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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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A Beginner's Guide

Algorithms are what we do in order not to have to do something. Algorithms consist of instructions to carry out tasks—usually dull, repetitive ones. Starting from simple building blocks, computer algorithms enable machines to recognize and produce speech, translate texts, categorize and summarize documents, describe images, and predict the weather. A task that would take hours can be completed in virtually no time by using a few lines of code in a modern scripting program. This book offers an introduction to algorithms through the real-world problems they solve.

Imagination in the Age of Computing

We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It’s as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman’s curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking.

Technology for Wellbeing and Human Potential

On the eve of Google’s IPO in 2004, Larry Page and Sergey Brin vowed not to be evil. Today, a growing number of technologists would go further, trying to ensure that their work actively improves people’s lives. Technology, so pervasive and ubiquitous, has the capacity to increase stress and suffering; but it also has the less-heralded potential to improve the well-being of individuals, society, and the planet.

What can artificial intelligence teach us about the mind? If AI’s underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It’s a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example.

A New Theory of Interactive Real-Time Simulations

Computer simulations conceive objects and situations dynamically, in their changes and progressions. In The Systemic Image, Inge Hinterwaldner considers not only the technical components of dynamic computer simulations but also the sensory aspects of the realization. Examining the optic, the acoustic, the tactile, and the sensorimotor impressions that interactive real-time simulations provide, she finds that iconicity plays a dominant yet unexpected role.

In this original and provocative study of computational creativity in music, David Cope asks whether computer programs can effectively model creativity—and whether computer programs themselves can create. Defining musical creativity, and distinguishing it from creativity in other arts, Cope presents a series of experimental models that illustrate salient features of musical creativity. He makes the case that musical creativity results from a process that he calls inductive association, and he contends that such a computational process can in fact produce music creatively.

A Cyber-Physical Systems Approach

The most visible use of computers and software is processing information for human consumption. The vast majority of computers in use, however, are much less visible. They run the engine, brakes, seatbelts, airbag, and audio system in your car. They digitally encode your voice and construct a radio signal to send it from your cell phone to a base station. They command robots on a factory floor, power generation in a power plant, processes in a chemical plant, and traffic lights in a city.

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.

Photographs have been doctored since photography was invented. Dictators have erased people from photographs and from history. Politicians have manipulated photos for short-term political gain. Altering photographs in the predigital era required time-consuming darkroom work. Today, powerful and low-cost digital technology makes it relatively easy to alter digital images, and the resulting fakes are difficult to detect. The field of photo forensics—pioneered in Hany Farid’s lab at Dartmouth College—restores some trust to photography.

A Revolutionary History of the Computer

In The Government Machine, Jon Agar traces the mechanization of government work in the United Kingdom from the nineteenth to the early twenty-first century. He argues that this transformation has been tied to the rise of "expert movements," groups whose authority has rested on their expertise. The deployment of machines was an attempt to gain control over state action—a revolutionary move.

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