Prediction Machines

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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.

出版者:Harvard Business Review Press
作者:Ajay Agrawal
出品人:
頁數:272
译者:
出版時間:2018-4-17
價格:0
裝幀:
isbn號碼:9781633695672
叢書系列:
圖書標籤:
  • 經濟學 
  • 人工智能 
  • AI 
  • 科技 
  • 預測 
  • 管理 
  • 科技商業 
  • 深度學習 
  •  
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"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.

具體描述

讀後感

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说起AI(人工智能),很多人的印象可能还停留在几年前“阿尔法狗”大展神威的场景,然而科学家的目标绝不是“人-机”对抗,而是要让人工智能更好地服务人类。AI有一项重要的能力,就是预测。这项能力在这部《AI极简经济学》里得到了充分的阐述。 该书由三位作者合作,阿杰伊...  

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从经济学的角度谈AI应该从何谈起?没有分析投入产出比,没有分析AI对经济学运作模式的颠覆和改变,也没有AI的经济学模型,只不过是几位经济学家对AI的思考。 当然还是非常有独到的观点和启发的,首先是关于人工智能现阶段的本质,作者提出的是预测,在人工智能沉寂30年后本轮趋...  

用戶評價

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準備再看一遍中文版…

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Cheap predictions for decision making and strategic adjustment under uncertainty & to increase productivity (automation)

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這本書完全不是給經濟學人寫的,常常提到的是如果你的公司想用ai應該什麼時候用,怎樣用。一半棄,對我來說沒大有收獲。

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沒有什麼特彆深刻的觀點。an overall disappointing read...

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沒有什麼特彆深刻的觀點。an overall disappointing read...

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