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Chinese Room Argument - 2 views

c2.com/...wiki ai strongai
shared by Alexander Phoenix on 29 Oct 09 - Cached
  • Alexander Phoenix on 29 Oct 09
     
    and why it's not an argument
  • Volucer Volucer on 30 Oct 09
     
    I think, it's not an argument at all. Empty metaphysics
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Goedel Escher Bach - 2 views

c2.com/wiki ai
shared by Alexander Phoenix on 07 Nov 09 - Cached
  • Alexander Phoenix on 07 Nov 09
     
    Think for yourself if it's reasonable for you to read about AI from somewhat philosophical point of view. That bookmark is both for the webpage and the book it represents.
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IEEE Spectrum: IBM Unveils a New Brain Simulator - 2 views

spectrum.ieee.org/...-unveils-a-new-brain-simulator ieee ai brain neuroscience neuroinformatics news
shared by Matvey Ezhov on 19 Nov 09 - Cached
  • The number of neurons and synapses in the simulation exceed those in a cat’s brain;
  • Nikolay Sibirtsev on 20 Nov 09
     
    Мда, немного демотивируют приведенные цифры о соотношении массы и потребляемой энергии. По их данным получается вычислительные мощности эквивалентные человеческому мозгу на 5 порядков больше потребляют энергии и на столько же больше весят.
  • Matvey Ezhov on 20 Nov 09
     
    Как раз это демотивировать не должно - расчет ведется на современной архитектуре. Упоминавшейся в статье чип ДАРПАы будет потреблять намного меньше.
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Mapping the brain - MIT news - 2 views

web.mit.edu/...brain-mapping.html brain neuroscience connectome
shared by Matvey Ezhov on 20 Feb 10 - Cached
  • To find connectomes, researchers will need to employ vast computing power to process images of the brain. But first, they need to teach the computers what to look for.
  • to manually trace connections between neurons
  • want to speed up the process dramatically by enlisting the help of high-powered computers.
  • ...5 more annotations...
  • To do that, they are teaching the computers to analyze the brain slices, using a common computer science technique called automated machine learning, which allows computers to change their behavior in response to new data.
  • With machine learning, the researchers teach computers to learn by example. They feed their computer electron micrographs as well as human tracings of these images. The computer then searches for an algorithm that allows it to imitate human performance.
  • Their eventual goal is to use computers to process the bulk of the images needed to create connectomes, but they expect that humans will still need to proofread the computers’ work.
  • Last year, the National Institutes of Health announced a five-year, $30 million Human Connectome Project to develop new techniques to figure out the connectivity of the human brain. That project is focused mainly on higher level, region-to-region connections. Sporns says he believes that a good draft of higher-level connections could be achieved within the five-year timeline of the NIH project, and that significant progress will also be made toward a neuron-to-neuron map.
    • Matvey Ezhov
      Matvey Ezhov on 21 Feb 10
       
      draft of human connectome within five years
  • Though only a handful of labs around the world are working on the connectome right now, Jain and Turaga expect that to change as tools for diagramming the brain improve. “It’s a common pattern in neuroscience: A few people will come up with new technology and pioneer some applications, and then everybody else will start to adopt it,” says Jain.
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Работы Роджера Пенроуза - рецензия - 1 views

www.scorcher.ru/...penrouse.php penrose ai mind
shared by Matvey Ezhov on 05 Oct 09 - Cached
  • Matvey Ezhov on 05 Oct 09
     
    Вроде бы качественная рецензия на книги Пенроуза.
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Лаборатория ИИ - 1 views

ailabs.pbworks.com/FrontPage вики ИИ ai brain neuroscience neuroinformatics wiki
shared by Matvey Ezhov on 11 Oct 09 - Cached
  • Matvey Ezhov on 11 Oct 09
     
    Наша вики - рабочее пространство для агрегации всей найденной информации по ИИ
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Мозг революции | Наука и техника | Наука и технологии России - 1 views

www.strf.ru/science.aspx ии мозг brain neuroscience Анохин
shared by Matvey Ezhov on 12 Oct 09 - Cached
  • Ещё в 1998 году, до появления американского отчёта, Михаил Ковальчук предложил собственную идеологию объединения тех же четырёх областей знания.
  • «Крупнейшие нейробиологи мира прогнозируют, что через несколько лет таблетки для стимуляции памяти могут оказаться такими же привычными для здоровых людей, как витамины», — отметил Константин Анохин.
  • Проект компании IBM позиционируется как разработка принципиально новой компьютерной архитектуры, которая через год-два будет сопоставима по своим возможностям с интеллектом крысы.
  • ...3 more annotations...
  • Когда им показывали сотни разных фотографий, выяснилось, что в передней области гипоталамуса клетки очень специализированы.
    • Matvey Ezhov
      Matvey Ezhov on 12 Oct 09
       
      Явная ошибка
  • Например, у одного пациента наблюдалась активация определённого нейрона в момент узнавания изображения актрисы Холли Берри. Причём пациенту предъявлялись её снимки в той или иной одежде, в различных ролях, карикатуры и даже кадр, на котором была просто надпись «Холли Берри» на экране компьютера. При взгляде ни на чьи другие фотографии данный конкретный нейрон не реагировал. При этом соседний с ним нейрон у того же пациента активизировался только на образ матери Терезы.
  • для объяснения принципов организации сознания нельзя использовать какие-то усредняющие сигналы
1More

Искусственный интеллект / Блог / Хабрахабр - 1 views

habrahabr.ru/...artificial_intelligence ai learning
shared by Alexander Phoenix on 13 Oct 09 - Cached
  • Alexander Phoenix on 13 Oct 09
     
    Один из коллективных блогов на Хабрахабре, от критики до сообщников, от каптчи до философии ИИ
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Квалиа - Википедия - 1 views

ru.wikipedia.org/...index.php квалиа сознание вики
shared by Matvey Ezhov on 14 Oct 09 - Cached
  • Matvey Ezhov on 14 Oct 09
     
    Важная тема.
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Изменчивый мозг : Троицкий вариант - Наука - 1 views

trvscience.ru/...izmenchivyj-mozg мозг нейробиология
shared by Matvey Ezhov on 18 Oct 09 - Cached
  • Измерения ТМС показали: в результате упражнений моторная зона пальцев тренируемой руки стремительно росла. Уже к концу первой недели она увеличилась в разы (рис. А).
  • По-видимому, главной составляющей расширения моторных зон у основной группы служила фокусировка на задаче и сознательный контроль движений.
  • Моторные области людей, выполнявших упражнения в уме, походили по размеру на соответствующие участки тех, кто по-настоящему занимался на клавиатуре (рис. С). Мысленная тренировка привела к реальной натренированности — к изменению нейрофизиологических свойств ткани мозга.
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  • В определенном смысле на уровне физического субстрата сознание не проводит различий между действительными и моделируемыми движениями, инициируя сходные изменения мозга.
  • Вероятно, анализируя поступающие сигналы, мозг распознал в них паттерн, который в базовых чертах характерен для информации, обычно идущей от органов зрения. Совместив эти сигналы со знанием о движениях головы, мозг попытался построить картинку. Когда он убедился в наличии обратной связи, то стал учиться интерпретировать идущие от языка импульсы как визуальную информацию. Грубо говоря, он рекрутировал язык для выполнения функции глаз.
  • Если в режиме реального времени снабжать сознание информацией о текущих физиологических параметрах организма (обычно остающейся для него недоступной), то эти показатели постепенно можно научиться менять и приводить в норму.
  • Описанная способность мозга к саморегуляции дала развитие отдельному направлению научной медицины. В этой связи, как правило, используют термин neurofeedback (нейрофидбэк), или биологическая обратная связь.
  • Поврежденная часть не способна отрасти заново, как не может отрасти потерянный палец или конечность. Но мозг иногда оказывается в состоянии преобразовать имеющуюся ткань, сформировав уникальные структуры и проложив новые нервные пути. Это гораздо более долгий процесс, и он может занимать годы.
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PLoS Computational Biology: Qualia: The Geometry of Integrated Information - 1 views

www.ploscompbiol.org/...10.1371%2Fjournal.pcbi.1000462 qualia consciousness PLoS
shared by Matvey Ezhov on 23 Oct 09 - Cached
  • Matvey Ezhov on 23 Oct 09
     
    According to the integrated information theory, the quantity of consciousness is the amount of integrated information generated by a complex of elements, and the quality of experience is specified by the informational relationships it generates. This paper outlines a framework for characterizing the informational relationships generated by such systems. Qualia space (Q) is a space having an axis for each possible state (activity pattern) of a complex. Within Q, each submechanism specifies a point corresponding to a repertoire of system states. Arrows between repertoires in Q define informational relationships. Together, these arrows specify a quale-a shape that completely and univocally characterizes the quality of a conscious experience. Φ- the height of this shape-is the quantity of consciousness associated with the experience. Entanglement measures how irreducible informational relationships are to their component relationships, specifying concepts and modes. Several corollaries follow from these premises. The quale is determined by both the mechanism and state of the system. Thus, two different systems having identical activity patterns may generate different qualia. Conversely, the same quale may be generated by two systems that differ in both activity and connectivity. Both active and inactive elements specify a quale, but elements that are inactivated do not. Also, the activation of an element affects experience by changing the shape of the quale. The subdivision of experience into modalities and submodalities corresponds to subshapes in Q. In principle, different aspects of experience may be classified as different shapes in Q, and the similarity between experiences reduces to similarities between shapes. Finally, specific qualities, such as the "redness" of red, while generated by a local mechanism, cannot be reduced to it, but require considering the entire quale. Ultimately, the present framework may offer a principled way for translating quali
1More

Technology Review: Intelligence Explained - page 1 - 1 views

www.technologyreview.com/...23695 intelligence brain neuroscience
shared by Matvey Ezhov on 24 Oct 09 - Cached
  • "Scientists are now able to switch the focus from particular regions of the brain to the connections between those regions," says Sherif Karama, a psychiatrist and a neuroscientist at McGill University's Montreal Neurological Institute.
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» Python in neuroscience - 1 views

www.ine-news.org/view.php neuroscience programming python
shared by Matvey Ezhov on 25 Oct 09 - Cached
  • Some already exist specifically for neural data analysis and simulation, such as PyMVPA2 and Brian3 respectively.
  • Matvey Ezhov on 25 Oct 09
     
    A widely used open-source programming language, Python is becoming the language of choice for neural data analysis and simulation.
3More

Technology Review: Intelligence Explained - page 2 - 1 views

www.technologyreview.com/...page2 intelligence brain neuroscience
shared by Matvey Ezhov on 25 Oct 09 - Cached
  • In 2007, Jung and Richard Haier, now professor emeritus of psychology at the University of California, Irvine, developed the first comprehensive theory drawn from neuroimaging of how the brain gives rise to intelligence.
    • Matvey Ezhov
      Matvey Ezhov on 25 Oct 09
       
      we need to find them
  • Applying existing theories of how information flows in the brain, Jung and Haier hypothesized that neural signals travel from nodes near the back of the brain, where sensory data is collected and synthesized, to those in the frontal lobes, which are responsible for decision making and planning. The connections between these nodes, they argued, are just as critical as the nodes themselves.
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Is this a unified theory of the brain? (Bayesian theory in New Scientist) - 1 views

reverendbayes.wordpress.com/...yesian-theory-in-new-scientist bayesian theory of the brain brain neuroscience ai science neuroinformatics
shared by Matvey Ezhov on 27 Oct 09 - Cached
  • Neuroscientist Karl Friston and his colleagues have proposed a mathematical law that some are claiming is the nearest thing yet to a grand unified theory of the brain. From this single law, Friston’s group claims to be able to explain almost everything about our grey matter.
  • Friston’s ideas build on an existing theory known as the “Bayesian brain”, which conceptualises the brain as a probability machine that constantly makes predictions about the world and then updates them based on what it senses.
  • A crucial element of the approach is that the probabilities are based on experience, but they change when relevant new information, such as visual information about the object’s location, becomes available. “The brain is an inferential agent, optimising its models of what’s going on at this moment and in the future,” says Friston. In other words, the brain runs on Bayesian probability.
  • ...6 more annotations...
  • “In short, everything that can change in the brain will change to suppress prediction errors, from the firing of neurons to the wiring between them, and from the movements of our eyes to the choices we make in daily life,” he says.
  • Friston created a computer simulation of the cortex with layers of “neurons” passing signals back and forth. Signals going from higher to lower levels represent the brain’s internal predictions, while signals going the other way represent sensory input. As new information comes in, the higher neurons adjust their predictions according to Bayesian theory.
  • Volunteers watched two sets of moving dots, which sometimes moved in synchrony and at others more randomly, to change the predictability of the stimulus. The patterns of brain activity matched Friston’s model of the visual cortex reasonably well.
  • Friston’s results have earned praise for bringing together so many disparate strands of neuroscience. “It is quite certainly the most advanced conceptual framework regarding an application of these ideas to brain function in general,” says Wennekers. Marsel Mesulam, a cognitive neurologist from Northwestern University in Chicago, adds: “Friston’s work is pivotal. It resonates entirely with the sort of model that I would like to see emerge.”
  • “The final equation you write on a T-shirt will be quite simple,” Friston predicts.
  • There’s work still to be done, but for now Friston’s is the most promising approach we’ve got. “It will take time to spin off all of the consequences of the theory – but I take that property as a sure sign that this is a very important theory,” says Dehaene. “Most other models, including mine, are just models of one small aspect of the brain, very limited in their scope. This one falls much closer to a grand theory.”
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Whole Brain Project™ - 1 views

www.wholebrainproject.org brain neuroscience Whole Brain Project
shared by Matvey Ezhov on 01 Nov 09 - Cached
  • Matvey Ezhov on 01 Nov 09
     
    "Simultaneous revolutions in neuroscience research and next generation software tools are merged in the Whole Brain Project™. The project joins neuroscientists and software engineers to employ experimental techniques to visualize and explore the burgeoning new discoveries about the brain's structure and function. Despite rapid progress in development of new experimental methods, our ability to simultaneously study the brain across all these scales remains quite limited. The Whole Brain Project looks to provide open source networks to help unify the disparate and heterogeneous data of neuroscientists."
  • Matvey Ezhov on 01 Nov 09
     
    Wooooohooo!!!!!!
  • Nikolay Sibirtsev on 01 Nov 09
     
    Пока не на что смотреть... Хотя может со временем и получится неплохая штука.
1More

NeuroLex - 1 views

neurolex.org/Main_Page brain neuroscience NeuroLex wiki
shared by Matvey Ezhov on 02 Nov 09 - Cached
  • Matvey Ezhov on 02 Nov 09
     
    The NeuroLex project, supported by the Neuroscience Information Framework project, is a dynamic lexicon of neuroscience terms. Unlike an encyclopedia, a lexicon provides the meaning of a term, and not all there is to know about it.
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