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Introducing Graphic Guides
Introducing Artificial Intelligence: A Graphic Guide
Half a century of research has resulted in machines capable of beating the best human chess players and humanoid robots that can interact. But can machines really think? Is the mind just a complicated computer program? Introducing Artificial Intelligence focuses on the issues behind one of science's most difficult problems.
176 pages, Paperback
First published January 1, 2007
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Displaying 1 - 30 of 79 reviews
April 23, 2019
Like the other books in this series, this provides a text-and-illustrations overview of key ideas and questions in the field of Artificial Intelligence, but lacks the depth of a deeper dive into the topic. Some important core concepts, such as the Turing machine, are explained in very confusing terms, and the odd line drawing/collage artwork sometimes obscures meanings rather than illustrates them. Reading a 2012 book on artificial intelligence in 2019 is going to seem, well, a little dated -- but it's interesting to see the core historical models of intelligence, artificial and otherwise, as well as how some of the predictions panned out (or didn't -- personal robots, not so much, and why no predictions for self-driving cars?)
September 14, 2018
Sorta boring and outdated. And not simple enough for a introduction. Graphic images are boring too.
January 30, 2018
Very short, but not really sweet.
This is an older book so potentially outdated now and I don't think the images added anything important other than a sales gimmick.
An interesting field of study, but none of the ideas were really introduced so much as stated and then the text moved on.
I would have rated this higher if it explored the topics in depth rather than focusing solely on breadth.
This is an older book so potentially outdated now and I don't think the images added anything important other than a sales gimmick.
An interesting field of study, but none of the ideas were really introduced so much as stated and then the text moved on.
I would have rated this higher if it explored the topics in depth rather than focusing solely on breadth.
July 31, 2019
A very short primer on AI basics.
It’s fun and a good introduction and not overly complicated. Images enhance and don’t distract.
You can already tell the narrative is a little dated even with Siri.
It’s free on kindle if you have amazon but beware that it’s super hard to read. Try paperback for best results.
It’s fun and a good introduction and not overly complicated. Images enhance and don’t distract.
You can already tell the narrative is a little dated even with Siri.
It’s free on kindle if you have amazon but beware that it’s super hard to read. Try paperback for best results.
January 17, 2021
The book tries too hard to be off-beat and fails spectacularly at it!
March 22, 2025
The notion of Artificial Intelligence (AI) has been around almost since the dawn of automated digital computing. In the 1950s, the first digital computers were physically enormous, wildly expensive, few in number, prodigal in energy consumption, and feeble in computing capacity. A modern smartphone runs rings around a room-sized computer from back then. But even at that earliest stage of their development, digital computers could vastly outperform human "computers" for many kinds of repetitive computing tasks. That is, before machines automated tedious arithmetic, teams of human "computers" had the job of manually crunching the numbers.
Even the earliest digital computers were superior to humans at any job that could be broken down into individually simple steps like addition, subtraction, multiplication, and division, along with symbol manipulation involving unambiguous logical rules. But humans can do many other important cognitive tasks that seem to defy this kind of reduction into simple steps. When humans can do a particular job, but they don't understand exactly how they are doing it, they can't break it down into steps that are simple enough for a computer to perform automatically. In such cases we say that the job requires "intelligence." The word "intelligence" itself defies precise explanation for the same reason - if we understood exactly what intelligence is, we would understand how we are solving problems that we don't understand how we are solving. Thus one definition of "intelligence" is functional and contingent on the current state of computing: the ability to do something that we can't explain to a computer yet. The act of imparting these kinds of abilities to a computer, to solve the same kinds of problems that humans need "intelligence" to solve, is called AI.
As I write this review in 2025, AI has been increasingly in the news. That's because we are currently living in an "AI spring" (or an AI boom). This AI boom began in the 2010s, and stands in glaring contrast to the long prior history of AI winter that marred the first 50 years of AI research and development. AI was for a long time one of the most over-hyped areas of technology, and it's finally starting to deliver on the hype.
A rough historical analogy is with the quest for powered flight. Since ancient times, humans had dreamed of flying like birds. The quest for this dream led to a long history of aviation. At first, that was a long history of failures, some of them spectular, until the Wright brothers finally cracked it in 1903 with their first successful airplane, the Wright Flyer. Imagine that you were living in 1910 or so, and you wanted to learn about these newfangled airplanes. Would you want to read a book that had been written in the year 1890? Such a book might be of historical interest, but it would have almost zero practical value, because nobody in the year 1890 knew exactly how to build a working airplane. The history of aviation up to 1903 was a long "aviation winter".
AI's own "Wright brothers" moment might have been on November 30, 2022 with the initial public release of ChatGPT. AI suddenly exploded into general human awareness. ChatGPT is a highly successful public-facing Large language model chatbot. According to Wikipedia:
So, can the book Introducing Artificial Intelligence: A Graphic Guide help? Maybe. Even though editions of this book have publication years in the 2010s, much if not all of the content seems to be largely the same as in the original edition, which came out in 2007. Another measure of the real age of the book is in its Further Reading section, which lists several books, the most recent being from 2002. This makes the book a work of history now, specifically a snapshot of what AI was like late in its long winter. It's like a book about aviation from the year 1890. That wouldn't be a complete waste of time, because history matters, but it might be a little bit dangerous if that was the only book you read. At the very least you would be underinformed, and possibly a little misinformed.
Finding an up-to-date introductory book about AI might be difficult just now. Writing books and getting them published takes a while, and it's barely been two years since AI became drastically relevant. Even worse, the whole field is rapidly changing now, so any book about ChatGPT for example would likely be out of date within a year or less. A book about AI that came out right now would probably be about the AI that existed six months ago, which might mean it's already out of date before the ink is dry.
While I wouldn't recommend against reading this book, it should not be the only thing you read about AI. (This is a great instance of Miguel de Unamuno's adage, in paraphrase, "The more books you read, the less harm they do.") A resource that tends to stay up-to-date is Wikipedia. In addition to the other Wikipedia articles I linked above, see Progress in artificial intelligence, and the Outline of artificial intelligence.
The main advantage of this book is that it's easy to read (if not to understand). The text volume is minimal and broken up by lots of illustrations. The illustrations tend to be incidental rather than directly informative, and the artistic style is a bit weird for my taste, but they break up the "wall of text" tedium that afflicts many works of dry technical prose.
I can't really speak to how well this book succeeds as an "introduction" because I've been following AI as a lay observer off and on for decades, right through that long winter. Many of the people and things in the book I had some prior familiarity with. If you're seeing it all for the very first time, I'd have to say god help you, because this book likely won't. But we don't need god any more since we now have working examples of AI itself - when (not if) something in the book confuses you, just ask ChatGPT (or Gemini, Copilot, etc.) about it.
A large fraction of the book is about philosophical issues in AI. That may have made sense at the time, when AI didn't have much practical value yet. But today, most people probably don't care about whether the machine that knocks them out of a job is "really" thinking or not. All that matters is that the machine is doing your job more reliably than you can, at less cost to your employer.
I give the book 4 stars anyway because it's about one of the most important topics right now, and a person needs to read everything they can about the AI that's about to replace them. Newer books about AI will almost certainly recount or at least allude to the history of the field, so this book will give you a head start.
Even the earliest digital computers were superior to humans at any job that could be broken down into individually simple steps like addition, subtraction, multiplication, and division, along with symbol manipulation involving unambiguous logical rules. But humans can do many other important cognitive tasks that seem to defy this kind of reduction into simple steps. When humans can do a particular job, but they don't understand exactly how they are doing it, they can't break it down into steps that are simple enough for a computer to perform automatically. In such cases we say that the job requires "intelligence." The word "intelligence" itself defies precise explanation for the same reason - if we understood exactly what intelligence is, we would understand how we are solving problems that we don't understand how we are solving. Thus one definition of "intelligence" is functional and contingent on the current state of computing: the ability to do something that we can't explain to a computer yet. The act of imparting these kinds of abilities to a computer, to solve the same kinds of problems that humans need "intelligence" to solve, is called AI.
As I write this review in 2025, AI has been increasingly in the news. That's because we are currently living in an "AI spring" (or an AI boom). This AI boom began in the 2010s, and stands in glaring contrast to the long prior history of AI winter that marred the first 50 years of AI research and development. AI was for a long time one of the most over-hyped areas of technology, and it's finally starting to deliver on the hype.
A rough historical analogy is with the quest for powered flight. Since ancient times, humans had dreamed of flying like birds. The quest for this dream led to a long history of aviation. At first, that was a long history of failures, some of them spectular, until the Wright brothers finally cracked it in 1903 with their first successful airplane, the Wright Flyer. Imagine that you were living in 1910 or so, and you wanted to learn about these newfangled airplanes. Would you want to read a book that had been written in the year 1890? Such a book might be of historical interest, but it would have almost zero practical value, because nobody in the year 1890 knew exactly how to build a working airplane. The history of aviation up to 1903 was a long "aviation winter".
AI's own "Wright brothers" moment might have been on November 30, 2022 with the initial public release of ChatGPT. AI suddenly exploded into general human awareness. ChatGPT is a highly successful public-facing Large language model chatbot. According to Wikipedia:
By January 2023, ChatGPT had become what was then the fastest-growing consumer software application in history, gaining over 100 million users in two months. ChatGPT's release spurred the release of competing products, including Gemini, Claude, Llama, Ernie, and Grok.The jaw-dropping capabilities of these chatbots continue to grow by the month, opening up vast new domains where computers might make human workers more productive, or perhaps redundant. AI has now emerged as a supremely disruptive technology, and most people will be disrupted in some way. Learning about AI might be one of the most important things a person can do right now. When folks are about to get blindsided, it's better to be one of the blindsiders than one of the blindsidees.
So, can the book Introducing Artificial Intelligence: A Graphic Guide help? Maybe. Even though editions of this book have publication years in the 2010s, much if not all of the content seems to be largely the same as in the original edition, which came out in 2007. Another measure of the real age of the book is in its Further Reading section, which lists several books, the most recent being from 2002. This makes the book a work of history now, specifically a snapshot of what AI was like late in its long winter. It's like a book about aviation from the year 1890. That wouldn't be a complete waste of time, because history matters, but it might be a little bit dangerous if that was the only book you read. At the very least you would be underinformed, and possibly a little misinformed.
Finding an up-to-date introductory book about AI might be difficult just now. Writing books and getting them published takes a while, and it's barely been two years since AI became drastically relevant. Even worse, the whole field is rapidly changing now, so any book about ChatGPT for example would likely be out of date within a year or less. A book about AI that came out right now would probably be about the AI that existed six months ago, which might mean it's already out of date before the ink is dry.
While I wouldn't recommend against reading this book, it should not be the only thing you read about AI. (This is a great instance of Miguel de Unamuno's adage, in paraphrase, "The more books you read, the less harm they do.") A resource that tends to stay up-to-date is Wikipedia. In addition to the other Wikipedia articles I linked above, see Progress in artificial intelligence, and the Outline of artificial intelligence.
The main advantage of this book is that it's easy to read (if not to understand). The text volume is minimal and broken up by lots of illustrations. The illustrations tend to be incidental rather than directly informative, and the artistic style is a bit weird for my taste, but they break up the "wall of text" tedium that afflicts many works of dry technical prose.
I can't really speak to how well this book succeeds as an "introduction" because I've been following AI as a lay observer off and on for decades, right through that long winter. Many of the people and things in the book I had some prior familiarity with. If you're seeing it all for the very first time, I'd have to say god help you, because this book likely won't. But we don't need god any more since we now have working examples of AI itself - when (not if) something in the book confuses you, just ask ChatGPT (or Gemini, Copilot, etc.) about it.
A large fraction of the book is about philosophical issues in AI. That may have made sense at the time, when AI didn't have much practical value yet. But today, most people probably don't care about whether the machine that knocks them out of a job is "really" thinking or not. All that matters is that the machine is doing your job more reliably than you can, at less cost to your employer.
I give the book 4 stars anyway because it's about one of the most important topics right now, and a person needs to read everything they can about the AI that's about to replace them. Newer books about AI will almost certainly recount or at least allude to the history of the field, so this book will give you a head start.
December 17, 2019
An interesting book considering it's a subject I know nothing about, but it's very dry.
The graphic novel approach seemed to lighten it a little, but I see nothing that it actually added to the book. I could have easily done without it.
The graphic novel approach seemed to lighten it a little, but I see nothing that it actually added to the book. I could have easily done without it.
February 29, 2024
If you have to read one book to get a grip of what is this hullabaloo about Artificial Intelligence, this is NOT that book.
Avoid it.
This book is a classic example of how you have a lots of information to give, but you present it in such haphazard manner that the reader gets so confused that she abandons it cursing the author.
Outdated, Unorganized and Irrelevant. Couldn't finish.
Avoid it.
This book is a classic example of how you have a lots of information to give, but you present it in such haphazard manner that the reader gets so confused that she abandons it cursing the author.
Outdated, Unorganized and Irrelevant. Couldn't finish.
February 14, 2016
หนังสือเก่าแล้ว (เขียนเมื่อสิบกว่าปีก่อน) แต่ดีมาก ช่วยให้เข้าใจประเด็นถกเถียงพื้นฐานเกี่ยวกับ AI เยอะมากๆ ตั้งแต่ประเด็นว่านักภววิทยา (Ontologists) นี่มันทำอะไรกัน ทำไมถึงเรียกว่า Ontologists ไปจนถึงข้อถกเถียงว่าด้วยสำนึกหรือจิตแบบควอนตัมของ Penrose ที่ก่อนหน้านี้ไม่เก็ทเลยว่ามันหมายถึงอะไร รวมถึงแนวคิดพื้นฐานเกี่ยวกับการศึกษาจิต ศาสตร์การรู้คิด (Cognitive science) และปัญญาประดิษฐ์อื่นๆ ซึ่งสัมพันธ์ๆ กันอยู่���ย่างแยกออกได้ยาก
Highly recommended for any rookies in AI, including we social scientists!
Highly recommended for any rookies in AI, including we social scientists!
March 8, 2018
I enjoyed this book and found it useful. A few points;
I'm not deep enough into A.I. to know if this book has a specific argument in relation to that culture. The general structure seems to be that old A.I. researchers from the 50's onward tended to believe very deeply in the idea of a pure constructed mind, seperate from its physical expression and tested mainly in a simulated 'ideal' world and that more recently, from the 90's onwards, the tide has turned towards the idea of intelligence being much more closely interrelated with bodily expression in the real world.
If this is the case then I find this change largely fits my moral and intellectual intuitions and prejudices. I am pleased to see it.
I believe I agree with Steven Hannard about the symbol grounding problem; 'Meaning can enter the system only when part of the system is grounded in the world, rather than being part of a closed self-referential system of symbols.'
If we take this as true; "... the cognitivistic paradigm's neglect of the fact that intelligent agents live in a real physical world leads to significant shortcomings in explaining intelligence" - Rolf Pfeifer and Christian Scheier. - Then it does lead to some very interesting thoughts about just, what the fuck, A.I. researchers were doing for 30 to 40 years. Because the ideas of; 'high level functions might be connected to bodies', 'when making super-complex things, we should start from the bottom up' and 'elaborate, perfectly interiorley-coherent systems of symbols, often suck for solving real-world problems'; these are not deep, complex or especially hard to parse conceits. There is no mystery box that needs to open before you can think like this. They are reasonable common sense.
And if this is the case then perhaps instead we should be asking exactly why A.I. researchers spent a very long time fucking about with things that either didn't work, or barely worked at all. This does remind me of the radical surgical treatments for cancer described in Siddbartha Mukherjee's 'The Emperor of all Maladies' which excised huge amounts of muscle and flesh from, generally, female or low-status male patients, and which were carried on far, far too long with little provable positive effect to show, or of recent descriptions of themes and fashions in medical and scientific research which suggest that for genuinely new concepts to be accepted, in some cases you simply have to wait for a generation of old scientists to die. And very largely it reminds me (as a lot of things seem to) of 'The Master and His Emissary' by Ian McGilchrist, which describes the obsessional need of a left-brained culture and mind-state to re-create the world as an internally-coherent abstract simulation of itself, and also described the compulsive overconfidence, monopic obsession with coherent internally-consistent data and incurious indifference to 'dirty', 'messy' or incoherent data from outside the simulation that such cultures and mind-states tend to have.
It is still theoretically possible that I might be wrong. A.I. researchers do have a long tradition of being deeply, massively wrong in their predictions but just because they have been wrong every point up till now, doesn't necessarily mean they will be wrong _this_ time. (Though they probably are.) The very fact that consciousness is, as the book puts it several times, 'a mystery', means that it could actually be just around the corner and some random researcher could just pop out with a pure-math disembodied computer brain that says 'hello'.
But this probably won't happen. What it will probably be is a few centuries of dicking around with robots, getting gradually better and better until we either hit a hard limit, are prevented from research by mindcrime concerns or finally do it.
There is a lot of Alan Turing in this book. Apparently he is just one of those guys who had all the good ideas before anyone else, so if you are an A.I. researcher and you are wandering through what you think is an unexplored mansion of thought and you open a mysterious ancient chest of ideas then 50/50 that Alan fucking Turing will just tumble outta there.
I did think the art was really astoundingly ugly. This did not impede the utility of the book or the transmission of its ideas, I understood everything it wished me to understand, and if I didn't then the fault is mine rather than the books.
More precisely, the art is grainy with awkward, strange looking people and a general aura of alienation and physical discomfort. The A.I. robot character who acts as a presenter is really fucking sinister and strange looking.
It's possible that this is all a deliberate aesthetic choice, the odd, ganky feel of the presentation does fit quite neatly with the strange feel of simulated minds, the slightly odd men who are into them and the freaky robots they make to test them.
And, it had no effect on comprehension.
If you don't know anything about A.I. and want to find out, and if you prefer books to just reading stuff online, and you want something light (physically) and light (cognitively) that you can carry around in a pocket or something and deal with using your spare everyday cognitive energy, then I would recommend this book.
I'm not deep enough into A.I. to know if this book has a specific argument in relation to that culture. The general structure seems to be that old A.I. researchers from the 50's onward tended to believe very deeply in the idea of a pure constructed mind, seperate from its physical expression and tested mainly in a simulated 'ideal' world and that more recently, from the 90's onwards, the tide has turned towards the idea of intelligence being much more closely interrelated with bodily expression in the real world.
If this is the case then I find this change largely fits my moral and intellectual intuitions and prejudices. I am pleased to see it.
I believe I agree with Steven Hannard about the symbol grounding problem; 'Meaning can enter the system only when part of the system is grounded in the world, rather than being part of a closed self-referential system of symbols.'
If we take this as true; "... the cognitivistic paradigm's neglect of the fact that intelligent agents live in a real physical world leads to significant shortcomings in explaining intelligence" - Rolf Pfeifer and Christian Scheier. - Then it does lead to some very interesting thoughts about just, what the fuck, A.I. researchers were doing for 30 to 40 years. Because the ideas of; 'high level functions might be connected to bodies', 'when making super-complex things, we should start from the bottom up' and 'elaborate, perfectly interiorley-coherent systems of symbols, often suck for solving real-world problems'; these are not deep, complex or especially hard to parse conceits. There is no mystery box that needs to open before you can think like this. They are reasonable common sense.
And if this is the case then perhaps instead we should be asking exactly why A.I. researchers spent a very long time fucking about with things that either didn't work, or barely worked at all. This does remind me of the radical surgical treatments for cancer described in Siddbartha Mukherjee's 'The Emperor of all Maladies' which excised huge amounts of muscle and flesh from, generally, female or low-status male patients, and which were carried on far, far too long with little provable positive effect to show, or of recent descriptions of themes and fashions in medical and scientific research which suggest that for genuinely new concepts to be accepted, in some cases you simply have to wait for a generation of old scientists to die. And very largely it reminds me (as a lot of things seem to) of 'The Master and His Emissary' by Ian McGilchrist, which describes the obsessional need of a left-brained culture and mind-state to re-create the world as an internally-coherent abstract simulation of itself, and also described the compulsive overconfidence, monopic obsession with coherent internally-consistent data and incurious indifference to 'dirty', 'messy' or incoherent data from outside the simulation that such cultures and mind-states tend to have.
It is still theoretically possible that I might be wrong. A.I. researchers do have a long tradition of being deeply, massively wrong in their predictions but just because they have been wrong every point up till now, doesn't necessarily mean they will be wrong _this_ time. (Though they probably are.) The very fact that consciousness is, as the book puts it several times, 'a mystery', means that it could actually be just around the corner and some random researcher could just pop out with a pure-math disembodied computer brain that says 'hello'.
But this probably won't happen. What it will probably be is a few centuries of dicking around with robots, getting gradually better and better until we either hit a hard limit, are prevented from research by mindcrime concerns or finally do it.
There is a lot of Alan Turing in this book. Apparently he is just one of those guys who had all the good ideas before anyone else, so if you are an A.I. researcher and you are wandering through what you think is an unexplored mansion of thought and you open a mysterious ancient chest of ideas then 50/50 that Alan fucking Turing will just tumble outta there.
I did think the art was really astoundingly ugly. This did not impede the utility of the book or the transmission of its ideas, I understood everything it wished me to understand, and if I didn't then the fault is mine rather than the books.
More precisely, the art is grainy with awkward, strange looking people and a general aura of alienation and physical discomfort. The A.I. robot character who acts as a presenter is really fucking sinister and strange looking.
It's possible that this is all a deliberate aesthetic choice, the odd, ganky feel of the presentation does fit quite neatly with the strange feel of simulated minds, the slightly odd men who are into them and the freaky robots they make to test them.
And, it had no effect on comprehension.
If you don't know anything about A.I. and want to find out, and if you prefer books to just reading stuff online, and you want something light (physically) and light (cognitively) that you can carry around in a pocket or something and deal with using your spare everyday cognitive energy, then I would recommend this book.
April 11, 2018
VERY out of date, in such a fast moving technology I suggest it is not worth reading, get something more up to date. Also very light on detail, could be summarised into more or less 2 sides of A4 and a couple of info graphics.
November 18, 2021
Simple
A simple introduction to the topic through popularization. I was disappointed the illustrations did not provide additional context, simply a place for speech bubbles.
A simple introduction to the topic through popularization. I was disappointed the illustrations did not provide additional context, simply a place for speech bubbles.
January 20, 2025
This book covers what it means to really call a system intelligent from a philosophical perspective. And like most philosophical musings, it wont help you apply the information in your job. This is especially the case as the book was written in 2002 and as a result is ignorant of the latest widely available developments in in chat gpt and other machine learning tools.
However the philosphy side is well done amd interesting. The book seems to be (convincly) making the claim that what people typically developed in the past were glorified calculators. Is essence, the 'AI' was manipulating symbols and basic models of the world but lacked the ability to handle the real complexities of the world without relying on human intelligence to map it out. This shouldn't count as intelligence because the map is not the territory. Real intelligence needs to come from systems that interact with the world without a human filter and this can only really be achieved by allowing these systems to ho through a process of evolution.
The book's aim seemed to be to explain this point and it gave you the history and philosophy needed to understand it. However, the book only introduces each idea and if you really want to understamd, you have to dive into the information elsewhere.
However the philosphy side is well done amd interesting. The book seems to be (convincly) making the claim that what people typically developed in the past were glorified calculators. Is essence, the 'AI' was manipulating symbols and basic models of the world but lacked the ability to handle the real complexities of the world without relying on human intelligence to map it out. This shouldn't count as intelligence because the map is not the territory. Real intelligence needs to come from systems that interact with the world without a human filter and this can only really be achieved by allowing these systems to ho through a process of evolution.
The book's aim seemed to be to explain this point and it gave you the history and philosophy needed to understand it. However, the book only introduces each idea and if you really want to understamd, you have to dive into the information elsewhere.
December 29, 2019
A deep look at the foundationd
Although this book was written in 2012, before deep learning took off, it provides insights into the history, pioneers, paradoxes and conceptual foundation of AI. There is focus on both symbolic and connectionist approaches with an integrated approach supposedly countering Searles Chinese room/gym argument. Further, there is a focus on robotics as an important thread which can lead to embodied and environmentally adjusted AI. A very good book on foundations and it does include some very bold predictions by a few futurists of AI.
Although this book was written in 2012, before deep learning took off, it provides insights into the history, pioneers, paradoxes and conceptual foundation of AI. There is focus on both symbolic and connectionist approaches with an integrated approach supposedly countering Searles Chinese room/gym argument. Further, there is a focus on robotics as an important thread which can lead to embodied and environmentally adjusted AI. A very good book on foundations and it does include some very bold predictions by a few futurists of AI.
October 21, 2019
My ratings of books on Goodreads are solely a crude ranking of their utility to me, and not an evaluation of literary merit, entertainment value, social importance, humor, insightfulness, scientific accuracy, creative vigor, suspensefulness of plot, depth of characters, vitality of theme, excitement of climax, satisfaction of ending, or any other combination of dimensions of value which we are expected to boil down through some fabulous alchemy into a single digit.
October 18, 2020
Este livro já tem uns anos, e nota-se. Não aborda a corrente explosão da IA, com o alastrar de algoritmos de machine learning, deep learning e redes neuronais, bem como as suas progressivas aplicaçóes. Mas não deixa de ser interessante, dando uma visão simplificada e ilustrada da evolução e tendências desta tecnologia, tocando mesmo em pontos muito complexos, como o que é realmente se define como "inteligência".
April 1, 2018
Gives a good overview of the philosophical and physical interpretations of AI.
The book puts forward interesting ideas for a beginner to AI. The graphical artistry with its examples add more depth to the more esoteric concepts. The book has a balanced approach to philosophies and ideas which in turn helps a reader refine their own ideas.
The book puts forward interesting ideas for a beginner to AI. The graphical artistry with its examples add more depth to the more esoteric concepts. The book has a balanced approach to philosophies and ideas which in turn helps a reader refine their own ideas.
January 30, 2020
It tries really hard at compressing the history of AI, explaining what it is and what the future holds in less than 200 pages that are mostly graphics.
The text is hard to grasp if you don't have much of an understanding of an AI to begin with, so it falls short of being a proper introduction.
Even though my edition came out in 2013 it feels very dated.
But the graphics are enjoyable.
The text is hard to grasp if you don't have much of an understanding of an AI to begin with, so it falls short of being a proper introduction.
Even though my edition came out in 2013 it feels very dated.
But the graphics are enjoyable.
March 2, 2021
Decent basic introduction
The book is nice introductory overview of AI. It is an easy read.
Its might be a bit too basic though and its structure makes it hard to revisit a certain subtopic as it seems to be designed to flow from beginning to end and that is the best way to read it.
The book is nice introductory overview of AI. It is an easy read.
Its might be a bit too basic though and its structure makes it hard to revisit a certain subtopic as it seems to be designed to flow from beginning to end and that is the best way to read it.
May 19, 2023
This is really good for breaking down the history and very simple concepts for someone like me who knew absolutely nothing. I felt like it was a good taste into the world of AI, and from here I can springboard into additional studies. The graphics are a bit strange but they complement the information and I think it's helpful for people who are more visual.
January 13, 2018
Distrust.
There were some typos in the text....made me distrust the content, since I'm unfamiliar with this topic. Perhaps, if I had more knowledge of this topic it would have been more beneficial.
There were some typos in the text....made me distrust the content, since I'm unfamiliar with this topic. Perhaps, if I had more knowledge of this topic it would have been more beneficial.
September 3, 2018
Pensei que fosse um guia gráfico, e rápido, do que é a AI a nível de programação. Mas afinal é uma apresentação das perspectivas de aproximação filosófica, psicológica, social, à AI.
Tem uns bonecos um pouco assutadores mas pronto..
Tem uns bonecos um pouco assutadores mas pronto..
October 17, 2018
Good overview of the AI landscape
Some fascinating stuff there. Specially around the link between mind and body and the birth of language as an interaction between communication and internal modeling. Good pointers to dig deeper on some issues.
Some fascinating stuff there. Specially around the link between mind and body and the birth of language as an interaction between communication and internal modeling. Good pointers to dig deeper on some issues.
May 2, 2019
Excellent introduction of ADVANCED concepts in AI.
Not for the newbie. Some basic knowledge of computers required. Great for advanced undergraduates and graduates students in the sciences & engineering. Connection of new Ai insights from BIOLOGY enlightening.
Not for the newbie. Some basic knowledge of computers required. Great for advanced undergraduates and graduates students in the sciences & engineering. Connection of new Ai insights from BIOLOGY enlightening.
July 31, 2019
Graphic glitches on the kindle app
Worthwhile overview of AI. History is good but the book is already outdated. An update would be helpful. 3 stars because of frustrating disappearing pictures that had actual content.
Worthwhile overview of AI. History is good but the book is already outdated. An update would be helpful. 3 stars because of frustrating disappearing pictures that had actual content.
October 12, 2019
A whirlwind tour of artificial Intelligence. It covers the topics from the initial days up the to early 2000s. It gives an introduction to people who shaped this field. It does not go into any detail, just a high-level summary of many things.
January 5, 2020
Reasonably good, I definitely learnt more on the breath of the field. I assumed it be more mathematically based concepts. So missed ideas such as genetic algorithms and more detailed ideas such as image recognition and what we can do with deep mind AI.
March 23, 2020
The book delves into the evolution of Artificial Intelligence and goes into the history of how it all happened and is likely to evolve during the future. It does not help the uninitiated into understanding of the complexity of this evolution.
February 17, 2021
A bit outdated but also very disjointed book glancing over concepts and theories without clear explanation. In the end I didn’t learn anything and was not quite sure of where the book was going. Would not recommend this read.
April 9, 2023
More about us, than them
A wonderful explanation about cognition, perception and the real pursuit of AI... Ie. To better understand how we see the world and act within it! Extremely enjoyable read!!!
A wonderful explanation about cognition, perception and the real pursuit of AI... Ie. To better understand how we see the world and act within it! Extremely enjoyable read!!!
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