Cal Newport book on having a Remarkable Life. ISBN:978-1455509126 (more)

John von Neumann (/vɒn ˈnɔɪmən/ von NOY-mən; Hungarian: Neumann János Lajos [ˈnɒjmɒn ˈjaːnoʃ ˈlɒjoʃ]; December 28, 1903 – February 8, 1957) was a Hungarian and American mathematician, physicist, computer scientist and engineer. Von Neumann had perhaps the widest coverage of any mathematician of his time,[9] integrating pure and applied sciences and making major contributions to many fields, including mathematics, physics, economics, computing, and statistics. He was a pioneer in building the mathematical framework of quantum physics, in the development of functional analysis, and in game theory, introducing or codifying concepts including cellular automata, the universal constructor and the digital computer. His analysis of the structure of self-replication preceded the discovery of the structure of DNA. During World War II, von Neumann worked on the Manhattan Project. He developed the mathematical models behind the explosive lenses used in the implosion-type nuclear weapon.[10] Before and after the war, he consulted for many organizations including the Office of Scientific Research and Development, the Army's Ballistic Research Laboratory, the Armed Forces Special Weapons Project and the Oak Ridge National Laboratory.[11] At the peak of his influence in the 1950s, he chaired a number of Defense Department committees including the Strategic Missile Evaluation Committee and the ICBM Scientific Advisory Committee. He was also a member of the influential Atomic Energy Commission in charge of all atomic energy development in the country. He played a key role alongside Bernard Schriever and Trevor Gardner in the design and development of the United States' first ICBM programs.[12] At that time he was considered the nation's foremost expert on nuclear weaponry and the leading defense scientist at the U.S. Department of Defense. https://en.wikipedia.org/wiki/John_von_Neumann (more)

Accelerated Expertise expert: https://acsilabs.org/team/lia-a-dibello/

a multi-layer-iterative Product Management process of Thinking in Bets (more)

In political jargon, a self-licking ice cream cone is a self-perpetuating system that has no purpose other than to sustain itself. The phrase appeared to have been first used in 1991–1992, in a book about Gulf War weapons systems by Norman Friedman,[1] and On Self-Licking Ice Cream Cones, a paper by Pete Worden about NASA's bureaucracy, to describe the relationship between the Space Shuttle and international Space Station. https://en.wikipedia.org/wiki/Self-licking_ice_cream_cone (more)

a place, also a type of calculation-by-simluation

The concept that internal details of a system can be ignored if you know the overall inputs, outputs and behaviour, so that the component may be used as part of a larger system or to operate on its own.

Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. (black box)

Observable is a platform where you can collaboratively explore, analyze, visualize, and communicate with data on the web. In this demo, you'll see how to work with your own data and discover business insights in just five minutes. https://observablehq.com/ (more)

Kin Lane proposes Bot (Daemon) Observability For Every Platform (more)

aka ludicity, hermit-tech https://ludic.mataroa.blog/about-me/ (more)

creating a story map

creator of story-mapping etc

Product Review for a book (more)

Seb Paquet notes a number of people with similar interests around the Network Economy. (John Robb, Michel Bauwens, etc.) (more)

"The medium is the message" (more)

BigCos in technology. see esp GAFA and High Tech Employee Antitrust Litigation. (more)

Hater of Mother Teresa, Henry Kissinger, and many others. (more)

one of the more embarrassing US Presidents (1969-1974). https://en.wikipedia.org/wiki/Richard_Nixon (more)

Nikhil Suresh: I Will Fucking Piledrive You If You Mention AI Again. I myself have formal training as a data scientist, going so far as to dominate a competitive machine learning event at one of Australia's top universities and writing a Master's thesis where I wrote all my own libraries from scratch. (more)