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Terrence J. Sejnowski

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The Deep Learning Revolution (Mit Press) Hardcover – Illustrated, October 23, 2018

by Terrence J. Sejnowski (Author)

4.3 93 ratings

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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 enormous 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.

Print length

352 pages
Language

English
Publisher

The MIT Press
Publication date

October 23, 2018
Grade level

12 and up
Reading age

18 years and up
Dimensions

9.2 x 6.3 x 0.9 inches
ISBN-10

026203803X
ISBN-13

978-0262038034
See all details

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Editorial Reviews

Review

"Sejnowski’s book is part history lesson, part textbook and part memoir, with varying levels of accessibility. Those with an existing interest in the topic will be charmed and enlightened."
—The Washington Post

"The Deep Learning Revolution is an important and timely book, written by a gifted scientist at the cutting edge of the AI revolution."
—Nature

"If you're serious about deep learning, as either a researcher, practitioner or student, you should definitely consider consuming this book."
—InsideBigData

"Sejnowski, a pioneer in the study of learning algorithms, is the author of The Deep Learning Revolution. He argues that the hype about killer AI or robots making us obsolete ignores exciting possibilities happening in the fields of computer science and neuroscience, and what can happen when artificial intelligence meets human intelligence."
—The Verge

About the Author

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 is the author of The Deep Learning Revolution (MIT Press) and other books.

Product details

Publisher ‏ : ‎ The MIT Press; Illustrated edition (October 23, 2018)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 352 pages
ISBN-10 ‏ : ‎ 026203803X
ISBN-13 ‏ : ‎ 978-0262038034
Reading age ‏ : ‎ 18 years and up
Grade level ‏ : ‎ 12 and up
Item Weight ‏ : ‎ 1.8 pounds
Dimensions ‏ : ‎ 9.2 x 6.3 x 0.9 inches

Best Sellers Rank: #472,150 in Books (See Top 100 in Books)
- #81 in Computer Vision & Pattern Recognition
- #190 in Natural Language Processing (Books)
- #880 in Artificial Intelligence & Semantics

Customer Reviews:
4.3 93 ratings

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Terrence J. Sejnowski

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Dr. Terrence Sejnowski received his Ph.D. in physics from Princeton University and was a postdoctoral fellow in neurobiology at Harvard Medical School before joining the faculty at Johns Hopkins, where he was a Professor of Biophysics. He moved to La Jolla and now holds the Francis Crick Chair at The Salk Institute for Biological Studies and is also a Distinguished Professor at the University of California, San Diego, where he is a director of the Institute for Neural Computation. He is also the President of the Neural Information Processing Systems (NeurIPS) Foundation, which organizes an annual conference that was the incubator for deep learning and was attended by 26,000 researchers in 2020. He is a member of the National Academy of Sciences, the National Academy of Engineering, the National Academy of Medicine, and the National Academy of Inventors, one of only three living scientists elected to all four national academies.

Sejnowski pioneered learning algorithms for neural networks in the 1980s. He co-invented the Boltzmann with Geoffrey Hinton and developed Independent Component Analysis (ICA), a machine learning algorithm for blind source separation of mixed signals. His book, The Deep Learning Revolution, explores the origins of modern artificial intelligence and its convergence with discoveries in brain science. He also pioneered computational neuroscience and his book with Patricia Churchland, The Computational Brain, showed how distributed population activity in neural network models gives rise to behavior. His Massive Open Online Course (MOOC), Learning How to Learn with Barbara Oakley, is based on learning in brains and has been viewed by over 3 million learners in over 200 countries, and their new book, Uncommon Sense Teaching, is aimed at helping teachers navigate the complexities of two major learning systems in brains.

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4.3 out of 5

93 global ratings

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Jack

Pure Quality

Reviewed in the United States on September 17, 2019

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This book is fantastic. Terrence J. Sejnowski is a true omiscent individual. In this book, you will learn not just about the history and evolution of AI, ML and DL but you will understand the correlation between cognitive neuroscience and deep learning. It is written as a "hybrid" memoir. And although, I understand the concepts of which he writes about. The way he wrote this book is just so rich, and in depth that you appreciate his stories, and experience. That said, he goes over a great detail about deep learning, and provides great examples.

He does a wonderful of breaking down the hierarchy of Visual cortex from the retina and thalamus to the temporal cortex showing a correspondence between cortical areas and layers of a convolutional neural network. And how it compares from human biology to computational neural networks.

In this book you will learn not just about deep learning, but you will dive into cognitive neuroscience, neuroscience, and deep learning.

I loved every single page of this book. I even purchased the audio book. Incredible quality. Terrence is an amazing author and I am a huge fan.

2 people found this helpful

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Michael George

excellent perspective from one of the outstanding contributors to deep learning

Reviewed in the United States on November 13, 2018

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This book is a memoir. In addition, although the author does not explain or go into detail about about deep learning, he gives a good perspective on its development over the time of his career, and places it in a larger perspective. Despite not explaining or clarifying technical terms, theory and practical methods, his book is fairly enlightening, as he contributed in important ways to the field, and knew or worked with numerous researchers who contributed significantly. The book has numerous insightful remarks. He seems to have a very open mind, an enormous amount of curiosity, and a tremendous dedication. I recommend his book to achieve some perspective on this currently important field, which has much potential for contributing to many fields of study, and itself has been a multidisciplinary field. Deep learning seems to have acquired much more importance in recent years with the great progress that has been made in computers, in their computing power, miniaturization and success that deep learning has achieved in numerous specialized areas.

17 people found this helpful

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Frederick Zhou

Great Books about history and development of Deep Learning

Reviewed in the United States on December 25, 2018

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This is a great book for you to understand and appreciate the work of those scientists who contributed the success of today's machine learning approach to artificial intelligence.
I am a practitioner of mathematical modeling with different methods. I always believed the nature can and did give us a lot inspiration for scientific discovery and the neural network borrowed the idea from biological neural structure. But this book demonstrated how extensively our progress in neurobiology and artificial intelligence directly derived from biological study of organic structure.
Highly recommend this book for those who have a technical background to enjoy the anecdotes as "gossipy" in their spare time. For some topic you will enjoy more if you know the technical background.

6 people found this helpful

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Randolph Crawford

Beware. This is an academic memoir about neural net work, not deep learning.

Reviewed in the United States on December 28, 2018

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This book is NOT about deep learning principles or practice. Despite its titillating title, this is strictly a personal memoir which deals entirely in stories about past colleagues, students, and friends who worked with the author in developing rhe field of neural networks.

Since about 1980 Professor Terrence Sejnowski has worked with biologically inspired neural nets. However, his work is NOT notable for the theory behind or the development of today's deep learning algorithms that arose circa 2006. Thus this book consists wholly of a light historical introduction to most of the people who were active in the days of early NNs (since 1975), and Dr Sejnowski's kinship with them, but little beyond that.

The text explains none of the technical details of Dr Sejnowski's work, nor the work of other NN pioneers, nor does it offer any tangible predictions or insights into the likely implications of NNs, deep learning, or AI.

Frankly, titled as it is, this book was a HUGE disappointment to me. It doesn't delve into deep learning nor any other facet of artificial intelligence to any extent. Read it only if you want a breezy history of Dr. Sejnowski.

97 people found this helpful

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Douglas L. Tooley

Makes accessible the AI revolution.

Reviewed in the United States on January 1, 2019

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The Information Age will mature with AI. It is all not so simple as you might think. Sejnowski was a major shaper of this field and I’m not aware of anything better.

I’m still waiting for the Tao of AI, etc.

2 people found this helpful

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Alex

Excellent introduction to artificial intelligence

Reviewed in the United States on November 9, 2018

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Very interesting and insightful summary and history of artificial intelligence. I am also very impressed by the quality of the print book . The cover and pages are some of the best quality I have seen in a hardcover book.

3 people found this helpful

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S. E.

Very dry book, with a weird mix of some insightful and some boring chapters

Reviewed in the United States on February 19, 2022

First of all, as many reviewers noted as well, the title is very misleading. A significant portion of the book is a pure memoir with no relevance to deep learning (I would give 1 star to those sections since I didn't pick this book up for those sections). But to be fair, there were also some very insightful chapters talking about the development of deep learning and how it benefited from the scientific developments in biology.

Overall it's a 3 star for me. I think it's a book worth reading if you have an interest in the field. But if you are trying to learn about deep learning, etc., stay away from this book as you'll probably be traumatized.

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Amazon Customer

Warning.....Really Biased for his own Group of Buddies in the field

Reviewed in the United States on March 14, 2019

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How can someone who was this deeply involved with this whole process of AI development totally ignore others doing parallel work and pretend they are being objective and complete? I was wary as soon as I went to the index and looked for Jeff Hawkins (who in my estimation is way ahead of where Sejnowski and Hinton are in figuring out this theory) and....you guessed it not mentioned. So he has a competing lab, but still, you should cover competitors who are way ahead of you. Just a warning, this is not the whole story and a bit self-serving for Hinton and Sejnowski.

14 people found this helpful

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Cliente de Amazon

Interesante

Reviewed in Mexico on May 17, 2023

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Un libro que hace un recorrido resumido de la evolución de este tipo de modelos matemáticos. Interesante para motivar una profundización sobre el tema sobre todo por su aplicación en la inteligencia artificial, tan de moda en nuestros días. Recomendable

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Marilu

Excelente conteúdo

Reviewed in Brazil on February 8, 2020

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Bem completo e com explicações detalhadas.

One person found this helpful

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Andrew William Cox

Excellent Publication

Reviewed in the United Kingdom on April 20, 2019

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This is an excellent and thorough overview of the topic.

Jaromir Konecny

Freude beim Lesen

Reviewed in Germany on December 4, 2018

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Das lesbarste Buch über künstliche Intelligenz, das ich je gelesen habe. Die vielen persönlichen Bezüge des Autors zu Wissenschaftlern in der KI- aber auch Hirnforschung lockern das Buch schön auf und erlauben dem Leser viele unbekannte Einblicke in die Geschichte von künstlicher Intelligenz, aber auch das Informative über der Entwicklung und Anwendung von künstlichen neuronalen Netzen kommt nicht zu kurz. Wunderbar!

3 people found this helpful

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babylion

全く面白くなかった・・・

Reviewed in Japan on May 14, 2019

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文章の中に良いフレーズがあったりしますが，全体的に知的好奇心をくすぐるような書物ではありませんでした．

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