Alan Perlis (1922–1990) American computer scientist
The Synthesis of Algorithmic Systems, 1966
The Emperor's Old Clothes
Alan Perlis (1922–1990) American computer scientist
The Synthesis of Algorithmic Systems, 1966
Robert Floyd (1936–2001) American computer scientist
1978 Turing Award Citation https://web.archive.org/web/20070708004814/http://awards.acm.org/citation.cfm?id=4173633&srt=all&aw=140&ao=AMTURING. <br class="br">About
John Backus (1924–2007) American computer scientist
"Can Programming Be Liberated From the von Neumann Style?" http://dl.acm.org/ft_gateway.cfm?id=1283933&type=pdf, 1977 Turing Award Lecture, Communications of the ACM 21 (8), (August 1978): pp. 639-640
Aimee Bender (1969) Novelist, short story writer
Source: The Particular Sadness of Lemon Cake
“… greatest single programming language ever designed. (About the Lisp programming language.)”
Alan Kay (1940) computer scientist
2003. Daddy, Are We There Yet? A Discussion with Alan Kay http://www.openp2p.com/pub/a/p2p/2003/04/03/alan_kay.html <br class="br">2000s
Erik Naggum (1965–2009) Norwegian computer programmer
Re: New Lisp ? http://groups.google.com/group/comp.lang.functional/msg/b69c767370ee7c43 (Usenet article). <br class="br">Usenet articles, Miscellaneous
“We keep, in science, getting a more and more sophisticated view of our essential ignorance.”
Warren Weaver (1894–1978) American mathematician
Source: "A Scientist Ponders Faith," Saturday Review, 3 (January 1959), as cited in: F.A. Hayek, Ronald Hamowy. The Constitution of Liberty: The Definitive Edition. 2013, p. 77.
Context: Is science really gaining in its assault on the totality of the unsolved? As science learns one answer, it is characteristically true that it also learns several new questions. It is as though science were working in a great forest of ignorance, making an ever larger circular clearing within which, not to insist on the pun, things are clear... But as that circle becomes larger and larger, the circumference of contact with ignorance also gets longer and longer. Science learns more and more. But there is an ultimate sense in which it does not gain; for the volume of the appreciated but not understood keeps getting larger. We keep, in science, getting a more and more sophisticated view of our essential ignorance.