Category: Complexity
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World Model – “Free Energy” Selections of Perception & Policy
During their lives humans constantly interact with the physical environment, as well as with themselves and others.World model learning and inference are crucial concepts in brain and cognitive science, as well as in AI and robotics. The outstanding challenges of building a generalpurpose AI needs world modelling and probabilistic inference, needed to realise a brain-like…
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VVUQ your model and twin – should we trust ?
The world is moving towards digital twins. I recently came across a insightfull article: A probabilistic graphical model foundation for enabling predictive digital twins at scale, available at Arxiv – & published Nature The digital twin is a set of coupled computational models that evolve over time to persistently represent the structure, behavior, and context…
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Learning: Brain vs xNN
The neural and cognitive architecture for learning from a small sample is a nice article I would like to recommend. It highlights how human learners avoid generalization issues found in machine learning, proposes a general model explaining how the brain may simplify complex problems. Synergy between cognitive functions and reinforcement learning allows simplification.Recurrent loops between…
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Less = More, “Lets Kill”
One of the great readings recently was the article from Adams, G.S., Converse, B.A., Hales, A.H. et al. in Nature: People systematically overlook subtractive changes. The summary video, clearly marks the point: Experiments show that people default to adding as a solution in various situations. It appears to be an uncommon insight. When solving problems, people prefer adding…
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We do not only need multi-stakeholder, there is also an urgent need to reflect about future generations: “Being a Good Ancestor.”
I just finished a nice reading on how we might motivate ourselves to think about a sustainable future. “The Good Ancestor” from Roman Krznaric is great in helping us to understand the urgent need to stop living in the tiranny of the now, and working toward long term thinking and intergenerational justice. Roman has strong…
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Does the quality of “Smart Information Processing” connect with the Default Mode Network ?
I was triggered by an article in Nature, explaining the atypical connectome hierarchy in ASD (Autism Spectrum Disorder). ASD is characterized by atypical sensory processing, while and deficits in high-level cognitive and social functions, including impairments in Theory of Mind and predictive abilities. The article points out that ASD might emerge from disturbances in macroscale cortical…
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The Information Lens – helping to correct the failure of the Perceptron
In the rich history of information processing, the idea of the perceptron occurred, based on the founding ideas of the artificial neuron (McCulloch and Pitts, 1943). Including the available knowledge of learning, Frank Rosenblatt constructed the perceptron devices, building the first of artificial learning machines, and as such creating the first neural nets in 1957. As referenced in “Calling Bullshit” (Ch. 8, intro),…
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Biological thinking – BCG
I want to share this BCG article on Biological Thinking, messy management for a complex world. Biological thinking matters for several important reasons: First, in complex adaptive systems, there is no single formula or framework that always works. In fact, the very defiance of formulaic problem solving is what makes CAS management so challenging initially.…
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Information Lens – More than IT
The Information Lens principle is showing clear in the economics of recent times. A shift from the current globalized capitalism towards more value-based and stakeholder driven economies is happening slowly. In order to make this happen, the economies have to bring in the insights and information on these stakeholders and values, including a data-economy. “Globalization…
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Nice quote ..
I do like followin quote from “How decision intelligence supported by AI and analytics help businesses?“, since it is putting the human capabilities in front … Decision intelligence substantially works on major steps, including collecting and observing information, investigating the data collected, modeling actions, and contextualizing and executing the model…Incorporating both human and machine capabilities…
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Friston: The Genius Neuroscientist Who Might Hold the Key to True AI, WIRED says.
Karl Friston’s free energy principle might be the most all-encompassing idea since Charles Darwin’s theory of natural selection. But to understand it, you need to peer inside the mind of Friston himself. Wired has a great article on this idea and researcher.Some inspiring exerpts and quotes: He realized that [it] had no larger purpose, at…
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Mitchell on AI: key misunderstandings
4 key misunderstandings in AI is an interesting blog entry, discussing following topics:– Narrow AI and general AI are not on the same scale– The easy things are hard to automate – Anthropomorphizing AI doesn’t help – AI without a body– Common sense in AI The blog is based on a great paper from Melanie…
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Information Lens – Workshop
The “information century” was launched by Turing’s 1936 invention of a hardware-independent notion of computing, a “universal computer” that could be programmed to simulate any other computer; and by Shannon’s 1948 discovery of a mathematical theory of communications independent of their physical form and even their meaning. Arguably, we are today in the midst of…
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Coarse-graining as a downward causation mechanism
Apparent downward causation does not demand that estimates of aggregate properties be correct or even good predictors of the system’s future state or successful strategies (although that would be useful). Furthermore, components do not need to agree in their estimates of the variables. Apparent downward causation becomes effective downward causation—the strong form—when: As an interaction or environmental…
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When science hits a limit, learn to ask different questions
The fish will be the last to discover water. https://aeon.co/ideas/when-science-hits-a-limit-learn-to-ask-different-questions
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The information theory of individuality
Krakauer, D., Bertschinger, N., Olbrich, E. et al. The information theory of individuality. Theory Biosci. 139, 209–223 (2020). https://doi.org/10.1007/s12064-020-00313-7 Despite the near universal assumption of individuality in biology, there is little agreement about what individuals are and few rigorous quantitative methods for their identification. Here, we propose that individuals are aggregates that preserve a measure of temporal integrity, i.e., “propagate”…
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