Sources about AI/our vision - we were promised smart AI long ago - we still wait:
Baylor College of Medicine (2011, May 9). Brain performs near optimal visual search. ScienceDaily:
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Quote: "... This ability to recognize target objects surrounded by distracters is one of the remarkable functions of our nervous system. ... "Target detection involves integrating information from multiple locations," said Ma. "Many objects might look like the target for which you are searching. It is a cognitive judgment as well as a visual one." ... "The visual system is automatically and subconsciously doing complex tasks," said Ma. "People see objects and how they relate to one another. We don't just see with our eyes. We see with our brains. Our eyes are the camera, but the process of interpreting the image in our brains is seeing." ..."
Expert system:
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Quote: "... Disadvantages
- The Garbage In, Garbage Out (GIGO) phenomenon: A system that uses expert-system technology provides no guarantee about the quality of the rules on which it operates. All self-designated "experts" are not necessarily so, and one notable challenge in expert system design is in getting a system to recognize the limits to its knowledge.
- Expert systems are notoriously narrow in their domain of knowledge ? as an amusing example, a researcher used the "skin disease" expert system to diagnose his rustbucket car as likely to have developed measles ? and the systems are thus prone to making errors that humans would easily spot. ...
- An expert system or rule-based approach is not optimal for all problems, and considerable knowledge is required so as to not misapply the systems. ...
- Ease of rule creation and rule modification can be double-edged. A system can be sabotaged by a non-knowledgeable user who can easily add worthless rules or rules that conflict with existing ones ..."
Horizon-effect:
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Quote: "... When evaluating a large game tree using techniques such as minimax or alpha-beta pruning, search depth is limited for feasibility reasons. However, evaluating a partial tree may give a misleading result. When a significant change exists just over the 'horizon' of the search depth, the computational device falls victim to the horizon effect. ..."
Mar. 7, 2008 Insect's Sensory Data Tells A New Story About Neural Networks:
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Quote: "... "In this system, the motion-sensitive neurons emit spikes very often and very precisely," said Nemenman. "Historically, people have observed a lot more random spike intervals. This research is a departure from the traditional understanding in that we see that the precision of spike timing that carries information about the fly's rotation is a factor of ten higher than even the most daring previous estimates." ... "This may be one of the main reasons why artificial neural networks do not perform anywhere comparable to a mammalian visual brain," said Nemenman ..."
University of Rochester Medical Center (2009, March 26). What Separates Humans From Mice? Bigger, Faster Astrocytes In Brain. ScienceDaily:
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Quote: "... There aren't many differences known between the rodent brain and the human brain, but we are finding striking differences in the astrocytes. ... "We have not really been able to understand why the human brain is so much more capable than that of any other animal," said neuroscientist Maiken Nedergaard, M.D., D.M.Sc., who led the study. "Some people have thought that it's simply that a bigger brain is a better brain, but an elephant's brain is bigger than a person's, for example, but it's not nearly as powerful. So that's not the answer. ... Rather than realizing their tools were incomplete, scientists assumed that astrocytes were silent. ... The brain's two signaling systems ? one composed of neurons, and one of astrocytes ? complement each other, Nedergaard said. Neurons send signals extremely quickly over long distances ? the hand touches a hot stove, for instance, and the brain detects the danger and moves the hand away, instantly. Astrocytes, in contrast, send slower signals whose function is still being worked out by scientists. ... And then you have a much slower network composed of astrocytes whose signals are 10,000 times slower but which might be able to process the information in a more sophisticated manner and retrieve memories. ..."
Salk Institute (2009, September 28). Attention Makes Sensory Signals Stand Out Amidst Background Noise In Brain. ScienceDaily:
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Quote: "... "Attention is an essential part of perception," says Reynolds. ..."
University Of California - Los Angeles (2004, December 14). UCLA Neuroscientist Gains Insights Into Human Brain From Study Of Marine Snail. ScienceDaily:
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Quote: "... "Our work implies that the brain mechanisms for forming these kinds of associations might be extremely similar in snails and higher organisms. People may think invertebrates are not very sophisticated, but we don't appreciate just how complicated their nervous systems are, and how complex their behaviors are. We don't fully understand even very simple kinds of learning in these animals."..."
Dec. 22, 2007 Neuronal Circuits Able To Rewire On The Fly To Sharpen Senses:
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Quote: "... "If you think of the brain like a computer, then the connections between neurons are like the software that the brain is running. Our work shows that this biological software is changed rapidly as a function of the kind of input that the system receives," said Nathan Urban, associate professor of biological sciences at Carnegie Mellon. ..."
2004-06-16, Sciencedaily: Gray Matters: New Clues Into How Neurons Process Information:
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Quote: "... "It's amazing that after a hundred years of modern neuroscience research, we still don't know the basic information processing functions of a neuron," said Bartlett Mel. ... "For lack of a better idea, it has always been thought that a brain cell sums up its excitatory inputs linearly, meaning that the excitation caused by two inputs A and B activated together equals the sum of excitations caused by A and B presented separately."
"We show that the cell significantly violates that rule," Mel said.
The team found that the summation of information within an individual neuron depends on where the inputs occur, relative to each other, on the surface of the cell. ... While the results are promising, the team is certain this is not the final word on the pyramidal neuron. ... "Undoubtedly, this is still too simple a model," Mel said. "But the two-layer model is a better description, it seems, than to assume that the neuron is simply combining everything linearly from everywhere. That's clearly not what these data show." ... Mel emphasizes that the "arithmetic" rules he and his colleagues found in pyramidal neurons may not apply to all neurons in the brain.
"There are other neurons that have different shapes, inputs, morphologies and ion channels," he said. "There might be a dozen different answers to the question, depending on what neuron you're looking at." ... [ Remark: This is a tentative model - we do not know if the brain behaves exactly as a computer!: ] "We tend to view the brain as a computer," he said. "If we want to figure out how this computer works, we must first know how its separate parts function." ..."
Dec. 27, 2005 MIT Researcher Finds Neuron Growth In Adult Brain:
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Quote: "... Despite the prevailing belief that adult brain cells don't grow, a researcher at MIT's Picower Institute for Learning and Memory reports in the Dec. 27 issue of Public Library of Science (PLoS) Biology that structural remodeling of neurons does in fact occur in mature brains. ..."
Oct. 12, 2004 Under The Surface, The Brain Seethes With Undiscovered Activity:
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Quote: "... There's an old myth that we only use 10 percent of our brains, but researchers at the University of Rochester have found in reality that roughly 80 percent of our cognitive power may be cranking away on tasks completely unknown to us. ... Placing the ferrets [
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] in a darkened room revealed that older ferrets' brains were still humming along at 80 percent as if they were processing visual information. Since this activity was absent in the youngsters, Weliky and his colleagues were left to wonder: What is the visual cortex so busy processing when there's no image to process? ... Weliky found two surprises. First, while the neurons of adult ferrets statistically seemed to respond similarly to the statistics of the film itself, younger ferrets had almost no relationship. This suggests that though the young ferrets are taking in and processing visual stimuli, they're not processing the stimuli in a way that reflects reality. ... Accepting all the neural traffic of a conscious brain as part of the equation let Weliky get a better idea of the actual processing going on. As it turned out, one of his control tests yielded insight into neural activity no one expected. ... This suggests that with your eyes closed, your visual processing is already running at 80 percent, and that opening your eyes only adds the last 20 percent. The big question here is what is the brain doing when it's idling, because it's obviously doing something important." ..."
Mar. 8, 2008 Can Moths Or Butterflies Remember What They Learned As Caterpillars?:
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Quote: "... However, scientists at Georgetown University recently discovered that a moth can indeed remember what it learned as a caterpillar. ..."
Do the gene expression orchestre influence the neurons "behavior/calculation"? And therefore us?:
Dec. 12, 2007 When She's Turned On, Some Of Her Genes Turn Off, Fish Study Shows:
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Quote: "... When a female is attracted to a male, entire suites of genes in her brain turn on and off, show biologists from The University of Texas at Austin studying swordtail fish. ... This is one of few studies to link changes in the expression of genes with changes in an individual's behavior in different social situations ... "What we have not appreciated until now is how dynamic the genome is," said Hofmann. "It is constantly changing and even in a very short period of time, 10 percent of the protein-coding genome can change its activity. We now have a genomic view of these dynamic processes within a social context." ..."
Apr. 23, 2008 Nurture Over Nature: Certain Genes Are Turned On Or Off By Geography And Lifestyle, Study Suggests:
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Quote: "... Although Idaghdour initially hypothesized that environmental factors would play a role in gene expression, he didn't expect such large differences. About 30 percent of genes were differentially expressed between urban dwellers and mountain agrarians. ..."
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What Computers Can't Do:
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Quote: "... [My personel opinion - it should also be encompas what "guides" us (soul/consciousness?) or if everything or a part are consciousness choices?: ] Dreyfus argued that human intelligence and expertise depend primarily on unconscious instincts rather than conscious symbolic manipulation, and that these unconscious skills could never be captured in formal rules. ... When Dreyfus' ideas were first introduced in the middle 60's, they were met with ridicule and outright hostility.[2][3] But by the 1980s, many of his perspectives were rediscovered by researchers working in robotics and the new field of connectionism ... [A] great misunderstanding accounts for public confusion about thinking machines, a misunderstanding perpetrated by the unrealistic claims researchers in AI have been making, claims that thinking machines are already here, or at any rate, just around the corner.[6] ... Dreyfus argued that human problem solving and expertise depend on our background sense of the context, of what is important and interesting given the situation, [] rather than on the process of searching through combinations of possibilities to find what we need. [] Dreyfus would describe it in 1986 as the difference between "knowing-that" and "knowing-how", based on Heidegger's distinction of present-at-hand and ready-to-hand.[12] ... Our sense of the situation is based, Dreyfus argues, on our goals, our bodies and our culture?all of our unconscious intuitions, attitudes and knowledge about the world. This ?context? or "background" (related to Heidegger's Dasein) is a form of knowledge that is not stored in our brains symbolically, but intuitively in some way. It affects what we notice and what we don't notice, what we expect and what possibilities we don't consider: we discriminate between what is essential and inessential. The things that are inessential are relegated to our "fringe consciousness" (borrowing a phrase from William James): the millions of things we're aware of, but we're not really thinking about right now.
Dreyfus claimed that he could see no way that AI programs, as they were implemented in the 70s and 80s, could capture this background or do the kind of fast problem solving that it allows. He argued that our unconscious knowledge could never be captured symbolically. If AI could not find a way to address these issues, then it was doomed to failure, an exercise in "tree climbing with one's eyes on the moon."[13] ... Dreyfus, who taught at MIT, remembers that his colleagues working in AI "dared not be seen having lunch with me."[22] ... Failed predictions. As Dreyfus had foreseen, the grandiose predictions of early AI researchers failed to come true. ... Today researchers are far more reluctant to make the kind of predictions that were made in the early days. (Although some futurists, such as Ray Kurzweil, are still given to the same kind of optimism.) ... The psychological assumption and unconscious skills. Many AI researchers have come to agree that human reasoning does not consist primarily of high-level symbol manipulation. ... McCorduck asks "If Dreyfus is so wrong-headed, why haven't the artificial intelligence people made more effort to contradict him?"[27] ... Daniel Crevier writes that "time has proven the accuracy and perceptiveness of some of Dreyfus's comments. ..."
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Crows using traffic to crack walnut:
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/Glenn