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Artificial Intelligence - Science topic

Artificial Intelligence
Questions related to Artificial Intelligence
Steps for AI
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The first thing is to understand what is Intelligence... Maybe one can formulate the process of thinking via simulate a series of more and more complex systems. Does it guarantee that if we take a dog-bot with 1,000 possible actions, an input and output devices, if we build a more complex bot, will it be smarter too?
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Learning for a machine could be simply accumulating information but for a human it is much more. Machines can can of course accumulate information, they can categorize it, link it to other related information and build up a database which may then be posed questions which it can answer. This still does not constitute intelligence however. Somehow you need to give it the ability to reflect on itself... self-awareness. Not an easy thing to do. Humans think things over, which we might call simple processing of information, but we also evaluate that process as we do it. We think about the way we think. This is the approach neural network system use to learn but in a very simplified way. Failures are slowly weeded out by changing the way neurons in the network are connected. Humans can reprogram themselves in much more dramatic ways although the same process is going on. I think that our brains are a step up from this in that it is not just the way that individual neurons connect but whole systems of neurons. We have so many inputs to our brain through nerve endings that if all the signals came in at once, we'd short circuit ourselves. However, we have an brain structure that screens out what we don't currently need to worry about. For example, we don't pay attention to our toes until someone steps on them. Perhaps and artificial consciouness needs the same ability - To shift its focus from on thing to another both as it "decides" or as relevant input appears. It needs to possess imagination which is no easy thing to program... maybe... in a primative form I guess imagination is just pulling random information, ideas or concepts together, blending them and seeing if the result makes any sense. In a sense that is something like the way genetic programming works. Imagination lets us generate new concepts and connect information which may not have any obvious existing connection. We also ask ourselves a lot of "What if" questions. Can a machine be made to do this? Maybe. We also ask a lot "What am I doing wrong?" when things don't go right. To sum up... 1. Data aquisition. 2. Data categorization and storage. 3. Processing data and looking for links with other data. 4. Creating random links between data and evaluating results. 5. Asking questions of itself. What if? Why is it so? Why does my creator hit Ctrl-Alt-Del so much? 6. Self evaluation and changing of behavior accordingly. Each one of these points could be another layer of programming over the top of the previous one. I think I'm just blowing a lot of hot air so I'll leave it there.
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I want to develop an OCR using Artificial Intelligence. Can anyone suggest how it will help me ?
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One approach that might work better than trying to match actual characters is to try and match the components that the characters are made with. For instance, is there a vertical line, is there a curve, is it on the left or right side of the vertical line, is there an angled line, is the angled line on the right or left of the vertical line, does it angle left or right, are there two angles on the same side of the line, etc.
I am not sure how handwriting recognition works, but any program that can figure out how to standardize written text, probably does not try to match the character directly but instead the type of loops, and changes in direction etc that make up handwriting.
I think OCR of handwritten stuff is much more difficult, because of the lack of cursive similarities between the characters across a wide number of people, you might have to train the OCR for the writer. One aspect of that that might involve A.I. is the ability to extract from a small number of documents the training samples you need to train the OCR for a specific individual. It gets even more complex when you add that some of the documents might have been written at a different time, or in a different country where the spelling was subtly different.
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It musn’t be confused with human consciousness, just as human consciousness shouldn’t be confused with whatever computer consciousness might emerge (or already exists)
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???
WHAT mustn't be confused, your statement seems to imply that there is some direct relationship between Artificial Intelligence and Consciousness.
While Consciousness has been studied by A.I. researchers, and Intelligence has been studied by Consciousness researchers, I believe they are really two different fields. In one field, the study is about how machines can learn and adapt to the environment, and in the other field, the study is about how machines can become aware that they are doing so.
You seem to suggest that there is some blurring of the distinctions that is inevitable but if anything Intelligence is becoming more and more distinct from Consciousness. I like to say that you don't have to be a genius to be conscious, and by the same token, you don't have to be conscious to be a genius.
Having made that distinction, the other assumption you seem to be making is that somehow we will mistake a machine that "Might be conscious" for a human that is. This is of course what Turing thought might be a good test, however what we find, is that humans tend to anthropomorphise machines. I know people who say their computers hate them, but it isn't the computers fault, that they jump to wrong conclusions about what the next step should be in installing software etc, and then end up with systems that are completely out of balance.
The computer doesn't hate them, it is just confused because they fed it garbage and expected it to make sense anyway.
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Dear colleagues,
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Whoever is the administrator of this network should ban tis person rightaway!!! This can not be tolerated in this professional network. Tis information should be circulated on all grups on this network.
Thank you.
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Note: Their (spammers) words are suit, attracting, stupidly melodious and egocentrically inclined, but unprofessional. By their fruits ye shall know them. So don't bother or pay attention to their "words". Never reply to their songs - That's all.
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enthiran is a possible intelligence or wat?
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Great approach...
But I recommend movie"Avtaar", this is best example of Neural Networks ever.
A must watch movie, by taking some idea from there we can implement human interaction with machine. By this above idea will be implemented very soon.
Warm Regards,
Chetan
hi
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Here is an article about cell biology, telomerase. http://www.guardian.co.uk/science/2010/nov/28/scientists-reverse-ageing-mice-humans
God and Consciousness.
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I think we must be very careful, when we let philosophers tell us how to do science. Science works on a consensus within each specialty, and every time you meet a new philosopher you learn that there is a new type of philosophy. Epistemology is not a science but a philosophy, and so when we let the philosophers tell us that it is the science of the science, we all but stall scientific progress. What does Epistemology have to do with peer review? can you tell me that?
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Now a days we have hex core microprocessor in market, but even after this so much improvement in microprocessor we don't have any remarkable change in performance overall(speed must be six times to Pentium).
Don't you think we must think for hardware improvement, or some idea how can we interface our hard drive to microprocessor in such way so that we can minimize the misses. Now miss rate is very high(as hard disks are quite slower comparatively).
All suggestions or comments are most welcomed as I want to work on it and looking for new ideas to work.
Partners in this project are also welcomed.
Thanks in advance..
Warm Regards,
Chetan
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Thanks Lava...
Give me some time to analyze things, and soon I revert you back...
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The link is dead.
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asslmkm...
hello, this is my first post. and i am intersted in A.I but still don't know much about it. especially about neural network or neurofuzzy. if i use it for economics problem or some empirical studies, is it true that NN or neurofuzzy just for estimation and forecasting? thx
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hi an answer: Except if YOU find another application...
Think
Fred
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How can we begin implementing AI in the world of programming ? What should be the start ?
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Perhaps programs to find the ideal method of government? Food for thought.
Benaz R. Merchant
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I am interested in learning this material.
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Welcome
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New member to the AI group
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Welcome in AI group, I hope you to find all the infomation that you wanted
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Hi,
I am doing Ph.D in IT and specialized in Information Secuirty. My current project is Artificial Intelligence in Export System. I am expecting some inputs from your. So kindly help me.
RS Gala,
M.Sc(IT), M.B.A, ISO LA 27001, 9001, 20000 and BS25999 (Ph.d IT)
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thank you, I am also in IT systems for last 10 years
High Level Logic (HLL) Open Source Project
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The High Level Logic (HLL) Open Source Project is off to a running start. HLL provides a light-weight agent framework that is easy and appropriate for smaller projects, yet powerful enough for sophisticated distributed systems. It has been extended with new artificial intelligence capabilities for processing "high level logic." Blog: http://highlevellogic.blogspot.com/
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The Ghosts in My Machine, Chapter 3 http://highlevellogic.blogspot.com/2010/11/ghosts-in-my-machine-chapter-3.html
Is our feelings kind of an intelligence?
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Is our feelings kind of an intelligence? Can we make computers solve problems by making them feel happy, sad, mad, ...?
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Antonio Damasio, a famous American/Portugese neuroscientist, defends the thesis that rationality is not possible without emotions. Emotions are needed to give values to our senses, and therefore serve as the base for making judgements/choices. See "Looking for Spinoza" (http://www.amazon.com/Looking-Spinoza-Joy-Sorrow-Fee/dp/B000OJI5XG/ref=sr_1_6?ie=UTF8&s=books&qid=1288821602&sr=8-6) and "the feeling of what happens" (http://www.amazon.com/Feeling-What-Happens-Emotion-Consciousness/dp/0156010755/ref=sr_1_2?ie=UTF8&s=books&qid=1288821602&sr=8-2) The problem with representation of emotions/feelings in computers is that you would first have to have a (correct) model of what feelings and emotions are, and currently this is mainly speculative. So every model of feelings/emotions in a computer will be based on assumptions of what feelings/emotions do, and should not be mistaken with actual human feelings and emotions. For example, according to Damasio, there is a difference between sensations (for instance a stab in your arm) and the feelings and emotions that are associated with it (pain). These feelings and emotions are interpretations of the brain to the received stimuli, and can be culturally different. Putting it a bit more abstract, this means that pain (love, grief,joy, etc.) are contextually determined and also far from fixed in one's lifetime. This is something that you will not be able to achieve with databases, tokens, compilers and so on, as these are by definition context-free. What you can achieve this way is a formal model of feelings and emotions, which may yield interesting results, but -as I said earlier- should not be mistaken for human feelings or emotions. If you would want to pursue a formal approach to feelings, then you may want to adapt the BDI logic of Wooldridge (http://www.amazon.com/Reasoning-Rational-Intelligent-Robotics-Autonomous/dp/0262515563/ref=sr_1_1?s=books&ie=UTF8&qid=1288822344&sr=1-1) for feelings and emotions. Wooldridge has formalised beliefs, desires and intentions (hence BDI).
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At the recent Web and Philosophy conference in Paris I presented the talk "Philosophy and the Social Web" http://slidesha.re/c1ujlW
It starts of by showing how the network effect is leading to massive centralisation of social networking sites to the detriment of sites such as this one. But it then describes how the distributed nature of the web can help solve this problem, if one uses the Semantic Web. Now the semantic web is usually thought of as a branch of AI, and this leads people to think that necessarily this means that it must the computer must do what is considered the intelligence part. Here we show how far one can go with very little computer intelligence, by getting the computers to use human intelligence and the network effect as far as possible.
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I have added detailed notes and references to these slides now pointing to academic papers, blog posts that go into more details, books etc.. http://bblfish.net/tmp/2010/10/26/
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Did you find the way people walk, how can we make the balance when we walk even run fast?
then,I have a question,why didn't we use the method we walk to the artificial intelligence.
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This video is not about walking upright, but I think that it's useful to show the state of art of a robot with balance: http://www.youtube.com/watch?v=W1czBcnX1Ww .
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123456789
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Continue ad nauseum
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I am glad to join in the group and will talk about some questions obout intelligence with other group members.tks!
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I think you are right Graeme. 'Intelligence' in computer research often basically can be translated to optimization problems, .i.e reducing the difference between a current situation and a desired situation.
I have come the conclusion (but probably that's just my philosophical side ;)) that (human) intelligence becomes manifest when trying to cope with uncertain and novel situations. In this sense, intelligence would be the capability to deal with uncertainty; to achieve something in demanding situations with only prior knowledge and experience to guide you.
From this perspective, the 'intelligence' of many AI solutions basically comes from the developer, and not from the agent that uses it.
FAIRS’10 - Forum for AI Research Students: (University of Cambridge )
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FAIRS'10 is intended to allow PhD and MRes/MPhil students working on AI related projects to discuss their research and issues around doing a PhD with senior scholars in the field and with other Forum attendees. The forum is aimed at those who have either completed a Master's degree in an AI field and who are interested in progressing to a PhD, or are current doctoral or research Masters students. It will give students the opportunity to receive feedback in addition to the supervisory arrangements at their own institution. Students will be expected to contribute to small workshop discussions on issues related to the conduct of the PhD. The programme will begin at 10.30 a.m. to reduce the need for attendees to stay in Cambridge on Sunday night. (If modestly priced accommodation is required, Cambridge Youth Hostel (see www.yha.org.uk) has bed and breakfast from £14.00 a night - please make your own reservation and payment arrangements). Registration for the Forum will open at 10.30 a.m. on Monday, but participants who cannot arrive before the 11.00 a.m. start are encouraged to come straight to the Forum venue. The programme for the Forum will include a number of structured sessions. After the welcome messages there will be a short workshop session to set the tone of the day, followed by a presentation and discussion of "Getting a PhD - Doing Good Research", led by experts in the AI field with extensive experience of supporting and examining PhD students. During the lunch break students are encouraged to discuss their research with other Forum attendees. The first afternoon session (1345-1430) will see the participants split into working groups depending on the stage of their PhD, for discussion of issues, problems, suggestions, etc. Each group will be facilitated by an academic with experience of PhDs, and everyone is expected to get involved. This is followed by a two panel sessions (1440-1530 and 1530-1620) allowing participants to put their questions about PhD research and careers to a panel of academics, recent PhD students, and industrial representatives. At the mid-afternoon and end-of-afternoon coffee breaks, students are again encouraged discuss their research with other attendees, and for an important opportunity for networking within the AI community. New this year will be hustings and voting for a student representative to the SGAI committee. Students who wish to be considered can nominate themselves on the FAIRS registration form, and in this session will have 5 minutes to convince the other participants to vote for them. The result of the vote will be announced in the final session. The evening session (from 1700) is a lighthearted (but useful!) session on how to Survive Your Viva. This session and the Forum as a whole will close at 1815. Students attending the Forum are of course invited to subsequently participate in the main AI-2010 conference (i.e. December 14th -16th 2010). A discounted Student Rate is available for student delegates at the conference. The Forum will be a stand-alone programme which will take place the day before the other conference workshops and tutorials being held on December 14th. Full details are at www.bcs-sgai.org/ai2010. http://www.ai-research.org.uk/FAIRS2010/index.html
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Thanks for your interests, please check file attached
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hello every one...
i have a proposal of creating the most advanced robot by integrating the human brain to a computer.
according to my way of thinking, if we could make this we can let the human brain to live forever
.
at the same time we can go for brain scanning, which can help a lot in the interrogations .....
pls guys... there are so many intellectuals in this forum... please guide me in my research .....
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I have a similar idea, in a specific area. Analyzing brain mood and altering it.
There already exists research on Binaural waves, which can be used to alter brain frequency, using slightly out-of-phase sounds to both ears, to cause the brain to resonate to a particular frequency (sleep, meditate, relax, normal, energetic, active and so on)(ref iBrainwave iPhone app).
The brain signals can easily be analyzed using biometrics: like EEGs do, but using lot smaller instruments, since we dont need so much resolution in detail for mood detection. Can use approximations to zone the mood using multiple measurements per instant.
So if there's a simple instrument system, which analyzes various parameters: like skin current (skin surface), perspiration, pulse rate (maybe using a neck collar near the jugular vein) & our own feedback (I want to be happy, active, relaxed, etc), we can design a system to measure, quantify, and then suitably alter brain mood using aural (binaural sounds, mood music), visual (mood lighting), and possibly more senses.
The system need not be intrusive at all, since all such measures can be taken externally, without surgical implants.
A bio robot can use such a system to analyze our thoughts and use it to judge what we want to do.
There's a lot of active research in this area. Try checking the physorg website. IEEE spectrum online has articles relating to brain controlled interfaces research too.
Portable, iPod-size embedded systems can be used to store a small AI to interface the system with external robots, so we can control interfaces wherever we are. No need to lug around our own personal robot.
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together v can..make gr8 research
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Ashish ....which batch of poornima?
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can anybody plzzzzzzzz tell me how to get articles on enhancement of dissolutin rate of simvastatin
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Well, asking computer nerds about natural steroids doesn't sound too productive....
Have you tried Google scholar? I find that if what I want is articiles it at least finds some, even if most of them were writen by me.
Ray Kurzweil: The Mind and How To Build One (video)
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Ray Kurzweil: The Mind and How To Build One (video) Will we ever create an accurate simulation of the human mind? Can we detect and measure consciousness? When will artificial intelligence surpass human intelligence? Humanity has questions about the development of AI, and for decades Ray Kurzweil has been trying to find the answers. Those who know the author, futurist, and inventor’s work will be familiar with his beliefs in the exponential growth of information technology, and the inclusion of more technologies into the IT label. Lately, Kurzweil has become increasingly interested in the human mind, how we may be able to understand it, and eventually how we could recreate it. He’s working on his seventh book, How the Mind Works and How to Build One, which will explore those concepts. This past August, at the annual Singularity Summit, Kurzweil gave attendees a sneak peak into his upcoming book via an hour long presentation with almost the the same name: “The Mind and How to Build One”. Thanks to the Summit organizers, The Singularity Institute, Kurzweil’s talk is now available to watch online; check it out in the video below. From his discussion on consciousness to his explanation of the processing methods of the cerebral cortex, this is one of the best Kurzweil presentations I’ve ever seen. I attended this year’s Singularity Summit, and had a great time. I remember some commenters at the Summit lamenting that Kurzweil started his talk rather slowly. However, I think the first 15 minutes of his presentation give some really valuable background to what he wants to discuss. Right away Kurzweil points out that the brain is not some mystic device, some quantumly unknowable system that we’ll never be able to understand. We can, for the first time in history, reliably peer inside the brain and see what’s happening. That’s an important step in creating a comprehensive map of how our brain behaves. But in terms of AI, we may not really need that map. Kurzweil explains that reverse engineering the brain isn’t absolutely necessary to develop artificial intelligence, it is just that understanding the brain can help us augment our pursuit of AI rather well. He relates how we’ve already had success with determining how the brain understands speech and visual input. These pattern recognition tasks have given us insight into how the rest of the organ processes information. With this context, Kurzweil’s ready to jump into the future of creating artificial minds. …But first he takes a bit of a detour. At 14:45 he starts to discuss the reasons why some people believe in the Singularity and others do not. Importantly, he points out that education, intelligence, and age aren’t the determining factors. Glad to hear that the people who disagree with the concept of the Singularity aren’t dumb, ignorant, or childish. At 17:44 he starts back towards the brain, explaining how the cerebral cortex is composed of modules, which he calls recognizers, that serve as linked labels for real world objects and metaphysical ideas. …and then he gets away from the mind again. From 19:00 to 25:15 he shows evidence supporting the theory that information technologies have experienced exponential growth. For those who have seen Kurzweil speak before you can skip that part of the video. If this is your first Kurzweil presentation I have some bad news: Singularity Institute didn’t include the slides in the video. Luckily I tracked down a similar presentation he gave to Google in 2009 (see it below). You can see all the graphs of exponential curves you’d ever want by checking out slides 5 through 44. The real meat of the presentation starts up after 25:00 when Kurzweil really gets into exploring concepts related to the brain. Jump to that point in the video and you won’t be disappointed. Slides 56 through 71 in the Google presentation are helpful to look through while you listen to him speak. Unfortunately, Kurzweil was not able to appear in person for the Singularity Summit, instead he teleconferenced in. I was in the auditorium for the presentation, and I remember him looking a little like a giant floating head, but luckily you’ll miss out on that when you see the video below. Part of why I like this presentation so much is that Kurzweil fills it with memorable statements that encourage the audience to learn more about the nature of their minds. At 26:04 he explains that consciousness, in its very nature, is not measurable. It is a subjective evaluation, not an objective one. Science is simply not going to be able to have a definitive test for consciousness. That’s very appealing to me as both a challenge to experimentalists, and a launching point for philosophers. At 27:30, Kurzweil explains how thoughts create the brain saying, “we create who we are by the thoughts we have.” Our thought patterns are literally rewiring our brain and our brain’s wiring is influencing our thoughts. Speaking from experience, that’s a wonderfully interesting concept to explore with friends over coffee late at night. At 39:25 he states that, “…the cerebral cortex is a LISP processor.” Referencing the computer language LISP that uses linked lists as a data structure. Kurzweil describes the cortex as filled with units (“recognizers”) that build complex concepts out of links to other concepts. That’s a delightful (and apparently accurate) way to understand the way our minds learn, and again, something fun to discuss with friends or inspire you to read a book about neuroscience. It also jives very well with Jeff Hawkins’ theories about the brain. Hawkins is the founder of Palm, Handspring, and most recently Numenta, a company that uses the architecture of the brain to help design narrow artificial intelligence for interesting things such as sorting through video footage. We here at the Hub are fans of Hawkins, and it’s nice to see that apparently Kurzweil is too. Further memorable sections: 43:00 – Kurweil discusses spindle neurons and the importance they have in our higher reasoning. 45:00 – He explains that we can only really test our perceptions of consciousness, not consciousness itself. 52:00 – The ‘Duck Theory’ of consciousness: If something looks like a duck, quacks like a duck, etc it’s probably a duck. In the same way, humanity will likely decide to accept artificial entities as ‘alive’ when they do the things that our consciousnesses do, even if we don’t have a test. 55:00 – Questions begin: 1) Is it possible the quantum wave function is a mental field? 2) How accurately do we need to model the brain to get intelligence? Neurons, subcellular, macromolecular? 3) Is scanning a human brain to the molecular level necessary before we get AI? I should say that this presentation at the Singularity Summit has become a little frustrating to me. Around minute 30, Kurzweil starts to discuss the amount of code it would take to simulate a brain. A poor interpretation of these comments lead to PZ Myers, a researcher and blogger of some renown, to trash the entire presentation. We covered Myers’ original blog posting, as well as Kurzweil’s response, when it happened. As such I won’t go into the debate too much here. Suffice to say that Kurzweil believes that our brains are encoded by our DNA, which represents a reasonable amount of code to try to simulate/recreate in the future. However, he also states outright that a simulated brain will need to be ‘taught’ because experience is a key element in the development of a mind (watch around 29:35). Myers seems to have missed all this and concluded that Kurzweil had a laughable naive comprehension of the complexity of the brain. Ugh. Misunderstandings such as these are not the best basis for reasonable debate. Over the years Kurzweil’s name has become somewhat synonymous with the Singularity. That’s to be expected, I guess, since he has written so many books that have directly or indirectly discussed the topic. I often lament that equivalence because it opens up a complex intellectual concept to boring ad hominem counter arguments. Today, however, I’m rather glad that Kurzweil is so often portrayed as the leader of the Singularity. He doesn’t always have the best stage presence, but it’s hard to ignore the depth of thought and clarity of vision he brings to his presentations. At the Singularity Summit Kurzweil painted a detailed picture of the brain as we know it today, and the way we may delve it more deeply in the future. I look forward to reading his upcoming book to see how he expands upon these ideas. http://singularityhub.com/2010/12/21/ray-kurzweil-the-mind-and-how-to-build-one-video/
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Similar thoughts to your question: http://www.linkedin.com/pulse/artificial-intelligence-look-forward-mayur-narkhede?articleId=6303264733319532544#comments-6303264733319532544&trk=prof-post
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hello dear friends , i want use the neural network for approximation of function with matlab toolbox , please help me ..
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You may look up the demo or help in matlab docs.
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Hi all,
I am new to this blog. I am interested in machine learning approach. can any one explain me with simple example about membership function in fuzzy logic.
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As a more practical example, take room temperature. The temperature of a room can be scaled between 0-30 degrees centigrade, but this says little about our sense of trmperature, say 'freezing', 'cold', 'uncomfortable', 'nice', 'warm', 'hot'. A fuzzy system accepts that 17 degrees can be both a little bit 'cold', 'uncomfortable', 'nice' and even a little bit 'warm'. Hence a fuzzy set. 17 degrees centigrade can therefore be 0.2*cold + 0.5*uncomfortable, + 0.2*nice + 0.1*warm. Every degree can be scaled accordingly, and so a fuzzy set basically transforms a linear scale to a different set, where different values can occur simultaneously
Wanna know your oppinon about Google Flu Trends
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Hello everyone. I want to ask you about the new Google project for monitoring the flu virus http://www.google.org/flutrends/intl/en_gb/about/how.html
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If we are talking about tracking outbreak of critical diseases, there is WHO health reporting by individual countries using ICD standards. Of course some countries would report an acute critical disease as some milder disease. This is to protect their tourism, ,but with ICD categories, educated guessing, perhaps AI-assisted is possible.
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Is when are they going to build processors based on a minimum sufficiency ergonomics of molecules to inflict artificial immune system surgical operations and DNA alteration of cells tissue?
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What I mean basically are small robots injected in blood and tissue capable of carrying work with individual cells.
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i want to know whether artificial intelligence can totally help man as much as his own central nervous system
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I thought facial recognition system are already operational at least for immigration and police applications. And that was at least 10 years back....
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What is the Ecological Impact, from production of the prime materials, final product, storage, transportation, energy consumption, to computer use?
Here, of course we may identify ecological positive impact usage and ecological negative impact usage.
But, overall, the computers are ecological, helps our environment or it destroys it.
What about the Ecology of Internet? Can we refer to the network from its built to its usage such as blogging, websites, and electronic journals?
What is the Impact on the Global Economy of computers and Internet / Networks and their usage?
So I proposed this new subject, perhaps members will find it interesting and useful.
Thanks,
Adrian Toader-Williams
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Because of the nature of the Marketing around consumer electronics obsolescence is a constant factor in waste, in that in order to sell the next most interesting component, the value of the former component must be culturally degraded. As a result, the product life-time of the electronics, is never fully realized, and often planned obsolescence is built into the circuit in order to limit it's active life. While a culture is growing around "Bending" old technologies to make new ones, E-waste is endless, and culturally "Hacking" old hardware is looked at as socially unacceptable despite the high technical skill required to make useful products.
As a result, electronics waste, has received quite a bit of attention, and shipping it offshore to contaminate other countries is frowned on. As a result, in order to clear the volume created, almost direct shipment to refineries is implemented, and in order to keep illness from spreading, dump-sites at local eco-stations actively discourage re-use.
At the refinery, expensive metals, and rare earths are recovered from the waste, mostly by burning the plastic away from the metals and refining the result as if it were ore.
This produces often toxic gasses from the plastic, which are often released into the atmosphere but at a high enough altitude that they do not directly contaminate the local atmosphere, but have been traced halfway around the world.
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Ideas & Sugg welcome
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Balasubramanian, Give us some idea of what you have and we can build on it for you.
Anantharaman, you can study robots while you are taking your degree. You start by building a small robot like the BoeBot. http://www.parallax.com/tabid/411/Default.aspx
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i think the growth of artificial intelligence could cause some defects to the nation like robots
can u plz explain this
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watch movie I robot of will smith and minority report of Tom cruise it is master piece this will generate ideas about defects of AI.
"Multi-Robot Systems, Trends and Developments" - a new InTech release!
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A quality InTech Open Access Publication, free to read, download and share: http://www.intechopen.com/books/show/title/multi-robot-systems-trends-and-development 29 chapters in three sections covering: task oriented approach, bio inspired approach, and modeling/design. In the first section, applications on formation, localization/mapping, and planning are introduced. The second section is on the behavior-based approach by means of artificial intelligence techniques. The last section includes research articles on development of architectures and control systems. We hope you'll enjoy the book and spread the word with your colleagues and friends! Regards, Nataly and the InTech team
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Nice resources, Nataly! Thanks for sharing.
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Due to Richard Dawkins mechanism of evolution works as a semiconductor, which conserves such mutation, which useful for surviving. Thus, instead of big steps, evolution goes by series of small steps. Let's consider its math expression. For Boltzmanian distribution w(E)=N*exp(-E/E0) exponential part doesn't change at changing of evolution trajectory.So, acceleration of the evolution progress can be only by renormalizing process. If we take the Dowkins' idea one gets increasing of probability of a big step of evolution as 2^n, here n ia a number of small steps. The same result is valid for the Gaussian distribution. The question is about a time scale of the one small step. Of course it depends on speed of generations change and of level of "noise". Sure the viruses and bacteria are champions of speed of the evolution process
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Well, Virus and Bacteria have short life-spans so that they can change faster than just about any other genome. While the Flu virus for instance changes during its lifetime within the body, Significant changes to the population in general happen much slower, and one of the reasons that we get new flu virus varieties every year, is that they survive between flu seasons in other animals that are not treated for every sniff and sneeze, and can trade genetic code so that if a particular gene is better for survival it will be inherited by a lot of animals and will therefore become a new viral strain. Aids on the other hand mutates every time it reproduces, and it is literally possible to have hundreds of strains in a single subject.
In multicellular animals much of this instability is damped out, and so the generations tend to be more consistent, with each other and often major new genetic markers depend on population dynamics and factors like inbreeding, or isolation of one gene pool from another, and are only noticed when a crisis results in competing genetic populations dying off, leaving one slightly more robust one as the base population on which other gene pools must be formed.
New free e-books online at InTechOpen
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Dear friends, Just to let you know about the following open access e-book which went live on our site today and which I thought might be of interest to this group: The Traveling Salesman Problem: Theory and Applications http://www.intechopen.com/books/show/title/traveling-salesman-problem-theory-and-applications There are 10 new books in total, and other titles include wireless networks and CFD. Hope that this may be of interest to you. Regards, Nataly and the InTech team
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Thanks a lot!
Free books for AI researchers
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Dear AI researchers, I would like to let you know about a resource that may be of interest to you: a collection of free books on AI and related subjects available for download from our reading platform www.intechopen.com. InTech is an open access publishing company founded by robotics researchers, so our collection of almost 300 full-text books has a definite bias towards robotics and AI. We also have a quarterly journal, "The International Journal of Advanced Robotics Systems" which is also available on our site. I hope you'll join the readers around the world who have found this resource useful. If so, I will be sure to let you know when new publications are released online. Best regards, Nataly Anderson
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Great work Nataly and your team !
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how warm sensitive neurons can be count in preoptic area of hypothalamus
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on increasing temperature of Preoptic area number of neuronal firing increases calculate single neuron firing action potential.
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In preoptic area 30 % warm sensitive and 10 % cold sensitive neurons present ,Is TRPV1 channel present on warm sensitive neurons or cold sensitive neurons if yes how can we find
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If you want to increase your memory focus on your each work and evaluate seriously of every aspect of your work. You should analyse in every work try to learn everything whatever you are watching, hearing, try to understand the mechanism of each incident. learn phone number daily. according to Ayurveda almond and walnut is brain food. Be healthy do exercise daily try to consecrate your brain.
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Optimization is a choice of parametrs in a process of minimization of a fixed functional.
Adaptation is a choice of a functional of a set, which provides their minimum minimorum.
This can be considered as a definition of AI. Multichannelling can be consider as a case of a random degeneration.
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Well, that shortage, comes mostly from A.I. researchers not being willing to spend the time to get familiar with Neuroscience, and the fact that at the micro-biological layer we are still learning about the interface between the DNA and the environment. The whole realm of epigenetics has become significantly more important since we have learned that a cells dna strands interact with their environment during development, and as part of nerve plasticity.
Another factor I think, is the unwillingness of the A.I. crowd to move away from the computer model of memory, and towards an implicit model instead.
The final factor seems to be the failure of the psychology mavens to fully understand the nature of the tissues in data-management within the brain.
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INVITATION
Apologies if you receive multiple copies of this CFP.
It is our great pleasure to invite you to submit a paper to a Special
Session on Computational Intelligence and its Applications as part of
the fifth Global Conference on Power Control and Optimization PCO 2011,
which will be held in Meridian Hotel, Dubai, United Arab Emirates, from
1 - 3 June 2011.
More details on the special session can be found in the attached.
Please, circulate this CFP widely among your colleagues.
Thank you.
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I could not figure out how to attach a document here.
================================================
A Special Session on Computational Intelligence and its Applications
This special session will bring together top researchers, practitioners, and students from around the world to discuss the latest advances in the field of Computational Intelligence and its application to real-world problems in software engineering, power control systems and methods of optimization, petroleum engineering, bioinformatics, chemical informatics, bioengineering and related fields. Computational Intelligence (CI) techniques including but not limited to artificial neural networks, fuzzy logic, evolutionary algorithms, ant colony optimization, particle swarm optimization, support vector machines, genetic algorithms, functional networks, and especially hybrid of various techniques. The use of computational
intelligence must play a substantial role in submitted papers. Submissions will be peer reviewed and accepted papers will be published in the conference proceedings and will be index in IEEE Explore, Thomson Reuters of ISI and SCOPUS. For more details you may enquire the session chair Tarek Helmy (helmy@kfupm.edu.sa) or the co-chair Anifowose Fatai (anifowo@kfupm.edu.sa).
Topics:
We encourage submission of papers on novel and modified hybrids and ensembles of intelligent and machine learning techniques for real-world problems including but not limited to:
• Power system applications i.e. planning, designing, distributing, operating, monitoring, etc.
• Analysis of large bioinformatics data sets.
• Soft computing and computational intelligent techniques for petroleum engineering tasks such as reservoir characterization, gas components predictions, etc.
• Fuzzy and hybrid optimization.
• Evolutionary algorithm.
• Biological and medical Ontology.
• Medical image analysis and pattern recognition.
Important Dates
• Submission of Full Papers: 01/03/2011.
• Notification with Peer Review: 30/03/2011.
• Camera-ready Paper: 25/04/2011.
• Registration: 30/04/2011
Session General Chair:
Tarek Helmy, Information and Computer Science Department, KFUPM, KSA (helmy@kfupm.edu.sa)
Session Technical Chair:
Fatai Anifowose, Artificial Intelligence Group, Center for Petroleum and Minerals, KFUPM, KSA (anifowo@kfupm.edu.sa)
Paper Submission:
Authors are invited to electronically submit their papers by email to helmy@kfupm.edu.sa or
anifowo@kfupm.edu.sa, written in English, presenting the results of original research or innovative practical applications relevant to the special session. The authors should format their papers in MS-Word as per the PCO 2010 guide: http://www.pcoglobal.com/PCO%20paper%20template.pdf
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Please contribute papers to the International Conference " IEEE Recent Advances in Intelligent Computational Systems" to be held at Trivandrum, India during 22-24 Sep. 2011
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Please visit theCFP link of the conference for details of the conference tracks and the paper submission :
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the working language is not English?
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Hi...
I need a project on Artificial Intelligence any kind off..........code is necessary plzzzzzz.
any body having a projcet then plz give me....at luckilyfahadhere@gmail.com
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Hi Faha Salaludin
I suggest that you should look at this website: http://aima.cs.berkeley.edu/
In this link, you can find a lot of open source projects in AI.
And then choosing a topic that you are interesting, For example, you can specifically be chosen with the principle of applications related to AI Technologies, such as planning, Machine Learning, or Robotics, etc.
After that you can tell with us. So,we can give you references that you are expected.
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I have a picture , and need to find a particular part in it,like a rectangular shap. what is the best to acces it with a mlp or hopfield network.all of this must be happen in less than 1 minute with a program for example in matlab.
be hungry for sience!!
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HI!
Please try control system toolbox in line with the so called point distributed model
A set of training images are landmarked with enough corresponding landmarks to sufficiently approximate the geometry of the original shapes. These landmarks are aligned using the generalized pro-crustes analysis, which minimizes the least squared error between the points.
Why the trouble Mohammed? I have interest to know more
How & Why? Artificial intelligence makes some progress, but robots still can't match humans
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How & Why? Artificial intelligence makes some progress, but robots still can't match humans Computers these days have serious human envy. When you call your bank, the robot on the other end doesn't want you to communicate using your touch-tone keypad anymore. No, it insists that you just speak to it, sometimes even adding, "You can use a wide variety of words." What a showoff. Your car is trying to emasculate you by taking over the parallel parking duties. And computers have long since drained all the fun out of chess. Fortunately, most robots aren't the complicated emotional beings that star in movies, and we're still pretty good at identifying android impostors. Even if you don't recognize the stilted robotic diction over the phone, they usually give themselves away when they can't understand a thing you're saying. But how long will it be before you have an entire conversation with a machine without realizing it? This isn't just cocktail party chatter; it's the long-term goal of artificial intelligence research. Alan Turing, the man many identify as the father of AI, in 1950 defined an intelligent machine as one that could masquerade as a human. Even without having to talk or understand the spoken word, there isn't a machine that can pass the Turing test. Truly humanlike intelligence has frustrated AI researchers because it involves two skills that machines are bad at: perceiving their environment and usefully incorporating past experiences into their knowledge base. Think, for a minute, about what it takes to recognize a can of soda sitting in your refrigerator. The photons bouncing off the scene in your refrigerator are recorded on your retina. The optic nerve translates the image into electrical signals and carries them to your brain. So far, so good for the machines. Digital cameras have long been able to capture photons and store them as transmittable electrical signals. The next step, though, is a bridge too far for most robots. Your brain manages to pick out the can from the rest of the scene, even though every time you see a soda can, it looks a little bit different. Your brain has what researchers call an internal representation of a soda can, so even if the lighting is different or the background changes or the can is a slightly different size, you still recognize it. It takes an incredible amount of computing power, plus the ability to filter out extraneous details, to make this happen. Computers are slowly acquiring the skill. Google, for example, is working on an "omnivorous search box" that can recognize images and sounds recorded on a smartphone. But the technology remains in its infancy. Building a knowledge base is even more difficult for a machine. John Laird, a professor of computer science and engineering who studies artificial intelligence at the University of Michigan, analogizes computers to the main character in the 2000 film "Memento," who cannot make memories as he tries to figure out who murdered his wife. "Most AI systems," says Laird, "do not have episodic memories. They don't make continuous records of their pasts." Like the lead character in "Memento," they are what Laird calls "cognitive cripples." While they can store information, they can't learn the way a human does. Even if we could construct computers with enough memory to store decades' worth of conversations, novels, meals and lectures, no one has figured out how to teach a machine to catalogue and access those memories quickly. For an example of how data management is every bit as important as raw computing power, consider Deep Blue, the computer that in 1997 defeated grandmaster Garry Kasparov. In theory, a computer with enough computing capacity should be able to beat a human in chess. It could play out every possible sequence of moves and always make the best choice. But no computer can do those computations fast enough. Deep Blue saved time and RAM by making decisions about which moves were worth considering and which could be ignored. In other words, Deep Blue used a form of reason, and not just superior processing speed, to beat Kasparov. The field boasts other recent accomplishments. The Pentagon's Defense Advanced Research Projects Agency, or DARPA, offered a $2 million prize in 2007 for a robotically driven car that could merge, park and pass in traffic as well as a human driver could. (Or, hopefully, better, given the way some people drive on the Beltway.) While the teams competing for the prize were given the map of the urban course in advance, their robots didn't learn exactly what it had to do within the course until five minutes before the green flag. DARPA also clogged the course up with 30 human-driven Ford Tauruses. Six of the 11 teams managed to complete their missions, although a few had minor scrapes. Inspired by that AI feat, Google has entered into a collaboration with Sebastian Thurn of Stanford, who won a previous DARPA challenge and came in second in this one, to develop robotic cars. While robots are working in Iraq and Afghanistan, most of them are remotely operated by humans. The Department of Defense is working with Laird on a robot that can enter a house before soldiers or monitor a perimeter while humans are inside. Humans will train the robots ahead of time by walking them through model buildings. The robot will project what it sees onto a tablet computer, and trainers can point to objects on the screen and give the robot such simple commands as "open." On the battlefield, soldiers would be able to turn the robot loose and let it work. Of course, Laird's proposed robots are a far cry from James Cameron's Terminator, and Thrun's winning robo-vehicle is a long way from Kit of "Knight Rider" fame. It's going to be decades before a robot passes the Turing test. Engineers such as Victor Zue of MIT are working on startlingly lifelike digital human images that will tell people that their flight is delayed. But there's nothing of general applicability out there. So don't expect to be employing your own robotic housemaid anytime soon. http://www.washingtonpost.com/wp-dyn/content/article/2010/12/20/AR2010122004781.html
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Artificial intelligence: Ten things you need to know about the future of AI 1. Artificial intelligence is developing faster than you think, and speeding up exponentially: Humans tend to think in straight lines, but every aspect of technological progress is actually accelerating – including AI. Futurist Ray Kurzweil calls this the “Law of Accelerating Returns”, and presents evidence that an amount of progress equal to the entire 20th century's gains was attained between 2000 and 2014. He also argues that the same amount will happen again before 2021. Understanding the exponential nature of progress and ignoring the inner tendency to think things will keep improving at the same rate is key to getting to grips with how fast we'll make scientific advances in the future. 2. You use artificial intelligence all day, every day Siri, Google Now, and Cortana are obvious examples of artificial intelligence, but AI is actually all around us. It can be found in vacuum cleaners, cars, lawnmowers, video games, Hollywood special effects, e-commerce software, medical research and international finance markets – among many other examples. John McCarthy, who originally coined the term “artificial intelligence” in 1956, famously quipped: “As soon as it works, no-one calls it AI anymore.” 3. Robots are definitely going to take your job Yeah, I know you're a special flower and everything, but the work you do is either already automatable or will be very soon. How soon? Most jobs will be done by robots within 30 years, says professor Moshe Vardi of Rice University, leading to unemployment rates greater than 50%. That might sound bad, but many academics studying the field believe that technological unemployment will open the door to a future where work is something people do for pleasure, not out of necessity. Proposals such as universal basic income are the beginnings of a societal support structure that could eventually allow this to become a reality.
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The journal welcomes the submission of manuscript that meets the general criteria of significance and scientific excellence. We invite you to submit your manuscript via email: telkomnika@journal.uad.ac.id, and cc: thsutikno@ieee.org for publication in the TELKOMNIKA Journal. Following acceptance, a paper will normally be published in the next available issue.
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date the importance of whatever?
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Hi,
I am starting to explore better ways to use ResearchGate, not just for my benefit but to do something of value for others.
I will start posting some links to various papers, publications, presentations, and briefs, as well as joining in to different discussions.
I am looking for networking, and collaboration, and work (job(s)).
Certainly I am open to sharing ideas, critiques, comments, views, and helping others. To
me, everything does require an attitude of synergy and symbiosis in order for us to
succeed, as scientists, as people.
FYI, if anyone is interested, I just wrote up this summary:
These are URLs about me, some of what I am doing, including past, and also including
things that are "orthogonal" and obviously more directed at surviving in a "non-friendly
ecosystem" as far as science and especially exploratory and non-mainstream
("non-major-institutional/corporate") R&D.
---------------------------
---------------------------------
and just about my background, http://tetradyn.com/professormd
I can do some things pro bono and voluntary, as part of a team, etc., to help advance the
general interests and causes of good research, solid science, improved education, and
better public understanding.
However, I also seek (need) work: part-time, temporary, full-time of course, in US and/or
anywhere in the world.
Best regards,
Martin D
+1-757-847-5511
+1-202-415-7295 cell
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Hi, Martin!
The best for you! I am retired, live in Riga, Latvia. Making my homepage http://basicrulesoflife.webs.com for the same reason - to distribute knowledge, help people understand themselves and manage their life. To try to be a bit happy. Interested in good articles about AI, human brain and happiness. When I find something useful I place it in my list. For everyone's reading and thinking.
Thank You for the 'not just for my benefit but to do something of value for others.', so do I.
Imants Vilks, former soviet radioengineer :))
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I am looking for a partner for my research on Mammograms(Breast Cancer Screening). Specially I am looking for students of Cancer Institute. Please revert back to me with your positive response.
Thanks and Regards,
Chetan Vashistth
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Hi Chetan
I have worked on breast cancer analysis. I did the microarray analysis of ER transcription factor. Can you tell me what kind of work you expect from ur partner??
Some of the Artificial Intelligence Research Institutions
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The Artificial Intelligence Lab at MIT [http://www.ai.mit.edu/] The MIT Artificial Intelligence Laboratory conducts research in many aspects of intelligence. Our aims are two-fold: to understand human intelligence at all levels, including reasoning, perception, language, development, learning, and social levels, and to build useful artifacts based on intelligence. University of Alberta AI Research Group [http://www.cs.ualberta.ca/~ai/] Universite Libre de Bruxelles [http://iridia.ulb.ac.be/Welcome.html] IRIDIA is the Artificial Intelligence research laboratory of the Université Libre de Bruxelles. It is deeply involved in theoretical and applied research in soft-computing. The major domains of competence are: (i) belief representation and AI techniques for process control and classification, (ii) nature inspired heuristics or the solution of combinatorial and continuous space optimization problems. Artificial Intelligence NV (Ai) [http://www.a-i.com/] Founded to create true artificial intelligence--making it possible for humans and computers to speak to each other in everyday language--Artificial Intelligence NV (Ai) is an international company with offices in Boston, Massachusetts and a research center in Tel Aviv, Israel. AIAI [http://www.aiai.ed.ac.uk/] AIAI is a technology transfer organisation that promotes and expedites the application of research on Artificial Intelligence for the benefit of industrial, commercial, government and academic clients. Kurzweil Applied Intelligence [http://www.kurzweiltech.com/ktiflash.html] Creator of speech recognition technology AAAI [http://www.aaai.org/] Founded in 1979, the American Association for Artificial Intelligence (AAAI) is a nonprofit scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. Artifical Intelligence Systems in Routine Clinical Use [http://www.coiera.com/ailist/list.html] This list contains summaries of 38 Artificial Intelligence systems that have been in routine use in medical settings. Deep Blue [http://www.research.ibm.com/deepblue/home/html/b.html] In a shocking finale that lasted barely more than an hour, World Champion Garry Kasparov resigned 19 moves into Game 6, handing a historic victory to Deep Blue.
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The CSI Special Interest Group on Artificial Intelligence has compiled various AI research activities, comprising of a list of academic and research institutions working in the field of AI in India. This compilation was done is 2006; it may not be updated with the recent activities of the institutions listed, but will definitely give initial leads. It can be accessed over here: http://sigai.cdacmumbai.in/index.php/airesearchinindia
plz give me article on neural network
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how the neural network work as per the perceptrons in multilayers
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There is a book called "Perceptrons" by Marvin Minske, that is the definitive work on Perceptrons. It was so influential that it nearly caused the destruction of the Neural Network simulation industry. What Minsky is noted for, is his assertion that Perceptrons were linear processing units and couldn't achieve 2nd Order behavior noted in advanced neurons. It wasn't until Herman Hesse, suggested a new formulation, and the idea of Parallel Distributed Processing (PDP) that the industry recovered. The PDP crowd however was interested in Parallel Distributed Processing, not brain simulation, so there has been a split within the industry into Natural NN's which are meant to simulate real neuron circuits, and Artificial NN, which are processing techniques that are useful for achieving things that might be otherwise difficult to do with a computer, but which can be trained by route or take advantage of the Parallel Distributed Processing paradigm. You might want to check out the HH neural model which is based on studies done on the Giant Squid Axion, and is the basis for the ion channel explanation of how synapses work. Greg Markus has suggested that there might be a need for the Neuroscientists to do a hostile "Take Over" of the Neural Networks, now that PDP has advanced to the point it is no longer using the neural model, in most calculations. After all Neural Networks, were always about simulating neural circuits, and ANN was only a stopping point along the way.
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I need some publications about dose prediction using artificial intelligence in nuclear medicine units
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Try this one:
Kalet et al. Prism: A new approach to radiotherapy planning software. International Journal of … (1996)
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hello people, do u consider patricle swarm optimization as an intelligence technique apt enough
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In general, search algorithms in np-hard search domains combine optimisation and exploration. Exploration is almost always random, unless the problem domain has some probabilistic patterns that may guide the exploration. Optimisation is the 'intelligence' of search strategies, but it comes with the price that it tends to narrow down search to certain areas of the problem domain. Exploration can 'stumble on' interesting new areas, after which optimisation can take over in those areas.
'Intelligence' therefore is partially a matter of what is possible in a certain problem domain. If the problem domain has patterns that give clues to where the best values can be found, then the more intelligent search algorithms can find those patterns an utilise them. However, if the problem domain has relatively few of those patterns, then relatively simple optimisers will work just as good as more complex ones. A 'technically advanced' search therefore depends on the type of problem you are facing.
In my research (see http://www.springer.com/engineering/book/978-3-642-10700-9, forthcoming) I categorise a problem domain along the following properties:
familiar/unknown, np-hard(y/n), static/dynamic, reactive (y/n) and contingent (y/n)
If you are optimising a TSP type of problem, then you usually work in a partially familiar, np-hard, static domain. Agent systems (and particle swarming algorithms are often used here) work in dynamic, and sometimes reactive problem domains.
Every search strategy thus faces the problem that it needs to address the challenges of the problem domain. A more intelligent solution is better equipped to deal with this, but if the problem domain does not require certain strategies, it would be of little use to implement them.
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There are two types of memory in the human brain, Declarative Memory which we are all familiar with from computers, where essentially the memory can be searched via some index where each entry is declared, and implicit memory which can't be searched and which contains significantly more memory than we know that we know, and sometimes seems to ride on the coat tails of declarative memory adding semantic content to the declarative memory.
This project is based on the discovery that implicit memory is the natural form of neural network memories, in simple networks, and that multiple networks are needed to achieve Declarative memories. As such, if we want to implement anything like a mammalian memory, we need to start with implicit memory and build our declarative memory on top.
Early research into cognitive function, suggested that the architectonics of the neo-cortex, favored a content addressable memory. Information theory now supports the idea that there are two types of memory, "Place-Code" addressed, and "Content" addressed.
If so Declarative Memory must be Place-Coded, like computer memory, and implicit memory must be content encoded, like certain router components.
To get you started, those of you with electronic and digital experience might want to look at content addressable memory circuits. I have developed one using a couple of R-S Flip-Flops and a NXOR gate per cell that lights a Red LED whenever the input on the match line is equivalent to the content in the flip flop. I am sure however that D type flip-flops and JK type flip-flops could be made to work. Care should be taken however because I am sure the basic content addressable memory cell, and the static memory cell it is based on are patented.
The idea is to create a static memory cell, using two flip flops in serial, and then compare the output of the last flip flop to the Match line.It is an extremely simple circuit, but does not really capture the nature of implicit memory, For one thing, we need some sort of long-term memory and maybe an intermediate term memory within the cell. I have thought of incorporating a Flash, or E2Prom cell, which might be useful, but due to the architecture and availablility of these popular technologies, might require external linkage to associate them with an actualImplicit memory cell.
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I found this in the FET programme documentation:
4.2 Challenge 2: Cognitive Systems, Interaction, Robotics
Engineering systems with the capability to sense and understand an unstructured environment
is a challenge which goes beyond today's systems engineering paradigm. Present day systems
engineering relies on specifying every eventuality a system will have to cope with in the
execution of its task(s), and programming the appropriate response in each case. With the
abundance of ever cheaper, smaller sensors, actuators and wireless tranceivers that link
systems to the real world and with other systems, this approach faces serious limitations:
- The real world is generally too nuanced, too complicated and too unpredictable to be
summarised within a limited set of specifications; there will inevitably be novel situations
and the system will always have gaps, conflicts or ambiguities in its own knowledge and
capabilities.
- Even in situations where unpredictable events are less likely, the problem of extracting
meaning and purpose from bursts of sensor data or strings of computer code arises,
because we don't have a formalisation of information processing that embodies semantics.
This makes a very good case for implicit memory as being valuable in order to add semantics to stimulus detected with inexpensive sensors. Where current systems require that the software and hardware be specified for each other, a system with a sophisticated implicit memory should be able to extract the data from a number of sensors, without requiring specific design time data. Essentially it should cozy up to the sensors, and learn how to evaluate their information content despite the nature of the sensor itself.
The same tolerance for genetic indeterminacy that is required for biological systems to make sense out of their universe, is needed in engineered systems that will have maintenance indeterminancy. Unlike the eye, for one instance where the genetic parameters have not changed in millions of years, but in which some range of function can be found depending on the specific DNA and development history of the organism, Electronic components have a specific lifecycle that is usually not measured in hundreds of years. They also have a specific marketing cycle that is similarly constrained. Thus it is entirely plausible that a specified optical sensor will have passed its marketing life-cycle before it has passed its operational life cycle.
If this is the case we can pretty well guarantee that even if new equipment has similar optical sensors, that they will be incompatible with the old circuit. In circuits where the software and the electronic components are matched by specifications, this means that maintenance will require the replacement of not only the hardware that has failed but the software that drives it.
However replacement of sophisticated software requires the ability to determine what the original software did, which due to licensing and copyright limitations, will not be readily apparent where the company writing the software is no longer available to offer software listings. Thus with specified systems, degradation is guaranteed, if only because software maintenance becomes impossible after some point of time. Hence Obsolescence and E-waste. Aware of this, manufacturers, tend to design their systems to arrive at a catastrophic failure rate, after approximately 2 times the duration of the warrantee.
One aspect of implicit memory is that it degrades gracefully, and adapts to inconsistencies in function between one part and another, thus adapting to the eventual failure of components. As well, because it adapts to the components in the first place, it is open to maintenance by replacement with a slightly different standard of component. There is a learning curve while a new component is fitted, but once that learning curve is done, the system has the capability of working with the new components different capabilities, instead of working only to a pre-designed specification.
Implicit memory therefore is quite important to this Challenge, which might be one reason why the FET people are interested in possibly funding it.
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“Some people worry that artificial intelligence will make us feel inferior, but then, anybody in his right mind should have an inferiority complex every time he looks at a flower.”
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I think supportive tools in AI and the likes are certainly feasible, but I think we are still very far from humanoid robots. The genome has much less genes than was expected, which gives rise to the suspicion that the complexity of humans are in the combinatorial nature of gene-gene and gene-enzyme processes.
Complexity is going to be the big issue in the coming decades...but then I am a complexity methodologist, so maybe I'm just creating a job for myself here....;)
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PLease, can I have some news about neural growing gas or neocognitron (neural nets) ?
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Defined as the process used by multi layered NN.
neural growing gas:
Defined as a self organizing NN.
How abstract? I don't know.
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Can a person with allergies have epigenenics happen and if so what would the effects on the neurons in the brain be...????
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Allergies are probably a form of inflamation. Which is a bodies attempt to repair itself. Epigenetics on the other hand is evolution outside the Genetic Schema that make up the genome. While there is a link possible in the transcription process that builds the cell from the genetic material, that link is probably related to the activation of genomic DNA, not to the activation of the inflamatory system. So inflamation can impact on transcription, of Genomic DNA.
If I understand your question, you are probably talking about the "Other" DNA in the cell, such as the DNA that makes up the mitochondria mechanism, which interprets the Genomic Code, into bases for proteins. Does this DNA mutate, Undoubtedly, but it is much less likely to spread itself except through matrilinear transfer since there isn't the dominant/recessive aspect that dominates gamete DNA.
The link between this DNA and the inflamation/allergy system of the body, is much less direct, since it is the transcripted RNA that feeds the mitochondria, and thus the mitochondrial processing is rate limited by the availability of transcription RNA. So I have to say that when epigenesis happens at least in the mitochondrial DNA, it is probably not influenced by inflamation.
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Can you program people to learn to trust? And how
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Ok, let us take a look at this from a different perspective since Canada doesn't have near the same sort of Black Ops budget. ;)
Essentially Trust is a strategy, of Association. You are more likely to trust people you associate with, and do not know well enough to model their responses, "Closeness breeds Contempt", is one interpretation of this effect. So the brain prioritizes trust based on some process of becoming aquainted with another. Too far from the norm, and you get distrust, too familiar and you get distrust, the problem is to keep the object that you want trusted just far enough away, that it is familiar without being predictable.
Now lets answer the implied question of how to "Program" people. This assumes that people are programmable like a computer. While scientsts agree that the Mind does not work like a computer, There is evidence that it automates many things it does, and therefore is at some level programmable
One of the reasons we don't know for sure how to program the mind, lies in the fact that we don't exactly know how the Central Processor, if there is one, works.
However this question has come up in different forms for millenia, and many different cultures answered the question of how to program the mind, by building some form of hypnotic technique,
The problem with hypnosis, it turns out, is that there is very simply a skill factor in the case of the subject, that makes some people more susceptible to programming than others. Further people have been able to break trance, despite hypnotic states, whenever they are asked to do something that affects their self-image.
The Gray area between hypnotism and Education, is something called Suggestion. Suggestion is something that the mind has defenses against and some think that hypnosis is merely a way of getting around those defenses, at least partially. Courses such as language can be taught using a super-learning technique to more clearly train the subject in a short period of time. It is thought that these techniques are a mass form of suggestion.
Education and Indoctrination, involve the reinforcement of concepts crammed into childrens heads while they are still maleable enough to accept them, before, the necessary defenses are developed, in early adolescence. The problem being that pre-adolescent minds, are not as capable of grasping more abstract thoughts, since knowledge is something that is built up over time, because there is a knowledge phase relationship that indicates that knowledge is learned in phases approximately 2 years apart.
It is only relatively recently, that scientists have taken to designing drugs, and brain washing techniques based on the concept of achieving direct mind-control. Because these were Black Ops projects, we have no idea of how well they work, except the fact that from time to time we hear of a date-rape, that involves drugs that are of fairly recent manufacturr such as Rohypnol. This suggests that the mind control techniques that have leaked out are anything but fully effective, or the data wouldn't even know she had been raped, or would accept it without thought. Perhaps it is more effective in the hands of a professional who knows what it does.
So, can you program someone to trust, I would have to say yes, but not everyone, and not every time.
Future direction of genetic fuzzy system
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Many approaches have been proposed to optimize the genetic fuzzy system, commonly rule reduction or selection and tuning of membership functions. Most people are doing research on these area, are there still any potential value or if there is any new direction that we can move towards? Please advice, thank you!
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Another interesting thing you might want to look into, is the idea of common phrases in the rule base. One way of looking at chromosomes, is that they are rule-bases of DNA. Another way of looking at them is that they are libraries of Genetic schemas. Modern research into DNA has indicated that the schema's are often more conserved than their order in the library. If you take your genetic language, and Macro-ize it by collecting common phrases in the rule-base, and substituting them with a macro-call to the phrase, then you can reduce the size of your rulebase, because you will be performing a functional compression scheme upon it. Another aspect is the repeat coding, which allows you to repeat a phrase a number of times simply by coding a repeat phrase in to the rule. The next trick might seem a little strange, and that is to analyze the profiles of the rules, and determine which rules are most commonly used at the same time, and split up the rule-base into chromosomes based on the idea that if two rules are needed at or about the same time, then they should be serviced with separate searches, so that the search latency is reduced. In other words the idea is to build a heirarchy of Rule-bases set up so that they can be searched concurrently, to reduce the search latency. Once you get into parallel searches of multiple rule-bases well where do you stop? The Brain uses massive parallelism and what I think might be CAM (Content Addressable Memory) based selection techniques for information. Essentially it asks each snippet of memory whether it is part of environment that is being experienced during perception, and that memory either agrees that it is, or fails to agree, and doesn't fire. You could do a parallel rule search using CAM to trigger the rule. If you do that, and the brain does something similar in the Cerebellum then your problem is how to deal with the sheer volume of parallel rules clamering for your attention. One way is to key the rules to outcomes and collect the rules according to common location of common phrases, and use a pseudo-sequencing scheme that allows you to select your path through the similar rules at the branch points in the rules rather than at the actual rule level. You can see this as a sort of clustering of rules by similarity. as long as your choices are made at the branch points, you don't have to actually choose between similar rules that share the same code. The selection of which step to take next, is determined mostly by content and goal. Some evaluation of which choice will take you closer to the goal is necessary, and some way of resolving the deadlock case where two alternate choices give you no purchase on which one will do the job better, A final stage might be needed to deal with the case where none of the options will get you closer to your goal, the "You can't get there from here" statement.
Handwriting NN & Fuzzy Logic
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A directory has been established for this sub-division in the files section. Additional file sections for DARPA and DoD projects and contacts, grants, etc.; and a directory for the Android Project; of course the primary component to be developed is the positronic [photonic Brain], of course that includes sensor sections, materials sciences, laser based systems, scintillator and spectrograph sciences, specialty Erbium and Lutetium Silicate blends for the fibers [Neural Networks - Physical as well as virtual]; the other systems will be bio-adapted materials demonstrating strength through reticulated structures; and human like range of motion without gears. A major project to be sure! The power systems will have to be scalar, that is a guarantee, it must be compact and high-power output, about 5KW per mg of weight. Possible with a Kron-like Resistor, but will need to utilize a new type of condenser-bio crystalline. Anyone in this group may participate - I hope many papers and dissertations can be written about this project.
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Actually, I have nothing against collaborative research, however, your patent documents on your wound treatment, are, I think way off topic even by the wide definition you have suggested for this group. What I am saying is that you can't collaborate, if you don't have some focus, and I am sorry, but so far I have seen little focus from you. This little rant, seems to illustrate my point, Preventive Medicine is an important part of the health system. But unless you are designing a health related project, and the projects you have posted files on, are not health related products, there is no need for filling the file area with unrelated files. Take for instance the file on the deformable wings of the one Predator Model NASA was working on. What were we supposed to learn from what amounts to a press release? That Optical fibers are lighter than wires for the same application? Frankly I think you have a lot of hobby horses that you want to trot out, and rant about. This isn't really where that type of thing should be done, a Blog-site would be much better. This is a social networking site, where people try to contact others with similar interests, not a platform on which to spout off about the failures of our particualr societies, unless you want to form a group specifically to network on the failures. Certainly A.I. is not about solving all the problems of the world, it is too hard a question for most of us to get our heads around. Instead we want to concentrate on how to make machines that are actually intelligent. (others may feel differently and that is their right).
Simple Machine intelligence could save lives
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While EMR's are probably best known for providing information to the health care team, a simple addition to the function of the record could allow doctors to avail themselves of recent information such as best or recommended practices for a particular problem or epidemiologic information on a particular diseases as confirmed case of the flu locally for patients with some or all of the presenting symptoms. I've seen more than one source that flu can literally go from vague symptoms to killing patients within a day. If I were an ER physician treating a waiting room full of vague complaints, presenting an index of suspicion for flu might save a life or two and keep lawyer in practice. My intention is to turn EMR's from simple patient report( almost like a credit report) into true medical information system supplemented by some machine intelligence when when appropriate. The opportunities are limitless The provider information systems could even go so far as to provided to patients and their families at home Best regards
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Ah! But then let's take a look at your average open source developer, who is developing for the joy and pleasure of developing alone. For my research I take an interest in the 'professional', or the 'craftsman', and beyond glory and honour, there is an intrinsic motivation to be found that is in the pleasure of being creative. The biggest problem of evil, I think, is that we tend to overrate it tremendously. In the end the great legacy of the past, constructions, buildings like cathedrals, the pyramids, etc. are not in the greatness of the rulers who ordered them to be built, but in the excellence of the many invisible souls who made it happen! There, in these invisible contributions, I think lies the true greatness of humankind!
Just joined
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I happy to be here. I hope discussions with members will build us all in our careers.
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Dun, you are most welcome. The honorable members of this group obtained remarkable results out of discussions ...well in the form of chatting. So what interests you most NOW?
Reinforcement learning
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Do you know any good survey paper about routing protocols for mobile ad hoc networks based on reinforcement learning approach ?
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Thank you so much for your comments thus far and have worked on various aspects of this for years with a variety of modalities, techniques and disciplines. I'd be happy to answer my results with a variety of approaches which you and others have mentioned. As soon as I can write it.
Medical diagnosis and treatment software
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I was hoping that might get some ideas on the sticky subject of medical diagnosis and treatement. In brief the idea is that given a preliminary set of test, symptoms and physical signs, how can a program begin to identify possible emergent cases and resulting approach, or discriminating among a group of common diseases with subsequent actions and identify valid outliers with the implication of disease or complications. Coming from a background in archaic statistics I' tempted to do a canonical correlation, or apply factor analysis as a intermediate step or an analysis of principle components. Try to forget that the complication are huge and the outcomes may be infinite as well as having a extremely large number of defendant variable to work with. I could go on and on with some of my ideas. The easiest answer is that it can't be done. My question is can a process with the given data useful for more direct and higher quality care. Note that there is some work by Larry Weed MD approaching such a problem but in my estimation , it is entirely too deterministic and would task massive , continuous skilled human input to maintain an application through this paradigm. We now have clouds, more powerful programs and even partial answers may be very useful. If you are inclined to give the obvious "IMPOSSIBLE" answer, would you be so kind as to enumerate on the most prominent obstacles would apply.
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In their book "Probabilistic Networks and Expert Systems" R. G. Cowell et al. describe a Bayesian Network helping in the diagnosis of Asian flu. In general graphical models can be interesting for such tasks with all the necessary precautions to take indeed.
ANN software
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Which neural network software do you recomend ? The neuro solutions site seems to be stuck in time, is their software up to date. Please comment .
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Hi, I believe they are outdated. Other approaches like Support Vector Machines and Conditional Random Fields give better results with stronger scientific basis
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In Artificial Intelligence studies, your studies are not complete until you understand the Evolution Heuristic.
A Heuristic is a strategy for approaching a problem. Unlike a logical statement which must be either true or false, a Heuristic is neither true nor false but instead an approach that works or doesn't work in a specific situation. What works in one situation may not work in another with different parameters.
The Parameters for Evolution are:
1. It must operate on a population rather than an individual
2. There must be a source of change repopulation and recombination
3. There must be a test of fitness applied at the individual level
4. unfit individuals must be eliminated from the population in some manner.
3 and 4 when applied together form the "Test to extinction" hypotheis of the meaning of survival.
It is obvious that most people do not understand evolution so they often talk as if individuals were evolved.
It is also obvious that people mistake the guidance of the heuristic to come from the source of change, rather than from the test of fitness.
To consider why this might be the wrong approach, imagine a statistical scatter graph of a random population based on any parametric property. Now mark a location as the top of the graph, and turn the graph so that location is at the top of the page. Now draw a line through the graph from top to bottom on the right hand side. This is the population that has been selected as unfit.
If you recombine the remaining population some of the new population will fall over the line an be considered unfit, over time, the new populations will gradually lose the ability to recombine to form variations that fall over the line. If we look at the new resulting scatter graph, we will see that the graph has moved to the left. It is however just as scattered, it just no longer contains the variations that used to fall over the line.
Randomness is direction neutral, but fitness is not.
If you understand that, then you will see that Evolution is very similar to a hill climbing heuristic, or a controlled descent heuristic the primary difference being that it is based on survival.
Survival however is not easily understood as a fitness measure, unless you understand Entropy.
The Second Law of Thermodynamics states that nothing happens unless it makes the Universe a little more entropic. A corrollary is that the more entropy is promoted by an event the more likely that event is to happen.
Organisms exist because they increase the entropy of the world significantly while reducing the entropy internal to themselves. One way of looking at it, is organisms export entropy. So do societies, if you want to see an example of this all you have to do is look at E-waste. People here in civilization all want a fast computer, as a result computers are constantly being replaced with faster ones, causing the old computers to become obsolete. Here we see it as buying a new computer and recycling our old one.
In china however, what is seen is large shipments of E-Waste that are stripped in primitive conditions in order to recover the valuable materials. This creates pollution, which makes china's industries unsuitable for making toys for our populations. In other words our tidy little management of E-waste here in first world countries, promotes pollution in second world countries and third world countries. This is the entropic cost of being a first world country.
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Very well said. But the BRAIN.
Organisms exist because they increase the entropy only of their surroundings, obviuosly. Against this let us consider the time taken for each elementary operation neurons operating at a maximum rate of only 100 Hz, while a conventional CPU carries out more than hundred million machine level operation per second. despite the built with very SLOW hardware, the brain has very remarkable capability. Though its paerformance tends to degenerate under partial damage only, while most engineering systems are brittle. remove some arbtrary parts, you may likely have the whole system ceased to function.
As a disciple of AI, neural networks is attampting to bring coputers a little closer to the brains capability by immitating certain aspects of information processing in the brain, so as to keep to its bearest minumum the so called E-Waste.
Chess and similar board game playing engines, and programming languages
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I will add this discussion here, so that it is shared with everyone. Currently, most of the best board game playing engines have been written in C. This is in high contrast to AI community, and numerical computation community, where languages such as Lisp and Fortran are more highly regarded. Is there a reason for the apparent non-existence of the functional and numerical languages in the field of board game playing engines? Why is C still the de-facto choice for these applications? Why hasn't there been any concrete demonstration of the power of the higher level languages, in the form of a powerful engine written in Lisp, Erlang, Fortran, JoCAML, or similar languages? I would expect that this is because these game playing engines are basically exercises in alpha-beta search algorithm, and this algorithm is trivial to implement in lower level languages. However, it would be equally trivial to implement this kind of search for example in Erlang with enhancements, so that the work would be divided between multiple nodes and processors, so that the overall efficiency would scale up in nearly linear fashion by adding new calculation nodes. In addition, a higher level language might give opportunities to use more complex heuristics in the evaluation of positions. In my opinion, it should be possible to demonstrate the power of these numerical processing and parallelization-oriented languages in chess engines. However, examples of such projects do not exist, and the most powerful chess playing engines at the moment have been written in C. At the top of my head, I can name two: Rybka and Fritz. Link: http://en.wikipedia.org/wiki/World_Computer_Chess_Championship I do not have experience if similar C-language preference is seen in Go playing engines. It would also be enlightening to know what programming languages are dominant in other games.
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I use Visual Basic 6 in my processor-intensive chess programming work. Easy to code and never had any real issues.
OP
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Mind control and programming have all played a significant role in everyone whether they realize it or not. Society has permanently been branded as a guide to follow standard procedures, rules and regulations. If not for the incongruity that individuals possess, or the power of free will, our lives would constantly be in a frivolous state of being; still in the grip of paralysis. We see it everywhere. All you have to do is look around. Some of the classic criteria involved in mind control exists in everything from religious affiliation that involve both subliminal and physical suggestions that may lead the receiving individual to substitute their conscious thinking for an apparent panacea for their life. We also see this in extreme cases of subliminal clarification such as advertising. This technique has been used for ages, and why not? Its seemingly inspired millions of people into doing what the company wants. Signs, commercials, music, entertainment; They all stand guilty as charged. Hypnosis also plays a part in the way our steady thinking is perceived. Hypnotist induce a trance like state on an individual to make a genuine connection between the person, mind, and soul. This method is described as state of mind you are in just before you fall asleep. Although you are still conscious you are in a euphoric presence. This may be achieved in so many directions. One of the most effective ways to induce this state is by having the individual clear their mind, then asking them to take several deep breathes, with their eyes shut, roll them back in their head, and tilt their head back (this causes blood to flow to the back) and continue deep meditative breathing. So mind control is without question definitely out there. You don't even have to leave home. Programming is a perfectly effective term used to describe the manner in which our individual thought process has become altered. Our perception and outlook becomes perceived into believing in a systematic order. N.L.P.'s (Neuro-Linguistic Programmer) use programming as a basic tool for their practice Neuro scientists are still experimenting with electro-magnetic radiation for purposes of studying hypnotic preservation in the brain. For some time now scientists have played the thought of infiltrating text and information patterns into parts of the brain which proliferates the function of control and memory. The advanced technology used today incorporates neural signals to maneuver mechanical or prosthetic limbs. These computational methods even go as far as being able to sense physical contact. After doing some research in the area itself, although I believe its extraordinarily fascinating, and maybe even beneficial; Even though it is known that we actually use basically all of our brain. If you think that the brain and its app: 100 billion neurons is only capable of using a filtered 10-15% of its potential. Would the human mind be able to process the whole entirety of the information instilled? It is however understood that we use basically of our brain.Would it reach an malfunction or overload? Between rate, temporal, and population code, I believe the neural development may be unstable for this type of progression. Both mind control and programming are interrelated and feed off each other. Technically without one, you can't have the other. The same synaptic response initiated during programming is found in the neurotransmitters that send signals throughout the brain. In an attempt to seek out the perpetrator, Look no further than ourselves. In fact look at everything that exists. People control people who control industry who control advertising, who in return control people. It could even be considered peer pressure! Its a chain reaction. We are all in on it. My personal experiences are complex since I was little doctors insisted I was schizophrenic, since then I have been doing work as an undergraduate physicist, NLP, trying to figure it all out So if you can see it, its exists. For some time now scientists have played the thought of infiltrating text and information patterns into parts of the brain which proliferates the function of control and memory. The advanced technology used today incorporates neural signals to maneuver mechanical or prosthetic limbs. These computational methods even go as far as being able to sense physical contact. I'm actually minoring in Computer Science and were discussing the Physics of networks, binary code, and artificial intelligence. Basically the way we interpret things as being the syntax of codes can actually develop patterns that respond to human stimulus, and translate computational methods in algorithms, processing, and networking. It is probably true that in time A.I. will surpass the human condition in research and development. Could be a most frightening sight.
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Mind control IS programming allthough programming is not neccesarily mind control. Next to electro-magnetic targeted emmissions & quite similar Microwave emissions, it has become quite easy for those with the knowledge & funds to target individuals & the masses. Having been submitted unvoluntarily by the organized bad guys for sure and possibly the good guys aswell....:)) It is amazing how one gets certain convenient labels like schizoid, schizo-affective, schizofrenic or even A-social. Acoustical hallucinations. The term Nasal halucinations I have never heard, probably I did not get this label because I have only told few about my experiences with these 'Nasal Hallucinations' Some 5 years ago, staying unvoluntary on a tropical Island, which started like paradise, I had a mint bush in my garden from which I made my daylie Tea. Suddenly the Minty bush had changed in Lemon smell & taste. After having established the structure of the Immense dry & hard soil was hard & dry as usual. Close research of the bush & leaves resulted in my knowledge no leaf had been glued on the bush. The smell & taste shifted from Minty to Lemon a couple of times. It was about 2 years later that I found the solution to that problem which had been just one of the manipulative ways to drive me crazy. 2 years later I read a piece about the limbic part of the brain where the taste & smell center is. Having witnessed what I witnessed on that Island, knowing these people have many Billions to spend Internationally. Thinking they pay much better than the good organized guys, the only logical conclusion can be that humankind is way further than the newest scientific journals are allowed to tell. Simple but dangerous deductions if one wishes to spread this information to 2 many. This being one of the most simple things I could but would not construct, it can indeed be a frightening thought for the sleepy masses. I don't think it is good to exhibition all my knowledge, not only for my own safety as I have been told by people who also told me that I had passed the exam on all mental & physical painlevels, having used everything they have available. Maybe they did and maybe they did not, I finally got used to the strange X-files kind of life I have been leading. My curiosity has not become less however my lips are much less loose
Living Cell theory
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can anybody explain about living cells & frame a protocol for it?
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Are you looking for a biology protocol or a Neuron Protocol. There is quite a bit of work going on in Simulation of different types of cells using A.I. techniques. One recent simulation on the Blue Gene computer in Switzerland attempted a statistical model of the Cylinders found in the Neocortex. It modelled 10000 neurons with one neuron per processor and ran for only a few seconds creating reams of data, that will take years to properly evaluate, and they are still tuning the model.
Learning to play a game from the opponent
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Hello, I am seriously interested on the methods of learning to play a game from the opponent, of course (i.e., teaching the machine to play a game). Imagine that you have a game on computer, for instance checkers. Your checkers perfectly know the rules of the game but have no idea on how to play to win. Fortunatelly, you have a good a perfect (or at least very good) player as the opponent for your machine. They can play together and probably the machine, making random (but onle the allowed ones) moves will usually lose the game. However, the machine can make use of the history of the finished games. I seek the answer for the question: how can we obtain it? Everyone is invited to this discussion :). Best regards, Adam Sobczyk
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It seems like the first step that needs to happen for something like this is figure out how to reduce the state space as much as possible by combining sets of similar moves (or rather, combining sets of initial board positions). For a whole-board game like chess this is less desirable, but its essential for something like Go in which large parts of the game consist of more or less local pattern recognition. To that end, what about using something like the methods used for grammar reconstruction? Basically the idea is to find sets of board positions where the same sequence occurs despite differences in the board position, and then assign that set of roughly interchangeable board positions a label such that when evaluating move statistics those positions can be seen as equivalent. More generally, a hierarchy of these equivalent board positions can be constructed, and tree searches can first occur at the top level of the hierarchy, expanding equivalency categories as move data becomes available to improve the precision of the move evaluations. Some papers on this method: http://www.iis.ee.ic.ac.uk/yiannis/LeeKimDemirisICRA2012.pdf for a game-based application of this and http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1187953/ for the original grammar reconstruction algorithm (ADIOS) I'm thinking of. At the end of the day, this still would not give you a representation where you could cleanly 'explain' the rules to another player using the collected data though (e.g. instead of 'the bishop moves diagonally' it'd simply have a huge database in which 'I have never seen a board position where the bishop has moved anything other than diagonally' is true). I think that would be an interesting thing to try to achieve (although harder than the original question), but I don't have a good idea of how to start there.
Thoughts Regarding Artificial Intelligence
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It is a pleasure to read your comments regarding artificial intelligence and for me to present a few of my thoughts. It is also sad that in my opinion we have not made much progress in AI over the last thirty-six years. I think you guys are asking the right questions and hopefully you’ll find the way to the answers that will lead to some breakthroughs. In 1971 I began my PHD Thesis entitled the “Simulation of Decision-Making” based on Arthur Samuel’s research using a Checker-Playing Program that learned from experience through the use of expert system rules and perceptrons (basic neural nets). While Arthur Samuel built his program to learn to play like his opponent, my program based its evaluation criteria adaptation on the game’s objective, as there was no guarantee that the opponent the machine played was any good, but winning the game was always the objective. The definition of intelligence is basically what you find in the dictionary: “… ability to think and learn: the ability to learn facts and skills and apply them, especially when this ability is highly developed”. I became convinced that key areas of AI had to include the ability of the program to make intelligent decisions based on some evaluation criteria, coupled with the use of adaptable algorithms able to learn and improve dynamically from experience in the intended space of the program’s use, and that if an application didn’t include learning and intelligent decision-making, it probably wasn’t AI. I am also convinced that awareness or perception of one’s existence is essential to real intelligence at a human’s level, as are some driving stimuli (goals and objectives) based on some fundamental criterion or objective. The definition of artificial intelligence that I always liked included words something like, “… and the ability to make good (useful) decisions and to learn in its performance…” Unfortunately, based on my definitions and beliefs it appears to me that we still have a very long way to go to achieve true artificial intelligence whereby a machine is able to demonstrate the kinds of knowledge abilities that we humans are able to exhibit, and in fact take for granted. As an example, given an AI program of one’s choice, does anyone think that for a half hour we could be discussing college football, and then suddenly shift to discussing the presidential campaign, and then shift to a discussion of where we might go for lunch and what we night have for lunch with intelligent conversation from the machine at a human’s level? Humans do this easily without much thought but for a computer program to do this and learn from the information discussed remains a research effort in my opinion. I remember 35 years ago when I learned the language LISP with which one could write a program that modified itself. It was obvious that LISP would allow one to write programs that were able to modify its procedures and processes and thus improve (learn) with experience. But with a little bit of work we humans learned that this was not true, and we do not seem to really understand how we learn and how we modify and reprogram ourselves to improve with experience. Thus, it appears to me that there are no significant breakthroughs that are going to change where we are with respect to true machine intelligence comparable or exceeding a human’s capability. If anyone is aware of work that appears to be a significant step forward, please let us know with a message describing the source of the information.
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I am interested with the development of the algorithms and methods offering the real AI. My inspiration comes from the experiences based on the optimisation techniques. This time I am testing my approeches on the logical games which I teach the computer to play. If anyone is interested to cooperate on that topic - please feel invited.
My views
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Here I have shared some of my ideas about A.I. http://intelligentcontrolsystem.blogspot.com/
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thanks
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I need a pdf file and vidoe file about neurosolution5 software.
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I have a pdf file about NeuroSolutions.
What do you think about publication?
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Prof. Dr. David Parnas(a pioneer in Software Engineering) has joined the group of scientists which openly criticize the number-of-publications-based approach towards ranking academic production. On his November 2007 paper Stop the Numbers Game, he elaborates on several reasons on why the current number-based academic evaluation system used in many fields by universities all over the world (be it either oriented to the amount of publications or the amount of quotations each of those get) is flawed and, instead of generating more advance of the sciences, it leads to knowledge stagnation.
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There are quite a number of other problems with the way publications are currently judged. I do a lot of research on methodology on complex systems, and this forces me to jump over scientific paradigms every now and then. It is almost impossible to get my research published, because every scientific discipline has their own criteria on what they consider 'rigorous' and what not. Before the mathematically inclined start priding themselves on this issue (and beating down on the social sciences and the humanities), my own research has shown that the 'hard' sciences tend to be very sloppy on their own self-reflexivity...they are a lot less 'rigorous' when the foundations of their own methodologies are put to discussion (because that's 'just' philosophy...) Social Scientist Edgar Morin has called for a 'crisis' in academia because of this 'blind knowledge' in his book 'on Complexity'. Others, like Systems theorist Gerald Weinberg, argues that some 'rigorous' methodologies just are inappropriate for certain kinds of complex themes. If scientist use these methodologies, then their models have little resemblance with the themes they purport to describe. Scientific 'rigour' them becomes a false kind of qualification for research excellence for those themes. All in all, I think science may be heading for a Kuhnesian 'revolution' or paradigm shift because of the complexity of the themes we are currently addressing...interesting times indeed!
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A new cloud-based simulation service was launched last week by the developers of MEME (a behaviour space like tool for NetLogo, Repast, and other platforms from AITIA International). Check the website (http://modelexploration.aitia.ai ) to find out how to run massive parameter sweep experiments in the cloud!
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aslam o alaikum :) amd welcome :)
RE:
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...So fundamentalism is a state of mind of some people, and not something that is caused by religion or so....
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Fundamentalism is state of mind and it is caused by the surrounding environment of a human brain. But it also changes with the time because human brain is always intuitive of changes and accepts it by will or by force. Human brain observes, try to understand, learn and adopt the facts on some meaningful grounds. When these grounds become solid enough to be protected with some arguable evidence, we call it fundamentalism.
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this is my reseach plan
"automated parking gate system"
to build the system, will applied
"pattern recognition" and "machine vision"
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Check your inbox on researchgate for my mail. I am willing to assist you. Contact laremtj@gmail.com or adewumia@ukzn.ac.za
morality
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The fact that it is artificial proves that it is not intelligent
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Cute play on words. I have nothing against play, and I certainly want to enjoy this subject. But - This site can be a very powerful forum to solve real robotic problems. Robot morality may be a bit futuristic, can we discuss things like how does a robot take a general project, break it down into a series of tasks and develop a solution? Straight from the dictionary - Artificial: Made by human beings; produced rather than natural. or: Brought about or caused by sociopolitical or other human-generated forces or influences intelligence: The capacity to acquire and apply knowledge. or: The faculty of thought and reason. People are trained in school by teachers, at home by parents, and on the streets by life experiences. Robots are trained by programmers. We both (people and robots) make decisions with the information we have available. How that happens in a robot is up to the programmer. I thought this section would deal more with how to teach a robot to use sensors for input, apply that input to its program, to face new and unusual problems.
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is this possible? write a program that can guess the human mind.
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@Mr. Smith
Correct me if i am wrong i think even random number
generator follows a pattern.
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hi,
all of member of this group,I fell please joining this group
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aslam o alaikum (means may ALLAH bless you with peace)
welcome ..
have a nice day :)
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what projects do you guys have for now?
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I'm still trying to get my implicit memory project off the ground, we missed the FET deadline.
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i was disconnected by research gate due to some reason for some days... sorry...
i miss your healthy discussions and fruitful comments.. i am searching a job after completing my MBA in HR.. no any job found yet... :(
but i hope for the best..
regards to all of you
have a nice day :)
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thank you :) jazak allah
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I am looking for guidance with LabView - could someone help?
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I learned it 95% with tutorials on the web. If you know just a little of the logic of programming, it should help you a lot. After 40-50 hours of work, try to seek a specialist around you, it will show you the way to good programming. The 5% I learned with a tutor was very important and took only two hours of his time...
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can u send me a techniques in puzzle solving
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Hmmm....
Lets try...
1. determine what the problem is.
2. build a model of the problem.
3. Genetically Generate a possible solution set for the problem
4. compare the model of the solutions set to the goal you want to solve the problem for
5. Determine if the solution set brings you closer to your goal.
6. Try 3 to 6 again until you reach a semi-optimal solution set.
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a new optimization technique...........much easier than the particle swarm optimization
the glowworm sarm optimization technique............excellent approach to metaheuristics.......
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aslam o alikum :)
what is the glowworm particle approach ?
can you please help me in understanding this
have a nice day :)
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a new optimization technique...........much easier than the particle swarm optimization
the glowworm sarm optimization technique............excellent approach to metaheuristics.......
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Hmmm... never heard of it before...
I have been working with a metaheuristic optimization technique concept for my AM language to be used in my Cognitive Engine. It integrates code compression/optimization techniques, predictive modeling, a metaheuristic search, for the pool of good enough code, a rewind mechanism, and similarity selection techniques for final macro selection from the experential pool pseudo sequence.
I would be interested in discussing with you the differences between the Glowworm Sam technique and my own.
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can anyone tell me that is there any organisation/institute that invite or entertain new biological research ideas and theories?
can anyone help me?
Best regards:
Aditya parekh
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thanks very much. will look forward to the mentioned institutes.
thank you again shridhar.
If you are also interested in such ideas then it will be my pleasure to have a discussion with you.
Best regards
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Hi all, is there any (compiled) list of available (commercial and free) ANN software?
Borislav
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hi...i'll be conducting a research study on data mining so I need neuro fuzzy toolbox that can install in Matlab software, can u help me please with it. you may have previous studies about the topic i'm planning to undergo
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Matlab has strong toolboxes for neural nets & genetic algorithms, among others. Check them out. They should definitely have enough to get you launched.
Charles Dworkis
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i am a new entery in this web site .i want you all share good and informative discussion and i will learn from you all :)
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You are most welcome. Wa alaeka salaam. Be in peace
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I recently started to become bored with robots. Seriously, they do nothing more than what you program them to do, and very often far less! Therefore I started thinking if it is possible to "release" some control over these machines, and study their behaviour afterwards. This has been the main line of my research in the past months, and I think I am getting somewhere.
You will find more details on my blog posts here or at http://lorenzoriano.wordpress.com/ . It is work in progress now, but stay tuned because new results are coming soon!
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I think my reply got lost at the ISP level. (Slow network connection)
to paraphrase it, this is unfinanced research, and because it is coming out of left field, and is not sponsored by a University, it depends on my limited ability to document it, in order to make it approachable.
While I have attempted in the past to document parts of it, I have yet to find anyone who can review the breadth of the project, because it is a new cognitive architecture, based on an Artificial Consciousness paradigm, in turn based on a new memory model which is heavily dependent on my own interpretation of histo-psychology, which in turn is based on cyto-architectonics.
the best treatments to date, consist of a Portal on Wikiversity at http://en.wikiversity.org/wiki/Portal:GreySmith_Insitute This portal is in reconstruction mostly because the original portal design became unmanageable and the cognitive architecture got burried in the indexing.
The next best treatment is in the book I am currently writing called "Memory Mechanics" which is currently in an early editing mode at chapter eight, and has been fleshed out to chapter 12. I hope to have about 16 chapters. Previous versions of the book proved unreadable I am hoping with the new editing effort this will not be the case with this version. this book is describing the cognitive architecture from the memory perspective, in order to describe the memory mechanisms involved and why they work the way they need to.
If I can complete the work, and get it reviewed, the next book in the series, will approach the subject from the Artificial Consciousness perspective, and it is only then, that I will be able to get around to the writing of a book based on the cognitive architecture.
The problem is simply that the project is too large for someone without backing to fully deal with and I have had no luck in finding anyone to review the ideas behind it. If only because it bridges too many disciplines, and is in too early a stage of research.
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I need computer program to integrate aviation RADAR System or ADS-B with eurocat system according to existeng PC computer hardware
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I think you can answer the question by satellite design software, but i have not any one in my area i mean my work.
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Grasping, storing and recall are 3 different functions attributed to memory enhancement. I have made an attempt to scientifically establish as "How it works". I would appreciate more inputs to further strengthen this theory.
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I may have a similar model, although I do not know what you mean by grasping. This model is based on my book, currently being rewritten called "Memory Mechanics".
In my model the first step in memory, is implicit similarity selection.
What your model doesn't cover, of course is implicit to explicit conversion creating an explicit "chunk" at the functional cluster level and breaking down the functional clusters "Data cloud" into mappable components via editing the chunk during rehearsal.
It is only once you have an explicit representation of memory that you can recall it,
An important step in recall, is the step of rehearsal, where the memory is kept active in working memory during it's useful life.
An interesting side effect of rehearsal, is that it "Writes Through" short term implicit memory to long-term implicit memory. This acts to qualify memories before transfer to long-term memory, since the only memories being rehearsed are the ones important enough to be recalled from time to time.
Processing is required to generate an index, and from it, a meta-index or index of indexes. Search within the index creates a metacognitive signal called "Feeling of knowing" if the memory or something similar enough is found in the index. A method exists whereby declarative indexes can be linked back to the content in the implicit memory, When there is a feeling of knowing, but the implicit memory link fails, a process called "Tip of the tongue" is started to recover the missing memory. Together these make up "Declarative Memory"
A last step is the Archiving of the index, periodically back to implicit memory so that it can become part of the processing. It is interesting to note that in humans the archiving step does not fully complete for 2-2.5 years after the original memory is laid in. As a result developmental psychologists have noticed that language development improves in distinct stages approximately every two years during early childhood.
I am deliberately not mentioning the skill memory which has a different role, and so would not be part of your model.
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I'm new to this group.. And found it as interesting source to understand the new areas.
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Hello everyone,
I'm also a member of this group but still didn't partecipate so much, I'm also interested in natural language understanding, I wonder if we can start talk about this topic and suggest some interesting articles.
I read something about neural network implementation by Elman (1991) and found it very interesting.
Artificial Cell theory
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Based on our knowledge of molecular biology and soft condensed matter, a constructive approach can be devised, inspired by the automata theory of J. v. Neumann. With the advances in cell-free expression a cell-like structure can be assembled from an extract supporting transcription and translation. First, we used a wheat germ extract to reconstitute elementary networks in vitro (1). Then, an Escherichia coli extract has been used to make a vesicle bioreactor that can sustain cell free expression for a few days (2). We are trying to develop this system to build a minimal cell. We are especially interested in the molecular and supramolecular mechanisms to get a self-reproducing system as well as the aspects of origin of life at the mesoscopic level.
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Hi Ebin, It sounds to me like you are deep into an interesting and complex research area. The origin of life has always fascinated me and if the approach you describe succeeds it will be a fantastic achievement. It is remarkable what a broad set of disciplines John von Neumann contributed to. My PHD thesis in 1973 was on the "Simulation of Human Decision-Making" and my approach used Arthur Samuel's machine learning mechanisms to gain experience. John von Neumann contributed to the concept of self-replicating machines and computers as we know them to operate today. However, instead of learning to play like its opponent, I had my program learn to accomplish the goals of success depending on what the program was attempting to achieve. It would seem to me that somehow the origin of life might be related to learning from experience. Good luck on the effort.
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Having had the digest version dumped to my e-mail for a while now, I can comment on the search accuracy, I note that none of the articles listed in the news actually involve my search terms. Further the search engine is selective and only lists about 4 of the six searches I asked for, and always the same 4, in other words this is not an effective search engine. Lately some of the articles have been blog posts, not actually articles from the so called magazines that are purported to be being searched. In short the quality factor is low and this Invitrogen search engine can be classified as a form of spam, masquerading as a search engine. I note that the request has been removed, this is probably wise.
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Dear AI group,
I'm currently doing research in how we can make robots learn to dance and for this research. At present, I have programmed a robot (simulation and real robot) to 'learn' to dance, without any preprogrammed actions. The robot first builds its own actions, which it then combines to form a dance, but there is still a lot to look into.
I have come to the conclusion that in order for this to be fully accomplished, there are two different trypes of results that need to analysed; one that shows a computational result to a dancing model and the other that is based on what people think (i.e. their perceptions of a robot dance).
I have developed a questionnaire in the form of a website that demonstrates some key points on dance and was wondering if you wouldn't mind taking part by honestly giving your comments on the robot's dancing.
All I need is approx. 30mins of your time please. Your feedback would greatly assist me on this research.
Furthermore, if anyone is doing work in this area, or has suggestions or interest, then it would be great to hear from you.
Thank you
Kind regards
ibs
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Hey Ibs,
It looks really promising, especially considering the fact that your robot is really LEARNING to dance...preprogrammed dancing is much easier to accomplish!
Judging the different types of movement has made me more convinced that you have to implement (if you haven't done so) a layer in-between the AI and the actually steering of the limbs, where you can implement various constraints (also the sequential ones that you demonstrate on the videos). What you can then do is 'punish' the AI if it selects certain combinations which are not allowed (like falling), and where the dog just does something else, while other combinations might result in a reward system. I can even imagine that you implement multiple layers of constraints, for instance where the lowest level constrains immediate movement of the limbs and the other layers sequences of movement. This way you get a NxM matrix where (sequences of) movement can be mutually weighed by th learning algorithms.
Cheers
Kees
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Since I've seen religion in action in person and in the news, perhaps a secular approach to A.I. would work. Even within religious circles misinterpretation leads to conflict, so how would A.I. be spiritual and not get past the 3 robotic law type rules such as those suggested by Asimov (though I hear there are better ways to do this as his laws fail outright) when faith can basically trump any logic man or science throws at it, so yeah, spirituality is a big bad idea. Also, adding emotions and a bit of imperfection in order for it not only to click with us but also for us to not feel odd around it and develop a sort of dissonance, say in deep space missions or undersea such as when you get culture shock, or chat too much online, game too much etc. Just sort of base it on constitutions like the USA where it has secularists (Jefferson, Franklin etc) mixed with religious people (Washington, Hancock I think, etc), that work to a common goal and show there doesn't have to be conflict between religion and theists. Give it a nice diagram of history including what religion has done good and bad, as well as science, male/female/children roles as well as animals (remember people that harm animals don't have compassion for man either when they do it for mere pleasure and not for food or defense). Quite a few more things could be added I'm sure, but that's a starter.
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I don't mean the particular programming details for specific one or two scenarios but rather I mean as a whole philosophy or mode of operation. Think of it as similar to Asimov's 3 robotic laws (which have been shown to be quite breakable) but as a programmer you also have to step back and make sure your work is what you wanted, like someone sculpting a statue (step back and make sure your idea of what you were " carving" out is not warped looking from a bit back where you can "see the big picture.") You'll have to do a mind map of sorts along with a flow chart to put that into code. It may require gathering data from the most intelligent individuals, since in psych 104 I learned those with higher intelligence deal with their problems easiest, i.e. they have the best mental health. You'll want this for A.I. as well, since having one go postal in one form or another is not a good idea, plus intelligence also makes for the good mental health of those it interacts with too. Plenty of other steps including how to deal with someone that's off their rocker but basics first. Am not a programmer myself by trade but I've done a bit but it wasn't anything fuzzy logic like LISP but did a bit of work with C and C++, Basic etc. Really basic stuff to be truthful. Oh and I did a bit of pascal and other things but other than knowing the basics of algorithms, being good at math somewhat, knowing about logic gates etc, I am not a programmer.
ANN implementation
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can any body tell me how can I code for back propagation for classification of sleep and wake using matlab...
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actually I am using ecg and respiratory effort signals. i did the preprocessing using periodogram method and got the coeff. values.now i need to give these coeff values as the input to ann. i dnt knw how to do that,...