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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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Making and Remaking the Modern Computer

Conceived in 1943, completed in 1945, and decommissioned in 1955, ENIAC (the Electronic Numerical Integrator and Computer) was the first general-purpose programmable electronic computer. But ENIAC was more than just a milestone on the road to the modern computer.

Foundations and Learning Algorithms

The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data.

Learn to Program While Solving Puzzles

This book builds a bridge between the recreational world of algorithmic puzzles (puzzles that can be solved by algorithms) and the pragmatic world of computer programming, teaching readers to program while solving puzzles. Few introductory students want to program for programming’s sake. Puzzles are real-world applications that are attention grabbing, intriguing, and easy to describe.

Affinity, Accelerators, Tasking, and SIMD

This book offers an up-to-date, practical tutorial on advanced features in the widely used OpenMP parallel programming model. Building on the previous volume, Using OpenMP: Portable Shared Memory Parallel Programming (MIT Press), this book goes beyond the fundamentals to focus on what has been changed and added to OpenMP since the 2.5 specifications.

An Introduction to Computational Geometry

Reissue of the 1988 Expanded Edition with a new foreword by Léon Bottou

A History of the Computer Services Industry

The computer services industry has worldwide annual revenues of nearly a trillion dollars and employs millions of workers, but is often overshadowed by the hardware and software products industries. In this book, Jeffrey Yost shows how computer services, from consulting and programming to data analytics and cloud computing, have played a crucial role in shaping information technology—in making IT work.

The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud?

In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a supervised learning setting. An emerging body of work on learning under different rules applies perturbations to decision and learning procedures. These methods provide simple and highly efficient learning rules with improved theoretical guarantees.

Intelligent Cars and the Road Ahead

“Smart, wide-ranging, [and] nontechnical.”
—Los Angeles Times

“Anyone who wants to understand what's coming must read this fascinating book.”
—Martin Ford, New York Times bestselling author of Rise of the Robots

Critical Perspectives on AI, Robots, and Ethics

One of the enduring concerns of moral philosophy is deciding who or what is deserving of ethical consideration. Much recent attention has been devoted to the "animal question"—consideration of the moral status of nonhuman animals. In this book, David Gunkel takes up the "machine question": whether and to what extent intelligent and autonomous machines of our own making can be considered to have legitimate moral responsibilities and any legitimate claim to moral consideration.

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