A couple of years ago I tried, vainly, to make that PDF into a more friendly format by splicing the pages so that they would form a PDF made of single pages. No joy, unfortunately. I haven't attempted an epub of it yet.

With the help of[1] and some glue code[2]:

  if __name__ == "__main__":
      import argparse
      parser = argparse.ArgumentParser(
          description=("Split up pdf from 2-up "
                       "to single page"))
      parser.add_argument("src", help="Source file")
      parser.add_argument("dst", help="Destination file")
      args = parser.parse_args()
      split_pages2(args.src, args.dst)

I produced a PDF[3] that appears to look ok at first glance (bit off on the margins, perhaps?).

[1] http://stackoverflow.com/questions/13345593/split-each-pdf-p...

[2] https://gist.github.com/ebe2445416ed8b683d93

[3] https://e12e.github.io/files/introcyb-split.pdf

Oh, good effort! Looks much better than what I managed.

Great piece in New Yorker on this sort of stuff by Evgeny Morozov.

http://www.newyorker.com/magazine/2014/10/13/planning-machin...

Cybernetics, known better today as control theory, is a significant discipline of math with lots of valuable insight applicable to broad areas of sciences and life. My favourite example - grokking the difference between open and closed-loop systems will let you discover the simple idea behind agile methodologies and how 90% of what's written about them is pure marketing bullshit.

Cybernetics is not control theory. Control theory existed some decades before Wiener and Ashby, and continued to develop separately from cybernetics. I am very interested in both fields, though less in modern cybernetics which is mostly philosophy and 'poetry' or something like that.

What I'm asking why this book in particular is relevant today.

Really, control theory helped you understand Agile? Please, do go on. I would love to hear the specifics.

TL;DR: waterfall is an open-loop system. In order to control it (the direction of your project, its results), you need to have a perfect model of system internals and know the input. Since you know neither, you simply can't control it. Agile is a closed-loop system, it contains a feedback loop, which lets you control the system even if you don't know the internals perfectly (and with human beings, you'll never know).

This is the core insight, though I'm probably skipping things in this description that you know implicitly when you've seen the math. The rest of discussion about agile is either minutiae of tuning the feedback loop for best results, or just marketing talk and bikeshedding.

Please explain!

History is relevant today. Historical posts are some of the best material we see on Hacker News. More historical posts, please!

According to the Wikipedia page on the author [1], "[Ashby's] two books, Design for a Brain and An Introduction to Cybernetics, were landmark works. They introduced exact and logical thinking into the nascent discipline and were highly influential." [1] states that Ashby's work influenced Stafford Beer and Gregory Chaitin.

Going back to a discipline's foundational works can be a good way to gain context and understanding.

[1] https://en.wikipedia.org/wiki/William_Ross_Ashby

Model predictive control is a hot topic in Computational Logistics atm (my field) I expect this is true of other fields too, these things seem to go like that.

https://en.wikipedia.org/wiki/Model_predictive_control

How is it not? (In the sense that an introduction to geometry is also relevant today)

It is a book of some 300 pages, I skimmed it. Doesn't seem true to the promise from the introduction - "to explain control theory without much math". It is also quite long.

For an introduction to control theory, I'd recommend Astrom & Murray, and for use of control theory in studying living beings W.T.Powers.

First time I hear W.T.Powers name but https://en.wikipedia.org/wiki/Perceptual_control_theory already inspires a lot.