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Prediction Machines: The Simple Economics of Artificial Intelligence (英语) 精装 – 2018年4月17日

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  • Prediction Machines: The Simple Economics of Artificial Intelligence
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基本信息

  • 出版社: Harvard Business Review Press (2018年4月17日)
  • 精装: 272页
  • 语种: 英语
  • ISBN: 1633695670
  • 条形码: 9781633695672
  • 商品尺寸: 15.9 x 1.9 x 24.1 cm
  • 商品重量: 490 g
  • ASIN: 1633695670
  • 用户评分: 分享我的评价
  • 亚马逊热销商品排名: 图书商品里排第83,385名 (查看图书商品销售排行榜)
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媒体推荐

Named one of the "Top Ten Technology Books of 2018" by Peter High, Forbes.com

"Compared with the amount of ink spilled over the prospects of artificial general intelligence and all its accompanying fears--the singularity!--there's been much less attention to the smaller changes already happening in the realm of A.I. and their quite profound economic implications. Enter Prediction Machines." -- The New York Times

"…a readily understandable guide to artificial intelligence and the immensely consequential effects it could have on our economy, our society and our political system." -- Robert E. Rubin, former U.S. Treasury secretary and co-chair Emeritus, Council on Foreign Relations

One of "10 Great Reads For The Summer" -- Dave McKay, President & CEO at RBC

"Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans and Avi Goldfarb. This 2018 book…on the timely topic of AI - tops my summer reading list. The authors…offer a compelling framework for mapping out the likely impact of AI on economies in the decades ahead. -- BlackRock Investment Management

Named a Hardcover Non-Fiction Bestseller by the Globe & Mail (Canada)

"An excellent book on the economics of Artificial Intelligence. Steeped in both economics and AI/ML, this book steers clear of hype (or anti-hype), applying standard economic concepts to a rapidly emerging phenomenon. The book is geared to business readers not economists or policymakers but it has a lot to offer to everyone... Highly recommended." -- Jason Furman, former Chair of President Obama's Council of Economic Advisors on Goodreads

"This is a timely book, well written, and accessible putting forward their insights, and is well worth reading." -- Irish Tech News

Advance Praise for Prediction Machines:

Lawrence H. Summers, Charles W. Eliot Professor, former president, Harvard University; former secretary, US Treasury; and former chief economist, World Bank--
"AI may transform your life. And Prediction Machines will transform your understanding of AI. This is the best book yet on what may be the best technology that has come along."

Susan Athey, Economics of Technology Professor, Stanford University; former consulting researcher, Microsoft Research New England--
"Prediction Machines is a path-breaking book that focuses on what strategists and managers really need to know about the AI revolution. Taking a grounded, realistic perspective on the technology, the book uses principles of economics and strategy to understand how firms, industries, and management will be transformed by AI."

Dominic Barton, Global Managing Partner, McKinsey & Company--
"Prediction Machines achieves a feat as welcome as it is unique: a crisp, readable survey of where artificial intelligence is taking us separates hype from reality, while delivering a steady stream of fresh insights. It speaks in a language that top executives and policy makers will understand. Every leader needs to read this book."

Kevin Kelly, founding executive editor, Wired; author, What Technology Wants and The Inevitable--
"This book makes artificial intelligence easier to understand by recasting it as a new, cheap commodity--predictions. It's a brilliant move. I found the book incredibly useful."

作者简介

Ajay Agrawal is Professor of Strategic Management and Peter Munk Professor of Entrepreneurship at the University of Toronto's Rotman School of Management. He is also cofounder of The Next 36 and Next AI, cofounder of the AI/robotics company Kindred, and founder of the Creative Destruction Lab. Ajay conducts research on technology strategy, science policy, entrepreneurial finance, and the geography of innovation.

Joshua Gans is Professor of Strategic Management and the holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at Toronto's Rotman School of Management. Gans is a frequent contributor to outlets like the New York Times, Harvard Business Review, Forbes, Slate, and the Financial Times. Joshua also writes regularly at several blogs including Digitopoly.

Avi Goldfarb is the Ellison Professor of Marketing at Toronto's Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, a Fellow at Behavioral Economics in Action at Rotman, and a Research Associate at the National Bureau of Economic Research. His research has been widely covered in the popular press.


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美国亚马逊: 4.5 颗星,最多 5 颗星 52 条评论
fitzalling
5.0 颗星,最多 5 颗星Three Economists Demystify Artificial Intelligence
2018年7月9日 - 已在美国亚马逊上发表
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sweiss
4.0 颗星,最多 5 颗星Not useful for data scientists
2018年6月5日 - 已在美国亚马逊上发表
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24 个人发现此评论有用.
Alex Tolley
3.0 颗星,最多 5 颗星A largely non-economic look at the possible effects of cheap AI deployed as prediction machines.
2018年12月7日 - 已在美国亚马逊上发表
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4 个人发现此评论有用.
krantix
5.0 颗星,最多 5 颗星Must read for anyone trying to understand how AI will reshape the economy
2018年4月20日 - 已在美国亚马逊上发表
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8 个人发现此评论有用.
Mark Ettinger
4.0 颗星,最多 5 颗星High-level view of less-than-obvious consequences of prediction technology
2018年6月27日 - 已在美国亚马逊上发表
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4 个人发现此评论有用.