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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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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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Six problem-solving mindsets for very uncertain times
McKinsey has a nice article helping to solve undecidability under uncertainty.And since a picture is worth so many words: Six mutually reinforcing approaches underly their success: (1) being ever-curious about every element of a problem;Think of the never-ending “whys”. Natural human biases in decision making, including confirmation, availability, and anchoring biases, often cause us to shut down…
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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…
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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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