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Rebooting AI: Building Artificial Intelligence We Can Trust

3.84  ·  Rating details ·  727 ratings  ·  104 reviews
Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust AI.

Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we are led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the foref
Hardcover, 288 pages
Published September 10th 2019 by Pantheon Books
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Average rating 3.84  · 
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Aug 04, 2019 rated it liked it
Shelves: non-fiction, tech
The central thesis of this book is that AI is not good enough. It is much closer to basic statistical inference than something that understands the world like a human. However, this is really all the authors needed. A short OpEd would be just as valuable as writing a 200-page book.

They have a lot of examples, which do advance their point, but it makes the writing feel repetitive. Yes, AI today cannot understand the implied points of a sentence. However, they then end up providing a bunch of simi
Dec 06, 2019 rated it it was amazing
I've read a lot of books on AI and the future of tech and economics in general and this is by far the most mature and sober. It's not a downer like some of the books that are all "everything that is capitalism is bad" but it's also not a breathless "AI and tech will save us and change everything." AI is really good at a few things--like playing Go, Jeopardy, finding facts, sorting, etc etc. But it's really bad at all the things that humans basically learn by the time they turn 5--like common sen ...more
Joy D
This book takes a look at the current state of development of Artificial Intelligence (AI). As one would expect, it is laid out in a logical manner. It traces the history of AI and what has (and has not) been achieved to date. The authors believe that AI is not as far advanced as many people believe, primarily due to a tendency for published articles and headlines to exaggerate accomplishments. A major premise is that AI needs to be trustworthy and safe, and currently falls short of this goal. A ...more
Scott Wozniak
Dec 14, 2020 rated it it was amazing
This book had a masterful balance of possible growth and realistic limits. It got technical enough to be specific but not so much that it got dry. Best AI book I’ve read yet.
Nestor Rychtyckyj
Nov 11, 2019 rated it it was amazing
This well-written and very accessible book by Gary Marcus and Ernest Davis should be required reading for anybody that is overwhelmed by the current boom (and hype) in Artificial Intelligence (AI). For most people - the term AI is referring exclusively to Deep Learning and ignoring all of the other significant work that is going on in the area. When every product from golf clubs to vacuum cleaners is now advertised as being “powered by AI”, perhaps it’s time to step back and take a look at where ...more
Nov 13, 2019 rated it liked it
Shelves: non-fiction
The first part of this book, covering the limits of current AI research, was quite solid. The number of examples might be a bit excessive, but it helped show me that I've fallen victim to the tendency to make assumptions about rates of progress. The book was worth it for this part.

Unfortunately, the book doesn't have much to offer in terms of solutions despite spending a large number of pages on it. There's no point in saying that AI would be better if we could solve extremely complex problems,
Jul 02, 2022 rated it liked it
Shelves: t_technology, t_brain
Rating: 3.5

This book took me way too long to read, the only thing that slightly redeemed the endless repetition was the cheeky jokes.

You'd think that a book praising the human mind for its ability to make inferences would shut the fuck up once and a while and let the reader infer -_-

Writing aside, I liked the information. It wasn't life changing but I especially liked the last chapter about applying good engineering practices to AI.

This book could've been an article except for all of the exam
Jan 29, 2021 rated it did not like it  ·  review of another edition
Video recognition is too narrow and negation in language is too difficult for word embedding-based methods to understand, and the authors are mad at this. They expect more and conclude everyone is working in the wrong direction.

This is a very annoying book. The authors seem to be mad at machine learning researchers for not working on the problems they bring to the table, for each of which they shallowly show how complex they are by referring to existing work (yes, of people working on said prob
Harsha Kokel
Aug 08, 2020 rated it really liked it
Shelves: recommend
This book is written for lay audience who tend to get carried away by impressive headlines. It is a tale of caution to not get excited by the current progress in AI and communicate the research at its scale; not make an exorbitant story out of it. This is important. Not only news articles but even research paper titles have seen a trend to make bold statements, but proving very little. So this book is a great reminder to call a spade a spade.

However, I think the tone of the book is a little sni
Aug 07, 2020 rated it liked it

The book is aimed at an audience of readers who are fascinated by the possibilities of AI but who are not technicians in the field. With this book, this reader is able not to be uninformed when reading blog articles on the subject.
The main point is that nowadays IA is not robust (i.e. it cannot be predicted when and to what extent it will go wrong) and for safety and security reasons it cannot be used in all areas (such as driving a car).


The authors analyze the state of the art of A
This is a nice, fairly short, introduction to the current limits to deep learning and AI. The authors point out how to watch for hype, explain where we actually are currently, and give suggestions on how we should approach making general AIs rather than the narrow AIs we currently have.

As somewhat of a skeptic when it comes to AI as it is now (I wouldn't trust a self-driving car right now), it is nice to see a comprehensive accounting for the problems AI now has while still acknowledging the ama
Yunke Xiang
Jan 06, 2020 rated it really liked it
This book tries to argue that we need some paradigm change for the current AI development. Instead of building machines that’s primarily fueled by big data and can handle specific tasks, we should have bolder vision and action and design machines that actually understands the world (have common sense, capable of reasoning).

The book has offered a lot of examples on where current AI long on promise but short on delivery. I enjoyed reading it because these are all most up to date examples from the
Overbooked  ✎
Disappointed by this book. Besides stating the obvious, it barely scratches the surface of the AI topic. If you have a good understanding of the subject and have read a few recent technical articles you are not likely to learn much new.

The authors highlight the limits of current AI research and development (predominantly based on deep learning) but they hardly add anything of value in terms of the direction that AI development should go instead. What this book proposes is a long term goal/vision
Jonathan Crabb
Nov 28, 2020 rated it it was amazing  ·  review of another edition
One of the best technology books that I have read in the past several years. Books related to technology tend to become out of date very quickly so I was happy to have picked this recent work up. The book does a very good job bringing the reader up to speed on the current state of AI and then explaining the nature of the current advances, both in its promise and its sever limitations. For the most part, this is done in very accessible language which most readers would be able to understand which ...more
Lucille E Nguyen
Aug 16, 2022 rated it liked it
Derivative work that draws from others. Generally acceptable for a non-specialist audience, but contains assertions about cognitive science and psychology regarding human intelligence vs. artificial intelligence that may prove short-sighted and premature.

Nonetheless, the prescriptions for how to view AI and how to implement them are the strongest points of the book, a welcome change from the typical over-hype of computational systems.
Filip Ilievski
May 24, 2020 rated it it was amazing
Brilliant storytelling and a balanced view of today's AI. As an AI researcher, this book was very suitable for me, though I expect it to be easy to follow by laymen too. I especially enjoyed the many examples throughout the book. The writing could be more compact, but I can leave with that ...more
Sep 02, 2020 rated it really liked it
Naturally I broadly agree with the call for symbolic knowledge representation, allowing mechanical reasoning, to be brought (back) to bear in combination with deep learning, which is inherently limited in statistical approximation of intelligence.
Jan 31, 2022 rated it really liked it
Shelves: books-i-have
Authors continues to debunk the hype around ML and AI, arguing that approach to IA must me changed, because general AI can not be reached with current methods. One can not reach the moon by climbing to slightly taller tree.

Book is not technical at all, good for novice.
Oct 22, 2022 rated it really liked it
Gives a fairly balanced view of the current state of AI.
An excellent summary of AI, intelligence, and considerations to safely harness the power
I enjoyed the author's logical flow in describing intelligence and what it means to solve a problem without creating one. There is no unnecessary fantasy or science fiction.

His problem definition is relevant to us today rather than being remote or under the realm of fiction.
Our current systems have nothing remotely like common sense, yet we increasingly rely on them. The real risk is not superintelligence,
Tom Satterthwaite
Feb 18, 2020 rated it really liked it
Provides great insight into the state of AI, how far it has come and how far it still has to go to attain the current levels of hype.
Ricardo Acuña
Nov 10, 2019 rated it really liked it  ·  review of another edition
Throughout the history, there are generally cycles that oscillate between the extremes of two dialectically opposed positions resulting in a new stage in the historical development of contraries. REBOOTING AI analyzes the current hype of the AI, and especially the "Deep Learning". The AI has reached such a point that it covers a good part of startup investments, technological developments, new products, and even politics. REBOOTING AI on this sense analyzes this current AI hype emphasizing that ...more
Oct 14, 2020 rated it liked it
(Spoiler free part)

The title is more telling than I first thought. The book is really about rebooting AI efforts, implying reconsidering 60 years of AI, and correcting the arguably poor direction of the Deep Learning-focused field/industry now. The authors do a very good job, going all the way back to the beginning of AI, presenting compelling arguments from their areas of expertise, and venturing in other key areas. The whole is to me restricted and biased, yet solid and constructive. Restricti
Connor Magary
Jan 02, 2022 rated it really liked it  ·  review of another edition
Pumped for AI to fold my laundry someday
Oct 18, 2020 rated it really liked it
The book is one of the few that discuses AI without only pointing out dangers or overselling the possibilities. Instead it shows how the AI community is needing to learn from real life learning - not just suck data into the black box and hope for the best.
Oct 13, 2019 rated it it was ok
Christopher Flesher
Oct 29, 2019 rated it did not like it
Just a bunch of complaints
Becky B
Apr 15, 2020 rated it really liked it
Shelves: nonfiction, science
A realistic look at the current abilities and limitations of modern AI and the author's suggestions about what needs to happen in order to get AI to the place where it could take care of household chores or put Grandpa to bed without calamity.

This was a good dose of reality to combat all the bells and whistles that AI makers throw at you in press releases. AI is nowhere near understanding language, it is lightyears away from any common sense, and the fact that search results or voice recognition
Derek Bridge
Mar 28, 2020 rated it really liked it
This book starts off as a good appraisal of the state-of-play in AI, especially the limitations of deep learning (which is the current in-vogue version of subsymbolic AI). The book is very clear about what deep learning is lacking, in particular representations of relational knowledge (especially common-sense knowledge ) and (relatedly) compositionality. The book acknowledges too that "classical AI" (symbolic AI) is brittle. So, the diagnosis is good. But there are two problems.

First is that the
Feb 05, 2020 rated it liked it
Shelves: science
Humans have been trying to make computers that think at least since the 1950s and during that time I think it's fair to say that there have been two main camps:

(1) A group that feels it is important to develop systems with a solid philosophical, mathematical and scientific foundation, in such a way that we understand what they are doing, why they are doing it, and whether what they are doing truly constitutes "intelligence."

(2) A group that feels it is more important to first develop systems tha
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Play Book Tag: Rebooting AI by Gary Marcus & Ernest Davis - 4 stars 1 6 Jul 29, 2021 08:46AM  

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Gary Marcus is an award-wining Professor of Psychology at New York University and director of the NYU Center for Child Language. He has written three books about the origins and nature of the human mind, including Kluge (2008, Houghton Mifflin/Faber), and The Birth of the Mind (Basic Books, 2004, translated into 6 languages). He is also the editor of The Norton Psychology Reader, and the author of ...more

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“More broadly, formal logic of the sort we have been talking about does only one thing well: it allows us to take knowledge of which we are certain and apply rules that are always valid to deduce new knowledge of which we are also certain.” 0 likes
“But the real story is how narrow Duplex was. For all the fantastic resources of Google (and its parent company, Alphabet), the system that they created was so narrow it could handle just three things: restaurant reservations, hair salon appointments, and the opening hours of a few selected businesses. By the time the demo was publicly released, on Android phones, even the hair salon appointments and the opening hour queries were gone. Some of the world’s best minds in AI, using some of the biggest clusters of computers in the world, had produced a special-purpose gadget for making nothing but restaurant reservations. It doesn’t get narrower than that.” 0 likes
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