圖書標籤: 人工智能 MIT AI learning Psychologia Deep 數學和計算機 2019
发表于2024-06-21
The Deep Learning Revolution pdf epub mobi txt 電子書 下載 2024
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.
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).
"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."
評分"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."
評分Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.
評分Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.
評分"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."
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...
評分多年前看世界特色建筑就知道了索尔克研究所,几何线条的极简设计,院子直通太平洋,那时候觉得这样的建筑有点不接地气,但其实对一些科学家来说那就是他们日常上班的地方。 读到的这本《深度学习》就是在索尔克研究所的美国“四院院士”对人工智能的介绍,从大众熟知的阿尔法狗...
評分 評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...
評分人工智能元年: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...
The Deep Learning Revolution pdf epub mobi txt 電子書 下載 2024