Sublime
An inspiration engine for ideas
how to write algorithms that could change their code and get smarter as they develop. We now call this evolutionary programming.
W. Brian Arthur • Complexity Economics: Proceedings of the Santa Fe Institute's 2019 Fall Symposium
Next, he tried to confirm that Graunt was correct about the probability of a boy’s birth being larger than 50%. He was building the foundation of the modern theory of testing statistical hypotheses.
Sharon Bertsch McGrayne • The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy
Generalists
Paul Sturrock • 3 cards
Survivorship bias
Prashanth Narayan • 2 cards
One after another, the greatest figures in physics seemed to develop an unexpected late-career interest in the mystery of life itself, even taking abrupt shifts toward the formal study of biology.
Fei-Fei Li • The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI
he discovered the long-sought grail of probability, what future mathematicians would call the probability of causes, the principle of inverse probability, Bayesian statistics, or simply Bayes’ rule.
Sharon Bertsch McGrayne • The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy
you have created a time-series which is chaotic.