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2025-02-02
The Deep Learning Revolution 2025 pdf epub mobi 电子书
作者是深度学习领域的领军人物,本书可以算是作者写的人工智能简史,涉及到作者参与的一些项目,作者跟许多业内知名科学家都有学术交往。 书中涉及到一些人工智能算法的基本原理,没学过高数、没有编程基础的读者恐怕是比较难看懂的。不过看不懂可以跳过去,至少一些学术发展的...
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...
评分作者是深度学习领域的领军人物,本书可以算是作者写的人工智能简史,涉及到作者参与的一些项目,作者跟许多业内知名科学家都有学术交往。 书中涉及到一些人工智能算法的基本原理,没学过高数、没有编程基础的读者恐怕是比较难看懂的。不过看不懂可以跳过去,至少一些学术发展的...
评分 评分作者是深度学习领域的领军人物,本书可以算是作者写的人工智能简史,涉及到作者参与的一些项目,作者跟许多业内知名科学家都有学术交往。 书中涉及到一些人工智能算法的基本原理,没学过高数、没有编程基础的读者恐怕是比较难看懂的。不过看不懂可以跳过去,至少一些学术发展的...
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.
Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.
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。
评分还可以
评分god damn crazy, wonderful articles!respect!
评分"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."
The Deep Learning Revolution 2025 pdf epub mobi 电子书