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AI Made Simple: A Beginner’s Guide to Generative Intelligence
Are you intrigued by the power of AI and want to explore its creative possibilities? Or are you new to this world and feeling a bit overwhelmed by this technology and how it could impact you? Either way, this book will tell you everything you need to know in simple, easy-to-understand language with lots of examples of actual content produced by Generative AI. Readers of AI Made Simple If you are ready to cut through the jargon to understand what Generative AI is all about and how you can use it to your advantage, AI Made Simple is for you. Scroll up to the top and order your copy today.
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238 pages, Paperback
Published May 5, 2024
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Displaying 1 - 14 of 14 reviews
August 2, 2025
average book on ai - use for bt
Generative AI is no longer a distant sci-fi dream. It’s writing code, designing campaigns, answering emails, and composing music – all in seconds.
most interesting part:
- according to some AI experts, artificial intelligence might be humanity’s true existential threat. In May 2023, over 350 AI executives, researchers, and engineers signed an open letter warning that their creation should be considered a societal risk on par with pandemics and nuclear war.
- Fears about AI often reflect the “Promethean myth” – the belief that powerful technology inevitably turns on its creators.
notes:
- AI isn’t just knocking at the door – it’s here inside the house. It’s writing your emails, recommending TV shows, and maybe even finishing your kids’ homework.
- What’s truly remarkable about these tools is their accessibility – anyone who can type a question into a search bar can use them.
- Most people already interact with AI in their daily lives without realizing it. FaceID technology, search engines, and fraud detection systems at banks – all of these use machine learning. ML enables computers to recognize and react to patterns, similar to how humans learn. When a child is taught what a fire hydrant is, they remember its appearance and can identify one later. ML works similarly – but it can only recognize patterns, not create new content.
- That leap has transformed how businesses operate. Companies now use Generative AI to automate repetitive tasks – increasing both efficiency and productivity. Generative AI also accelerates innovation with its ability to explore vast solution spaces, generate novel ideas, and optimize various processes.
- With little more than a browser and a prompt, anyone can experiment, build, and create.
- With tools like ChatGPT and Gemini now widely available, we’re entering a new era of work, creativity, and problem-solving. The challenge now is to learn how to use these tools thoughtfully – and prepare for a future they’re already helping shape.
- Like much of the internet it was trained on, it reflects both the brilliance and the flaws of human behavior.
- To get high-quality results, you have to speak its language. And that language is prompts.
- This process of giving feedback, rewording prompts, and adding instructions is called prompt chaining. Instead of expecting perfect results on the first try, you can iterate and refine, just as you would when collaborating with a human.
- DALL-E isn’t the only player in the game, either. Midjourney is known for its especially high-quality visuals and can be accessed through Discord, though it has a steeper learning curve and limited privacy. Getty Images offers a premium option trained on its own library for commercial use, while Adobe’s Firefly is integrated with Photoshop but has some image accuracy issues. Each tool offers different strengths depending on whether your focus is creative play or professional output.
- Generative AI isn’t limited to still images. In music, tools like AIVA, Boomy, Soundful, Mubert, and Soundraw let users create tracks using sliders or simple prompts.
- Generative AI tools are helping individuals and teams produce more with fewer resources. With a bit of practice, anyone can tap into these tools to expand their creative reach and bring bold ideas to life.
- Hallucinations highlight one of generative AI’s most serious limitations: it doesn’t actually “know” anything. It just predicts what to say based on patterns in its training data. That means it can produce plausible but entirely fictional information without indicating it’s doing so.
- Beyond accuracy issues, AI lacks the human elements that make communication meaningful
- Generative AI is evolving quickly and will keep changing the way we create, communicate, and work. But even as it grows more capable, it remains a tool and not a substitute for human judgment. Knowing its flaws and using it wisely is essential to ensuring it enhances our lives instead of complicating them.
- data-driven medicine will help discover new drugs at lower costs and enable precision medicine tailored to individual patients. Transportation will become safer and more efficient with autonomous vehicles. Education will be revolutionized through personalized AI teachers that can adapt to each student’s learning style. And immersive entertainment will reshape our leisure experiences.
- While risks like misinformation, bias, and job displacement are real, history shows new technologies tend to create more opportunities than they destroy. And verification tools and ethical guidelines are rapidly improving.
- If used wisely, AI could help solve our biggest challenges – from climate change to public health – while expanding creativity, democratizing knowledge, and advancing scientific discovery. As Microsoft CEO Satya Nadella says, “AI is just at the beginning of the S-curve.” Enormous possibilities lie ahead.
Generative AI is no longer a distant sci-fi dream. It’s writing code, designing campaigns, answering emails, and composing music – all in seconds.
most interesting part:
- according to some AI experts, artificial intelligence might be humanity’s true existential threat. In May 2023, over 350 AI executives, researchers, and engineers signed an open letter warning that their creation should be considered a societal risk on par with pandemics and nuclear war.
- Fears about AI often reflect the “Promethean myth” – the belief that powerful technology inevitably turns on its creators.
notes:
- AI isn’t just knocking at the door – it’s here inside the house. It’s writing your emails, recommending TV shows, and maybe even finishing your kids’ homework.
- What’s truly remarkable about these tools is their accessibility – anyone who can type a question into a search bar can use them.
- Most people already interact with AI in their daily lives without realizing it. FaceID technology, search engines, and fraud detection systems at banks – all of these use machine learning. ML enables computers to recognize and react to patterns, similar to how humans learn. When a child is taught what a fire hydrant is, they remember its appearance and can identify one later. ML works similarly – but it can only recognize patterns, not create new content.
- That leap has transformed how businesses operate. Companies now use Generative AI to automate repetitive tasks – increasing both efficiency and productivity. Generative AI also accelerates innovation with its ability to explore vast solution spaces, generate novel ideas, and optimize various processes.
- With little more than a browser and a prompt, anyone can experiment, build, and create.
- With tools like ChatGPT and Gemini now widely available, we’re entering a new era of work, creativity, and problem-solving. The challenge now is to learn how to use these tools thoughtfully – and prepare for a future they’re already helping shape.
- Like much of the internet it was trained on, it reflects both the brilliance and the flaws of human behavior.
- To get high-quality results, you have to speak its language. And that language is prompts.
- This process of giving feedback, rewording prompts, and adding instructions is called prompt chaining. Instead of expecting perfect results on the first try, you can iterate and refine, just as you would when collaborating with a human.
- DALL-E isn’t the only player in the game, either. Midjourney is known for its especially high-quality visuals and can be accessed through Discord, though it has a steeper learning curve and limited privacy. Getty Images offers a premium option trained on its own library for commercial use, while Adobe’s Firefly is integrated with Photoshop but has some image accuracy issues. Each tool offers different strengths depending on whether your focus is creative play or professional output.
- Generative AI isn’t limited to still images. In music, tools like AIVA, Boomy, Soundful, Mubert, and Soundraw let users create tracks using sliders or simple prompts.
- Generative AI tools are helping individuals and teams produce more with fewer resources. With a bit of practice, anyone can tap into these tools to expand their creative reach and bring bold ideas to life.
- Hallucinations highlight one of generative AI’s most serious limitations: it doesn’t actually “know” anything. It just predicts what to say based on patterns in its training data. That means it can produce plausible but entirely fictional information without indicating it’s doing so.
- Beyond accuracy issues, AI lacks the human elements that make communication meaningful
- Generative AI is evolving quickly and will keep changing the way we create, communicate, and work. But even as it grows more capable, it remains a tool and not a substitute for human judgment. Knowing its flaws and using it wisely is essential to ensuring it enhances our lives instead of complicating them.
- data-driven medicine will help discover new drugs at lower costs and enable precision medicine tailored to individual patients. Transportation will become safer and more efficient with autonomous vehicles. Education will be revolutionized through personalized AI teachers that can adapt to each student’s learning style. And immersive entertainment will reshape our leisure experiences.
- While risks like misinformation, bias, and job displacement are real, history shows new technologies tend to create more opportunities than they destroy. And verification tools and ethical guidelines are rapidly improving.
- If used wisely, AI could help solve our biggest challenges – from climate change to public health – while expanding creativity, democratizing knowledge, and advancing scientific discovery. As Microsoft CEO Satya Nadella says, “AI is just at the beginning of the S-curve.” Enormous possibilities lie ahead.
Read
July 1, 2025In "AI Made Simple: A Beginner's Guide to Generative Intelligence", Rajeev Kapur delivers a practical, digestible overview of a rapidly advancing technology that’s already shaping daily life and professional landscapes. The book offers an entry point into the world of generative artificial intelligence, showing readers how tools like ChatGPT and DALL·E can perform tasks ranging from writing and design to coding and music composition. What once seemed like futuristic speculation is now an integral part of the workplace and creative industries. Kapur’s message is clear: AI is not waiting for anyone to catch up. It’s here, and it’s changing how people think, work, and solve problems. But as exciting as the technology is, many are still unsure of what AI actually is, how it functions, or how to use it without getting left behind. This book addresses those gaps with accessible explanations and real-world examples.
At its core, generative AI refers to systems that can create entirely new content – whether that’s text, visuals, sound, or even video – based on patterns it’s learned from large datasets. Unlike traditional AI that mainly recognizes and processes information, generative models like ChatGPT go a step further by producing original outputs. This leap allows businesses to automate complex workflows, creators to explore new artistic possibilities, and individuals to accomplish tasks once thought to require human ingenuity. Anyone with a basic internet connection and the ability to type a prompt can now access advanced tools previously reserved for specialists. This accessibility is leveling the playing field in sectors ranging from education and journalism to marketing and entrepreneurship.
However, this immense power comes with serious ethical and practical concerns. One key issue is ownership – if an AI generates a painting, song, or article, who actually owns it? The original creator of the training data? The person who wrote the prompt? Legal and moral questions abound. Another worry is misinformation. Because generative AI systems can produce content quickly and convincingly, they’re also capable of spreading falsehoods at scale. These challenges demand not just technical solutions, but thoughtful public discussion and policy. Kapur makes it clear that the rise of generative AI may be as significant as past paradigm shifts like the internet or the Industrial Revolution.
For those new to this field, Kapur offers step-by-step guidance on how to begin using generative AI tools, focusing mainly on ChatGPT. Starting is simple: visit the platform, create an account, and start experimenting with different prompts. The key to mastering these systems lies in repetition and experimentation. ChatGPT’s responses are only as good as the inputs it receives, and learning to fine-tune those inputs is essential. The platform also includes features like temperature settings, which affect how creative or factual a response will be, and token limits that can constrain output length. Kapur explains how the more you practice writing effective prompts, the better your results become.
ChatGPT is not perfect. It can’t browse the real-time internet unless equipped with a special browsing feature, and sometimes it generates answers that are wrong or misleading while sounding completely confident. These 'hallucinations' are one of the technology’s major limitations. Generative AI works by predicting patterns, not by accessing facts. So it may invent convincing but fictional details, a flaw that users must always watch out for. Even so, when used with care, ChatGPT is a valuable asset that can help with tasks ranging from idea generation and editing to research and planning.
Beyond text, generative AI also excels at visual and audio creation. Tools like DALL·E can turn written prompts into stunning images, allowing users to create artwork, ads, or illustrations without needing design skills. Other platforms like Midjourney and Adobe Firefly offer alternatives, each with different strengths. In music, applications like Boomy, Soundraw, and Mubert let users compose original tracks, making professional-level audio more accessible than ever. For video, tools such as Fliki, Descript, and Runway allow even amateurs to script, shoot, and edit high-quality videos using only a few inputs. However, these tools also raise red flags. AI-generated media has already fooled millions – such as fake songs featuring celebrity voices and deepfake videos used to commit fraud or influence elections.
Much of the book focuses on the art of crafting effective prompts. This is where users must learn to be both clear and strategic. A vague request like 'Write a blog post' will yield a bland, generic output. But a detailed prompt with background context, tone, length constraints, and specific instructions can result in something surprisingly personalized and useful. Kapur introduces concepts like 'prompt chaining' – refining your instructions over several interactions – and 'prompt engineering,' which is the deliberate practice of optimizing AI input to steer output quality. This skill, Kapur suggests, will soon become as vital as knowing how to write an email or use a spreadsheet.
Kapur doesn’t shy away from AI’s darker aspects. He cites troubling examples: a lawyer submitting fake legal citations generated by ChatGPT, a rabbi fooling congregants with an AI-written sermon, and an AI producing racist content when prompted with misleading instructions. These instances demonstrate how easily the system can be abused or manipulated. Even with guardrails, generative AI reflects the biases, misinformation, and toxic behaviors found in its training data. That makes oversight and user responsibility crucial. There’s also the environmental cost: training a single large model can emit more carbon than several cars produce over their entire lifetimes.
Still, despite the dangers, Kapur remains cautiously optimistic. He highlights breakthroughs like AI-assisted drug discovery, where algorithms rapidly analyzed chemical compounds and led scientists to a promising new antibiotic. This feat would have taken humans years to accomplish alone. AI, in this view, becomes a force multiplier – not a replacement for human intelligence, but a complement to it. He references how professional Go players improved their strategy after being beaten by DeepMind’s AlphaGo, showing that exposure to intelligent systems can push people to greater levels of performance.
As the technology continues to evolve, Kapur emphasizes that human values, creativity, and responsibility must remain at the center. AI doesn’t possess awareness or intention; it is a powerful tool shaped by its users. The dangers it poses – misinformation, bias, job displacement – are real, but not inevitable. With proper regulation, ethical design, and user education, AI can help solve global challenges, boost productivity, and enable new forms of expression. Rather than fear the future, Kapur urges readers to engage with it actively, learning the tools and shaping how they’re used.
In conclusion, "AI Made Simple" is both a guidebook and a call to action. It demystifies the inner workings of generative AI while emphasizing its relevance across industries and creative fields. Kapur’s writing encourages readers to see AI not as a threat, but as a partner – a tool that, if used thoughtfully, can unlock vast new possibilities. But to benefit from it, we must first understand it, experiment with it, and confront its risks with clarity and caution. This book is a timely invitation to do just that.
At its core, generative AI refers to systems that can create entirely new content – whether that’s text, visuals, sound, or even video – based on patterns it’s learned from large datasets. Unlike traditional AI that mainly recognizes and processes information, generative models like ChatGPT go a step further by producing original outputs. This leap allows businesses to automate complex workflows, creators to explore new artistic possibilities, and individuals to accomplish tasks once thought to require human ingenuity. Anyone with a basic internet connection and the ability to type a prompt can now access advanced tools previously reserved for specialists. This accessibility is leveling the playing field in sectors ranging from education and journalism to marketing and entrepreneurship.
However, this immense power comes with serious ethical and practical concerns. One key issue is ownership – if an AI generates a painting, song, or article, who actually owns it? The original creator of the training data? The person who wrote the prompt? Legal and moral questions abound. Another worry is misinformation. Because generative AI systems can produce content quickly and convincingly, they’re also capable of spreading falsehoods at scale. These challenges demand not just technical solutions, but thoughtful public discussion and policy. Kapur makes it clear that the rise of generative AI may be as significant as past paradigm shifts like the internet or the Industrial Revolution.
For those new to this field, Kapur offers step-by-step guidance on how to begin using generative AI tools, focusing mainly on ChatGPT. Starting is simple: visit the platform, create an account, and start experimenting with different prompts. The key to mastering these systems lies in repetition and experimentation. ChatGPT’s responses are only as good as the inputs it receives, and learning to fine-tune those inputs is essential. The platform also includes features like temperature settings, which affect how creative or factual a response will be, and token limits that can constrain output length. Kapur explains how the more you practice writing effective prompts, the better your results become.
ChatGPT is not perfect. It can’t browse the real-time internet unless equipped with a special browsing feature, and sometimes it generates answers that are wrong or misleading while sounding completely confident. These 'hallucinations' are one of the technology’s major limitations. Generative AI works by predicting patterns, not by accessing facts. So it may invent convincing but fictional details, a flaw that users must always watch out for. Even so, when used with care, ChatGPT is a valuable asset that can help with tasks ranging from idea generation and editing to research and planning.
Beyond text, generative AI also excels at visual and audio creation. Tools like DALL·E can turn written prompts into stunning images, allowing users to create artwork, ads, or illustrations without needing design skills. Other platforms like Midjourney and Adobe Firefly offer alternatives, each with different strengths. In music, applications like Boomy, Soundraw, and Mubert let users compose original tracks, making professional-level audio more accessible than ever. For video, tools such as Fliki, Descript, and Runway allow even amateurs to script, shoot, and edit high-quality videos using only a few inputs. However, these tools also raise red flags. AI-generated media has already fooled millions – such as fake songs featuring celebrity voices and deepfake videos used to commit fraud or influence elections.
Much of the book focuses on the art of crafting effective prompts. This is where users must learn to be both clear and strategic. A vague request like 'Write a blog post' will yield a bland, generic output. But a detailed prompt with background context, tone, length constraints, and specific instructions can result in something surprisingly personalized and useful. Kapur introduces concepts like 'prompt chaining' – refining your instructions over several interactions – and 'prompt engineering,' which is the deliberate practice of optimizing AI input to steer output quality. This skill, Kapur suggests, will soon become as vital as knowing how to write an email or use a spreadsheet.
Kapur doesn’t shy away from AI’s darker aspects. He cites troubling examples: a lawyer submitting fake legal citations generated by ChatGPT, a rabbi fooling congregants with an AI-written sermon, and an AI producing racist content when prompted with misleading instructions. These instances demonstrate how easily the system can be abused or manipulated. Even with guardrails, generative AI reflects the biases, misinformation, and toxic behaviors found in its training data. That makes oversight and user responsibility crucial. There’s also the environmental cost: training a single large model can emit more carbon than several cars produce over their entire lifetimes.
Still, despite the dangers, Kapur remains cautiously optimistic. He highlights breakthroughs like AI-assisted drug discovery, where algorithms rapidly analyzed chemical compounds and led scientists to a promising new antibiotic. This feat would have taken humans years to accomplish alone. AI, in this view, becomes a force multiplier – not a replacement for human intelligence, but a complement to it. He references how professional Go players improved their strategy after being beaten by DeepMind’s AlphaGo, showing that exposure to intelligent systems can push people to greater levels of performance.
As the technology continues to evolve, Kapur emphasizes that human values, creativity, and responsibility must remain at the center. AI doesn’t possess awareness or intention; it is a powerful tool shaped by its users. The dangers it poses – misinformation, bias, job displacement – are real, but not inevitable. With proper regulation, ethical design, and user education, AI can help solve global challenges, boost productivity, and enable new forms of expression. Rather than fear the future, Kapur urges readers to engage with it actively, learning the tools and shaping how they’re used.
In conclusion, "AI Made Simple" is both a guidebook and a call to action. It demystifies the inner workings of generative AI while emphasizing its relevance across industries and creative fields. Kapur’s writing encourages readers to see AI not as a threat, but as a partner – a tool that, if used thoughtfully, can unlock vast new possibilities. But to benefit from it, we must first understand it, experiment with it, and confront its risks with clarity and caution. This book is a timely invitation to do just that.
November 10, 2023
Get ahead and learn AI before you get left behind
Rajeev explains the many different uses of current AI products today and weighs the benefits and drawbacks of them.
This book will give you a beginner-friendly understanding of Generative AI and all of its potential applications.
As you swipe through this review, you will see how Rajeev outlines the use of AI for developing digital art to craft your resume and cover letter to the importance of it in leadership today.
Don’t worry about AI taking your job because the technology is wiser than you but you should worry about losing your job to another human who understands how to leverage this amazing tool more than yourself.
Don’t fall behind by avoiding to learn how to use AI for your own gain and to better our world as a whole.
Highly recommend his book!
Rajeev explains the many different uses of current AI products today and weighs the benefits and drawbacks of them.
This book will give you a beginner-friendly understanding of Generative AI and all of its potential applications.
As you swipe through this review, you will see how Rajeev outlines the use of AI for developing digital art to craft your resume and cover letter to the importance of it in leadership today.
Don’t worry about AI taking your job because the technology is wiser than you but you should worry about losing your job to another human who understands how to leverage this amazing tool more than yourself.
Don’t fall behind by avoiding to learn how to use AI for your own gain and to better our world as a whole.
Highly recommend his book!
January 13, 2026
A vastly over-promoted, under-delivered promise of easy access to AI and its use in the LLMs of today. The history of AI development is skipped over, omitting key figures who made the advances facilitating rapid training of LLMs. Much bombast about the impact of AI.
This book focuses on getting you to use the available commercial "AI" products and apply them for daily tasks.
There must be better books for teaching non-technical people about AI and LLMs. This is not one of them.
For reference, I hold a Ph.D. in Computer Science and worked in the computer industry for 30 years.
This book focuses on getting you to use the available commercial "AI" products and apply them for daily tasks.
There must be better books for teaching non-technical people about AI and LLMs. This is not one of them.
For reference, I hold a Ph.D. in Computer Science and worked in the computer industry for 30 years.
October 28, 2023
Are you ready for the next Age of Enlightenment?
Because ready or not, we are already in it with the creation of Generative AI!
If you are intrigued by the almost limitless potential of AI technology or terrified how it will impact you, this book is one you need to read. The author explains the many different uses of current AI products today and weighs the benefits and drawbacks of them. AI Made Simple is the perfect way to get familiarized with this new incredible technology.
Because ready or not, we are already in it with the creation of Generative AI!
If you are intrigued by the almost limitless potential of AI technology or terrified how it will impact you, this book is one you need to read. The author explains the many different uses of current AI products today and weighs the benefits and drawbacks of them. AI Made Simple is the perfect way to get familiarized with this new incredible technology.
December 24, 2023
This is an okay and very basic introduction to generative AI. Just what I needed. I’m now looking for my next book about AI. I’ve tried ChatGPT and, so far, haven’t been impressed (generic text and some absolutely wrong information). But I do believe the field is exploding and will transform our lives.
January 1, 2024
Not much depth but scratches the surface - good enough as a exec read
April 26, 2025
Dated and Biased: Not Recommended
This book is going to need a lot of updates and new editions, and I'm sure the author would be exuberant about updating it. In new revolutionary industries, there's a lot of fraud and money-grabs. Time, the great equalizer, has not done her part in separating the venal from the ethical, and the potent from the artificial. Let me be clear: I'm not saying the author is a fraud. I do not know. Furthermore, the book is not a covert sales pitch. The only thing the author is unethically selling is perhaps this book. It depends how he does it though, but on Amazon it states: "this book will tell you everything you need to know in simple, easy-to-understand language with lots of examples of actual content produced by Generative AI." This is simply not true.
Unfortunately, I read this text, and a big part of that is my fault. To prospective readers: never, ever read a book that is filled with modern examples in an entirely new industry.
Now to the actual content: I'd estimate that over 70% of the content has to do with modern examples and AI prompts that anyone can do. There's no insight whatsoever in watching somebody prompt random things. There are issues even with the prompts: It's not an inherently bad thing to use ChatGPT, but why only it? There are other language models with impressive capabilities and different strengths/weaknesses. The machine is only as good as its builder, and OpenAI has been proven to be biased. That doesn't mean it's bad or not useful for examples, but more could have been used. What is the reason to funnel prospective readers into ChatGPT? Why would a (as I write this review) clearly biased language model have a monopolistic hold over the author's example outputs? Well, there's a reason why the author can flagrantly ignore the bias, and that's because the author is biased himself.
As I write this review, if you had ordered this book and waited for it to be shipped to your home over the last few years, there's more than a 1% chance that ChatGPT's model would have been upgraded. The upgrades are pretty significant, so who would endeavor to write a book on something as mutable as a specific AI model? I'm not against practicality, but the author should have taught a course.
When buying a book like this, I'd expect much more technicality and history. And that could have been done in the simplest way possible. You know what? Maybe it's a subject that just can't be explained simply enough for somebody with no background in basic mathematics and AI. And perhaps it's unsuitable for someone who would want to at least put forth a bit of effort in learning it. Then so be it! Why write a book that would maybe be suitable for a 2nd grader? The author couldn't have possibly dumbed it down more—to the point of giving you no actual insight into what AI fundamentally is.
This book gets a 1-star review because the intended audience—say a 55-year-old woman who has never had any technical expertise—would have been much better off reading an internet article or taking a small and short course. And frankly, the 8-year-olds don't need to know this. They will adapt and learn something much newer and more advanced by the time they get around to it.
This book is going to need a lot of updates and new editions, and I'm sure the author would be exuberant about updating it. In new revolutionary industries, there's a lot of fraud and money-grabs. Time, the great equalizer, has not done her part in separating the venal from the ethical, and the potent from the artificial. Let me be clear: I'm not saying the author is a fraud. I do not know. Furthermore, the book is not a covert sales pitch. The only thing the author is unethically selling is perhaps this book. It depends how he does it though, but on Amazon it states: "this book will tell you everything you need to know in simple, easy-to-understand language with lots of examples of actual content produced by Generative AI." This is simply not true.
Unfortunately, I read this text, and a big part of that is my fault. To prospective readers: never, ever read a book that is filled with modern examples in an entirely new industry.
Now to the actual content: I'd estimate that over 70% of the content has to do with modern examples and AI prompts that anyone can do. There's no insight whatsoever in watching somebody prompt random things. There are issues even with the prompts: It's not an inherently bad thing to use ChatGPT, but why only it? There are other language models with impressive capabilities and different strengths/weaknesses. The machine is only as good as its builder, and OpenAI has been proven to be biased. That doesn't mean it's bad or not useful for examples, but more could have been used. What is the reason to funnel prospective readers into ChatGPT? Why would a (as I write this review) clearly biased language model have a monopolistic hold over the author's example outputs? Well, there's a reason why the author can flagrantly ignore the bias, and that's because the author is biased himself.
As I write this review, if you had ordered this book and waited for it to be shipped to your home over the last few years, there's more than a 1% chance that ChatGPT's model would have been upgraded. The upgrades are pretty significant, so who would endeavor to write a book on something as mutable as a specific AI model? I'm not against practicality, but the author should have taught a course.
When buying a book like this, I'd expect much more technicality and history. And that could have been done in the simplest way possible. You know what? Maybe it's a subject that just can't be explained simply enough for somebody with no background in basic mathematics and AI. And perhaps it's unsuitable for someone who would want to at least put forth a bit of effort in learning it. Then so be it! Why write a book that would maybe be suitable for a 2nd grader? The author couldn't have possibly dumbed it down more—to the point of giving you no actual insight into what AI fundamentally is.
This book gets a 1-star review because the intended audience—say a 55-year-old woman who has never had any technical expertise—would have been much better off reading an internet article or taking a small and short course. And frankly, the 8-year-olds don't need to know this. They will adapt and learn something much newer and more advanced by the time they get around to it.
October 8, 2024
The irony is that ChatGPT could have written this book -- and much of it did come straight out of its mouth! :P
Most of it is shallow regurgitation of what you already see in the news, on tech blogs, and through X/Twitter posts. Every chapter discusses some capability of ChatGPT, like writing, image creation, or music composition, but it never actually tells you how to activate any of this in your work. Instead, it stays surface level, like someone sipping coffee and relaying interesting gossip. Examples:
"Take some time to explore the platform so you can further understand its capabilities, limitations, and features. Learn how to format your prompts, and familiarize yourself with any adjustable settings, such as temperature and a Max Tokens amount."
"If you were going to compare, you could say that the old chatbot is like a horse and buggy, while ChatGPT is more like a sleek Lamborghini. It can take you for an amazing ride- if you know how to get the most of it."
"If you want to be alarmist, it's almost like ChatGPT is God."
"If you want to go beyond what's written here, take a look at the amazing YouTube videos users have posted that give you examples and offer more in-depth training."
"The more vivid descriptions you give the tool, the more likely you'll get the music you're after."
"Any corporation can develop a plugin and make it available to ChatGPT users."
This is all just wind. Vapid statements that provide no insight, new knowledge, or inspiration to use a tool toward some stated end goal. Without drilling deeper -- What coding language? What IDE should I install? What APIs are available? What platforms supported? How the SDK works? Examples of optimal prompt engineering? -- the book is nothing but a series of superficial observations already available via mainstream media. I have no better understanding of how to harness generative AI, or where to begin developing for it, aside from asking ChatGPT questions.
Even worse, every few pages, the author Rajeev Kapur asks ChatGPT some random question, and copy/pastes the entire response into the book, wasting another 2-3 pages for random useless content. News flash: Your readers already know how to use ChatGPT. They didn't buy a book to read what ChatGPT advises about finding true love. Total waste of paper, ink, and time.
The worst part is all the useless philosophy about whether or not AI will take over the world and dominate the human race. This is such dystopian nonsense that this book borderline straddles fiction. Save your hypotheses and pontification for the National Enquirer, Forbes, or Reader's Digest. But if you want to know where to begin developing or creating, how to do so, and see hands-on examples, this book gives you nothing.
Its one saving grace is that it namedrops tools that use generative AI, such as Ellie, Fireflies, Murf, GhostWryter, Heyday, Wordtune Read, Regie AI, Soundful, Soundraw, Boomy, and MusicLM.
But I could have just asked ChatGPT for that list.
(And you still have to explore and try them yourself, as the book says nothing about applying them skillfully to solve a problem.)
Most of it is shallow regurgitation of what you already see in the news, on tech blogs, and through X/Twitter posts. Every chapter discusses some capability of ChatGPT, like writing, image creation, or music composition, but it never actually tells you how to activate any of this in your work. Instead, it stays surface level, like someone sipping coffee and relaying interesting gossip. Examples:
"Take some time to explore the platform so you can further understand its capabilities, limitations, and features. Learn how to format your prompts, and familiarize yourself with any adjustable settings, such as temperature and a Max Tokens amount."
"If you were going to compare, you could say that the old chatbot is like a horse and buggy, while ChatGPT is more like a sleek Lamborghini. It can take you for an amazing ride- if you know how to get the most of it."
"If you want to be alarmist, it's almost like ChatGPT is God."
"If you want to go beyond what's written here, take a look at the amazing YouTube videos users have posted that give you examples and offer more in-depth training."
"The more vivid descriptions you give the tool, the more likely you'll get the music you're after."
"Any corporation can develop a plugin and make it available to ChatGPT users."
This is all just wind. Vapid statements that provide no insight, new knowledge, or inspiration to use a tool toward some stated end goal. Without drilling deeper -- What coding language? What IDE should I install? What APIs are available? What platforms supported? How the SDK works? Examples of optimal prompt engineering? -- the book is nothing but a series of superficial observations already available via mainstream media. I have no better understanding of how to harness generative AI, or where to begin developing for it, aside from asking ChatGPT questions.
Even worse, every few pages, the author Rajeev Kapur asks ChatGPT some random question, and copy/pastes the entire response into the book, wasting another 2-3 pages for random useless content. News flash: Your readers already know how to use ChatGPT. They didn't buy a book to read what ChatGPT advises about finding true love. Total waste of paper, ink, and time.
The worst part is all the useless philosophy about whether or not AI will take over the world and dominate the human race. This is such dystopian nonsense that this book borderline straddles fiction. Save your hypotheses and pontification for the National Enquirer, Forbes, or Reader's Digest. But if you want to know where to begin developing or creating, how to do so, and see hands-on examples, this book gives you nothing.
Its one saving grace is that it namedrops tools that use generative AI, such as Ellie, Fireflies, Murf, GhostWryter, Heyday, Wordtune Read, Regie AI, Soundful, Soundraw, Boomy, and MusicLM.
But I could have just asked ChatGPT for that list.
(And you still have to explore and try them yourself, as the book says nothing about applying them skillfully to solve a problem.)
December 31, 2023
A pretty good introduction to generative AI that I downloaded for a buck and read in less than a couple hours. It’s exactly what I was looking for, a gentle, approachable, and fairly forgettable book that explains AI in extremely simple terms. It describes all of the generative AI models (such as GPT and BERT), explains the advantages and benefits of AI, describes how to start using generative AI, gives the basics of prompt writing and prompt engineering, provides an overview of the uses of generative AI to create art and music, and summarizes the specialized generative AI tools you can use to accomplish specific tasks (such as Ellie and Heyday). Of course, it's an extremely high-level book and it's overly optimistic about the impact generative AI will have on society, downplaying its limitations, ethical concerns, and apocalyptic scenarios. It's probably not the best book on AI, but it's a good starter book for anyone exploring generative AI. The book includes many bland and impersonal examples written by ChatGPT that unfortunately tend to dampen anyone's enthusiasm for the technology.
May 8, 2024
fantastic book
An absolute must read for anyone trying to understand this evolving world of technology. As a business owner it is crucial that I stay up to date on what’s going on in the world of AI and this was a truly fantastic read! I highly recommend to anyone looking to expand their knowledge on the topic.
An absolute must read for anyone trying to understand this evolving world of technology. As a business owner it is crucial that I stay up to date on what’s going on in the world of AI and this was a truly fantastic read! I highly recommend to anyone looking to expand their knowledge on the topic.
June 20, 2024
Good AI Introduction for any level
Simple, straightforward and more importantly, balanced in the presentation of the capabilities, limitations and risks associated with AI. Some “acronym” jargon, but that is everywhere and the back of the book is a good glossary. Want to. Get a feel for what AI is and where it may head? Start here
Simple, straightforward and more importantly, balanced in the presentation of the capabilities, limitations and risks associated with AI. Some “acronym” jargon, but that is everywhere and the back of the book is a good glossary. Want to. Get a feel for what AI is and where it may head? Start here
August 25, 2024
Excelente libro para principiantes
Me ha ayudado a entender lo que realmente es AI. Solo tenia ideas limitadas sobre el tema, ahora entiendo el potencial de esta herramienta. Lo próximo aprender a utilizar AI.
Me ha ayudado a entender lo que realmente es AI. Solo tenia ideas limitadas sobre el tema, ahora entiendo el potencial de esta herramienta. Lo próximo aprender a utilizar AI.
June 12, 2024
A basic introduction to the challenges and benefits of generative AI. A good start for learning about this new science.
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