Sid Meier’s Memoir! is the story of an obsessive young computer enthusiast who helped launch a multibilliondollar industry. Writing with warmth and ironic humor, Meier describes the genesis of his influential studio, MicroProse, founded in 1982 after a trip to a Las Vegas arcade, and recounts the development of landmark games, from vintage classics like Pirates! and Railroad Tycoon, to Civilization and beyond.Articulating his philosophy that a videogame should be “a series of interesting decisions,” Meier also shares his perspective on the history of the industry, the psychology of gamers, and fascinating insights into the creative process, including his ten rules of good game design.

    Shattering the myth of muses, higher powers, even creative “types,” Jonah Lehrer demonstrates that creativity is not a single gift possessed by the lucky few. It’s a variety of distinct thought processes that we can all learn to use more effectively.Lehrer reveals the importance of embracing the rut, thinking like a child, daydreaming productively, and adopting an outsider’s perspective (travel helps). He unveils the optimal mix of old and new partners in any creative collaboration, and explains why criticism is essential to the process. Then he zooms out to show how we can make our neighborhoods more vibrant, our companies more productive, and our schools more effective.You’ll learn about Bob Dylan’s writing habits and the drug addictions of poets. You’ll meet a Manhattan bartender who thinks like a chemist, and an autistic surfer who invented an entirely new surfing move. You’ll see why Elizabethan England experienced a creative explosion, and how Pixar’s office space is designed to spark the next big leap in animation.Collapsing the layers separating the neuron from the finished symphony, Imagine reveals the deep inventiveness of the human mind, and its essential role in our increasingly complex world. http://www.jonahlehrer.com/

    Scott McCloud's Understanding Comics is a seminal examination of comics art: its rich history, surprising technical components, and major cultural significance. Explore the secret world between the panels, through the lines, and within the hidden symbols of a powerful but misunderstood art form.

    We're rebelling against technology that's too complicated, DVD players with too many menus, and software accompanied by 75-megabyte "read me" manuals. The iPod's clean gadgetry has made simplicity hip. But sometimes we find ourselves caught up in the simplicity paradox: we want something that's simple and easy to use, but also does all the complex things we might ever want it to do. In The Laws of Simplicity, John Maeda offers ten laws for balancing simplicity and complexity in business, technology, and design—guidelines for needing less and actually getting more.Maeda—a professor in MIT's Media Lab and a world-renowned graphic designer—explores the question of how we can redefine the notion of "improved" so that it doesn't always mean something more, something added on.Maeda's first law of simplicity is "Reduce." It's not necessarily beneficial to add technology features just because we can. And the features that we do have must be organized (Law 2) in a sensible hierarchy so users aren't distracted by features and functions they don't need. But simplicity is not less just for the sake of less. Skip ahead to Law 9: "Failure: Accept the fact that some things can never be made simple." Maeda's concise guide to simplicity in the digital age shows us how this idea can be a cornerstone of organizations and their products—how it can drive both business and technology. We can learn to simplify without sacrificing comfort and meaning, and we can achieve the balance described in Law 10. This law, which Maeda calls "The One," tells us: "Simplicity is about subtracting the obvious, and adding the meaningful."

     Today, encyclopedias, jetliners, operating systems, mutual funds, and many other items are being created by teams numbering in the thousands or even millions. While some leaders fear the heaving growth of these massive online communities, Wikinomics proves this fear is folly. Smart firms can harness collective capability and genius to spur innovation, growth, and success. A brilliant guide to one of the most profound changes of our time, Wikinomics challenges our most deeply-rooted assumptions about business and will prove indispensable to anyone who wants to understand competitiveness in the twenty-first century. Based on a $9 million research project led by bestselling author Don Tapscott, Wikinomics shows how masses of people can participate in the economy like never before. They are creating TV news stories, sequencing the human genome, remixing their favorite music, designing software, finding a cure for disease, editing school texts, inventing new cosmetics, or even building motorcycles. You'll read about: • Rob McEwen, the Goldcorp, Inc. CEO who used open source tactics and an online competition to save his company and breathe new life into an old-fashioned industry. • Flickr, Second Life, YouTube, and other thriving online communities that transcend social networking to pioneer a new form of collaborative production. • Mature companies like Procter & Gamble that cultivate nimble, trust-based relationships with external collaborators to form vibrant business ecosystems. An important look into the future, Wikinomics will be your road map for doing business in the twenty-first century.

     into their ideal job   Each year tens of thousands of students will, after years of hard work and enormous amounts of money, earn their Ph.D. And each year only a small percentage of them will land a job that justifies and rewards their investment. For every comfortably tenured professor or well-paid former academic, there are countless underpaid and overworked adjuncts, and many more who simply give up in frustration.   Those who do make it share an important asset that separates them from the pack: they have a plan. They understand exactly what they need to do to set themselves up for success.  They know what really moves the needle in academic job searches, how to avoid the all-too-common mistakes that sink so many of their peers, and how to decide when to point their Ph.D. toward other, non-academic options.   Karen Kelsky has made it her mission to help readers join the select few who get the most out of their Ph.D. As a former tenured professor and department head who oversaw numerous academic job searches, she knows from experience exactly what gets an academic applicant a job. And as the creator of the popular and widely respected advice site The Professor is In, she has helped countless Ph.D.’s turn themselves into stronger applicants and land their dream careers.   Now, for the first time ever, Karen has poured all her best advice into a single handy guide that addresses the most important issues facing any Ph.D., including:   -When, where, and what to publish -Writing a foolproof grant application -Cultivating references and crafting the perfect CV -Acing the job talk and campus interview -Avoiding the adjunct trap -Making the leap to nonacademic work, when the time is right  The Professor Is In addresses all of these issues, and many more.

    It presents the mathematical foundations of computer graphics with a focus on geometric intuition, allowing the programmer to understand and apply those foundations to the development of efficient code. - The fundamental mathematics used in graphics programs - The basics of the graphics pipeline - BSP trees - Ray tracing - Surface shading - Texture mapping Advanced topics include: - Curves and surfaces - Color science - Global illumination - Reflection models - Image-based rendering - Visualization Extensive exercises and references for further reading enhance each chapter. An introduction for novices---a refresher for professionals.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    In addition to explaining the basic moves, this book provides writing templates that show students explicitly how to make these moves in their own writing.

    You think you can solve your human error problem by telling people to be more careful, by reprimanding the miscreants, by issuing a new rule or procedure. These are all expressions of 'The Bad Apple Theory', where you believe your system is basically safe if it were not for those few unreliable people in it. This old view of human error is increasingly outdated and will lead you nowhere. The new view, in contrast, understands that a human error problem is actually an organizational problem. Finding a 'human error' by any other name, or by any other human, is only the beginning of your journey, not a convenient conclusion. The new view recognizes that systems are inherent trade-offs between safety and other pressures (for example: production). People need to create safety through practice, at all levels of an organization. Breaking new ground beyond its successful predecessor, The Field Guide to Understanding Human Error guides you through the traps and misconceptions of the old view. It explains how to avoid the hindsight bias, to zoom out from the people closest in time and place to the mishap, and resist the temptation of counterfactual reasoning and judgmental language. But it also helps you look forward. It suggests how to apply the new view in building your safety department, handling questions about accountability, and constructing meaningful countermeasures. It even helps you in getting your organization to adopt the new view and improve its learning from failure. So if you are faced by a human error problem, abandon the fallacy of a quick fix. Read this book.

    Author Mike Selinker (Betrayal at House on the Hill) has invited some of the world's most talented and experienced game designers to share their secrets on game conception, design, development, and presentation. In these pages, you'll learn about storyboarding, balancing, prototyping, and playtesting from the best in the business.

    Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming. Packed with jokes, pop culture references, and the author's own hilarious artwork, Learn You a Haskell for Great Good! eases the learning curve of this complex language, and is a perfect starting point for any programmer looking to expand his or her horizons. The well-known web tutorial on which this book is based is widely regarded as the best way for beginners to learn Haskell, and receives over 30,000 unique visitors monthly.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    We dangle goodies (from candy bars to sales commissions) in front of people in much the same way we train the family pet. Drawing on a wealth of psychological research, Alfie Kohn points the way to a more successful strategy based on working with people instead of doing things to them. "Do rewards motivate people?" asks Kohn. "Yes. They motivate people to get rewards." Seasoned with humor and familiar examples, Punished By Rewards presents an argument unsettling to hear but impossible to dismiss.

    Reveals how to run an online business profitably in spite of the Internet's inherently free culture, disseminating the principles of a ''priceless economy'' in six categories that pertain to advertising, labor exchange, and advanced-version fees.