百科
这个词条暂时没有中文维基百科条目,下面是英文维基百科的内容(英文原文):
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World is a book by Pedro Domingos released in 2015. Domingos wrote the book in order to generate interest from people outside the field.
Overview
The book outlines five approaches of machine learning: inductive reasoning, connectionism, evolutionary computation, Bayes' theorem and analogical modelling. The author explains these tribes to the reader by referring to more understandable processes of logic, connections made in the brain, natural selection, probability and similarity judgments. Throughout the book, it is suggested that each different tribe has the potential to contribute to a unifying "master algorithm".
Towards the end of the book the author pictures a "master algorithm" in the near future, where machine learning algorithms asymptotically grow to a perfect understanding of how the world and people in it work. Although the algorithm doesn't yet exist, he briefly reviews his own invention of the Markov logic network.
In the media
In 2016 Bill Gates recommended the book, alongside Nick Bostrom's Superintelligence, as one of two books everyone should read to understand AI. In 2018 the book was noted to be on Chinese Communist Party general secretary Xi Jinping's bookshelf.
Reception
A computer science educator stated in Times Higher Education that the examples are clear and accessible. In contrast, The Economist agreed Domingos "does a good job" but complained that he "constantly invents metaphors that grate or confuse". Kirkus Reviews praised the book, stating that "Readers unfamiliar with logic and computer theory will have a difficult time, but those who persist will discover fascinating insights."
A New Scientist review called it "compelling but rather unquestioning".
以上文字摘自英文维基百科「The Master Algorithm」(去掉了参考文献等尾部小节),按 CC BY-SA 4.0 使用,作者为维基百科的各位编者。
资料卡
- 原题
- The Master Algorithm
- 原作语言
- 英语
- 首次出版
- 2015 年 9 月 22 日
- 首版出版社
- 基础书籍出版社
- 主题
- 人工智能
资料卡来自 Wikidata Q21428158(CC0),众包数据,个别字段可能不全。
