These books, both fiction and non-fiction, hold special meaning in guiding some of our vision -- technically, philosophically, and culturally. While some subjects or topics have aged poorly, they serve in some historical capacity. This list is by no means exhaustive, but we hope will offer some insight to who we are. Feel free to read along and/or recommend something.
Set in twenty-first century Shanghai, it is the story of what happens when a state-of-the-art interactive device falls in the hands of a street urchin named Nell. Her life—and the entire future of humanity—is about to be decoded and reprogrammed...
In the year 2044, reality is an ugly place. The only time teenage Wade Watts really feels alive is when he's jacked into the virtual utopia known as the OASIS. Wade's devoted his life to studying the puzzles hidden within this world's digital confines—puzzles that are based on their creator's obsession with the pop culture of decades past and that promise massive power and fortune to whoever can unlock them.
But when Wade stumbles upon the first clue, he finds himself beset by players willing to kill to take this ultimate prize. The race is on, and if Wade's going to survive, he'll have to win—and confront the real world he's always been so desperate to escape.
The Matrix is a world within the world, a global consensus- hallucination, the representation of every byte of data in cyberspace...
Case had been the sharpest data-thief in the business, until vengeful former employees crippled his nervous system. But now a new and very mysterious employer recruits him for a last-chance run. The target: an unthinkably powerful artificial intelligence orbiting Earth in service of the sinister Tessier-Ashpool business clan. With a dead man riding shotgun and Molly, mirror-eyed street-samurai, to watch his back, Case embarks on an adventure that ups the ante on an entire genre of fiction.
Only once in a great while does a writer come along who defies comparison -- a writer so original he redefines the way we look at the world. Neal Stephenson is such a writer and Snow Crash is such a novel, weaving virtual reality, Sumerian myth, and just about everything in between with a cool, hip cyber-sensibility to bring us the gigantic thriller of the information age. In reality, Hiro Protagonist delivers pizza for Uncle Enzo's Cosa Nostra Inc., but it the Metaverse he's a warrior prince.
Plunging headlong into the enigma of a new computer virus that's striking down hackers everywhere, he races along the neon-lit streets on a search-and-destroy mission for the shadowy virtual villain threatening to bring about infocalypse. Snow Crash is a mind-altering romp through a future America so bizarre, so outrageous... you'll recognize it immediately.
The three laws of Robotics: 1) A robot may not injure a human being or, through inaction, allow a human being to come to harm 2) A robot must obey orders givein to it by human beings except where such orders would conflict with the First Law. 3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.
With these three, simple directives, Isaac Asimov changed our perception of robots forever when he formulated the laws governing their behavior. In I, Robot, Asimov chronicles the development of the robot through a series of interlinked stories: from its primitive origins in the present to its ultimate perfection in the not-so-distant future--a future in which humanity itself may be rendered obsolete.
Here are stories of robots gone mad, of mind-read robots, and robots with a sense of humor. Of robot politicians, and robots who secretly run the world--all told with the dramatic blend of science fact and science fiction that has become Asmiov's trademark.
By 2021, the World War had killed millions, driving entire species into extinction and sending mankind off-planet. Those who remained coveted any living creature, and for people who couldn’t afford one, companies built incredibly realistic simulacrae: horses, birds, cats, sheep. They even built humans. Immigrants to Mars received androids so sophisticated they were indistinguishable from true men or women. Fearful of the havoc these artificial humans could wreak, the government banned them from Earth. Driven into hiding, unauthorized androids live among human beings, undetected. Rick Deckard, an officially sanctioned bounty hunter, has been commissioned to find rogue androids, and “retire” them. But when cornered, androids fight back—with lethal force.
Santiago Ramón y Cajal was a mythic figure in science. Hailed as the father of modern anatomy and neurobiology, he was largely responsible for the modern conception of the brain. His groundbreaking works were New Ideas on the Structure of the Nervous System and Histology of the Nervous System in Man and Vertebrates. In addition to leaving a legacy of unparalleled scientific research, Cajal sought to educate the novice scientist about how science was done and how he thought it should be done. This recently rediscovered classic, first published in 1897, is an anecdotal guide for the perplexed new investigator as well as a refreshing resource for the old pro.
Cajal was a pragmatist, aware of the pitfalls of being too idealistic -- and he had a sense of humor, particularly evident in his diagnoses of various stereotypes of eccentric scientists. The book covers everything from valuable personality traits for an investigator to social factors conducive to scientific work.
Only a few books stand as landmarks in social and scientific upheaval. Norbert Wiener's classic is one in that small company. Founder of the science of cybernetics—the study of the relationship between computers and the human nervous system—Wiener was widely misunderstood as one who advocated the automation of human life. As this book reveals, his vision was much more complex and interesting. He hoped that machines would release people from relentless and repetitive drudgery in order to achieve more creative pursuits. At the same time he realized the danger of dehumanizing and displacement. His book examines the implications of cybernetics for education, law, language, science, technology, as he anticipates the enormous impact—in effect, a third industrial revolution—that the computer has had on our lives.
Acclaimed one of the "seminal books...comparable in ultimate importance to...Galileo or Malthus or Rousseau or Mill," Cybernetics was judged by twenty-seven historians, economists, educators, and philosophers to be one of those books published during the "past four decades," which may have a substantial impact on public thought and action in the years ahead. -- Saturday Review
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
As Director of the Office of Scientific Research and Development, Dr. Vannevar Bush has coordinated the activities of some six thousand leading American scientists in the application of science to warfare. In this significant article he holds up an incentive for scientists when the fighting has ceased. He urges that men of science should then turn to the massive task of making more accessible our bewildering store of knowledge. For years inventions have extended man's physical powers rather than the powers of his mind. Trip hammers that multiply the fists, microscopes that sharpen the eye, and engines of destruction and detection are new results, but not the end results, of modern science. Now, says Dr. Bush, instruments are at hand which, if properly developed, will give man access to and command over the inherited knowledge of the ages. The perfection of these pacific instruments should be the first objective of our scientists as they emerge from their war work. Like Emerson's famous address of 1837 on "The American Scholar," this paper by Dr. Bush calls for a new relationship between thinking man and the sum of our knowledge. —THE EDITOR
"Shaping Things is about created objects and the environment, which is to say, it's about everything," writes Bruce Sterling in this addition to the Mediawork Pamphlet series. He adds: "Seen from sufficient distance, this is a small topic."
Sterling offers a brilliant, often hilarious history of shaped things. We have moved from an age of artifacts, made by hand, through complex machines, to the current era of "gizmos." New forms of design and manufacture are appearing that lack historical precedent, he writes; but the production methods, using archaic forms of energy and materials that are finite and toxic, are not sustainable. The future will see a new kind of object; we have the primitive forms of them now in our pockets and briefcases: user-alterable, baroquely multi-featured, and programmable, that will be sustainable, enhanceable, and uniquely identifiable. Sterling coins the term "spime" for them, these future-manufactured objects with informational support so extensive and rich that they are regarded as material instantiations of an immaterial system. Spimes are designed on screens, fabricated by digital means, and precisely tracked through space and time. They are made of substances that can be folded back into the production stream of future spimes, challenging all of us to become involved in their production. Spimes are coming, says Sterling. We will need these objects in order to live; we won't be able to surrender their advantages without awful consequences.
The vision of Shaping Things is given material form by the intricate design of Lorraine Wild. Shaping Things is for designers and thinkers, engineers and scientists, entrepreneurs and financiers; and anyone who wants to understand and be part of the process of technosocial transformation.
A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
The world of smart shoes, appliances, and phones is already here, but the practice of user experience (UX) design for ubiquitous computing is still relatively new. Design companies like IDEO and frogdesign are regularly asked to design products that unify software interaction, device design and service design -- which are all the key components of ubiquitous computing UX -- and practicing designers need a way to tackle practical challenges of design. Theory is not enough for them -- luckily the industry is now mature enough to have tried and tested best practices and case studies from the field.
Smart Things presents a problem-solving approach to addressing designers' needs and concentrates on process, rather than technological detail, to keep from being quickly outdated. It pays close attention to the capabilities and limitations of the medium in question and discusses the tradeoffs and challenges of design in a commercial environment. Divided into two sections, frameworks and techniques, the book discusses broad design methods and case studies that reflect key aspects of these approaches. The book then presents a set of techniques highly valuable to a practicing designer. It is intentionally not a comprehensive tutorial of user-centered design'as that is covered in many other books'but it is a handful of techniques useful when designing ubiquitous computing user experiences.
In short, Smart Things gives its readers both the "why" of this kind of design and the "how," in well-defined chunks.
This is a one-of-a-kind reference for anyone with a serious interest in mathematics. Edited by Timothy Gowers, a recipient of the Fields Medal, it presents nearly two hundred entries, written especially for this book by some of the world's leading mathematicians, that introduce basic mathematical tools and vocabulary; trace the development of modern mathematics; explain essential terms and concepts; examine core ideas in major areas of mathematics; describe the achievements of scores of famous mathematicians; explore the impact of mathematics on other disciplines such as biology, finance, and music--and much, much more.Unparalleled in its depth of coverage, The Princeton Companion to Mathematics surveys the most active and exciting branches of pure mathematics, providing the context and broad perspective that are vital at a time of increasing specialization in the field. Packed with information and presented in an accessible style, this is an indispensable resource for undergraduate and graduate students in mathematics as well as for researchers and scholars seeking to understand areas outside their specialties.
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.
Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. 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.
Probalistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become an active field of research and practice in artifical intelligence, operations research and statistics in the last two decades. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradim has been striking. In this book, the author extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results gleaned from a decade's research.
Nelson writes passionately about the need for people to understand computers deeply, more deeply than was generally promoted as computer literacy, which he considers a superficial kind of familiarity with particular hardware and software. His rallying cry "Down with Cybercrud" is against the centralization of computers such as that performed by IBM at the time, as well as against what he sees as the intentional untruths that "computer people" tell to non-computer people to keep them from understanding computers. In Dream Machines, Nelson covers the flexible media potential of the computer, which was shockingly new at the time.