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There is an additional element of importance: these systems usually generate implicit internal models of their environments, models progressively revised and improved as the system accumulates experience. The systems learn.
Jessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
The Unaccountability Machine — why do big systems make bad decisions?
ft.com
guaranteed in “deeper” networks with more than two layers, it was possible to build a system that could produce results that were often good enough, opportunistically climbing up the mountain by taking small steps of the right sort, using a technique called backpropagation—now the workhorse of deep learning.*4 Backpropagation works by estimating th
... See moreErnest Davis • Rebooting AI: Building Artificial Intelligence We Can Trust
Byrne Hobart • Software is the new Hardware
Pareto Principle dictates that: Roughly 80% of consequences will come from 20% of the causes.
Anthony Raymond • Ikigai & Kaizen: The Japanese Strategy to Achieve Personal Happiness and Professional Success (How to set goals, stop procrastinating, be more productive, build good habits, focus, & thrive)
“toy” models of economies—simple models that are so abstract they bear little resemblance to reality.
Jessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
“I’ve been grading my students’ lab reports both for their scientific merit,” Professor Potts said, “and for the language in which they tell me what they did, what their results were and how they interpret those results.
William Zinsser • Writing to Learn: How to Write - and Think - Clearly About Any Subject at All
These are all highly contestable statements.