出版社: MIT
出版年: 2018-6-22
页数: 280
定价: $27.95
装帧: Hardcover
ISBN: 9780262038034
内容简介 · · · · · ·
How deep learning -- from Google Translate to driverless cars to personal cognitive assistants -- is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormus profits from automated trading on the New York Stock Exchang...
How deep learning -- from Google Translate to driverless cars to personal cognitive assistants -- is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormus profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
作者简介 · · · · · ·
Terrence J. Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies and is a Distinguished Professor at the University of California, San Diego. He was a member of the advisory committee for the Obama administration's BRAIN initiative and is President of the Neural Information Processing (NIPS) Foundation. He has published twelve books, including (w...
Terrence J. Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies and is a Distinguished Professor at the University of California, San Diego. He was a member of the advisory committee for the Obama administration's BRAIN initiative and is President of the Neural Information Processing (NIPS) Foundation. He has published twelve books, including (with Patricia Churchland) The Computational Brain (25th Anniversary Edition, MIT Press).
原文摘录 · · · · · ·
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The Deep Learning Revolution的书评 · · · · · · ( 全部 18 条 )
这本书很硬,但我终于弄懂了:人工智能之道在于道法自然
深度学习的哲学基础和成长之路
这篇书评可能有关键情节透露
深度学习的哲学基础和三次革命 深度学习(神经网络)的轮回大概是30年一次,在1950年代的雏形形成、1980年代的算法突破之后,我们在2010年代迎来了深度学习的第三次革命。 说这番话的不是别人,正是杰弗里·辛顿齐名的特伦斯·谢诺夫斯基,美国的杰出科学家,一位神经网络的先... (展开)三月读书笔记《深度学习》
回到未来:人工智能是不是潘多拉之盒?
深度学习神经网络和物联网
> 更多书评 18篇
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中信出版社 (2019)7.5分 736人读过
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订阅关于The Deep Learning Revolution的评论:
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1 有用 綦 2020-01-23 09:10:13
Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.
0 有用 读书看电影 2024-02-01 03:41:54 美国
作者真的是博学多才
0 有用 飞儿 2020-07-28 12:23:21
更像是科普读物
2 有用 Nova 2019-02-10 13:11:45
与其说这本书回顾了半个多世纪来深度学习的发展,不如说这是一本深度学习和脑神经科学的科普书。深度学习涉及的每个领域基本都介绍了,当然部分章节不是特别深入,比如第十七章关于 NLP 的内容。总体来说,是一本非常棒的科普书,适合快速了解 AI 再过去半个多世纪的发展历程。读完再也不会被一知半解的媒体忽悠了。
0 有用 未 Siri 2019-03-02 16:37:02
还可以
0 有用 读书看电影 2024-02-01 03:41:54 美国
作者真的是博学多才
0 有用 飞儿 2020-07-28 12:23:21
更像是科普读物
1 有用 Östrom 2020-02-05 11:59:05
超级硬核的一本书,作者是一个转行Neuroscience关注AI领域的物理学家,主要介绍Neuroscience和Deeplearning结合的几个研究领域,虽然有几个算法还有芯片那一部分没特别弄懂,但是总体来说非常开阔眼界,获得新知。“Nature/ evolution is cleverer than we are”,AI发展获得巨大进步主要还是依靠研究大脑的工作原理,从而进行算法模拟,真道法... 超级硬核的一本书,作者是一个转行Neuroscience关注AI领域的物理学家,主要介绍Neuroscience和Deeplearning结合的几个研究领域,虽然有几个算法还有芯片那一部分没特别弄懂,但是总体来说非常开阔眼界,获得新知。“Nature/ evolution is cleverer than we are”,AI发展获得巨大进步主要还是依靠研究大脑的工作原理,从而进行算法模拟,真道法自然。看完之后对brain function 好上头。 (展开)
1 有用 綦 2020-01-23 09:10:13
Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.
1 有用 Vollon 2019-11-15 15:17:17
god damn crazy, wonderful articles!respect!