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thinkahol *

Being No One - The MIT Press - 0 views

mitpress.mit.edu/...default.asp

Being No One - The MIT Press

shared by thinkahol * on 23 Feb 12 - Cached
  • thinkahol * on 23 Feb 12
     
    According to Thomas Metzinger, no such things as selves exist in the world: nobody ever had or was a self. All that exists are phenomenal selves, as they appear in conscious experience. The phenomenal self, however, is not a thing but an ongoing process; it is the content of a "transparent self-model." In Being No One, Metzinger, a German philosopher, draws strongly on neuroscientific research to present a representationalist and functional analysis of what a consciously experienced first-person perspective actually is. Building a bridge between the humanities and the empirical sciences of the mind, he develops new conceptual toolkits and metaphors; uses case studies of unusual states of mind such as agnosia, neglect, blindsight, and hallucinations; and offers new sets of multilevel constraints for the concept of consciousness. Metzinger's central question is: How exactly does strong, consciously experienced subjectivity emerge out of objective events in the natural world? His epistemic goal is to determine whether conscious experience, in particular the experience of being someone that results from the emergence of a phenomenal self, can be analyzed on subpersonal levels of description. He also asks if and how our Cartesian intuitions that subjective experiences as such can never be reductively explained are themselves ultimately rooted in the deeper representational structure of our conscious minds.
Matvey Ezhov

On Biological and Digital Intelligence - 0 views

www.goertzel.org/...icalAndDigitalIntelligence.htm

shared by Matvey Ezhov on 09 Sep 09 - Cached
  • In essence, Hawkins argues that, to whatever extent the concept of “consciousness” can’t be boiled down to brain theory, it’s simply a bunch of hooey.
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      Not true!
  • in which conscious experience is more foundational than physical systems or linguistic communications
  • Conscious experiences are associated with patterns, and patterns are associated with physical systems, but none of these is fully reducible to the other. 
  • ...22 more annotations...
  • He makes the correct point that roughly-human-level AI’s will have dramatically different strengths and weaknesses from human being, due to different sensors and actuators and different physical infrastructures for their cognitive dynamics.  But he doesn’t even touch the notion of self-modifying AI – the concept that once an AI gets smart enough to modify its own code, it’s likely to get exponentially smarter and smarter until it’s left us humans in the dust.
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      Совершенно не имеет отношения к теме, подход Хокинса легко масштабируется до сверх- и сверх-сверх-сверхчеловеческого интеллекта.
  • therefore if AI closely enough emulates the human brain it won’t radically self-modify either
  • Rather, I think the problem is that the field of AI has come to focus on “narrow AI” – programs that solve particularly, narrowly-defined problems – rather than “artificial general intelligence” (AGI). 
  • cognitive science, artificial general intelligence, philosophy of mind and abstract mathematics
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      т.о. Гортзел признается, что вообще принимает и не считает нужным принимать нейронауку в расчет, т.е. опирается только на эмпирические представления о том, как работает сознание.
  • So what we’re doing is creating commercial narrow AI programs, using the software framework that we’re building out with our AGI design in mind.
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      и в этом его большое отличие от платформы Хокинса, которая имеет одинаковую структуру для всех ее применений
  • I tend to largely agree with his take on the brain
  • I think he oversimplifies some things fairly seriously – giving them very brief mention when they’re actually quite long and complicated stories.  And some of these omissions, in my view, are not mere “biological details” but are rather points of serious importance for his program of abstracting principles from brain science and then re-concretizing these principles in the context of digital software.
  • One point Hawkins doesn’t really cover is how a mind/brain chooses which predictions to make, from among the many possible predictions that exist.
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      тут он вроде бы прав...
  • Hawkins proposes that there are neurons or neuronal groups that represent patterns as “tokens,” and that these tokens are then incorporated along with other neurons or neuronal groups into larger groupings representing more abstract patterns.  This seems clearly to be correct, but he doesn’t give much information on how these tokens are supposed to be formed. 
  • So, what’s wrong with Hawkins’ picture of brain function?  Nothing’s exactly wrong with it, so far as I can tell.
  • But Edelman then takes the concept one step further and talks about “neural maps” – assemblies of neuronal groups that carry out particular perception, cognition or action functions.  Neural maps, in essence, are sets of neuronal groups that host attractors of neurodynamics.  And Edelman then observes, astutely, that the dynamics of the population of neuronal groups, over time, is likely to obey a form of evolution by natural selection.
  • How fascinating if the brain also operates in this way!
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      да нифига... слов нет
  • Hawkins argues that creativity is essentially just metaphorical thinking, generalization based on memory.  While this is true in a grand sense, it’s not a very penetrating statement.
  • Evolutionary learning is the most powerful general search mechanism known to computer science, and is also hypothesized by Edelman to underly neural intelligence.  This sort of idea, it seems to me, should be part of any synthetic approach to brain function.
  • Hawkins mentions the notion, and observes correctly that Hebbian learning in the brain is a lot subtler than the simple version that Donald Hebb laid out in the late 40’s.   But he largely portrays these variations as biological details, and then shifts focus to the hierarchical architecture of the cortex. 
  • Hawkins’ critique of AI, which in my view is overly harsh.  He dismisses work on formal logic based reasoning as irrelevant to “real intelligence.” 
  • So – to sum up – I think Hawkins’ statements about brain function are pretty much correct
  • What he omits are, for instance,   The way the brain displays evolutionary learning as a consequence of the dynamics of multiple attractors involving sets of neural clusters The way the brain may emergently give rise to probabilistic reasoning via the statistical coordination of Hebbian learning
  • Learning of predictive patterns requires an explicit or implicit search through a large space of predictive patterns; evolutionary learning provides one approach to this problem, with computer science foundations and plausible connections to brain function; again, Hawkins does not propose any concrete alternative.
  • crucial question of how far one has to abstract away from brain function, to get to something that can be re-specialized into efficient computer software.  My intuition is that this will require a higher level of abstraction than Hawkins seems to believe.  But I stress that this is a matter of intuitive judgment – neither of us really knows.
  • Of course, to interpret the Novamente design as an “abstraction from the brain” is to interpret this phrase in a fairly extreme sense – we’re abstracting general processes like probabilistic inference and evolutionary learning and general properties like hierarchical structure from the brain, rather than particular algorithms. 
    • Matvey Ezhov
      Matvey Ezhov on 09 Sep 09
       
      наконец-то он сказал это
  • Although I’m (unsurprisingly) most psyched about the Novamente approach, I think it’s also quite worthwhile to pursue AGI approaches that are closer to the brain level – there’s a large space between detailed brain simulation and Novamente, including neuron-level simulations, neural-cluster-level simulations, and so forth. 
thinkahol *

Future Intelligence | Watch Free Documentary Online - 0 views

topdocumentaryfilms.com/future-intelligence

Future Intelligence | Watch Free Documentary Online

shared by thinkahol * on 16 Mar 11 - No Cached
  • thinkahol * on 16 Mar 11
     
    Catch a first-time glimpse at smart technology that will put android helpers in the home, network commuters and entire cities to the Web, and bring us entertainment systems that can virtually make dreams come true. Advances in artificial intelligence are creating machines with near human-like mental agility. Intelligence will be embedded everywhere - even in our clothing, thanks to smaller, more powerful computers. Soon, we will be able to build computers with artificial intelligence and processing power that rivals the human brain. Intelligence will be everywhere, in our clothing, our vehicles and homes. Intelligent robots will serve us - until they don't feel like doing so anymore. And what happens then…?
Matvey Ezhov

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
Volucer Volucer

Bigger not necessarily better, when it comes to brains - 1 views

www.physorg.com/news177692594.html

AI ИИ brain neuroscience news наука

shared by Volucer Volucer on 22 Nov 09 - Cached
  • Volucer Volucer on 22 Nov 09
     
    "In fact, the models suggest that counting could be achieved with only a few hundred nerve cells and only a few thousand could be enough to generate consciousness. "
mikhail-miguel

Building Consistent Characters with MidJourney and ChatGPT: Unlocking the Power of Visu... - 0 views

www.amazon.com/...ref=sr_1_2

'Certification RE Use of ChatGPT and MidJourney' Artificial-Intelligence AI

shared by mikhail-miguel on 27 Jul 23 - No Cached
  • mikhail-miguel on 27 Jul 23
     
    Tired of the same stock photos next to each news article, blog post, and presentation? Me too. So when I wrote "The Art of Prompt Engineering with ChatGPT," I decided to build custom illustrations using MidJourney. I used a great trick that allowed me to rebuild my characters in different contexts throughout the book. Due to popular demand, I'm launching this book to teach you how to build your own consistent characters. In this book, you will learn: How text-to-image AI tools work How to get set up with MidJourney How to write basic prompts in MidJourney How to develop a character in MidJourney How to contextualise your character How to build backgrounds and compositions Not only that, but I've also added an extra section on using ChatGPT within your character building process, which covers: How to get ChatGPT to develop your characters and build them into MidJourney prompts How to get ChatGPT to contextualise your characters based on any text and build them into MidJourney prompts How to get ChatGPT to build backgrounds for your contextualised characters and build them into MidJourney prompts Get Certified and Show off Your Knowledge! Early Adopters of AI Tools should be able to have their expertise visible to their professional network. Chapter 17 of this book sets you up with a project to implement everything you have learned by creating a visual children's story with ChatGPT and MidJourney. ChatGPT Trainings has put together a certification program that lets you submit your project as proof of your new abilities, and in return you will receive a recognised and verifiable certification that can be added to your LinkedIn Profile. Head over to www.ChatGPTtrainings.com/certifications for more information
mikhail-miguel

The AI Product Manager's Handbook (+Free PDF Ed.) - 0 views

a.co/eCoUR9o

'Recommended Books' Artificial-Intelligence AI

shared by mikhail-miguel on 27 Jul 23 - No Cached
  • mikhail-miguel on 27 Jul 23
     
    Master the skills required to become an AI product manager and drive the successful development and deployment of AI products to deliver value to your organization. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Build products that leverage AI for the common good and commercial success Take macro data and use it to show your customers you're a source of truth Best practices and common pitfalls that impact companies while developing AI product Book Description Product managers working with artificial intelligence will be able to put their knowledge to work with this practical guide to applied AI. This book covers everything you need to know to drive product development and growth in the AI industry. From understanding AI and machine learning to developing and launching AI products, it provides the strategies, techniques, and tools you need to succeed. The first part of the book focuses on establishing a foundation of the concepts most relevant to maintaining AI pipelines. The next part focuses on building an AI-native product, and the final part guides you in integrating AI into existing products. You'll learn about the types of AI, how to integrate AI into a product or business, and the infrastructure to support the exhaustive and ambitious endeavor of creating AI products or integrating AI into existing products. You'll gain practical knowledge of managing AI product development processes, evaluating and optimizing AI models, and navigating complex ethical and legal considerations associated with AI products. With the help of real-world examples and case studies, you'll stay ahead of the curve in the rapidly evolving field of AI and ML. By the end of this book, you'll have understood how to navigate the world of AI from a product perspective. What you will learn Build AI products for the future using minimal resources Identify opportunities where AI can be leveraged to meet business needs Collaborate with cross-function
mikhail-miguel

LMSYS Chatbot Arena Vision (Multimodal): Benchmarking LLMs and VLMs in the Wild - 0 views

chat.lmsys.org/?vision

LLM Artificial-Intelligence VLM AI LMSYS

shared by mikhail-miguel on 11 Jun 24 - No Cached
  • mikhail-miguel on 11 Jun 24
     
    The Chatbot Arena has launched a new beta feature supporting images, allowing users to interact with chatbots through images. Each conversation can include the submission of one image, as long as it is under 15MB. The Chatbot Arena logs user requests, including the images submitted, for research purposes. Although this data is not currently publicly disclosed, there may be a possibility of doing so in the future. Therefore, it is recommended that users avoid sending confidential or personal information through this feature. This feature is in its early development stage, so there may be issues or bugs. Users are encouraged to report any issues through the Chatbot Arena communication channels.
Matvey Ezhov

Recursive Self-Improvement - The Transhumanist Wiki - 2 views

transhumanistwiki.com/...Recursive_Self-Improvement

ai classic AI

shared by Matvey Ezhov on 20 Oct 09 - Cached
  • True Artificial Intelligence would bypass problems of biological complexity and ethics, growing up on a substrate ideal for initiating Recursive Self-Improvement. (fully reprogrammable, ultrafast, the AI's "natural habitat".) This Artificial Intelligence would be based upon: 1) our current understanding of the central algorithms of intelligence, 2) our current knowledge of the brain, obtained through high-resolution fMRI and delicate Cognitive Science experiments, and 3) the kind of computing hardware available to AI designers.
  • Humans cannot conduct any of these enhancements to ourselves; the inherent structure of our biology and the limited level of our current technology makes this impossible.
  • Recursive Self-Improvement is the ability of a mind to genuinely improve its own intelligence. This might be accomplished through a variety of means; speeding up one's own hardware, redesigning one's own cognitive architecture for optimal intelligence, adding new components into one's own hardware, custom-designing specialized modules for recurrent tasks, and so on.
  • ...2 more annotations...
  • Unfortunately, the neurological structures corresponding to human intelligence are likely to be highly intricate, delicate, and biologically very complex (unnecessarily so; evolution exhibits no foresight, and most of the brain evolved in the absence of human General Intelligence).
  • 2) advances in Cognitive Science that indicate the complexity of certain brain areas is largely extraneous to intelligence,
    • Matvey Ezhov
      Matvey Ezhov on 20 Oct 09
       
      Очень серьезно допущение, которое может быть ошибочно. Нам известно, что все зоны кортекса участвуют в формировании модели мира индивида, а значит и сознания.
Matvey Ezhov

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.”
Pump Wat

Pool Water Pumps for Clean and Safe Swimming Pools - 2 views

I have a swimming pool at home and I want it to be always clean and safe to use. That is why I bought water pumps from Pump Solutions Australasia, the leading wholesaler of pumps for industrial a...

pumps

started by Pump Wat on 13 Jul 11 no follow-up yet
mikhail-miguel

Be My Eyes - App connects the blind with volunteers (bemyeyes.com). - 0 views

www.bemyeyes.com

Artificial-Intelligence AI

shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Be My Eyes: App connects the blind with volunteers (bemyeyes.com).
mikhail-miguel

Jounce Artificial Intelligence - Copywriting and artwork that used to take marketers da... - 0 views

jounce.ai

Artificial-Intelligence AI

shared by mikhail-miguel on 23 Jul 23 - No Cached
  • mikhail-miguel on 23 Jul 23
     
    Jounce Artificial Intelligence: Copywriting and artwork that used to take marketers days and weeks to create can now be done in a fraction of the time (jounce.ai). Jounce Artificial Intelligence: Free Unlimited Artificial Intelligence Copywriting and Artwork for Marketers (jounce.ai).
mikhail-miguel

Jounce Artificial Intelligence - Copywriting and artwork that used to take marketers da... - 0 views

www.jounce.ai

Artificial-Intelligence AI

shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Jounce Artificial Intelligence: Copywriting and artwork that used to take marketers days and weeks to create can now be done in a fraction of the time (jounce.ai). Jounce Artificial Intelligence: Free Unlimited Artificial Intelligence Copywriting and Artwork for Marketers (jounce.ai).
mikhail-miguel

Copilotly - Search better, write faster, and be more productive with Copilotly A.I (cop... - 0 views

www.copilotly.com

Artificial-Intelligence AI

shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Copilotly: Search better, write faster, and be more productive with Copilotly A.I (copilotly.com).
mikhail-miguel

Ameela - Ameela is a free logo design maker for startups that claims to be inspired by ... - 0 views

amee.la

Artificial-Intelligence AI

shared by mikhail-miguel on 23 Jul 23 - No Cached
  • mikhail-miguel on 23 Jul 23
     
    Ameela: Ameela is a free logo design maker for startups that claims to be inspired by Artificial Intelligence (amee.la).
mikhail-miguel

Elektrif Artificial Intelligence - Generate personalized convos & rephrase messages to ... - 0 views

www.elektrif.ai

Artificial-Intelligence AI

shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Elektrif Artificial Intelligence: Generate personalized convos & rephrase messages to be more engaging (elektrif.ai).
mikhail-miguel

Freshly.ai - Determines if a public company may be a good investment (freshly.ai). - 0 views

freshly.ai/discuro-form

Artificial-Intelligence AI

shared by mikhail-miguel on 27 Jul 23 - No Cached
  • mikhail-miguel on 27 Jul 23
     
    Freshly.ai: Determines if a public company may be a good investment (freshly.ai).
Vanshika Jain

How can I get my ex back - - 0 views

blackmagicvashikaranguru.weebly.com/...-how-can-i-get-my-ex-back

shared by Vanshika Jain on 09 May 16 - No Cached
  • Vanshika Jain on 09 May 16
     
    Love relationship is very emotional so problems is easily occur in this relationship, if you are in love with someone then you may be face communication issues then you just need to approach your...
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