No recent scientific enterprise has been so alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. How intelligent are the best of today's AI programs? To what extent can we entrust them with decisions that affect our lives? How human-like do we expect them to become, and how soon do we need to worry about them surpassing ...
No recent scientific enterprise has been so alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. How intelligent are the best of today's AI programs? To what extent can we entrust them with decisions that affect our lives? How human-like do we expect them to become, and how soon do we need to worry about them surpassing us in most, if not all, human endeavours?
From leading AI researcher and award-winning author Melanie Mitchell comes a knowledgeable and captivating account of modern-day artificial intelligence. Flavoured with personal stories and a twist of humor, Artificial Intelligence illuminates the workings of machines that mimic human learning, perception, language, creativity and common sense. Weaving together advances in AI with cognitive science and philosophy, Mitchell probes the extent to which today's 'smart' machines can actually think or understand, and whether AI requires such elusive human qualities in order to be reliable, trustworthy and beneficial.
Artificial Intelligence: A Guide for Thinking Humans provides readers with an accessible, entertaining, and clear-eyed view of the AI landscape, what the field has actually accomplished, how much further it has to go, and what it means for all of our futures.
作者简介
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Melanie Mitchell is Davis Professor at the Santa Fe Institute and Professor of Computer Science at Portland State University. Melanie's book "Complexity: A Guided Tour" won the 2010 Phi Beta Kappa Science Book Award, was named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society's 2010 book prize. Her newest book is "Artificial In...
Melanie Mitchell is Davis Professor at the Santa Fe Institute and Professor of Computer Science at Portland State University. Melanie's book "Complexity: A Guided Tour" won the 2010 Phi Beta Kappa Science Book Award, was named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society's 2010 book prize. Her newest book is "Artificial Intelligence: A Guide for Thinking Humans".
Melanie originated the Santa Fe Institute's Complexity Explorer project, which offers free online courses related to complex systems. For more information, go to http://complexityexplorer.org.
接女朋友回家等她聚餐结束时一口气读两百页。作者主观论断过多，“我怀疑”的表述多次出现。这本书2019年出版，六年后的今天作者质疑或悲观的很多方面已得到解决，尤其是在“机器实现人类理解的能力”方面，以ChatGPT为代表的大语言多模态模型展现出非凡的语言理解和生成能力，能对人类的输入做出交互。大语言模型必然不是终点，重要因素之一就是作者所说缺乏常识决定大模型的上限。下一阶段模拟Theory of M...接女朋友回家等她聚餐结束时一口气读两百页。作者主观论断过多，“我怀疑”的表述多次出现。这本书2019年出版，六年后的今天作者质疑或悲观的很多方面已得到解决，尤其是在“机器实现人类理解的能力”方面，以ChatGPT为代表的大语言多模态模型展现出非凡的语言理解和生成能力，能对人类的输入做出交互。大语言模型必然不是终点，重要因素之一就是作者所说缺乏常识决定大模型的上限。下一阶段模拟Theory of Mind，实现自我-他人-世界的感知，接近杨立坤所言的世界模型。作者博客持续更新，延续本书最后一章“抽象和类比”的讨论。
对具身智能的态度有所转变：算法模拟再多次也比不上和真实世界的一次交互；人工智能系统要想获得类人或超人智能，就必须被赋予感官、在真实世界的交互中自主学习。(展开)
本书作者梅拉妮·米歇尔是波特兰州立大学计算机教授，也是科普畅销书《复杂》的作者，曾师从认知科学家、人工智能先驱和《GEB》的作者侯世达，且侯世达阅读并评论了本书手稿的每个章节。本书英文名《Artificial Intelligence: A Guide For Thinking Humans》翻译过来“人工智能...
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四川科学技术出版社·湛庐2021版
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四川科学技术出版社·湛庐2021版
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四川科学技术出版社·湛庐2021版
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四川科学技术出版社·湛庐2021版
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四川科学技术出版社·湛庐2021版
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四川科学技术出版社·湛庐2021版
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Farrar, Straus and Giroux2019版
李阿龙
四川科学技术出版社·湛庐2021版
1 有用 总是困的小谭 2023-09-20 14:50:18 澳大利亚
(paperback)
2 有用 Ov's Pianist 2021-06-14 08:10:34
AI令人恐惧的不是抢掉工作和称霸世界，那些都太远了，最可怕的是人类引以为豪的对艺术的创作可以被简单的算法所取代，导致我们丢掉对自我认知的信心。
0 有用 _adagio 2023-01-13 02:25:52 荷兰
不错的科普书
0 有用 已注销 2023-09-18 06:21:39 美国
至少三分之一根本读不懂！要补课了
0 有用 W 2025-04-14 08:14:53 英国
接女朋友回家等她聚餐结束时一口气读两百页。作者主观论断过多，“我怀疑”的表述多次出现。这本书2019年出版，六年后的今天作者质疑或悲观的很多方面已得到解决，尤其是在“机器实现人类理解的能力”方面，以ChatGPT为代表的大语言多模态模型展现出非凡的语言理解和生成能力，能对人类的输入做出交互。大语言模型必然不是终点，重要因素之一就是作者所说缺乏常识决定大模型的上限。下一阶段模拟Theory of M... 接女朋友回家等她聚餐结束时一口气读两百页。作者主观论断过多，“我怀疑”的表述多次出现。这本书2019年出版，六年后的今天作者质疑或悲观的很多方面已得到解决，尤其是在“机器实现人类理解的能力”方面，以ChatGPT为代表的大语言多模态模型展现出非凡的语言理解和生成能力，能对人类的输入做出交互。大语言模型必然不是终点，重要因素之一就是作者所说缺乏常识决定大模型的上限。下一阶段模拟Theory of Mind，实现自我-他人-世界的感知，接近杨立坤所言的世界模型。作者博客持续更新，延续本书最后一章“抽象和类比”的讨论。 对具身智能的态度有所转变：算法模拟再多次也比不上和真实世界的一次交互；人工智能系统要想获得类人或超人智能，就必须被赋予感官、在真实世界的交互中自主学习。 (展开)