Prediction Machines

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出版者:Harvard Business Review Press
作者:Ajay Agrawal
出品人:
页数:272
译者:
出版时间:2018-4-17
价格:0
装帧:
isbn号码:9781633695672
丛书系列:
图书标签:
  • 经济学
  • 人工智能
  • AI
  • 科技
  • 预测
  • 管理
  • 科技商业
  • 深度学习
  • 人工智能
  • 机器学习
  • 数据分析
  • 预测模型
  • 科技趋势
  • 算法设计
  • 大数据
  • 智能系统
  • 未来科技
  • 自动化
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具体描述

"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google

Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.

But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

When AI is framed as cheap prediction, its extraordinary potential becomes clear:

- Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions.

- Prediction tools increase productivity--operating machines, handling documents, communicating with customers.

- Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete.

Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

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.

目录信息

读后感

评分

2018年Facebook被爆5000万用户信息用于政治选举,2019年Snapchat滥用特权监控用户信息。互联网公司种种隐私数据丑闻,从侧面反映了AI面临的挑战之一,就是如何合理的收集和使用用户的隐私数据? 如果AI无法应用隐私数据,那么AI还能叫AI吗?根据本书作者的核心观点,预测越来越...  

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不得不说这几年深度学习、人工智能之类的概念炒得火热,听说生物学只要加入AI的概念,用大数据分析之类的,就可以发一篇二区论文,还有动不动就耸人听闻的“未来这些工作会被人工智能淘汰”标题,身为跟AI有一点点沾边的电信专业的毕业生,一个对深度学习有过一点微末了解的人...  

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读这本书的时候,突然想起来这个视频,觉得有必要推荐大家看一下。库克2017MIT毕业演讲(完整视频+中英全文) 。 当下,对时事再不敏感的人也可以感受到人工智能的迅速发展,它正在以不可阻挡的态势席卷全球。无论是 iPhone 的神经网络引擎、AlphaGo 的围棋算法,还是无人驾驶...  

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主要内容是AI的各种应用案例介绍。作者把这些案例分到五个部分介绍:预测、决策、工具、战略、社会。 看书名和介绍以为会从经济学的角度解读AI,有更多的新鲜的视角和观点,读后比较失望,基本是见过的案例和视角。 总体评价3星,有参考价值。 以下是书中一些内容的摘抄,【】...  

用户评价

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就像北京雾霾天下的阳光,朦朦胧胧的,不知道是有还是没有

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AI has entered our life. Willing to learn what it can really help us and what damage it can bring as well.

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AI has entered our life. Willing to learn what it can really help us and what damage it can bring as well.

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AI has entered our life. Willing to learn what it can really help us and what damage it can bring as well.

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这本书完全不是给经济学人写的,常常提到的是如果你的公司想用ai应该什么时候用,怎样用。一半弃,对我来说没大有收获。

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