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Algorithmic Desire

2021-03-15 Philosophy
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Release : 2021-03-15
Genre : Philosophy
Kind : eBook
Book Rating : 356/5 ( reviews)

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Book Synopsis Algorithmic Desire by : Matthew Flisfeder

Download or read book Algorithmic Desire written by Matthew Flisfeder. This book was released on 2021-03-15. Available in PDF, EPUB and Kindle. Book excerpt: In Algorithmic Desire, Matthew Flisfeder shows that social media is a metaphor that reveals the dominant form of contemporary ideology: neoliberal capitalism. The preeminent medium of our time, social media’s digital platform and algorithmic logic shape our experience of democracy, enjoyment, and desire. Weaving between critical theory and analyses of popular culture, Flisfeder uses examples from The King’s Speech, Black Mirror, Gone Girl, The Circle, and Arrival to argue that social media highlights the antisocial dimensions of twenty‐first-century capitalism. He counters leading critical theories of social media—such as new materialism and accelerationism—and thinkers such as Gilles Deleuze and Michel Foucault, proposing instead a new structuralist account of the ideology and metaphor of social media. Emphasizing the structural role of crises, gaps, and negativity as central to our experiences of reality, Flisfeder interprets the social media metaphor through a combination of dialectical, Marxist, and Lacanian frameworks to show that algorithms may indeed read our desire, but capitalism, not social media, truly makes us antisocial. Wholly original in its interdisciplinary approach to social media and ideology, Flisfeder’s conception of “algorithmic desire” is timely, intriguing, and sure to inspire debate.

Algorithmic Desire

2021-03-15
Download Algorithmic Desire PDF Online Free

Author :
Release : 2021-03-15
Genre :
Kind : eBook
Book Rating : 333/5 ( reviews)

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Book Synopsis Algorithmic Desire by : Matthew Flisfeder

Download or read book Algorithmic Desire written by Matthew Flisfeder. This book was released on 2021-03-15. Available in PDF, EPUB and Kindle. Book excerpt: "Algorithmic Desire shows that social media is a metaphor that reveals the dominant form of contemporary ideology: neoliberal capitalism. The author interprets the social media metaphor through dialectical, Marxist, and Lacanian frameworks"--

What Algorithms Want

2017-03-10 Computers
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Release : 2017-03-10
Genre : Computers
Kind : eBook
Book Rating : 928/5 ( reviews)

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Book Synopsis What Algorithms Want by : Ed Finn

Download or read book What Algorithms Want written by Ed Finn. This book was released on 2017-03-10. Available in PDF, EPUB and Kindle. Book excerpt: The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek. We depend on—we believe in—algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things. If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.

Building Winning Algorithmic Trading Systems, + Website

2014-07-21 Business & Economics
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Release : 2014-07-21
Genre : Business & Economics
Kind : eBook
Book Rating : 987/5 ( reviews)

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Book Synopsis Building Winning Algorithmic Trading Systems, + Website by : Kevin J. Davey

Download or read book Building Winning Algorithmic Trading Systems, + Website written by Kevin J. Davey. This book was released on 2014-07-21. Available in PDF, EPUB and Kindle. Book excerpt: Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas. A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system—enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm. Learn the systems that generated triple-digit returns in the World Cup Trading Championship Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms Test your new system using historical and current market data Mine market data for statistical tendencies that may form the basis of a new system Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice.

Algorithms, Automation, and News

2021-05-18 Language Arts & Disciplines
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Release : 2021-05-18
Genre : Language Arts & Disciplines
Kind : eBook
Book Rating : 39X/5 ( reviews)

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Book Synopsis Algorithms, Automation, and News by : Neil Thurman

Download or read book Algorithms, Automation, and News written by Neil Thurman. This book was released on 2021-05-18. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the growing importance of algorithms and automation—including emerging forms of artificial intelligence—in the gathering, composition, and distribution of news. In it the authors connect a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these chapters share some of the noble ambitions of the pioneering publications on ‘reporting algorithms’, such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematise computational journalism by, for example, pointing out some of the challenges inherent in applying artificial intelligence to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner. The chapters in this book were originally published as a special issue of Digital Journalism.

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