognize activation patterns in the brain and associate them with particular stimuli. This has been tried with words and even images both in wake and dreaming state. Here an example that should blow everybody minds:<br><a href="https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf" rel="noreferrer" target="_blank">https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf</a><br>Again, from this study we can see that it doesn't matter how the pattern is generated, but that there is a pattern of activation. These patterns are unique for each individual but statistically they are similar enough that after training over many subjects you can give a statistical estimate that the person is seeing or even thinking about something in particular. Again, IT WORKS people ! <br></div></blockquote><div><br></div><div><div>I consider this a knock-down argument against the functional role of glutamate (or other molecules) in the sensation of red. These tests use only blood flow data, which is a proxy for neural activity. They are not measuring ratios of specific neurotransmitters or molecules, or introspecting the activity within the cell, the fMRI looks only at which neurons are more vs. less active. And yet, from this data we can extract images and colors. This proves that neural activity embodies this information.</div></div></div></div></blockquote><div><br></div><div>I guess I've failed to communicate something important about why we use glutamate. The primary reason we use glutamate is precisely because of its ease of falsifiability. I fully expect redness to be falsified (someone will experience redness with no glutamate present) and something different from glutamate will then be tried, and eventually something will be found to be experimentally proven to be redness. Easy and obvious falsifiability is what everyone is missing, so THAT is what I'm most attempting to communicate with the glutamate example.</div><div><br></div><div>If you guys think there are knock down arguments for why a redness quality is simply due to recursive network configurations (I am not yet convinced, and am still predicting otherwise (see below), and it's much easier to say glutamate than whatever stuff you guys are talking about, which nobody is concisely stating, and I have problems understanding), then please, every time I say 'glutamate', do a substitution for anything you like such as 'Recursive network model A', or any other yet to be falsified theory. And let's leave it up to the experimentalists to prove who is right, like good, humble, theoretical scientists should.</div><div><br></div><div><br></div><div>P.S.</div><div>At least <a href="https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf" rel="noreferrer" target="_blank">that paper</a> you referenced has pictures (composed of real qualities), not just abstract text (tells you nothing about qualities), as text only would be completely meaningless, right?</div><div>But why don't you guys ask the publishers of that paper, how they came up with the qualities displayed on the images depicting what they are detecting?</div><div>Here is a link to <a href="https://www.youtube.com/watch?v=6FsH7RK1S2E&t=1s" rel="noreferrer" target="_blank">Jack Galant's work</a>, done over a decade ago, to which all these modern examples are just derivative works, easily done with modern AI tools.</div><div>When I saw <a href="https://www.youtube.com/watch?v=6FsH7RK1S2E&t=1s" rel="noreferrer" target="_blank">Jack Galant's work</a> back then, I knew he had a problem determining what qualities to display on his screens, depicting what he was detecting. The fMRI only providing abstract qualityless data which is meaningless without a quality grounded dictionary.<br></div><div>So I called him and asked him how he knew what qualities to display. He immediately admitted they "false-colored" them (Jack Gallant's words). They used the original color codes in the digital images they were showing to their subjects, to determine what color to display. In other words, they were grounding their colors to physical light, which is nothing like either the properties of a strawberry, which the light merely represents, or the very different properties of conscious knowledge they are detecting and describing with qualityless abstract text. As Giovanni admits, they are correcting for any changes in physical properties or qualities they are detecting so they can falsely map all those diverse sets of properties they are detecting back to the same false colored light, blinding them to any possible inverted qualities they may be detecting in all that diversity.</div><div><br></div><div>By the way, I added this <a href="https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf" rel="noreferrer" target="_blank">Japanese paper</a> to the list of yet another example of quality blind papers, including Jack Galant's work that only uses one falsely grounded abstract word for all things representing 'red' <a href="https://canonizer.com/topic/603-Color-Exprnc-Observation-Issue/1-Agreement" rel="noreferrer" target="_blank">here</a>.<br></div><div><br></div><div>If anyone finds a peer reviewed paper that is not quality blind. (other than <a href="https://www.dropbox.com/s/k9x4uh83yex4ecw/Physicists%20Don%27t%20Understand%20Color.docx?dl=0" rel="noreferrer" target="_blank">mine</a>, which is about to be published) will you please let me know about one? As I will trust someone that believes and understands that qualities are necessarily real properties of real hallucinations in our brain. I predict they are just the physical properties they are detecting but only abstractly describing and then false coloring.</div></div></div></blockquote></div></div><div dir="auto"><br></div><div dir="auto"><br></div><div dir="auto">Brent,</div><div dir="auto"><br></div><div dir="auto">I appreciate that added detail and correction. If the colors in the reconstructed images are false colors or inferred by the AI from the reconstructed image then I retract my statement of it being a knockdown argument against the molecular basis of color qualia. I still suspect color information is encoded in the patterns of neural activity, but it may be at a low enough level that the fMRI lacks the spatial resolution to detect it.</div><div dir="auto"><br></div><div dir="auto">Jason </div></div>
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