I love to read! I’m always reading… and most of all, I love to read about Artificial Intelligence.

我喜欢看书！ 我一直在阅读……最重要的是，我喜欢阅读有关人工智能的文章。

I want to share here some of my favorite AI books that surely will inspire you. These are great books for anyone who wants to get serious on AI algorithms and how we humans can relate to this topic today and in the future.

我想在这里分享一些我最喜欢的AI书，这些书肯定会给您带来启发。 对于那些想认真对待AI算法以及我们人类如何与现在和将来联系起来的人来说，这些书都是很棒的书。

《为什么》：因果关系新科学(The Book of Why: The New Science of Cause and Effect)

Written by the Chancellor’s professor of computer science and statistics at UCLA and Turing Award winner Judea Pearl and Dana Mackenzie, a Ph.D. mathematician turned science writer, has written for a variety of popular science magazine over the last 20 years, including New Scientist, Scientific American, and Discover.

由加州大学洛杉矶分校(UCLA)的计算机科学与统计大臣教授以及图灵奖获得者Judea Pearl和Dana Mackenzie撰写。 数学家转变为科学作家，在过去20年中为各种流行科学杂志撰写文章，包括《新科学家》，《科学美国人》和《发现》。

This book tells the story of science that has changed the way we distinguish facts from fiction, and yet has remained under the radar of the general public.

这本书讲述的科学故事改变了我们将事实与小说区分开的方式，但仍然受到了公众的关注。

“Correlation is not causation.” This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. What might sound like a reasonable assertion metastasized in the twentieth century into one of science’s biggest obstacles, as a legion of researchers became unwilling to claim that one thing could cause another? This all changed with Judea Pearl, whose work on causality was not just a victory for common sense, but a revolution in studying the world.

“关联不是因果关系。” 经过科学家一个多世纪的吟诵，这一口头禅实际上导致了因果关系的禁止。 在二十世纪，随着一大批研究人员不愿宣称某件事可能导致另一件事的发生，听起来像是一个合理的主张变成了科学的最大障碍之一？ 裘迪亚·珀尔(Judea Pearl)的一切都改变了，他的因果关系研究不仅是常识的胜利，而且是研究世界的一场革命。

The causal revolution, instigated in this book by Judea Pearl and his colleagues, has cut through a century of confusion and established causality — the study of cause and effect — on a firm scientific basis.

本书的作者朱迪亚·珀尔(Judea Pearl)和他的同事们鼓吹了因果关系革命，它克服了一个世纪的混乱，并在牢固的科学基础上确立了因果关系—研究因果关系。

Pearl’s work enables us to know not just whether one thing causes another: it lets us explore the world and the worlds that could have been.

Pearl的工作使我们不仅知道一件事是否会引起另一件事：它还使我们能够探索世界和本来可以的世界。

It shows us the essence of human thought and the key to artificial intelligence, and if you want to understand it more in-depth, you need to read The Book of Why.

它向我们展示了人类思想的本质和人工智能的关键，如果您想更深入地理解它，则需要阅读《为什么》 。

如何建立思想：揭示人类思想的秘密(How to Create a Mind: The Secret of Human Thought Revealed)

Ray Kurzweil, an inventor, and futurist who has published books on health, artificial intelligence, transhumanism, and the technological singularity, is arguably today’s most influential and often controversial futurist.

雷·库兹韦尔( Ray Kurzweil )是发明家和未来主义者，他出版了有关健康，人工智能，超人类主义和技术奇异性的书籍，可以说是当今最有影响力且经常引起争议的未来主义者。

In How to Create a Mind, Kurzweil presents a provocative exploration of the most critical project in human-machine civilization — reverse-engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.

在《如何创造思维》中，库兹韦尔对人类机器文明中最关键的项目进行了一次挑衅性的探索，即对大脑进行逆向工程以精确地了解其工作原理，并利用这些知识来制造更智能的机器。

Kurzweil discusses how the brain functions, how the mind emerges from the brain, and the implications of vastly increasing the powers of our intelligence in addressing the world’s problems. He thoughtfully examines emotional and moral intelligence and the origins of consciousness. The author envisions the radical possibilities of our merging with the intelligent technology we are creating.

库兹韦尔(Kurzweil)讨论了大脑如何运作，大脑如何出现思维，以及在解决世界问题方面极大提高我们的智力力量的含义。 他若有所思地检查了情绪和道德智力以及意识的起源。 作者设想了我们与正在创建的智能技术合并的根本可能性。

Sure to be one of the most widely discussed and debated science books of the year, How to Create a Mind is sure to take its place alongside Kurzweil’s previous classics, which include Fantastic Voyage: Live Long Enough to Live Forever and The Age of Spiritual Machines

当然，《如何创造一个心灵》一定会成为库兹韦尔以前的经典著作，包括《神奇的航程：活得足够长，能永远活到永远》和《精神机器的时代》，肯定会成为当年最受讨论和辩论的科学书籍之一。

Life 3.0：在人工智能时代成为人类 (Life 3.0: Being Human in the Age of Artificial Intelligence)

How will Artificial Intelligence affect crime, war, justice, jobs, society, and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology — and there’s nobody better qualified or situated to explore that future than Max Tegmark, a Swedish-American physicist and cosmologist. He is a professor at the Massachusetts Institute of Technology and the scientific director of the Foundational Questions Institute.

人工智能将如何影响犯罪，战争，正义，工作，社会以及我们的人文意识？ 人工智能的兴起比任何其他技术都有更大的潜力改变我们的未来，而且没有人比瑞典裔美国物理学家和宇宙学家Max Tegmark更有资格或有条件探索这个未来。 他是麻省理工学院的教授和基础问题研究所的科学主任。

This book empowers you to join what may be the most important conversation of our time. It doesn’t shy away from the full range of viewpoints or the most controversial issues — from superintelligence to meaning, consciousness, and the ultimate physical limits on life in the cosmos.

这本书使您能够加入我们时代最重要的对话。 它并没有回避所有观点或最有争议的问题-从超级智能到意义，意识以及对宇宙生命的最终物理限制。

情感机器：常识性思维，人工智能和人类心灵的未来(The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind)

Our minds are working all the time, but we rarely stop to think about how they work.

我们的思想一直在工作，但是我们很少停止思考它们是如何工作的。

The author, Marvin Lee Minsky (born August 9, 1927, died January 24, 2016), was an American cognitive scientist in artificial intelligence (AI), co-founder of Massachusetts Institute of Technology’s AI laboratory, and author of several texts on AI and philosophy.

作者Marvin Lee Minsky (生于1927年8月9日，去世于2016年1月24日)，是美国人工智能(AI)认知科学家，麻省理工学院AI实验室的共同创始人，以及多篇有关AI的著作的作者和哲学。

The human mind has many different ways to think, said Marvin Minsky, the leading figure in artificial intelligence and computer science. We use these different ways of thinking in other circumstances, and some of them don’t even associate with thinking.

人工智能和计算机科学领域的领先人物Maven·明斯基(Marvin Minsky)表示，人的思维方式有很多不同。 在其他情况下，我们使用这些不同的思维方式，其中有些甚至与思维无关。

“The Emotion Machine” explains how our minds work, how they progress from simple kinds of thought to more complex forms that enable us to reflect on ourselves — what most people refer to as consciousness, or self-awareness.

“情感机器”解释了我们的思想是如何工作的，它们是如何从简单的思想发展为更复杂的形式的，这些形式使我们能够反思自己-大多数人所说的意识或自我意识。

Once we know thinking, we can build machines — artificial intelligence — that can assist with our thinking, machines that can follow the same thinking patterns that we follow, and think as we do. These humanlike thinking machines would also be emotion machines — just as we are.

一旦我们知道了思维，我们就可以制造可以帮助我们思考的机器-人工智能，可以遵循我们遵循的相同思维模式并像我们所做的那样思考的机器。 就像我们一样，这些类似于人类的思维机器也将成为情感机器。

This is a brilliant book that challenges many ideas about thinking and the mind. It is as insightful and provocative as it is original, the fruit of a lifetime spent thinking about thinking.

这是一本精彩的书，它挑战了有关思维和思维的许多观念。 它与原始语言一样具有洞察力和挑衅性，是一生思考的成果。

人工智能：一种现代方法 (Artificial Intelligence: A Modern Approach)

The long-anticipated revision of this best-selling book by Stuart Russell, Professor of Computer Science and Smith-Zadeh Professor in Engineering, University of California, Berkeley and Honorary Fellow, Wadham College, Oxford and Peter Norvig, Director of Research at Google, offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.

加州大学伯克利分校计算机科学教授Stuart Russell和工程学教授Smith-Zadeh以及牛津大学沃德姆学院名誉院士和Google研究总监Peter Norvig对这本畅销书进行了长期期待的修订，提供有关人工智能理论和实践的最全面，最新的介绍。

The book is as close to exhaustive as is currently available in the field, including in-depth treatments of non-technical learning material while providing an accessible and understandable overview of significant concepts.

该书与该领域目前可用的书一样详尽，包括对非技术学习资料的深入处理，同时提供了对重要概念的易于理解的理解。

Since the 2003 edition, increased coverage has been given to topics such as constraint satisfaction, local search planning methods, multi-agent systems, game theory, statistical natural language processing, and uncertain reasoning over time.

自2003年版以来，越来越多的主题涉及诸如约束满足，本地搜索计划方法，多主体系统，博弈论，统计自然语言处理以及不确定的推理等主题。

Attention has also been given to providing more detailed descriptions of algorithms for probabilistic inference, fast propositional inference, probabilistic learning approaches including EM, and other topics.

还已经提供了对概率推理，快速命题推理，包括EM在内的概率学习方法以及其他主题的算法的更详细描述。

The comprehensive, up-to-date coverage includes a unified view of the field organized around the rational decision-making paradigm.

全面，最新的报道包括围绕理性决策范式组织的领域的统一视图。

The authors’ approach delivers in-depth coverage of basic and advanced topics. It provides a basic understanding of the frontiers of AI without compromising complexity or depth.

作者的方法深入介绍了基本主题和高级主题。 它提供了对AI前沿的基本了解，而不会影响复杂性或深度。

It conveys an in-depth understanding and a clear explanation of such concepts as supervised and unsupervised machine learning. Thus, to the layman, a sense of why there will be no jobs for machine learning supervisors!

它传达了对有监督和无监督机器学习等概念的深入理解和清晰解释。 因此，对于外行来说，这就是为什么为什么机器学习主管将没有工作的原因！

It is highly recommended. Intellectually, Artificial Intelligence: A Modern Approach provides both a conceptual artificial intelligence gym and a running track to limber upon. The more you use it, the more you will get from it.

强烈建议。 从智力上讲，人工智能：一种现代方法既提供了概念性的人工智能健身房，又提供了一条可以继续前进的跑道。 您使用它的次数越多，您将获得的收益越多。

结论 (Conclusion)

These five masterpieces are not just good AI books, but I would consider them some of the most exciting and thoughtfully structured textbooks I’ve seen on this subject.

这五个杰作不仅是好的AI书籍，而且我认为它们是我在该主题上见过的最激动人心且结构合理的一些教科书。

They present useful information about particular aspects of AI while providing fascinating historical background.

他们提供有关AI特定方面的有用信息，同时提供迷人的历史背景。

I always think that people, especially in the scientific and engineering society, underestimate the importance of simple explanations of difficult concepts, especially concerning people that are new in the field; these books help on making difficult concepts seem not so difficult!

我一直认为，人们，特别是科学和工程社会的人们，低估了对困难概念进行简单解释的重要性，尤其是对于本领域的新​​手而言。 这些书有助于使困难的概念看起来并不那么困难！

Disclaimer: I do not receive any money from the authors or editors or have any direct relationship with anyone. Mine are simple indications based on my positive learning experience through their excellent books.

免责声明：我没有从作者或编辑那里得到任何钱，也没有与任何人有直接关系。 根据我通过出色的书本所获得的积极的学习经验，这些都是简单的指示。