When most of us think about artificial intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that artificial intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate.
In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible - and possibly terrifying - future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to widen to include intelligent machines.
©2017 Luke Dormehl (P)2017 HighBridge, a Division of Recorded Books
This book is a trivial compilation of a bunch of loosely coonected topics, with no depth. Clearly the author does not have technical background in the topic, thus unable to be selective or focused. Full of name/date droppings.
It feels as if someone did a Google search and patched the results into a book, with some writing skills.
Quite disappointing and painful to listen to the entire book.
There are a number of non-technical writers that have written outstanding books around science and technology, but this is not even close.
l'enfer c'est les autres
There's nothing in this book for which I could recommend it. There's a little history of AI and multiple news stories from the recent press all probably familiar to most listeners. The world is changing and networks and AI are happening, but at the most the author only gives surface explanations for what's really going on. There is a story to be told for what's happening, but the author only seems to get the current events in themselves but can't tie them together and is out of his depth when it comes to connecting the dots.
There is a revolution going on right now. The author talks a little bit about Google and its language translation program. He does talk about how the 'machine learning' algorithms made the translator problem solvable and more robust then the previous expert system approach, but he can't take the listener beyond platitudes when he talks about that or other current happenings in the field.
He thinks future teaching should consider that students don't need to remember facts as much since they can always look dates and such up off of the internet. But, I would say that if the student doesn't understand the context that comes from the connections that knowing the facts bring, then they will not understand the meaning of what is really going on. Ironically, that belief contributes to why the author could not connect the dots and wrote such a substandard book that really should be ignored by people who love this topic as much as I do.
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