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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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Edited by Pavan Balaji

With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today.

Intelligence does not arise only in individual brains; it also arises in groups of individuals. This is collective intelligence: groups of individuals acting collectively in ways that seem intelligent. In recent years, a new kind of collective intelligence has emerged: interconnected groups of people and computers, collectively doing intelligent things. Today these groups are engaged in tasks that range from writing software to predicting the results of presidential elections.

Military drones have recently been hailed as a revolutionary new technology that will forever change the conduct of war. And yet the United States and other countries have been deploying such unmanned military systems for more than a century. Written by a renowned authority in the field, this book documents the forgotten legacy of these pioneering efforts, offering the first comprehensive historical and technical accounting of unmanned air, land, sea, and underwater systems. Focusing on examples introduced during the two world wars, H. R.

Attention in the Age of Embodied Information

The world is filling with ever more kinds of media, in ever more contexts and formats. Glowing rectangles have become part of the scene; screens, large and small, appear everywhere. Physical locations are increasingly tagged and digitally augmented. Amid this flood, your attention practices matter more than ever. You might not be able to tune this world out. So it is worth remembering that underneath all these augmentations and data flows, fixed forms persist, and that to notice them can improve other sensibilities.

In Adversarial Design, Carl DiSalvo examines the ways that technology design can provoke and engage the political. He describes a practice, which he terms “adversarial design,” that uses the means and forms of design to challenge beliefs, values, and what is taken to be fact. It is not simply applying design to politics—attempting to improve governance for example, by redesigning ballots and polling places; it is implicitly contestational and strives to question conventional approaches to political issues.

With robots, we are inventing a new species that is part material and part digital. The ambition of modern robotics goes beyond copying humans, beyond the effort to make walking, talking androids that are indistinguishable from people. Future robots will have superhuman abilities in both the physical and digital realms. They will be embedded in our physical spaces, with the ability to go where we cannot, and will have minds of their own, thanks to artificial intelligence.

The Fourth Great Scientific Domain

Computing is not simply about hardware or software, or calculation or applications. Computing, writes Paul Rosenbloom, is an exciting and diverse, yet remarkably coherent, scientific enterprise that is highly multidisciplinary yet maintains a unique core of its own. In On Computing, Rosenbloom proposes that computing is a great scientific domain on a par with the physical, life, and social sciences.

The Mathematical Foundations of Music

“Mathematics can be as effortless as humming a tune, if you know the tune,” writes Gareth Loy. In Musimathics, Loy teaches us the tune, providing a friendly and spirited tour of the mathematics of music—a commonsense, self-contained introduction for the nonspecialist reader. It is designed for musicians who find their art increasingly mediated by technology, and for anyone who is interested in the intersection of art and science.

The idea that human history is approaching a “singularity”—that ordinary humans will someday be overtaken by artificially intelligent machines or cognitively enhanced biological intelligence, or both—has moved from the realm of science fiction to serious debate. Some singularity theorists predict that if the field of artificial intelligence (AI) continues to develop at its current dizzying rate, the singularity could come about in the middle of the present century.

Algorithms, Worked Examples, and Case Studies

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

  • Page 4 of 91