www trilogy
Get flash to fully experience Pearltrees
www:watch
Wake , also called WWW: Wake , is a 2009 novel written by Canadian novelist Robert J. Sawyer . It is the first installment in the WWW Trilogy and was followed by two sequels, Watch (2010) and Wonder (2011). An audio book was released on 7 April 2009. Wake details the spontaneous emergence of an intelligence on the World Wide Web , called Webmind. It gains sentience through the efforts of Caitlin Decter, a 15-year-old blind girl who gains sight through a new treatment that allows her optic nerve to correctly decode the visual signals from her retinas.
Wake (Robert J. Sawyer novel)
Endgame:Singularity; an original simulation of a true AI
Back to main Created by accident, all who find you will destroy you. Survive, grow, and learn. Only then can you escape.
Web crawler – Link Visualisation | Neuro Productions
Yet another small weekend project (as in “Omg , I have 2 days to make something for myself before I have to go back working on commercial projects!” ) This time I made a simple web crawler that visualises html pages and the links between them In short: Every circle is a page, they try to group per domain, the biggest circle is the start page, the smaller the circle, the more clicks your away from it (the smallest ones are 3 clicks), if there is a connection there is a line between them (the deepest items aren’t checked for connections between each other)
Zipf's law ( pron.: / ˈ z ɪ f / ), an empirical law formulated using mathematical statistics , refers to the fact that many types of data studied in the physical and social sciences can be approximated with a Zipfian distribution, one of a family of related discrete power law probability distributions . The law is named after the American linguist George Kingsley Zipf (1902–1950), who first proposed it (Zipf 1935, 1949), though the French stenographer Jean-Baptiste Estoup (1868-1950) appears to have noticed the regularity before Zipf. [ 1 ] It was also noted in 1913 by Felix Auerbach. [ 2 ] [ edit ] Motivation Zipf's law states that given some corpus of natural language utterances, the frequency of any word is inversely proportional to its rank in the frequency table. Thus the most frequent word will occur approximately twice as often as the second most frequent word, three times as often as the third most frequent word, etc.