In 1971, at the height of the Vietnam War and at a time of great political and social instability, two of the world's leading intellectuals, Noam Chomsky and Michel Foucault, were invited by Dutch philosopher Fons Edlers to debate an age-old question: is there such a thing as "innate" human nature independent of our experiences and external influences? The resulting dialogue is one of the most original, provocative, and spontaneous exchanges to have occurred between contemporary philosophers, and above all serves as a concise introduction to their basic theories. What begins as a philosophical argument rooted in linguistics (Chomsky) and the theory of knowledge (Foucault), soon evolves into a broader discussion encompassing a wide range of topics, from science, history, and behaviorism to creativity, freedom, and the struggle for justice in the realm of politics. In addition to the debate itself, this volume features a newly written introduction by noted Foucault scholar John Rajchman and includes additional text by Noam Chomsky.

    But this isn't the age of distrust--far from it. In this revolutionary book, world-renowned trust expert Rachel Botsman reveals that we are at the tipping point of one of the biggest social transformations in human history--with fundamental consequences for everyone. A new world order is emerging: we might have lost faith in institutions and leaders, but millions of people rent their home to total strangers, exchange digital currencies, or find themselves trusting a bot. This is the age of "distributed trust", a paradigm shift driven by innovative technologies that are rewriting the rules of an all-too-human relationship. If we are to benefit from this radical shift, we must understand the mechanics of how trust is built, managed, lost and repaired in the digital age. In the first book to explain this new world, Botsman provides a detailed map of this uncharted landscape--and explores what's next for humanity.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    The coming wave, says Rheingold, is the result of super-efficient mobile communications-cellular phones, personal digital assistants, and wireless-paging and Internet-access devices that will allow us to connect with anyone, anywhere, anytime. From the amusing ("Lovegetty" devices in Japan that light up when a person with the right date-potential characteristics appears in the vicinity) to the extraordinary (the overthrow of a repressive regime in the Philippines by political activists who mobilized by forwarding text messages via cell phones), Rheingold gives examples of the fundamentally new ways in which people are already engaging in group or collective action. He also considers the dark side of this phenomenon, such as the coordination of terrorist cells, threats to privacy, and the ability to incite violent behavior. Applying insights from sociology, artificial intelligence, engineering, and anthropology, Rheingold offers a penetrating perspective on the brave new convergence of pop culture, cutting-edge technology, and social activism. At the same time, he reminds us that, as with other technological revolutions, the real impact of mobile communications will come not from the technology itself but from how people use it, resist it, adapt to it, and ultimately use it to transform themselves, their communities, and their institutions.

    Unlike traditional empirical psychology, it is more oriented toward the how than the what. An experiment in mind design is more likely to be an attempt to build something and make it work--as in artificial intelligence--than to observe or analyze what already exists. Mind design is psychology by reverse engineering.When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's Computing Machinery and Intelligence) and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are philosophical in that they address fundamental issues and concepts; and all are scientific in that they are technically sophisticated and concerned with concrete empirical research.ContributorsRodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder

    Making reference to an astonishing number of cultures & drawing on scholarship published in no less than half a dozen European languages, Eliade's "The Myth of the Eternal Return makes both intelligible & compelling the religious expressions & activities of a wide variety of archaic & "primitive" religious cultures. While acknowledging that a return to the "archaic" is no longer possible, Eliade passionately insists on the value of understanding this view in order to enrich our contemporary imagination of what it is to be human.

    We often overlook the historical link between mathematics and technological advances, says Stewart—but this connection is integral to any complete understanding of human history.Equations are modeled on the patterns we find in the world around us, says Stewart, and it is through equations that we are able to make sense of, and in turn influence, our world. Stewart locates the origins of each equation he presents—from Pythagoras's Theorem to Newton's Law of Gravity to Einstein's Theory of Relativity—within a particular historical moment, elucidating the development of mathematical and philosophical thought necessary for each equation's discovery. None of these equations emerged in a vacuum, Stewart shows; each drew, in some way, on past equations and the thinking of the day. In turn, all of these equations paved the way for major developments in mathematics, science, philosophy, and technology. Without logarithms (invented in the early 17th century by John Napier and improved by Henry Briggs), scientists would not have been able to calculate the movement of the planets, and mathematicians would not have been able to develop fractal geometry. The Wave Equation is one of the most important equations in physics, and is crucial for engineers studying the vibrations in vehicles and the response of buildings to earthquakes. And the equation at the heart of Information Theory, devised by Claude Shannon, is the basis of digital communication today.An approachable and informative guide to the equations upon which nearly every aspect of scientific and mathematical understanding depends, In Pursuit of the Unknown is also a reminder that equations have profoundly influenced our thinking and continue to make possible many of the advances that we take for granted.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Today, twenty million people worldwide are surfing the Net. Where Wizards Stay Up Late is the exciting story of the pioneers responsible for creating the most talked about, most influential, and most far-reaching communications breakthrough since the invention of the telephone. In the 1960's, when computers where regarded as mere giant calculators, J.C.R. Licklider at MIT saw them as the ultimate communications devices. With Defense Department funds, he and a band of visionary computer whizzes began work on a nationwide, interlocking network of computers. Taking readers behind the scenes, Where Wizards Stay Up Late captures the hard work, genius, and happy accidents of their daring, stunningly successful venture.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    He takes us into the secret world of "Survivor" Spoilers, where avid internet users pool their knowledge to unearth the show's secrets before they are revealed on the air. He introduces us to young "Harry Potter" fans who are writing their own Hogwarts tales while executives at Warner Brothers struggle for control of their franchise. He shows us how "The Matrix" has pushed transmedia storytelling to new levels, creating a fictional world where consumers track down bits of the story across multiple media channels.Jenkins argues that struggles over convergence will redefine the face of American popular culture. Industry leaders see opportunities to direct content across many channels to increase revenue and broaden markets. At the same time, consumers envision a liberated public sphere, free of network controls, in a decentralized media environment. Sometimes corporate and grassroots efforts reinforce each other, creating closer, more rewarding relations between media producers and consumers. Sometimes these two forces are at war.Jenkins provides a riveting introduction to the world where every story gets told and every brand gets sold across multiple media platforms. He explains the cultural shift that is occurring as consumers fight for control across disparate channels, changing the way we do business, elect our leaders, and educate our children.

    Davis uncovers startling connections between such seemingly disparate topics as electricity and alchemy; online role-playing games and religious and occult practices; virtual reality and gnostic mythology; programming languages and Kabbalah. The final chapters address the apocalyptic dreams that haunt technology, providing vital historical context as well as new ways to think about a future defined by the mutant intermingling of mind and machine, nightmare and fantasy.

    Another AI discovered a new antibiotic by analyzing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality.In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before.

    While this has had the positive effect of equalizing access to knowledge, it also has lowered the bar on what depth of knowledge is required to consider oneself an "expert." A cult of anti-expertise sentiment has coincided with anti-intellectualism, resulting in massively viral yet poorly informed debates ranging from the anti-vaccination movement to attacks on GMOs. This surge in intellectual egalitarianism has altered the landscape of debates-all voices are equal, and "fact" is a subjective term. Browsing WebMD puts one on equal footing with doctors, and Wikipedia allows all to be foreign policy experts, scientists, and more. As Tom Nichols shows in The Death of Expertise, there are a number of reasons why this has occurred-ranging from easy access to Internet search engines to a customer satisfaction model within higher education. The product of these interrelated trends, Nichols argues, is a pervasive distrust of expertise among the public coinciding with an unfounded belief among non-experts that their opinions should have equal standing with those of the experts. The experts are not always right, of course, and Nichols discusses expert failure. The crucial point is that bad decisions by experts can and have been effectively challenged by other well-informed experts. The issue now is that the democratization of information dissemination has created an army of ill-informed citizens who denounce expertise.When challenged, non-experts resort to the false argument that the experts are often wrong. Though it may be true, but the solution is not to jettison expertise as an ideal; it is to improve our expertise. Nichols is certainly not opposed to information democratization, but rather the enlightenment people believe they achieve after superficial internet research. He shows in vivid detail the ways in which this impulse is coursing through our culture and body politic, but the larger goal is to explain the benefits that expertise and rigorous learning regimes bestow upon all societies.

    An Australian millionaire says Millennials could all afford homes if we'd just give up avocado toast. Thanks, millionaire. This Millennial is here to prove them all wrong.Millennials have been stereotyped as lazy, entitled, narcissistic, and immature. We've gotten so used to sloppy generational analysis filled with dumb clichés about young people that we've lost sight of what really unites Millennials. Namely:-We are the most educated and hard-working generation in American history.-We poured historic and insane amounts of time and money into preparing ourselves for the 21st century labor market.- We have been taught to consider working for free (homework, internships) a privilege for our own benefit.- We are poorer, more medicated, and more precariously employed than our parents, grandparents, even our great grandparents, with less of a social safety net to boot. Kids These Days, is about why. In brilliant, crackling prose, early Wall Street occupier Malcolm Harris gets mercilessly real about our maligned birth cohort. Examining trends like runaway student debt, the rise of the intern, mass incarceration, social media, and more, Harris gives us a portrait of what it means to be young in America today that will wake you up and piss you off. Millennials were the first generation raised explicitly as investments, Harris argues, and in Kids These Days he dares us to confront and take charge of the consequences now that we are grown up.