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';New Dark Ageis among the most unsettling and illuminating books I've read about the Internet, which is to say that it is among the most unsettling and illuminating books I've read about contemporary life.'New YorkerAs the world around us increases in technological complexity, our understanding of it diminishes. Underlying this trend is a single idea: the belief that our existence is understandable through computation, and more data is enough to help us build a better world. In reality, we are lost in a sea of information, increasingly divided by fundamentalism, simplistic narratives, conspiracy theories, and post-factual politics. Meanwhile, those in power use our lack of understanding to further their own interests. Despite the apparent accessibility of information, we're living in a new Dark Age. From rogue financial systems to shopping algorithms, from artificial intelligence to state secrecy, we no longer understand how our world is governed or presented to us. The media is filled with unverifiable speculation, much of it generated by anonymous software, while companies dominate their employees through surveillance and the threat of automation. In his brilliant new work, leading artist and writer James Bridle surveys the history of art, technology, and information systems, and reveals the dark clouds that gather over our dreams of the digital sublime.
NEW YORK TIMES BESTSELLER • Lauded Star Wars author James Luceno returns to pen an intense tale of ambition and betrayal that sets the stage for Rogue One: A Star Wars Story. War is tearing the galaxy apart. For years the Republic and the Separatists have battled across the stars, each building more and more deadly technology in an attempt to win the war. As a member of Chancellor Palpatine's top secret Death Star project, Orson Krennic is determined to develop a superweapon before the Republic's enemies can. And an old friend of Krennic's, the brilliant scientist Galen Erso, could be the key. Galen's energy-focused research has captured the attention of both Krennic and his foes, making the scientist a crucial pawn in the galactic conflict. But after Krennic rescues Galen, his wife, Lyra, and their young daughter, Jyn, from Separatist kidnappers, the Erso family is deeply in Krennic's debt. Krennic then offers Galen an extraordinary opportunity: to continue his scientific studies with every resource put utterly at his disposal. While Galen and Lyra believe that his energy research will be used purely in altruistic ways, Krennic has other plans that will finally make the Death Star a reality. Trapped in their benefactor's tightening grasp, the Ersos must untangle Krennic's web of deception to save themselves and the galaxy itself.
This book provides a broad survey of the field of biochips, including fundamentals of microelectronics and biomaterials interaction with various, living tissues, as well as numerous, diverse applications. Although a wide variety of biochips will be described, there will be a focus on those at the brain-machine interface. Analysis is included of the relationship between different categories of biochips and their interactions with the body and coverage includes wireless remote control of biochips and arrays of microelectrodes, based on new biomaterials.
This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications.The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.
This brief monograph is an in-depth study of the infinite divisibility and self-decomposability properties of central and noncentral Student's distributions, represented as variance and mean-variance mixtures of multivariate Gaussian distributions with the reciprocal gamma mixing distribution. These results allow us to define and analyse Student-Lévy processes as Thorin subordinated Gaussian Lévy processes. A broad class of one-dimensional, strictly stationary diffusions with the Student's t-marginal distribution are defined as the unique weak solution for the stochastic differential equation. Using the independently scattered random measures generated by the bi-variate centred Student-Lévy process, and stochastic integration theory, a univariate, strictly stationary process with the centred Student's t- marginals and the arbitrary correlation structure are defined. As a promising direction for future work in constructing and analysing new multivariate Student-Lévy type processes, the notion of Lévy copulas and the related analogue of Sklar's theorem are explained.
Applied data-centric social sciences aim to develop both methodology and practical applications of various fields of social sciences and businesses with rich data. Specifically, in the social sciences, a vast amount of data on human activities may be useful for understanding collective human nature. In this book, the author introduces several mathematical techniques for handling a huge volume of data and analysing collective human behaviour. The book is constructed from data-oriented investigation, with mathematical methods and expressions used for dealing with data for several specific problems. The fundamental philosophy underlying the book is that both mathematical and physical concepts are determined by the purposes of data analysis. This philosophy is shown throughout exemplar studies of several fields in socio-economic systems. From a data-centric point of view, the author proposes a concept that may change people's minds and cause them to start thinking from the basis of data. Several goals underlie the chapters of the book. The first is to describe mathematical and statistical methods for data analysis, and toward that end the author delineates methods with actual data in each chapter. The second is to find a cyber-physical link between data and data-generating mechanisms, as data are always provided by some kind of data-generating process in the real world. The third goal is to provide an impetus for the concepts and methodology set forth in this book to be applied to socio-economic systems.