The Deep Learning Revolution pdf epub mobi txt 电子书 下载 2025
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).
- 人工智能
- MIT
- AI
- learning
- Psychologia
- Deep
- 数学和计算机
- 2019
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.
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人工智能元年：2016？ 对于一个普通大众而言，2016无疑是人工智能元年：阿尔法狗（AlphaGO）对战韩国围棋界18次世界冠军获得者李世石。其后，2017年，阿尔法狗化生Master横扫网络围棋服务器，5月，阿尔法狗连胜柯洁三场。就从那个时候，我身边不少患有中年焦虑症的朋友又有了新...
评分智能来自于哪里，是设计而来，还是学习演化而来？这个问题可能不好回答，所以把它拆解为两个更容易回答的小问题。第一个是人类智能来自于哪里，是设计而来，还是学习演化而来？长期以来，宗教不断告诉人们，既然人是上帝等神秘力量造出来的，人的智能当然也是拜其所赐，这些强...
评分这是上周末刚刚拿到手的一本书，这是我看的最快的一本书，用了两天时间快速读完。这是一本超出我的知识面的书籍，还好作者思路清晰，让我能够简单理解这本书的最表层内容。学术部分直接忽略吧。（安慰一下自己，给自己一个博览群书的理由。如果你只读每个人都读的书，你也只能...
评分这是一本优秀的深度学习发展历程科普书！人工智能的历史说长不长，但说短也不短，上世纪五十年代至今，却历经一波三折！书中介绍了很多人工智能发展过程中的重要突破，一路坎坷到如今当下最火热的研究方向，离不开众多科研人员的孜孜探索。本书讲述了许多对今天深度学习发展有...
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"Neural nets are often too complex to explain their decisions in relatable terms, they can perpetuate social discrimination if trained on biased data, and they can be used for autonomous weapons that might become trigger-happy. Granted, humans are also opaque, unfair and ornery."
评分超级硬核的一本书，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。
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