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funny
informative
medium-paced
funny
informative
lighthearted
fast-paced
funny
informative
fast-paced
This is a really engaging introduction to AI, mixing lighthearted examples with the more serious consequences. I really enjoyed this book, and would definitely recommend it as an intro to machine learning for anyone interested.
This is an excellent overview of the process and problems with AI as well as where they are useful and where they are not. I also think it's a necessary follow-up read for those who've read "Weapons of Math Destruction"--it's much better at explaining how biases happen within an algorithm--and it also helps disperse the fears of AIs taking over the world (though it does also show how mimicking their coders can lead to unforeseen as well as invisible results). It adds a great deal of much needed perspective to the AI discussions.
"You Look Like a Thing and I Love You" is a great, quick read for anyone who is even remotely curious about what things like AI, machine learning or neural networks actually mean and how it affects your day-to-day life.
Whether it's facial recognition, to self-driving cars, to the search results you get from Google, this book describes the different types of machine learning algorithms, often in a humorous way (the first few pages deal with the author trying to generate pick-up lines using a neural network -- hence the title of this book).
It's a quick read and dives into some of the limitations that machine learning algorithms are bound by and how machine learning algorithms can be tricked, return results outside the parameters of a problem, or even cheat (e.g., when one AI agent was given an objective to minimize the number of times a character died in a video game, it found out how to simply pause the game).
One particular section of the book talks about the recently released GPT-2 data model by OpenAI, which can be used to generate fairly intelligent and coherent sounding blocks of text. It prompted me to try and run the model on my own machine.
After giving the model a prompt of "machine learning can be scary," the computer responded with the following block of text: "The problem is, it's easy to forget that we can't avoid the problem with software. It's often hard to avoid the problem, but knowing how to avoid it is not the same as knowing how to avoid it. The problem is, the problem is easy to avoid, but the problem is hard to avoid."
Do we need to worry about robot overlords any time soon? Probably not.
This is a book that I'd recommend to both people who are tech savvy and to parents who might still call you with questions on how to turn on a computer... or at least anyone curious to how machine learning affects various aspects of our lives.
Whether it's facial recognition, to self-driving cars, to the search results you get from Google, this book describes the different types of machine learning algorithms, often in a humorous way (the first few pages deal with the author trying to generate pick-up lines using a neural network -- hence the title of this book).
It's a quick read and dives into some of the limitations that machine learning algorithms are bound by and how machine learning algorithms can be tricked, return results outside the parameters of a problem, or even cheat (e.g., when one AI agent was given an objective to minimize the number of times a character died in a video game, it found out how to simply pause the game).
One particular section of the book talks about the recently released GPT-2 data model by OpenAI, which can be used to generate fairly intelligent and coherent sounding blocks of text. It prompted me to try and run the model on my own machine.
After giving the model a prompt of "machine learning can be scary," the computer responded with the following block of text: "The problem is, it's easy to forget that we can't avoid the problem with software. It's often hard to avoid the problem, but knowing how to avoid it is not the same as knowing how to avoid it. The problem is, the problem is easy to avoid, but the problem is hard to avoid."
Do we need to worry about robot overlords any time soon? Probably not.
This is a book that I'd recommend to both people who are tech savvy and to parents who might still call you with questions on how to turn on a computer... or at least anyone curious to how machine learning affects various aspects of our lives.
funny
informative
lighthearted
fast-paced
I would argue that the neural network is in fact EXCELLENT at naming cats.
A fascinating overview of AI today. Easy to read and easy to understand, the book lays out just what is AI and perhaps importantly these days what isn't AI. Some of the examples and stories are fab and all torn from real-life and sometimes the headlines.
Beware of giraffes...
And also, what a fabulous title!
Beware of giraffes...
And also, what a fabulous title!
All my reviews live at https://deedispeaking.com/reads/.
I read You Look Like a Thing and I Love You as part of my subscription to the Next Big Idea Club, which is curated by Malcolm Gladwell, Adam Grant, Susan Cain, and Daniel Pink. I thought it was an interesting little book that told me a lot of quirky stories about AI, and gave me a bit more vocabulary with which to discuss AI. I didn’t necessarily learn anything life-changing, but I did find myself entertained.
Janelle Shane runs a blog called AI Weirdness, where she draws cute and funny cartoons and reports on the weird and also funny results of AI experiments. This book is really an extension of that blog, or maybe a more organized precursor. She goes through systematically to explain what AI is (and what it isn’t) and what it can do (and what it cannot, and why). She gives fun examples to illustrate. For example, “you look like a thing and I love you” was an AI algorithm’s attempt to write a pick-up line.
Admittedly, I listened to this one’s audiobook, so I missed out on a lot of the cute cartoons that pepper the book’s pages as well. But while I think they would have added smiles, I don’t know that they would have added much substance.
If you know absolutely nothing about AI (which, you might surprise yourself actually), then this book could be really eye-opening for you. But if you’re even a bit familiar, I thought this book felt more like novelty knowledge. Still, that can be fun, too (and it was)!
I read You Look Like a Thing and I Love You as part of my subscription to the Next Big Idea Club, which is curated by Malcolm Gladwell, Adam Grant, Susan Cain, and Daniel Pink. I thought it was an interesting little book that told me a lot of quirky stories about AI, and gave me a bit more vocabulary with which to discuss AI. I didn’t necessarily learn anything life-changing, but I did find myself entertained.
Janelle Shane runs a blog called AI Weirdness, where she draws cute and funny cartoons and reports on the weird and also funny results of AI experiments. This book is really an extension of that blog, or maybe a more organized precursor. She goes through systematically to explain what AI is (and what it isn’t) and what it can do (and what it cannot, and why). She gives fun examples to illustrate. For example, “you look like a thing and I love you” was an AI algorithm’s attempt to write a pick-up line.
Admittedly, I listened to this one’s audiobook, so I missed out on a lot of the cute cartoons that pepper the book’s pages as well. But while I think they would have added smiles, I don’t know that they would have added much substance.
If you know absolutely nothing about AI (which, you might surprise yourself actually), then this book could be really eye-opening for you. But if you’re even a bit familiar, I thought this book felt more like novelty knowledge. Still, that can be fun, too (and it was)!
Presented in the same witty and engaging way as the blog that inspired it, AIweirdness. Well structured and suiting the longer format, with interesting relevant case studies.
funny
informative
medium-paced