预测机器
Prediction machines
Ajay Agrawal · 初版 2018 年
2人推荐
3位读者提及
3次提及
人工智能的概念——抢走饭碗的机器人、自动驾驶汽车以及自主管理型组织——牢牢抓住了人们的想象力，让身处其中、必须承担其后果的我们既感惊叹又觉不安。但如果事情其实并没有那么复杂呢？这三位知名经济学家指出，人工智能的真正功用在于降低预测的成本。而一旦你开始从成本的角度切入，便可运用一些成熟的经济学理论来拨开概念炒作的迷雾。对于所有管理者而言，恒久的挑战在于如何在不确定性下做出决策。而 AI 所带来的贡献
Hacker News 上怎么说
正在加载完整评论……
……《Trick Mirror: Reflections on Self-Delusion》https://www.amazon.com/Trick-Mirror-Self-Delusion-Jia-Tolent... 《Talking to Strangers: What We Should Know about the People We Don't Know》https://www.amazon.com/Talking-Strangers-Should-about-People... 《Prediction Machines: The Simple Economics of Artificial Intelligence》https://www.amazon.com/Prediction-Machines-Economics-Artific...
…Self-Delusion" https://www.amazon.com/Trick-Mirror-Self-Delusion-Jia-Tolent... "Talking to Strangers: What We Should Know about the People We Don't Know" https://www.amazon.com/Talking-Strangers-Should-about-People... "Prediction Machines: The Simple Economics of Artificial Intelligence" https://www.amazon.com/Prediction-Machines-Economics-Artific...
……Ben Macintyre。第 8 本，Jia Tolentino 的《Trick Mirror: Reflections on Self-Delusion》。第 9 本，Malcolm Gladwell 的《Talking to Strangers: What We Should Know about the People We Don't Know》。第 10 本，Ajay Agrawal、Joshua Gans 和 Avi Goldfarb 的《Prediction Machines: The Simple Economics of Artificial Intelligence》。
…Ben Macintyre. No. 8. "Trick Mirror: Reflections on Self-Delusion" by Jia Tolentino. No. 9. "Talking to Strangers: What We Should Know about the People We Don't Know" by Malcolm Gladwell. No. 10. "Prediction Machines: The Simple Economics of Artificial Intelligence," by Ajay Agrawal, Joshua Gans and Avi Goldfarb.
……数以千计招人的岗位根本不具备大部分这些条件。不过有一个小小的利好消息：Agrawal 等人在一本通俗读物《Prediction Machines》中总结了他们的理论，探讨 ML 将如何让预测变得便宜。这本书可预期的成功会有所帮助。基本上，它讲的是 ML 能做什么，通篇却没有涉及到任何具体的 ML 实现：它只是把 ML 视作一种关键支柱技术，就像搜索引擎、数字化……
…thousands of jobs looking for candidates don’t have most of that. There is a small piece of good news: Agrawal & al. summarised their theory on how ML will make predictions cheaper in a all-access book, Prediction Machines. The predictable success of that book will help. Basically, it tells about what ML does, without ever doing any ML at all: it just looks at how it’s a lynchpin technology, like search engine, digital…