Tag: #HumanAI
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Resemblance to reAIlity …
Questioner: How much will LLM impact human activity?Answer: Hmmm, the oncoming singularity?Q: YesA: Try … Tudor’s Graph. Q: What’s the data behind this?A: Seriously? Ok, let me make it clearer …
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How Occam’s razor guides human decision-making
A rather complex but very interesting article was published @PennLibraries and (somewhat more recent) @bioRXiv But for those who want to understand by a lecture, I can recommend the Simons Faoundation lecture from Joshua Gold (also available on Youtube: How Occam’s Razor Guides Human and Machine Decision-Making) Occam’s razor is the principle stating that, all…
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As a human it would be quite easy to spot
Man beats machine at Go in human victory over AI A human player has comprehensively defeated a top-ranked AI system at the board game Go, in a surprise reversal of the 2016 computer victory that was seen as a milestone in the rise of artificial intelligence. Kellin Pelrine beat the machine by taking advantage of…
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Cognitive Computational Neuroscience
Cognitive science has developed computational models that decompose cognition into functional components. Computational neuroscience has modeled how interacting neurons can implement elementary components of cognition. It is time to assemble the pieces of the puzzle of brain computation and to better integrate these separate disciplines. Modern technologies enable us to measure and manipulate brain activity…
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Prediction: multi-scale pattern completion of the future
The notion of the brain as a prediction machine has been extremely influential and productive in cognitive sciences.One prominent framework is of a “Bayesian brain” that explicitly generates predictions and uses resultant errors to guide adaptation. The prediction-generation component of this framework may involve little more than a pattern completion process. Brain-like systems can get…
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Designing Ecosystems of Intelligence from First Principles
Karl Friston joins VERSES as Chief Scientist to Lead New Era in Artificial Intelligence.VERSES published its research paper to arxiv.org to explore the applications and implications of Active Inference on the future of Artificial Intelligence. “Designing Ecosystems of Intelligence from First Principles” lays out a vision of research and development in the field of artificial intelligence…
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Technology readiness levels for machine learning systems
The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards…
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Beslissen: FEP, AI, Bayes
“We sample the world to ensure our predictions become a self-fulfilling prophecy.” Karl Friston De beslissingswetenschappen en neurowetenschappen werden recent verrijkt door het principe van vrije energie (Free Energy Principle / FEP) van Karl Friston. FEP is misschien wel het meest allesomvattende idee sinds de theorie van natuurlijke selectie van Charles Darwin. Samenvattend is het…
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Rethinking Computational Approaches to the Mind
Rethinking Computational Approaches to the Mind Fundamental Challenges and Future Perspectives One-day Online Symposium21st October 2022 REGISTER HERE This one-day online event will bring together researchers with expertise in various areas such as complexity science, machine learning & artificial intelligence, information theory & data science, as well as computational/theoretical neuroscience & philosophy to explore different computational approaches…
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Begin with the decision-maker
I enjoyed the article “The first step in AI might surprise you” on AI, ML, Data Science from Cassie so much, I decided to steal some quotes: Leaders, figure out who’s calling the shots. If it’s you, then let’s designate you “The Decision-Maker“ for this project. Otherwise, delegate the position to someone else and ask them to read the…
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Are Dogs outsmarting human primates?
I just love the intelligence of nature, behaving as a complex adaptive system, working with minimal effort to a beneficial solutions. As such, nature often behaves smarter than self-conscious human primates, without going into difficult reasoning and decision making processes. A great text putting this fact into evidence is the 2012 lecture “The dog and…
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Will it ever happen?
Evolution of Brains and Computers: The Roads Not Taken – Can machines ever achieve true intelligence? , is a perspective article in entropy by Ricard Solé and Luís F. Seoane, has a great discussion on intelligence. When computers started to become a dominant part of technology around the 1950s, fundamental questions about reliable designs and…
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Why Can the Brain (And Not a Computer) Make Sense of the Liar Paradox?
Ordinary computing machines prohibit self-reference because it leads to logical inconsistencies and undecidability. In contrast, the human mind can understand self-referential statements without necessitating physically impossible brain states. Why can the brain make sense of self-reference? This paper addresses this question by defining the Strange Loop Model, which features causal feedback between two brain modules,…
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What Does It Mean for AI to Understand?
Melanie Mitchell has a great article, she just announced at Complexity Digest: Language models can generate uncannily humanlike prose (and poetry!) and seemingly perform sophisticated linguistic reasoning. How can we test if these machines actually understand what they’re doing? Read the full article at: www.quantamagazine.orghttps://www.quantamagazine.org/what-does-it-mean-for-ai-to-understand-20211216/# Understanding language requires understanding the world, and a machine exposed only…
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Designing for Human-AI interaction is hard. (So steal like an artist :-)
Following is and interesting article/blog , and just “stolen like an artist” from https://www.simonoregan.com/short-thoughts/the-design-difficulties-of-human-ai-interaction Designing for Human-AI interaction is hard. Here Yang et al. catalog where designers run into problems when applying the traditional 4Ds process to designing AI systems. These difficulties can be broadly attributed to two sources: This uncertainty and complexity combination then…
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AI: Analogy Included ?
There is a great Quanta article on Melanie Mitchell, discussing her effort to include analogy into AI. Some quotes: “Today’s state-of-the-art neural networks are very good at certain tasks, but they’re very bad at taking what they’ve learned in one kind of situation and transferring it to another” — the essence of analogy. “Analogy isn’t…
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Decision Intelligence – some basics
Google’s chief decision scientist Cassie Kozyrkov says that the ultimate business advantage in using AI is decision intelligence — the automation of the full action-to-outcome process. “Decision intelligence is the discipline of turning information into better actions at any scale.” If you think that AI takes the human out of the equation, think again! Cassie Kozyrkov, Introduction to Decision…
