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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
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. 
Matvey Ezhov

IEEE Spectrum: The Cat Brain Cliff Notes - 1 views

spectrum.ieee.org/...the-cat-brain-cliff-notes

ieee ai brain neuroscience IBM

shared by Matvey Ezhov on 27 Nov 09 - Cached
  • It should be pretty clear at this point that no one's going to be building a Caprica Six any time soon.
    • Matvey Ezhov
      Matvey Ezhov on 27 Nov 09
       
      Damn, they ruined my dream! :D
  • "No, no, it's not a cat brain. A cat-SCALE simulation."
  • Matvey Ezhov on 27 Nov 09
     
    More on IBM "Cat's Brain"
  • Volucer Volucer on 13 Dec 09
     
    =)
Matvey Ezhov

Can We 'Learn To See?': Study Shows Perception Of Invisible Stimuli Improves With Training - 0 views

www.sciencedaily.com/...091021172659.htm

cortex neuroscience news

shared by Matvey Ezhov on 23 Oct 09 - Cached
  • A Harvard Medical School study last year found that one blindsight patient could maneuver down a hallway filled with obstacles, even though the subject could not actually see. Schwiedrzik said the new research may help blindsight patients gain conscious awareness of what their minds can see, and he suggested that new research should address whether the brains in blindsight patients and people with normal vision process the information the same way.
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