A Glossary of Ideas

What is Good?


conflicting definitions


All models are wrong

All models are wrong, but some are useful.

—Attributed to George Box

Originating from statistical modeling, this aphorism applies quite broadly. A model is a simplified representation of a piece of reality, so it’s not the actual reality, so its behavior can’t be exactly identical to the reality it models. The most important fact of any model is thus, does it behave enough like its object to give correct answers for the questions we are asking it?

Example: π = 3

Question: Will this tape wrap around this tree? If you can only look at the items and have to answer quickly, guess the diameter of the trunk, triple it, and subtract that from a guess of the length of tape. A fast answer whose accuracy is probably limited by the error in estimation, not in the math. A very useful model in limited circumstances, and especially good at countering our apparently bias toward underestimated diameters. If you are cutting lengths of rope to go around the tree, however, this model is terrible, because of its imprecision, its bias toward smaller answers, and the likely need for extra length to secure each rope.

“In theory, it shouldn’t work in practice.”

Scientific theories are not analogies


The power to understand and predict the quantities of the world should not be restricted to those with a freakish knack for manipulating abstract symbols. http://worrydream.com/KillMath/

“As simple as possible, but not simpler”

On bullshit (typology)

Remote vs In Person


actually a decent analogy.

2 brains < 1 brain + 1 brain

Common Knowledge

Gell-Mann Amnesia

Media carries with it a credibility that is totally undeserved. You have all experienced this, in what I call the Murray Gell-Mann Amnesia effect. (I call it by this name because I once discussed it with Murray Gell-Mann, and by dropping a famous name I imply greater importance to myself, and to the effect, than it would otherwise have.)

Briefly stated, the Gell-Mann Amnesia effect works as follows. You open the newspaper to an article on some subject you know well. In Murray’s case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward—reversing cause and effect. I call these the “wet streets cause rain” stories. Paper’s full of them.

In any case, you read with exasperation or amusement the multiple errors in a story—and then turn the page to national or international affairs, and read with renewed interest as if the rest of the newspaper was somehow more accurate about far-off Palestine than it was about the story you just read. You turn the page, and forget what you know.

That is the Gell-Mann Amnesia effect. I’d point out it does not operate in other arenas of life. In ordinary life, if somebody consistently exaggerates or lies to you, you soon discount everything they say. In court, there is the legal doctrine of falsus in uno, falsus in omnibus, which means untruthful in one part, untruthful in all. But when it comes to the media, we believe against evidence that it is probably worth our time to read other parts of the paper. When, in fact, it almost certainly isn’t. The only possible explanation for our behavior is amnesia.

Leaky Abstraction

Leaky Abstraction of accomplishment

[] the holes: what do I want, do I have it, what can I do, am I doing it well, is it doing what I hoped it would do, repeat.

[] misc: quality control, and things you wouldn't even think to spell out.  'it doesn't explode'

[] knowing how to use a tool vs knowing when to use a tool



Cunningham’s law:

Murphy’s law states that the best way to get the right answer on the internet is not to ask a question; it’s to post the wrong answer. What are some examples where you applied this law?

Cunningham’s law states that the best way to get an answer on the Internet is not to ask a question but to post the wrong answer.

Cunningham’s law in person: works great; but everybody thinks you’re stupid

cf gell-mann amnesia

Fermi: Not even wrong

slate pitch

prototypes and rough drafts of visions

I see what it will become

“No second impressions”

“no second impressions” and showing people partial drafts. Knuth and digital typography. examples from https://history.stackexchange.com/questions/51018/was-donald-knuth-the-first-person-to-typeset-a-book-using-a-computer:

No, Knuth was not the first person to typeset a book “with a computer”.

The TEX project was started in 1978 by Don­ald E. Knuth, while re­vis­ing the sec­ond vol­ume of his Art of Com­puter Pro­gram­ming. When he got the galleys back, he saw that the pub­lisher had switched to a new dig­i­tal type­set­ting sys­tem and was shocked at the poor qual­ity.

What are TEX and its friends? (CTAN Comprehensive TEX Archive Network)

And this is indeed a humble beginning, as it took quite a while to fine-tune TeX78 until realising that so many design mistakes were made that a fresh start was called for:

14 Mar 1978
 # 4:30am, \TeX's first page is successfully output!
* 26 Mar 1978
# Finally the entire test program was \TeX ed. Happy Easter! Six hours today.

From http://www.ctan.org/tex-archive/systems/knuth/dist/errata#errorlog.tex

That manual was published in September 1978. As Knuth wrote the user manual does not seem to count as a real book and he mentions in the article a 28-page book that appeared end of 1978 as the first book published by TeX.

Of course, user manuals don't count as real milestones in publishing. I like to think that the first real book to be printed with TEX was a 28-page keepsake that was made for my wife's relatives at Christmastime, 1978. This book included eighteen original linoleum block illustrations, into which we pasted XGP-produced text set in a special 14-point extended variant of the prototype Computer Modern font. In order to compensate for the XGP's limited resolution, we prepared magnified copy and the printer reduced it to 70%; the effective resolution was therefore about 286 pixels/inch. The title, opening pages, and colophon are illustrated here (reduced another 65% from the published size). About 100 copies were printed, of which roughly 25 were sold and the remaining 75 were given as gifts. A complete library citation for this book would read as follows: "Lena Bernice: Her Christmas in Wood County, 1895. By Elizabeth Ann James, with illustrations by Jill Carter Knuth. Columbus, Ohio: Rainshine Press, 1978."

enter image description here

Donald E. Knuth: "TeX Incunabula", TUGboat, Volume 5, No. 1, 1983 (PDF) Illustration in there of the first pages)

It only got real, arguably, then with Donald E. Knuth: “The TEXbook”, Addison Wesley, 1984, using TEX Version 3.0:

Gentle Reader: This is a handbook about TEX, a new typesetting system intended for the creation of beautiful books—and especially for books that contain a lot of mathematics.
(From the preface, emphasis added)

In fact Knuth was inspired to develop his system after seeing another book:

He had just received his first samples from the new typesetting system of the publisher's, and its quality was so far below that of the first edition of Volume 2 that he couldn't stand it. Around the same time, he saw a new book (Artificial Intelligence, by Patrick Winston) that had been produced digitally, and ultimately realized that typesetting meant arranging 0's and 1's (ink and no ink) in the proper pattern, and said (approximately), "As a computer scientist, I really identify with patterns of 0's and 1's; I ought to be able to do something about this", so he set out to learn what were the traditional rules for typesetting math, what constituted good typography, and (because the fonts of symbols that he needed really didn't exist) as much as he could about type design.

Curiously, while the first edition of the book by Winston was the inspiration for TeX, already the second version came out in 1984 using TeX! Comparison to earlier methods used at the MIT Press, the progress is obviuos.


Everyone has a testing platform; some also have a production platform.

Misc: what do you want? vs what will it cost vicious cycle in estimation and requirements gathering