Train an em to do some job and copy it a million times: an army of workers is at your disposal. When they can be made cheaply, within perhaps a century, ems will displace humans in most jobs. In this new economic era, the world economy may double in size every few weeks. Some say we can't know the future, especially following such a disruptive new technology, but Professor Robin Hanson sets out to prove them wrong. Applying decades of expertise in physics, computer science, and economics, he uses standard theories to paint a detailed picture of a world dominated by ems. While human lives don't change greatly in the em era, em lives are as different from ours as our lives are from those of our farmer and forager ancestors. Ems make us question common assumptions of moral progress, because they reject many of the values we hold dear. Read about em mind speeds, body sizes, job training and career paths, energy use and cooling infrastructure, virtual reality, aging and retirement, death and immortality, security, wealth inequality, religion, teleportation, identity, cities, politics, law, war, status, friendship and love. This book shows you just how strange your descendants may be, though ems are no stranger than we would appear to our ancestors. To most ems, it seems good to be an em.

    Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review. If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: "I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.

    On Lisp explains the reasons behind Lisp's growing popularity as a mainstream programming language. On Lisp is a comprehensive study of advanced Lisp techniques, with bottom-up programming as the unifying theme. It gives the first complete description of macros and macro applications. The book also covers important subjects related to bottom-up programming, including functional programming, rapid prototyping, interactive development, and embedded languages. The final chapter takes a deeper look at object-oriented programming than previous Lisp books, showing the step-by-step construction of a working model of the Common Lisp Object System (CLOS). As well as an indispensable reference, On Lisp is a source of software. Its examples form a library of functions and macros that readers will be able to use in their own Lisp programs.

    If you're a business or IT professional, this short hands-on guide teaches you how to pull and transform data with SQL in significant ways. You will quickly master the fundamentals of SQL and learn how to create your own databases.Author Thomas Nield provides exercises throughout the book to help you practice your newfound SQL skills at home, without having to use a database server environment. Not only will you learn how to use key SQL statements to find and manipulate your data, but you'll also discover how to efficiently design and manage databases to meet your needs.You'll also learn how to:Explore relational databases, including lightweight and centralized modelsUse SQLite and SQLiteStudio to create lightweight databases in minutesQuery and transform data in meaningful ways by using SELECT, WHERE, GROUP BY, and ORDER BYJoin tables to get a more complete view of your business dataBuild your own tables and centralized databases by using normalized design principlesManage data by learning how to INSERT, DELETE, and UPDATE records

    The coming Augmented Age, however, promises a level of disruption, behavioral shifts and changes that are unparalleled. While consumers today are camping outside of an Apple store waiting to be one of the first to score a new Apple Watch or iPhone, the next generation of wearables will be able to predict if we re likely to have a heart attack and recommend a course of action. We watch news of Google s self-driving cars, but don t likely realize this means progressive cities will have to ban human drives in the next decade because us humans are too risky. Following on from the Industrial or Machine Age, the Space Age and the Digital Age, the Augmented Age will be based on four key disruptive themes Artificial Intelligence, Experience Design, Smart Infrastructure, and Health Tech. Historically the previous ages brought significant disruption and changes, but on a net basis jobs were created, wealth was enhanced, and the health and security of society improved. What will the Augmented Age bring? Will robots take our jobs, and AI s subsume us as inferior intelligences, or will this usher in a new age of abundance? Augmented is a book on future history, but more than that, it is a story about how you will live your life in a world that will change more in the next 20 years than it has in the last 250 years. Are you ready to adapt? Because if history proves anything, you don't have much of a choice."

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    The topic everyone in the world should be talking about.

    Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

    It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

    I. is explored and explained in this best selling text. Assuming no prior knowledge, it covers topics like neural networks and robotics. This text explores the range of problems which have been and remain to be solved using A. I. tools and techniques. The second half of this text is an excellent reference.

    He traces AI's origins in ancient myth, through literary classics like Frankenstein, to today's sci-fi blockbusters, arguing that a fascination with AI is hardwired into the human psyche. He explains AI's history, technology, and potential; its manifestations in intelligent machines; its connections to neurology and consciousness, as well as—perhaps most tellingly—what AI reveals about us as human beings.In Our Own Image argues that we are on the brink of a fourth industrial revolution—poised to enter the age of Artificial Intelligence as science fiction becomes science fact. Ultimately, Zarkadakis observes, the fate of AI has profound implications for the future of science and humanity itself.

    In this lively book of essays, Stephen Wolfram takes the reader along on some of his most surprising and engaging intellectual adventures in science, technology, artificial intelligence and language design.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    With it has 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. 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 wrote much of the statistical modeling software in 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, and projection pursuit.

    By combining ArcGIS tutorials with self-study exercises intended to gradually build upon basic skills, the GIS Tutorial 1 is fully adaptable to individual needs, as well as the classroom setting. The tutorial demonstrates a range of GIS functionality, from creating maps and collecting data to using geoprocessing tools and models as well as ArcGIS 3D Analyst and ArcGIS Spatial Analyst extensions for further analysis. GIS Tutorial 1 includes a data CD for working through the exercises and fully functioning 180-day trial DVD of ArcGIS Desktop10 software, making it the smart choice for GIS beginners.