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
发表于2024-09-09
Prediction Machines pdf epub mobi txt 电子书 下载 2024
"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.
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.
AI has entered our life. Willing to learn what it can really help us and what damage it can bring as well.
评分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。
评分经济学家在tech究竟有什么贡献呢。。觉得需要体验一下才知道了。目前觉得添乱比贡献多。。
评分没有什么特别深刻的观点。an overall disappointing read...
评分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。
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...
评分相对于人工智能而言,人类的问题,除了感知过于灵敏,恐怕还有因为种种自身的原因限制所以容易“反馈的不及时”吧。所以,尽管各类还处在开放状态中的人工智能至今依旧存在许多问题和困境,其中也有了AlphaGo成功地击败了人类最优秀棋手的例子。更多的人则是在这个容易焦虑的时...
评分主要内容是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,【】...
评分从经济学的角度谈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...
评分随着人工智能的发展,预测成本的下降意味着随处可见,将会降低替代品的价值的同时,增加互补品的价值,包括判断、行动和数据。 人类会被挤出局吗? 人工智能当前的进步浪潮带给我们的不是智能,而是智能的一个关键组成部分,预测。预测依赖于数据,这就意味着人类比机器有两点...
Prediction Machines pdf epub mobi txt 电子书 下载 2024