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).
发表于2025-04-08
The Deep Learning Revolution 2025 pdf epub mobi 电子书
看到王勇老师的朋友圈的推荐买了这本书,在人工智能深度学习领域炽热的今天读这本书倒比较应景,约汉森顿,杨卫坤和约书亚获得了2018年的图灵奖,为深度学习在人工领域的高潮添加了一颗明珠。作为和约汉森顿交流合作颇多的作者而言,出这本书颇合时宜。 去年读了一本人工智能诸...
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...
评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...
评分图书标签: 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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评分god damn crazy, wonderful articles!respect!
评分Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.
评分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。
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The Deep Learning Revolution 2025 pdf epub mobi 电子书