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The Art of Prompt Engineering with ChatGPT: Accessible Edition (Learn AI Tools the Fun ... - 0 views

www.amazon.com/...B0BZ4T68Q4 '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
     
    Accessible Edition To make 'The Art of Prompt Engineering with ChatGPT' as beautiful as possible we designed the layout and published it here as a pdf. However, this wasn't the best option for those who used a kindle to read, or for those who had accessibility needs. So this is the accessible edition, rebuilt using a reflow able format. If you bought the original and need to use the accessibility features, just email us at nathan@ChatGPTtrainings.com. Let's move beyond basic examples and 'test this prompt.' ChatGPT is an amazing AI tool that can change the way we work. Bill Gates recently said that ChatGPT is as important an invention as the internet, and it could change the world. To make the most of ChatGPT and go beyond simple uses, you need to master prompt engineering. Check out a sample chapter: www.ChatGPTtrainings.com March Update - 2 New Sections with 34 More Pages of Content For this monthly update, we added a new section on Advanced Prompt Engineering to help you take your ChatGPT skills to a higher level once you've learned the basics. This section covers the co-creation approach, where you take control, and [format] your output, where you'll learn my favorite way to get the exact results you want. We also included a new section on GPT-4, with information on how to start, debunking past hype, and looking at some new improvements. This book will keep evolving as ChatGPT grows, making sure that everything you read and learn stays up-to-date and relevant. All updates are free and automatic for Kindle copies, and if you bought a hardcopy, you can email me at Nathan@ChatGPTtrainings.com with your proof of purchase to get a PDF update. Why This Book? This book helps you learn the art of working with ChatGPT to get much better results. This skill, prompt engineering, is what sets good apart from great when using ChatGPT. Learn 4 key techniques and tools for writing better prompts Master 2 advanced prompt engineering tools to take your skills further F
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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. 
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Sketchar - Art learning app that's changing how people learn creative skills (sketchar.... - 0 views

sketchar.io Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Sketchar: Art learning app that's changing how people learn creative skills (sketchar.io).
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TutorAI - AI-powered learning platform; enter topic, get learning options (tutorai.me). - 0 views

www.tutorai.me Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    TutorAI: AI-powered learning platform; enter topic, get learning options (tutorai.me).
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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
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Perceptual Learning Relies On Local Motion Signals To Learn Global Motion - 0 views

www.sciencedaily.com/...090921134836.htm news brain neuroscience
shared by Matvey Ezhov on 09 Oct 09 - Cached
  • The brain first perceives changes in visual input (local motion) in the primary visual cortex. The local motion signals are then integrated in the later visual processing stages and interpreted as global motion in the higher-level processes. But when subjects in a recent experiment using moving dots were asked to detect global motion (the overall direction of the dots moving together), the results show that their learning relied on more local motion processes (the movement of dots in small areas) than global motion areas.
  • show that the improvement in detection of global motion is not due to learning of the global motion but to learning of local motion of the moving dots in the test.
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Transvribe - Transvribe is designed to make learning on YouTube 10x more productive (tr... - 0 views

www.transvribe.com Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Transvribe: A tool for efficient youtube learning (transvribe.com). Transvribe: Transvribe is designed to make learning on YouTube 10x more productive (transvribe.com).
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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
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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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Piano Genie - Have some fun pretending you're a piano virtuoso using machine learning (... - 0 views

piano-genie.glitch.me Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Piano Genie: Have some fun pretending you're a piano virtuoso using machine learning (piano-genie.glitch.me).
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ResearchRabbit - ResearchRabbit learns what you love and improves its recommendations! ... - 0 views

www.researchrabbit.ai Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    ResearchRabbit: ResearchRabbit learns what you love and improves its recommendations! (researchrabbit.ai). ResearchRabbit: Supercharge your research workflows (researchrabbit.ai).
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Codeamigo - Interactive coding tutorial tool using Artificial Intelligence to help user... - 0 views

codeamigo.dev Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Codeamigo: Interactive coding tutorial tool using Artificial Intelligence to help users learn how to code (codeamigo.dev).
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TalkPal - TalkPal is The Most Efficient Way to Learn a Language Using Artificial Intell... - 0 views

talkpal.ai Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    TalkPal: TalkPal is The Most Efficient Way to Learn a Language Using Artificial Intelligence (talkpal.ai).
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Q-Chat - Q-Chat is Quizlet's Artificial Intelligence used to help make learning fun and... - 0 views

quizlet.com/qchat Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Q-Chat: Q-Chat is Quizlet's Artificial Intelligence used to help make learning fun and easy with more than just flashcards (quizlet.com).
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Stable Diffusion - Deep learning text-to-image model (stability.ai). - 0 views

stability.ai Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Stable Diffusion: Deep learning text-to-image model (stability.ai).
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Hourone - Create Artificial Intelligence videos from text to for better learning & deve... - 0 views

hourone.ai Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    Hourone: Create Artificial Intelligence videos from text to for better learning & development (hourone.ai).
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What on earth? - Create stories with one-word prompts for fun learning (whatonearth.xyz). - 0 views

www.whatonearth.xyz Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    What on earth?: Create stories with one-word prompts for fun learning (whatonearth.xyz).
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ResearchRabbit - ResearchRabbit learns what you love and improves its recommendations! ... - 0 views

researchrabbit.ai Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    ResearchRabbit: ResearchRabbit learns what you love and improves its recommendations! (researchrabbit.ai). ResearchRabbit: Supercharge your research workflows (researchrabbit.ai).
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LangoTalk - Learn 6 languages 6x faster with Artificial Intelligence chat (langotalk.org). - 0 views

www.langotalk.org Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    LangoTalk: Learn 6 languages 6x faster with Artificial Intelligence chat (langotalk.org).
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FlowGPT - Share, discover & learn useful ChatGPT prompts to increase productivity (flow... - 0 views

flowgpt.com Artificial-Intelligence AI
shared by mikhail-miguel on 09 Jul 23 - No Cached
  • mikhail-miguel on 09 Jul 23
     
    FlowGPT: Share, discover & learn useful ChatGPT prompts to increase productivity (flowgpt.com).
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