Goodreads helps you keep track of books you want to read.
Start by marking “The Deep Learning Revolution (The MIT Press)” as Want to Read:
The Deep Learning Revolution (The MIT Press)
Enlarge cover
Rate this book
Clear rating
Open Preview

The Deep Learning Revolution (The MIT Press)

3.76  ·  Rating details ·  248 ratings  ·  36 reviews

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 Exch

Kindle Edition, 352 pages
Published September 28th 2018 by The MIT Press
More Details... Edit Details

Friend Reviews

To see what your friends thought of this book, please sign up.

Reader Q&A

To ask other readers questions about The Deep Learning Revolution, please sign up.

Be the first to ask a question about The Deep Learning Revolution

This book is not yet featured on Listopia. Add this book to your favorite list »

Community Reviews

Showing 1-30
Average rating 3.76  · 
Rating details
 ·  248 ratings  ·  36 reviews

More filters
Sort order
Start your review of The Deep Learning Revolution (The MIT Press)
Dec 21, 2018 rated it did not like it  ·  review of another edition
Shelves: quit-reading
This book is NOT about deep learning. Despite its grand title, this book is strictly a memoir.

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 deep neural nets (AKA deep learning). As such, this book consists of a very lightweight historical introduction to some of the people who were active in the early days of NNs, and Dr Sejnowski's kinship with them, but little more.

Apr 04, 2019 rated it really liked it  ·  review of another edition
I disagree with the other reviews that state this is purely a 'memoir.' It is more than that.
Terry describes the evolution of neural networks and the personalities that helped the field along the way. He was a part of it, hence the 'memior' theme, but goes beyond his own contributions and neatly outlines the evolution of the idea from both personnel and theoretical perspectives. This won't teach you how to perform deep learning, but will help you understand how we got to where we are today.
William Boyle
This book is not about deep learning. You'll learn more about how the eye works than anything else.. was interesting, just not really even remotely what I was expecting given the title...
Oct 20, 2018 rated it really liked it  ·  review of another edition
4.5/5. Good book with many historical details. The author is clearly at the forefront of research and I liked that he gives references (up to 2017). But I wish there would be more details in places. I am aware that this book is not a textbook but I wish the Sejnowski would provide more technical details. As a bird eyes view however, I highly recommend the book to everyone who is interested in neural networks and the deep learning revolution. It whet my appetite for more (I think I will pick up h ...more
Peter (Pete) Mcloughlin
Once you get past the beginning with the techno-libertarian boosterism there lies a fascinating history of the development of artificial intelligence from the days of Turing to the present. This is a good history and tech primer of this key topic. You don't have to swallow the hype to be interested in the very real progress in the field. Good stuff.
Bouga Bougi
Jan 16, 2019 rated it did not like it  ·  review of another edition
Half of this book consists of Sejnowski flattering himself, the rest of the content is poorly explained. I learned nothing from this book that I did not already learn from much easier readings. This book is nothing but a waist of paper.
Mar 21, 2020 rated it really liked it  ·  review of another edition
Deep learning is a term you hear nowadays, a lot if you are working in the computer industry. Artificial intelligence, Neural networks, Machine learning, Big Data Analytics are some other terms we come across, particularly so if you live in Silicon Valley. For the non-computer person, it can all be confusing to sort out what each of these concepts means and how they impact our lives. I have had a reasonable interest in Artificial Intelligence ever since I saw Stanley Kubrick’s film, ‘2001: A Spa ...more
Mar 05, 2019 rated it it was amazing  ·  review of another edition
This is one of the best scientific biographies I have ever read. It is short. It is full of insights. It tells an interesting story. It presents both the man and his friends. It explains what this revolution is all about. The only two problems: (i) the revolution is still ongoing; (ii) sometimes the author skips years making me wonder what happened within those time periods. Even with all these shortcomings it is still in the same league with Eric Kandel and other great scientific writers. Here' ...more
Chris Esposo
Jul 12, 2020 rated it it was amazing  ·  review of another edition
This is an excellent personal history of the development of neural networks as a subdiscipline of AI in the 80s, to their current incarnation, as a mainline area of practical and theoretical machine learning (and AI), which in a real way, driving much of the growth-in-value of the field both academically and in real-dollar terms in business, for the past decade or so. The author is a contemporary of Hinton, and has collaborated with him several times in the early days of the field in the 80s an ...more
Dec 12, 2018 rated it really liked it  ·  review of another edition
Terry Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies in La Jolla, California. He has been at the forefront of neuroscience, the understanding of neural networks and their application in the development of artificial intelligence for the past 30 years. His book is both an enlightening history of this subject and a semi-autobiographical journey of his role and the roles of the other leading participants in this exciting and ground breaking journey in science a ...more
Feb 07, 2019 rated it liked it  ·  review of another edition
I wanted to continue reading about deep learning research since much of our society uses this technology today. We use it now in our smart phones, retinal scans, self driving cars, face scanning at airports, etc. and its use will only increase. This technology will expand into the financial, medical and judicial areas in the next 10-20 years. How much they expand will be determined by how free people want to be with their own personal information. However, by combining deep learning in medicine, ...more
Ozan Erdem
Feb 09, 2020 rated it really liked it  ·  review of another edition
This was an interesting read about the history of deep learning, from one of the significant influencers of the field. If you know nothing about deep learning and looking for an introductory book, this is not a good one to start with.

Even though it doesn't contain much technical detail, it has good references to many foundational works in neural networks/deep learning. Sometimes it feels like the narrative is too focused on mimicking human brain, whereas I believe the modern interpretation of de
Brad Garton
Jun 17, 2019 rated it it was amazing  ·  review of another edition
I really enjoyed this book! It's an overview of the history of Deep Learning and how it relates to cognitive science, and AI from one of the early practitioners. It covers progress in Neural Network based Deep learning and future research areas. It does a lot of name dropping, of people who were significant in past research and important papers written in the field that have had significant impact on current and past research. This is not a HOW TO book for deep learning, which I gather from some ...more
Kaustubh Sule
Oct 23, 2020 rated it it was amazing  ·  review of another edition
This is book is for those who have started exploring applications of ML and AI in their own field and want a Top down perspective of what exactly is deep learning and how does it help in real world applications.

No Mathematics involved although a broad understanding of probability is required in some sections . This book explains origins of deep learning from author’s perspective and how it is fundamentally different from logical programming from which computer science evolved in 1950 to 2000.

Jan 22, 2020 rated it really liked it  ·  review of another edition
Beautiful book. It guides the reader through the history of Artificial Intelligence. From the first mathematical approaches to the modern deep learning algorithms, mixed with personal anecdotes from the author, who is an important/key figure in the history of AI.
The book emphasizes the relationship between cognitive neurosciences, mathematical algorithms, computing technology and how these three enabled the modern AI revolution.

A very good read, I highly recommend but bear in mind that it is a m
May 21, 2019 rated it really liked it  ·  review of another edition
This is an extraordinary low-effort book, but still well worth your while. It is a loose and quick history of the network schools of machine learning, blended with random anecdotes and opinions put together in such a way that it feels more like reading Dr. Sejnowski's livejournal page than a book.

Nevertheless, this is Terrence Sejnowski's. His livejournal posts are worth more than most people's books, because a small droplet of his thinking and experience distills a great deal of value.
Mariusz Bidelski
The parts that are technical I find too difficult for a novice in the field - maybe because the topics covered are glossed over and kept short to make room for the autobiographic part of the book. Which is interesting in it’s own way, but a bit too dense in names, dates of conferences and anecdotes.
Jul 31, 2019 rated it really liked it  ·  review of another edition
Shelves: computer-science
Solid intro to deep learning. I'd definitely lose the thread the deeper he went into neuroscience but still really entertaining and it gave me a good framework to think about the kinds of problems deep learning solves.
Rangaprabhu Parthasarathy
There is a lot of good information in this book. But it is marred by the author talking so much about his achievements and how he was part of every aspect of this DL revolution that takes a lot away from the book.
Matt Swaffer
Aug 17, 2020 rated it it was amazing  ·  review of another edition
Absolute must-read for anyone interested in the field of artificial intelligence. Excellent technical explanations mixed with a well-told history of the field in general and of deep learning specifically.
Ken Hamner
Feb 27, 2019 rated it it was amazing  ·  review of another edition
Very well written and informative book. Highly recommended.
Apr 02, 2019 rated it liked it  ·  review of another edition
Good for an overview for history, concepts, etc.
This book doesn't explain the math behind any theory though. It just talks about their history, implications, problems, etc.
Guy Aridor
Apr 09, 2019 rated it really liked it  ·  review of another edition
One of those books that is less about the subject but more about a personal memoir from a towering figure in the field about the field as it progressed over time. Enjoyed it a lot!
Ami Iida
Jul 30, 2019 rated it really liked it  ·  review of another edition
Shelves: ai
deeplearning,machine learning,GANs etc.....
An index of who is who in the field. A great historical review but some background knowledge is needed
Interesting review of the biological and physical origins of neural networks. A good amount of stuff went right over my head.
Bryant Macy
Really interesting survey of research from life sciences, mathematics and AI.
Andrei Nutas
Jan 10, 2020 rated it really liked it  ·  review of another edition
An excellent book for anyone that wants to gain a historic understanding about the field of AI, the people that helped make it a reality and the challenges they faced.
Feb 24, 2020 rated it it was ok  ·  review of another edition
Shelves: non-fiction
Good historical survey in some ways but too much name-dropping of people and where they got their degrees.
天天 拿大熊
Oct 05, 2020 rated it did not like it  ·  review of another edition
Do not expect too much from this book.
« previous 1 next »
There are no discussion topics on this book yet. Be the first to start one »

Readers also enjoyed

  • The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity
  • Human Compatible: Artificial Intelligence and the Problem of Control
  • AI Superpowers: China, Silicon Valley, and the New World Order
  • How Smart Machines Think
  • The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
  • Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
  • Machine Learning
  • Life 3.0: Being Human in the Age of Artificial Intelligence
  • The Sentient Machine: The Coming Age of Artificial Intelligence
  • Possible Minds: 25 Ways of Looking at AI
  • The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity
  • Human + Machine: Reimagining Work in the Age of AI
  • Digital Transformation: Survive and Thrive in an Era of Mass Extinction
  • AIQ: How People and Machines Are Smarter Together
  • Infinite Powers: How Calculus Reveals the Secrets of the Universe
  • The Book of Why: The New Science of Cause and Effect
  • Artificial Intelligence For Dummies
See similar books…

Goodreads is hiring!

If you like books and love to build cool products, we may be looking for you.
Learn more »
Terrence Joseph Sejnowski is an Investigator at the Howard Hughes Medical Institute and is the Francis Crick Professor at The Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory. His research in neural networks and computational neuroscience has been pioneering.
Sejnowski is also Professor of Biological Sciences and Adjunct Professor in the Departments o

Related Articles

San Francisco is a gold rush town. There aren’t many books about people in their 20s who move to Silicon Valley with dreams of earning a living...
34 likes · 2 comments
“It’s All about Scaling Most of the current learning algorithms were discovered more than twenty-five years ago, so why did it take so long for them to have an impact on the real world? With the computers and labeled data that were available to researchers in the 1980s, it was only possible to demonstrate proof of principle on toy problems. Despite some promising results, we did not know how well network learning and performance would scale as the number of units and connections increased to match the complexity of real-world problems. Most algorithms in AI scale badly and never went beyond solving toy problems. We now know that neural network learning scales well and that performance continues to increase with the size of the network and the number of layers. Backprop, in particular, scales extremely well. Should we be surprised? The cerebral cortex is a mammalian invention that mushroomed in primates and especially in humans. And as it expanded, more capacity became available and more layers were added in association areas for higher-order representations. There are few complex systems that scale this well. The Internet is one of the few engineered systems whose size has also been scaled up by a million times. The Internet evolved once the protocols were established for communicating packets, much like the genetic code for DNA made it possible for cells to evolve. Training many deep learning networks with the same set of data results in a large number of different networks that have roughly the same average level of performance.” 0 likes
More quotes…