Nine Algorithms That Changed the Future

Nine Algorithms That Changed the Future

The Ingenious Ideas That Drive Today's Computers

Book - 2012
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Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease?

This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more.

These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.

Publisher: Princeton, N.J. : Princeton University Press, c2012.
ISBN: 9780691147147
Branch Call Number: 006.3 MACCORM
Characteristics: x, 219 p. : ill. ; 25 cm.


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Jun 07, 2013

This book describes nine revolutionary algorithms without delving into deep computer science or mathematics. Ideas such as these truly are the core of software engineering, and one of the main reasons I got into this field. In the conclusion, the author speculates on what sorts of solutions might be generated in the near future - very interesting ideas. In my opinion, both the description the Pattern Recognition algorithms and the overview of the Halting Problem were more complex than they needed to be. A discussion of neurons from other popular science books would improve the former; the latter may just require editing. Regardless, this is a very good introduction to these algorithms. (Jun 1-3)


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