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Opera ("Aria") browser - 0 views

www.opera.com/...browser-ai

Alternative-AI-Tools Artificial-Intelligence AI

shared by mikhail-miguel on 27 Jul 23 - No Cached

mikhail-miguel on 27 Jul 23

Opera features an integrated AI called Aria that you can access from the sidebar. You can use a keyboard shortcut (CTRL or Command and /) to start using Aria as well. The AI is also available in Opera's Android browser. The AI stems from Opera's partnership with ChatGPT creator OpenAI. Aria connects to GPT to help answer users' queries. The AI incorporates live information from the web and it can generate text or code and answer support questions regarding Opera products. In addition, Opera One can generate contextual prompts for Aria when you right click or highlighting text in the browser. If you prefer to use ChatGPT or ChatSonic, you can access those from the Opera One sidebar too. Opera says users don't have to engage with the browser's AI features if they don't want to. For one thing, you'll need to be logged into an Opera account to use Aria.

<div class="cArrow"> </div><div class="cContentInner">Opera features an integrated AI called Aria that you can access from the sidebar. You can use a keyboard shortcut (CTRL or Command and /) to start using Aria as well. The AI is also available in Opera's Android browser. The AI stems from Opera's partnership with ChatGPT creator OpenAI. Aria connects to GPT to help answer users' queries. The AI incorporates live information from the web and it can generate text or code and answer support questions regarding Opera products. In addition, Opera One can generate contextual prompts for Aria when you right click or highlighting text in the browser. If you prefer to use ChatGPT or ChatSonic, you can access those from the Opera One sidebar too. Opera says users don't have to engage with the browser's AI features if they don't want to. For one thing, you'll need to be logged into an Opera account to use Aria.</div>

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PracticeTalking - Using AI, have fun or educational conversations or even practice impo... - 0 views

practicetalking.net

Artificial-Intelligence AI

shared by mikhail-miguel on 23 Jul 23 - No Cached

mikhail-miguel on 23 Jul 23

PracticeTalking: Using AI, have fun or educational conversations or even practice important conversations before they actually happen (practicetalking.net).

<div class="cArrow"> </div><div class="cContentInner">PracticeTalking: Using AI, have fun or educational conversations or even practice important conversations before they actually happen (practicetalking.net).</div>

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

a.co/eCoUR9o

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

<div class="cArrow"> </div><div class="cContentInner">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</div>

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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 on 09 Sep 09
  
  Not true!
  
  <div class="cArrow"> </div><div class="cContentInner">Not true!</div>
  
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in which conscious experience is more foundational than physical systems or linguistic communications
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Conscious experiences are associated with patterns, and patterns are associated with physical systems, but none of these is fully reducible to the other. 
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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 on 09 Sep 09
  
  Совершенно не имеет отношения к теме, подход Хокинса легко масштабируется до сверх- и сверх-сверх-сверхчеловеческого интеллекта.
  
  <div class="cArrow"> </div><div class="cContentInner">Совершенно не имеет отношения к теме, подход Хокинса легко масштабируется до сверх- и сверх-сверх-сверхчеловеческого интеллекта.</div>
  
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therefore if AI closely enough emulates the human brain it won’t radically self-modify either
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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). 
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cognitive science, artificial general intelligence, philosophy of mind and abstract mathematics
- 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.
  
  <div class="cArrow"> </div><div class="cContentInner">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.</div>
  
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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 on 09 Sep 09
  
  и в этом его большое отличие от платформы Хокинса, которая имеет одинаковую структуру для всех ее применений
  
  <div class="cArrow"> </div><div class="cContentInner">и в этом его большое отличие от платформы Хокинса, которая имеет одинаковую структуру для всех ее применений</div>
  
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I tend to largely agree with his take on the brain
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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.
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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 on 09 Sep 09
  
  тут он вроде бы прав...
  
  <div class="cArrow"> </div><div class="cContentInner">тут он вроде бы прав...</div>
  
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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. 
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So, what’s wrong with Hawkins’ picture of brain function?  Nothing’s exactly wrong with it, so far as I can tell.
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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.
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How fascinating if the brain also operates in this way!
- Matvey Ezhov on 09 Sep 09
  
  да нифига... слов нет
  
  <div class="cArrow"> </div><div class="cContentInner">да нифига... слов нет</div>
  
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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.
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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.
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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. 
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Hawkins’ critique of AI, which in my view is overly harsh.  He dismisses work on formal logic based reasoning as irrelevant to “real intelligence.” 
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So – to sum up – I think Hawkins’ statements about brain function are pretty much correct
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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
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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.
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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.
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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 on 09 Sep 09
  
  наконец-то он сказал это
  
  <div class="cArrow"> </div><div class="cContentInner">наконец-то он сказал это</div>
  
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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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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.

<div class="cArrow"> </div><div class="cContentInner">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.</div>

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