The Pattern On The Stone: The Simple Ideas That Make Computers Work (Science Masters)

Most people are baffled by how computers work and assume that they will never understand them. What they don't realize—and what Daniel Hillis's short book brilliantly demonstrates—is that computers' seemingly complex operations can be broken down into a few simple parts that perform the same simple procedures over and over again. Computer wizard Hillis offers an easy-to-follow explanation of how data is processed that makes the operations of a computer seem as straightforward as those of a bicycle.Avoiding technobabble or discussions of advanced hardware, the lucid explanations and colorful anecdotes in The Pattern on the Stone go straight to the heart of what computers really do. Hillis proceeds from an outline of basic logic to clear descriptions of programming languages, algorithms, and memory. He then takes readers in simple steps up to the most exciting developments in computing today—quantum computing, parallel computing, neural networks, and self-organizing systems.Written clearly and succinctly by one of the world's leading computer scientists, The Pattern on the Stone is an indispensable guide to understanding the workings of that most ubiquitous and important of machines: the computer.

• Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today's Computers
• Tubes: A Journey to the Center of the Internet
• Code: The Hidden Language of Computer Hardware and Software (Developer Best Practices)
• Rebooting AI: Building Artificial Intelligence We Can Trust
• Four Futures: Life After Capitalism (Jacobin)
• Adventures of a Computational Explorer
• Human Compatible: Artificial Intelligence and the Problem of Control
• Nature's Numbers: The Unreal Reality Of Mathematics
• An investigation of the laws of thought: on which are founded the mathematical theories of logic and probabilities
• Good Video Games and Good Learning: Collected Essays on Video Games, Learning and Literacy, 2nd Edition (New Literacies and Digital Epistemologies Book 27)