What do you think?
Rate this book
Artificial Intelligence For Dummies
Step into the future with AI The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!
338 pages, Kindle Edition
First published March 16, 2018
246 people are currently reading
395 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 30 of 36 reviews
February 6, 2019
I read this for scifi novel research. A good intro into the world of AI... a bit repetitive at the end and I'd quibble with some of his assertions and characterizations as being too rigid, but on the whole, useful.
September 12, 2018
I am interested in artificial intelligence so I thought I would read this book. I enjoyed reading about AI safe jobs. I also liked reading about AI and space. I also liked reading the chapter on 20 things that AI has failed at. I thought I learned a lot about AI by reading this book. I enjoyed reading it. I wish I could write better book reviews. Maybe there is a book on writing book reviews.
March 15, 2022
I am intrigued by the term Artificial Intelligence but I don't even what does it means. There are a lot of movies using the idea of AI but it's all nonsense. How would an AI fall in love with a human if the only function of AI is to think like a human based on the input given to it? Without further ado, I wanted to discuss what I learned from this book. An old friend of mine told me to try Data Analysis since I enjoy numbers; hence this is the perfect book to start what I am supposed to be working on later on.
The difference between AI and humans is that self-awareness only happens to the latter. An AI can only process what input is given to it. There are a lot of limitations to what AI can do because to function as a human, there is the hardware needed to replicate it. The function of AI is to simplify redundant work.
Machine learning is a technology that helps computers learn from data. A perfect analogy for this is Jane teaching Tarzan how to be human by showing him what things/person looks like. You keep inserting data to teach him. And that's where DATA ANALYSIS enters. The data entered should be transformed, cleaned, and accurate data. It is similar to the student and teachers relationship. The teacher must reference his/her lessons correctly in order not to confuse the students. That's how important Data Analysis is in AI.
To elucidate this topic: Data Analysis is the first step to combine and extract accurate information. Followed by machine learning to feed the computer of the extracted information. You can successfully apply machine learning only after data analysis provides correctly prepared input. Deep learning is a technology that strives to imitate the human brain. It is just a small part of machine learning to master the idea of something. And finally, the AI where the computer finds the patterns and provides a requested output. It doesn't understand anything, it can't create or discover anything new, and it has no intrapersonal knowledge, so it can't empathize with anyone about anything. It behaves as designed by a human programmer, and what you often take for intelligence is only a mix of clever programming and vast amounts of data analyzed in a specific manner.
---> In a nutshell, Data Analysis is the provider of information i.e. books, teachers, Internet, etc; while Machine Learning is the user of that information to become something i.e. students becoming professional in the future.
There are a lot of applications of AI in this book. There's even a device powered by AI that allows a quadriplegic person to walk and that's forking awesome. And others...
I like this idea of Data Analysis where data is compared to oil.
After reading the book, the field of Data Analysis, Machine Learning, Deep Learning, and Artificial Intelligence is interesting that it makes me excited and fear how to learn all this stuff. I get the gist of these topics but the question now is HOW TO LEARN THIS STUFF? I am already learning Python and hopefully, that's the start of changing my behavior towards programming. I needed to get this skill and get out of my own version of RAT CYCLE.
As my computer's wallpaper, "Talk is cheap. Show me the code." -Linus Torvalds.
I am showing you now.
I want to clarify when I wanted this field. 1)This is what I learned for 5 years. 2)This is an interesting field that will not bore me and find other stuff to fill my stupid mind i.e. dating, marriage, and society's so-called norms. 3)This is the only solution that I see to end my suffering for my current job.
The difference between AI and humans is that self-awareness only happens to the latter. An AI can only process what input is given to it. There are a lot of limitations to what AI can do because to function as a human, there is the hardware needed to replicate it. The function of AI is to simplify redundant work.
Machine learning is a technology that helps computers learn from data. A perfect analogy for this is Jane teaching Tarzan how to be human by showing him what things/person looks like. You keep inserting data to teach him. And that's where DATA ANALYSIS enters. The data entered should be transformed, cleaned, and accurate data. It is similar to the student and teachers relationship. The teacher must reference his/her lessons correctly in order not to confuse the students. That's how important Data Analysis is in AI.
To elucidate this topic: Data Analysis is the first step to combine and extract accurate information. Followed by machine learning to feed the computer of the extracted information. You can successfully apply machine learning only after data analysis provides correctly prepared input. Deep learning is a technology that strives to imitate the human brain. It is just a small part of machine learning to master the idea of something. And finally, the AI where the computer finds the patterns and provides a requested output. It doesn't understand anything, it can't create or discover anything new, and it has no intrapersonal knowledge, so it can't empathize with anyone about anything. It behaves as designed by a human programmer, and what you often take for intelligence is only a mix of clever programming and vast amounts of data analyzed in a specific manner.
"Data analysis concentrates on understanding and manipulating the data so that it can become more useful and provide insights on the world, whereas machine learning strictly focuses on taking inputs from data and elaborating a working, internal representation of the world that you can use for practical purposes."
---> In a nutshell, Data Analysis is the provider of information i.e. books, teachers, Internet, etc; while Machine Learning is the user of that information to become something i.e. students becoming professional in the future.
There are a lot of applications of AI in this book. There's even a device powered by AI that allows a quadriplegic person to walk and that's forking awesome. And others...
I like this idea of Data Analysis where data is compared to oil.
Data is not just money that rains from the sky; it requires effort to make it useful. Just as you can't immediately use unrefined oil because it has to be changed into something else by chemical processes that turn it into gas, plastics, or other chemicals, so data must undergo significant transformations to acquire value."
"You have a weak AI when the AI shows intelligent behavior but isn't conscious like a human being. A strong AI occurs when the AI can really think as a human."---->this is the goal in the field of AI. It's interesting but am still in the beginning of everything. I'll get there someday. KAIZEN is the key.
"Artificial intelligence aims to find solutions to some difficult problems related to human abilities (such as recognizing objects, or understanding speech or text); robotics aims to use machines to perform tasks in the physical world in a partially or completely automated way."-----> AI more on brain; robotics more on physical.
Keep It Simple, Stupid (KISS) principle is the best idea to keep in mind when it comes to developing AI applications.
After reading the book, the field of Data Analysis, Machine Learning, Deep Learning, and Artificial Intelligence is interesting that it makes me excited and fear how to learn all this stuff. I get the gist of these topics but the question now is HOW TO LEARN THIS STUFF? I am already learning Python and hopefully, that's the start of changing my behavior towards programming. I needed to get this skill and get out of my own version of RAT CYCLE.
As my computer's wallpaper, "Talk is cheap. Show me the code." -Linus Torvalds.
I am showing you now.
I want to clarify when I wanted this field. 1)This is what I learned for 5 years. 2)This is an interesting field that will not bore me and find other stuff to fill my stupid mind i.e. dating, marriage, and society's so-called norms. 3)This is the only solution that I see to end my suffering for my current job.
This entire review has been hidden because of spoilers.
June 6, 2018
A great book overall, particularly for the newcomers to the A.I. Field. The authors cover a variety of topics related to A.I., without getting too technical but without oversimplifying things either. They look at what A.I. is, beyond the hype, its relationship with data, how modern technologies like deep learning have helped it become an everyday term, and how A.I. is bound to affect our world in the years to come.
I particularly liked the clarifications made about what constitutes A.I. and how the whole field is related, but not the same as robots. Also, the authors covered in depth how A.I. is both an interesting scientific field of research and a technology that plays a relevant role in business; this is something refreshingly different to what other A.I. experts write about it, as they tend to focus more on the math and engineering parts.
Although this book won’t make you an expert in A.I., it can provide you with a very good understanding of what the field entails and how it is useful. Whether you are a computer science student, an A.I. engineer, or a business person involved in tech, you’ll have something to learn from this book, which makes the whole field be both very accessible and intriguing.
I particularly liked the clarifications made about what constitutes A.I. and how the whole field is related, but not the same as robots. Also, the authors covered in depth how A.I. is both an interesting scientific field of research and a technology that plays a relevant role in business; this is something refreshingly different to what other A.I. experts write about it, as they tend to focus more on the math and engineering parts.
Although this book won’t make you an expert in A.I., it can provide you with a very good understanding of what the field entails and how it is useful. Whether you are a computer science student, an A.I. engineer, or a business person involved in tech, you’ll have something to learn from this book, which makes the whole field be both very accessible and intriguing.
November 27, 2023
I felt this was a good overview of AI in general, although for an audiobook published in November 2023, it was wildly outdated! I guess they just took many, many years to actually publish the audiobook version. Anyway, like I said, it did provide more historical info and context for a lot of things I'd been piecing together here and there. I appreciated the comprehensive breadth if not much depth—except for the handful of places where it went from barely scratching the surface to sudden intense math and jargon. Still, on the whole, a good overview of a complex and quickly moving topic.
January 22, 2024
Great overview on artificial intelligence, what it is, it's limits, it's future applications. Not too technical.
March 28, 2021
The book provides some good examples where AI can be applied and at the same time describes its limitations.
However, the book is a bit repetitive and introductory chapter has plenty of technical information which a personally skipped.
But overall, I would recommend this book if you want to get an idea what AI is and how it works.
However, the book is a bit repetitive and introductory chapter has plenty of technical information which a personally skipped.
But overall, I would recommend this book if you want to get an idea what AI is and how it works.
May 28, 2022
Good introduction to AI, covering the history and development of the field, specific hardware, technical constraints, use cases and possibilities, dangers and opportunities. A good place to start learning about Artificial Intelligence.
July 25, 2024
Eindelijk dit boek uit. Maar het is niet slecht genoeg voor 1 ster, sommige informatie is oprecht interessant te noemen.
Het interessantste wat in het boek benoemd werd, was het Chinese kamer-experiment, wat duidelijk illustreert dat je dingen niet hoeft te begrijpen om iets te kunnen doen. Het laat zien dat computers dus niet noodzakelijk iets begrijpen terwijl ze het uitvoeren. Mooi inzichtelijk.
Verder ook wel goede dingen over de kansen en bedreigingen van AI, uitleg over waarom AI nooit de mens zal "vervangen". Ruimtevaart, zelfrijdende auto's en rijhulpsystemen, allerlei dingen waar je als mens nu of in de toekomst mee te maken kan krijgen.
Qua leesbaarheid is het boek soms veel te technisch met allerlei formules, grafieken en andere wiskundigheden. Daarnaast vind ik het zó vreemd dat bronnen direct IN DE TEKST als hyperlink worden aangegeven. Werk desnoods met voetnoten of een literatuurlijst per hoofdstuk of zoiets, een QR-code of verkorte link naar een website over het boek waarin je de meest recente links kan vinden of zoiets. Dit is echt heel chaotisch en gezien het een vrij actueel onderwerp is, vraag ik me af hoeveel links uit de tekst inmiddels al dood zijn. Sowieso is links midden in een zin plakken not done. Zoiets dóé je niet. Klaar.
De tekst is vrij verouderd en op sommige plekken is er echt wat mis gegaan met het vertalen van het boek. Vertaalfouten, tikfouten, nee, het is geen heel leesbaar boek. Het was een ware worsteling en dat is zonde gezien de inhoud kansen biedt en best interessant is.
Wat interessante noten:
"Als onderdeel van het creëeren van de dataset die je nodig hebt voor analyse, maak je een kopie van de oorspronkelijke gegevens in plaats van die aan te passen. Houd de originele, ruwe data altijd zuiver zodat je die later voor andere analyses kunt gebruiken." ~ bladzijde 36-37
"Het AI-effect houdt in dat succesvolle intelligente computerprogramma's al snel de erkentelijkheid van mensen kwijtraken en stille acteurs worden, terwijl de aandacht verlegd wordt naar AI-problemen die nog steeds om een oplossing vragen." ~ bladzijde 46
"Als je een boek wilt begrijpen, lees je het pagina voor pagina. De sequenties zijn genest. Binnen een pagina is een sequentie van woorden en binnen woorden is een sequentie van letters. Om het boek te begrijpen, moet je de sequentie van letters, woorden en pagina's begrijpen. Een Recurrent Neural Network (RNN) is het antwoord omdat het actuele input verwerkt terwijl het eerdere input naloopt." ~ bladzijde 196
"Robots zijn een relatief recent idee. Het woord is afgeleid van het Tsjechische woord robota, dat dwangarbeid betekent. De term verscheen voor het eerst in het toneelstuk Rossum's Universal Robots uit 1920, van de Tsjechische schrijver Karel Capek." ~ bladzijde 206
Het interessantste wat in het boek benoemd werd, was het Chinese kamer-experiment, wat duidelijk illustreert dat je dingen niet hoeft te begrijpen om iets te kunnen doen. Het laat zien dat computers dus niet noodzakelijk iets begrijpen terwijl ze het uitvoeren. Mooi inzichtelijk.
Verder ook wel goede dingen over de kansen en bedreigingen van AI, uitleg over waarom AI nooit de mens zal "vervangen". Ruimtevaart, zelfrijdende auto's en rijhulpsystemen, allerlei dingen waar je als mens nu of in de toekomst mee te maken kan krijgen.
Qua leesbaarheid is het boek soms veel te technisch met allerlei formules, grafieken en andere wiskundigheden. Daarnaast vind ik het zó vreemd dat bronnen direct IN DE TEKST als hyperlink worden aangegeven. Werk desnoods met voetnoten of een literatuurlijst per hoofdstuk of zoiets, een QR-code of verkorte link naar een website over het boek waarin je de meest recente links kan vinden of zoiets. Dit is echt heel chaotisch en gezien het een vrij actueel onderwerp is, vraag ik me af hoeveel links uit de tekst inmiddels al dood zijn. Sowieso is links midden in een zin plakken not done. Zoiets dóé je niet. Klaar.
De tekst is vrij verouderd en op sommige plekken is er echt wat mis gegaan met het vertalen van het boek. Vertaalfouten, tikfouten, nee, het is geen heel leesbaar boek. Het was een ware worsteling en dat is zonde gezien de inhoud kansen biedt en best interessant is.
Wat interessante noten:
"Als onderdeel van het creëeren van de dataset die je nodig hebt voor analyse, maak je een kopie van de oorspronkelijke gegevens in plaats van die aan te passen. Houd de originele, ruwe data altijd zuiver zodat je die later voor andere analyses kunt gebruiken." ~ bladzijde 36-37
"Het AI-effect houdt in dat succesvolle intelligente computerprogramma's al snel de erkentelijkheid van mensen kwijtraken en stille acteurs worden, terwijl de aandacht verlegd wordt naar AI-problemen die nog steeds om een oplossing vragen." ~ bladzijde 46
"Als je een boek wilt begrijpen, lees je het pagina voor pagina. De sequenties zijn genest. Binnen een pagina is een sequentie van woorden en binnen woorden is een sequentie van letters. Om het boek te begrijpen, moet je de sequentie van letters, woorden en pagina's begrijpen. Een Recurrent Neural Network (RNN) is het antwoord omdat het actuele input verwerkt terwijl het eerdere input naloopt." ~ bladzijde 196
"Robots zijn een relatief recent idee. Het woord is afgeleid van het Tsjechische woord robota, dat dwangarbeid betekent. De term verscheen voor het eerst in het toneelstuk Rossum's Universal Robots uit 1920, van de Tsjechische schrijver Karel Capek." ~ bladzijde 206
This entire review has been hidden because of spoilers.
February 8, 2020
Хубава книжка, бих преслушал две, три глави пак след време. Добро въведение и обобщение на темата. Книгите фор дъмис са супер добри. Но се вижда, че полето е много по-дълбоко от написаното в тази книга. Но и се вижда, че за сега това което наричат изкуствен интелект е просто експертна система.
Храниш го с много примери и той си намира някакъв начин, от пеоба и грешка да ти ги разпознава.
Така както ние упим по патология да разпознаваме различни болести от микроскопски препара��и. Гледаш много докато не се научиш.
В бъдеще изглежда изкуствен интелект ще е много полезен на хората за подобни неща. Тип анализиране на ДНК, анализиране на големи данни, мисля си си тезиране н�� основни теми и идеи от енциклопедии например. Сравняване на 100тина учебника по някъв предмет и намиране на сходствата и правене на обзори.
И всичко свързано с транспорта коли, космически кораби и пр.
Изкуството за мен е преди всичко начин за синтезиране на есенциата от някаква реалност, та в това ИИ може също да помогне със събирането и обработването на данни.
В бъдеще хората ще е добре да имат базова идея ор статистика и дата сайанс и вероятно бейсик програмиране (които аз нямам за сега) за да могат си играят с ИИ.
Вероятно ще се появят и интерфейси за идиоти и програмирането ще стане елементарно.
Трябва да науча малко пайтън и да поразцъкам някой от ИИ играчките със отворен код
Храниш го с много примери и той си намира някакъв начин, от пеоба и грешка да ти ги разпознава.
Така както ние упим по патология да разпознаваме различни болести от микроскопски препара��и. Гледаш много докато не се научиш.
В бъдеще изглежда изкуствен интелект ще е много полезен на хората за подобни неща. Тип анализиране на ДНК, анализиране на големи данни, мисля си си тезиране н�� основни теми и идеи от енциклопедии например. Сравняване на 100тина учебника по някъв предмет и намиране на сходствата и правене на обзори.
И всичко свързано с транспорта коли, космически кораби и пр.
Изкуството за мен е преди всичко начин за синтезиране на есенциата от някаква реалност, та в това ИИ може също да помогне със събирането и обработването на данни.
В бъдеще хората ще е добре да имат базова идея ор статистика и дата сайанс и вероятно бейсик програмиране (които аз нямам за сега) за да могат си играят с ИИ.
Вероятно ще се появят и интерфейси за идиоти и програмирането ще стане елементарно.
Трябва да науча малко пайтън и да поразцъкам някой от ИИ играчките със отворен код
March 8, 2024
Interesting reading for anyone who wants to take the first step towards AI and has little to cero knowledge in the field. This book provides an accessible introduction to Artificial Intelligence, Big Data, and Machine Learning, making it a perfect starting point for anyone with little to no prior knowledge. I enjoyed reading the first half of the book for its ability to explain basic concepts in a simple manner avoiding technical jargon. Although, the last half of the book feels dated.
Definitely not for intermediate or advance AI levels.
Definitely not for intermediate or advance AI levels.
July 3, 2021
foa, i'm a trained computer engineer. though my specialisation is in automation & control instead of AI per se, I'm far from being a noob, so please add salt to suit your situation.
i guess the book can be helpful to someone totally uninitiated on the subject of AI and doesn't intend to go too much deeper but if you want more. Surely there are better introductory books on the subject of AI, or intelligence in general
i guess the book can be helpful to someone totally uninitiated on the subject of AI and doesn't intend to go too much deeper but if you want more. Surely there are better introductory books on the subject of AI, or intelligence in general
June 9, 2023
Really shitty in terms of content. This book did not know who its audience was. Chapter 7 was little more than a list of software using AI in medicine, something that felt like a list one could find online, not something where I learned about how AI works. Chapters 2 and 3 felt like they were targeting a totally different audience, those who are experts and are thinking about cases in which they can use AI. This book felt like it had been written by an AI, not a human.
July 8, 2023
Essential reading for anyone interested in AI. Tells you what it can and can't do and it's the "can't do" that enthusiasts and other promoters need to read. As an aid and an assistant to everyday tasks and chores, AI is essential and that aspect of things will only increase and get better. But for those who want C-3PO or Robby the Robot around the house, you're going to have to wait, probably for a very long time.
January 5, 2024
AI is advancing so fast that the tech news in 2023 was all about AI.
This book was published in 2018.
It is now January 2024, so about 4 years have passed.
Thus, the book lacks the freshness of AI information.
Today's news is that the Windows keyboard will have an AI button.
This is the first time in 30 years that the keyboard design has changed.
News feeds are more useful for up-to-date information on AI like this, but essential learning is better learned in texts like this one.
This book was published in 2018.
It is now January 2024, so about 4 years have passed.
Thus, the book lacks the freshness of AI information.
Today's news is that the Windows keyboard will have an AI button.
This is the first time in 30 years that the keyboard design has changed.
News feeds are more useful for up-to-date information on AI like this, but essential learning is better learned in texts like this one.
June 6, 2024
This is not a book on working with AI, but a book about what AI is doing to make our lives better. From self-driving cars to medical breakthroughs, AI has been around since the 50s and has just recently started entering the public eye. Self-driving cars are having much success, but there are still bugs to work out, in medicine, it has allowed for faster diagnoses and quicker responses to life-threatening situations.
August 7, 2022
Part of the book requires some background on computer science and machine learning to understand, so it's not for any ordinary readers. I found it ok because I had such a background, but I sometimes still got confused. Also I found that the last portion of the book (Part 6) is repeating what it already discussed in earlier parts.
Other than that, the book is interesting to read.
Other than that, the book is interesting to read.
March 15, 2023
Provides an overview of AI applications and current limitations from the lens that really only serves the consumer. I may check out the “Machine Learning for Dummies� instead, as I was hoping this book would serve as starting point for a more technical breakdown.
Not poor quality, but wouldn’t recommend.
Not poor quality, but wouldn’t recommend.
June 28, 2023
There were a lot of interesting topics in this book. However there was a ton of repetition of the same ideas, it could have been a lot more concise. It would have been cool to follow more real life stories instead of quick tidbits on articles. I felt myself losing interest and having to force myself to keep moving, but maybe that’s just me.
February 21, 2025
I found it very shallow, unstructured with to much fluff in it, so I quit after maybe half of the book. The book tries to cover everything and because of that it stays pretty much on the surface. Sometimes less is more.
When reading it I didn’t have the impression that the authors are very proficient in the topic, I rather had the feeling that the content was generated with AI.
When reading it I didn’t have the impression that the authors are very proficient in the topic, I rather had the feeling that the content was generated with AI.
February 22, 2019
Feels like it was thrown together in a week from a collection of bullet points and web links. Not insightful, poorly edited (there’s a screen shot of a Word document with the spell check squiggly under a word, missing words, etc.), and just tedious to read through. I eventually gave up.
January 10, 2024
This is free on audible. Stopped reading when I realised it is published in 2018. A bit pointless given the progress in AI the last few years.
Also - the narration in audible is horrible. It sounds like it's read by an AI :)
Also - the narration in audible is horrible. It sounds like it's read by an AI :)
June 11, 2024
In my quest to read all the books I could get my hands on on the topic of artificial intelligence, I read this one, not expecting much from it. I was pleasantly surprised to find that it wasn't bad at all, contrary to the opinion I had perhaps unfairly formed of this series.
December 31, 2024
A very nice summary of the overall AI/ML space.
I appreciated the medium depth that this book goes into in a wide array of artificial intelligence and machine learning technologies and applications.
I appreciated the medium depth that this book goes into in a wide array of artificial intelligence and machine learning technologies and applications.
June 19, 2018
Nice one to start digging the subject
September 18, 2019
Good description of the core concepts, history and examples of artificial intelligence. Explains how much of the subject area is ‘hype.�
October 23, 2019
Fantastic and thorough look at the past, present, and future of AI for any interested reader.
January 27, 2020
Down-to-earth, well grounded, critical rendering of the state of the art and future possibilities that it allows to foresee. No exuberant fantasies. Clear and easy for the beginners in this field.
August 4, 2023
Quirky, fun, smart .... certainly a poitn of reference in my future with AI
Currently reading
October 8, 2023Bookmark...
9 Oct
Chapter 2
Defining the role of data
9 Oct
Chapter 2
Defining the role of data
Displaying 1 - 30 of 36 reviews
Can't find what you're looking for?
Get help and learn more about the design.