What Algorithms Want: Imagination in the Age of Computing (Hardcover)
Ed Finn
- 出版商: MIT
- 出版日期: 2017-03-10
- 售價: $1,048
- 貴賓價: 9.5 折 $996
- 語言: 英文
- 頁數: 272
- 裝訂: Hardcover
- ISBN: 0262035928
- ISBN-13: 9780262035927
-
相關分類:
Algorithms-data-structures 資料結構與演算法
立即出貨(限量) (庫存=1)
買這商品的人也買了...
-
$299Python Power!: The Comprehensive Guide
-
$840Interactive Data Visualization for the Web (Paperback)
-
$1,320$1,254 -
$1,020$969 -
$360$306 -
$2,220$2,109 -
$505Xcode實戰:Apple平臺開發實用技術、技巧及最佳流程
-
$1,798$1,708 -
$2,680$2,546 -
$875$831 -
$990$941 -
$1,620$1,539 -
$490$417 -
$380$323 -
$1,570$1,492 -
$360$180 -
$1,485$1,411 -
$1,300$1,274 -
$1,330$1,264 -
$550$468 -
$390$371 -
$1,485Deep Learning with Python (Paperback)
-
$750$713 -
$940$893 -
$2,280$2,166
商品描述
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.