Computer Mathematics

The Singularity Is Near: When Humans Transcend Biology

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: the union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

Godel, Escher, Bach: An Eternal Golden Braid

Twenty years after it topped the bestseller charts, Douglas R. Hofstadter's Gödel, Escher, Bach: An Eternal Golden Braid is still something of a marvel. Besides being a profound and entertaining meditation on human thought and creativity, this book looks at the surprising points of contact between the music of Bach, the artwork of Escher, and the mathematics of Gödel. It also looks at the prospects for computers and artificial intelligence (AI) for mimicking human thought. For the general reader and the computer techie alike, this book still sets a standard for thinking about the future of computers and their relation to the way we think.

Hofstadter's great achievement in Gödel, Escher, Bach was making abstruse mathematical topics (like undecidability, recursion, and 'strange loops') accessible and remarkably entertaining. Borrowing a page from Lewis Carroll (who might well have been a fan of this book), each chapter presents dialogue between the Tortoise and Achilles, as well as other characters who dramatize concepts discussed later in more detail. Allusions to Bach's music (centering on his Musical Offering) and Escher's continually paradoxical artwork are plentiful here. This more approachable material lets the author delve into serious number theory (concentrating on the ramifications of Gödel's Theorem of Incompleteness) while stopping along the way to ponder the work of a host of other mathematicians, artists, and thinkers.

The world has moved on since 1979, of course. The book predicted that computers probably won't ever beat humans in chess, though Deep Blue beat Garry Kasparov in 1997. And the vinyl record, which serves for some of Hofstadter's best analogies, is now left to collectors. Sections on recursion and the graphs of certain functions from physics look tantalizing, like the fractals of recent chaos theory. And AI has moved on, of course, with mixed results. Yet Gödel, Escher, Bach remains a remarkable achievement. Its intellectual range and ability to let us visualize difficult mathematical concepts help make it one of this century's best for anyone who's interested in computers and their potential for real intelligence. --Richard Dragan

Topics Covered: J.S. Bach, M.C. Escher, Kurt Gödel: biographical information and work, artificial intelligence (AI) history and theories, strange loops and tangled hierarchies, formal and informal systems, number theory, form in mathematics, figure and ground, consistency, completeness, Euclidean and non-Euclidean geometry, recursive structures, theories of meaning, propositional calculus, typographical number theory, Zen and mathematics, levels of description and computers; theory of mind: neurons, minds and thoughts; undecidability; self-reference and self-representation; Turing test for machine intelligence.

The Unofficial LEGO MINDSTORMS NXT Inventor's Guide

The LEGO® MINDSTORMS® NXT set includes a variety of powerful electronic parts (motors, sensors, and the programmable NXT microcomputer) and lots of building elements. With these parts you can create thousands of unique, intelligent robots. The Unofficial LEGO MINDSTORMS NXT Inventor's Guide helps you to harness the capabilities of the NXT set and effectively plan, build, and program your own NXT robots.

The first part of the book contains a brief introduction to the NXT set. You'll then examine the pieces in the NXT set and the roles they play in construction. Next, you'll learn practical building techniques, like how to build sturdy structures and work with gears. Then it's time to learn how to program with the official NXT-G programming language (and learn a bit about several unofficial programming languages). You'll also learn what author David J. Perdue calls the MINDSTORMS method: a strategy for creating your own robots. Finally, you'll follow step-by-step instructions for building, programming, and testing six sample robots (all of which can be built using only the parts found in one NXT set). These six robots include:

• Zippy-Bot, a two-wheeled vehicle with a ball caster
• Bumper-Bot, a version of Zippy-Bot that explores your room and avoids objects
• Claw-Bot, a version of Zippy-Bot that searches for objects and pushes them away with its claw
• Tag-Bot, a four-wheeled steering vehicle that dashes around while you try to "tag" it with a flashlight
• Guard-Bot, a six-legged walking robot that launches a ball at intruders
• Golf-Bot, a stationary robot that finds a target and then hits a ball into the target

You'll also find an NXT-G Quick Reference, which provides information on the 30 types of standard programming blocks, and the LEGO MINDSTORMS NXT Piece Library, which features detailed information and images of the more than 80 types of LEGO pieces in the NXT set.

So go ahead. Grab your NXT set, fire up your creative mind, and see what you can invent with The Unofficial LEGO MINDSTORMS NXT Inventor's Guide.

Pattern Recognition and Machine Learning (Information Science and Statistics)

The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.

This completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher. The book is supported by a great deal of additional material, and the reader is encouraged to visit the book web site for the latest information.

Coming soon:

*For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text)

*For instructors, worked solutions to remaining exercises from the Springer web site

*Lecture slides to accompany each chapter

*Data sets available for download

I Am a Strange Loop

The Age of Spiritual Machines: When Computers Exceed Human Intelligence

How much do we humans enjoy our current status as the most intelligent beings on earth? Enough to try to stop our own inventions from surpassing us in smarts? If so, we'd better pull the plug right now, because if Ray Kurzweil is right we've only got until about 2020 before computers outpace the human brain in computational power. Kurzweil, artificial intelligence expert and author of The Age of Intelligent Machines, shows that technological evolution moves at an exponential pace. Further, he asserts, in a sort of swirling postulate, time speeds up as order increases, and vice versa. He calls this the "Law of Time and Chaos," and it means that although entropy is slowing the stream of time down for the universe overall, and thus vastly increasing the amount of time between major events, in the eddy of technological evolution the exact opposite is happening, and events will soon be coming faster and more furiously. This means that we'd better figure out how to deal with conscious machines as soon as possible--they'll soon not only be able to beat us at chess, but also likely demand civil rights, and might at last realize the very human dream of immortality.

The Age of Spiritual Machines is compelling and accessible, and not necessarily best read from front to back--it's less heavily historical if you jump around (Kurzweil encourages this). Much of the content of the book lays the groundwork to justify Kurzweil's timeline, providing an engaging primer on the philosophical and technological ideas behind the study of consciousness. Instead of being a gee-whiz futurist manifesto, Spiritual Machines reads like a history of the future, without too much science fiction dystopianism. Instead, Kurzweil shows us the logical outgrowths of current trends, with all their attendant possibilities. This is the book we'll turn to when our computers first say "hello." --Therese Littleton

The national bestseller by the "ultimate thinking machine" (Forbes) whose predictions for the future are startling, provocative--and closer to fruition than you think.

Ray Kurzweil is the inventor of the most innovative and compelling technology of our era, an international authority on artificial intelligence, and one of our greatest living visionaries. Now he offers a framework for envisioning the twenty-first century--an age in which the marriage of human sensitivity and artificial intelligence fundamentally alters and improves the way we live. Kurzweil's prophetic blueprint for the future takes us through the advances that inexorably result in computers exceeding the memory capacity and computational ability of the human brain by the year 2020 (with human-level capabilities not far behind); in relationships with automated personalities who will be our teachers, companions, and lovers; and in information fed straight into our brains along direct neural pathways. Optimistic and challenging, thought-provoking and engaging, The Age of Spiritual Machines is the ultimate guide on our road into the next century.

"The Age of Spiritual Machines will blow your mind. . . . Kurzweil lays out a scenario that might seem like science fiction if it weren't coming from a proven entrepreneur."-- San Francisco Chronicle
The Age of Spiritual Machines appeared on national bestseller lists, including the Boston Globe and the San Francisco Chronicle
Kurzweil's first book, The Age of Intelligent Machines, won the Association of American Publishers Award for the Most Outstanding Computer Science Book of 1990

On Intelligence

Jeff Hawkins, the high-tech success story behind PalmPilots and the Redwood Neuroscience Institute, does a lot of thinking about thinking. In On Intelligence Hawkins juxtaposes his two loves--computers and brains--to examine the real future of artificial intelligence. In doing so, he unites two fields of study that have been moving uneasily toward one another for at least two decades. Most people think that computers are getting smarter, and that maybe someday, they'll be as smart as we humans are. But Hawkins explains why the way we build computers today won't take us down that path. He shows, using nicely accessible examples, that our brains are memory-driven systems that use our five senses and our perception of time, space, and consciousness in a way that's totally unlike the relatively simple structures of even the most complex computer chip. Readers who gobbled up Ray Kurzweil's (The Age of Spiritual Machines and Steven Johnson's Mind Wide Open will find more intriguing food for thought here. Hawkins does a good job of outlining current brain research for a general audience, and his enthusiasm for brains is surprisingly contagious. --Therese Littleton

From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines.

The Elements of Statistical Learning

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.

This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind

Professional Microsoft Robotics Developer Studio (Wrox Programmer to Programmer)

Wrox's Professional Microsoft Robotics Developer Studio is one of the first guides to Microsoft's new platform for visualizing and programming robotics applications. Written by the founding architect of the product, Professional Microsoft Robotics Studio is heavy on examples making this a hands-on guide that will get readers building robotics applications quickly using 3 case-study robots: an indoor security robot, winning Magellan competitor and a chess-playing robotic arm.

Topics include:

• Common Concurrency Runtime
• Sending and Receiving Messages
• Building and Accessing Services
• Using a browser and the Internet as the UI for a robot
• Using supported hardware and integrating new hardware
• Simulating the real world for robotic interactions
• Extending the simulation environment
• Deploying to hardware
• Using the Visual Programming Language
• and more.

Source code and online support at Wrox.com.