How Smart Machines Think

De: Sean Gerrish, Kevin Scott - foreword

Narrado por: Timothy Andrés Pabon

Duración: 9 h y 5 m

Resumen del Editor

The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, and computer programs can be trained to play Atari games. But how do all these things work? 

In this audiobook, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. 

Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine; and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. 

He explains how artificial neural networks enable computers to perceive the world - and to play Atari video games better than humans. Gerrish weaves the stories behind these breakthroughs into the narrative, introducing listeners to many of the researchers involved and keeping technical details to a minimum. 

Science and technology buffs will find this audiobook an essential guide to a future in which machines can outsmart people.

©2018 Massachusetts Institute of Technology (P)2018 Tantor

an excellent overview!

HIGHLY suggest it for everyone who has a general knowledge about of predictive learning but wants more, excellent pacing

Great book but not loving the narration

I hate to be negative but just have to point out that the narrator sounds like the radio host of a smooth jazz elevator music channel or a sleep hypnotist.

How Neural Networks ended the AI winter

This book more than many focuses on the latest development in machine learning. Artificial Intelligence is such a broad subject and has been going on for decades making it easy to dismiss progress.

The adoption of Neural Network, although an old concept, has only just started surpassing expectations. This is mostly due to the exponential increase in processing speed, and the colossal amount of data, something that was not available until recently and is expected to increase at the same rate.

I enjoyed this book for its focus, accuracy, and easy to understand explanations for a subject that can be overwhelming. Expectations for the near future will be hyperbolic. Highly recommended read for all.

a useful overview of recent developments

I found this a very useful high-level review of some of the more visible developments in AI. Useful for someone who already has a good grasp of statistics and statistical learning, but can probably reach beyond that audience.

I advise 😉

Great book i certainly play it again to catch all of it. It's must read

Motivational story telling for Data Scientists

If you already know the science behind AI, deep neural networks and machine learning, then this can be an inspirational tome describing how these various projects succeeded, what domains and resources are needed, and potential opportunities in other applications. For example, the information fusion in autonomous vehicles can be applied in many other dynamic systems with constant data streams and ability to influence decisions to minimize costs, time or energy functions.

Really Awesome Book!

It was really hard to stop listening. It is a great overview of how different AI techniques have been used over the years. The best was that he goes over each process step by step.

interesting insights of how computerized machines

Gives great insights in strategies for how computerized systems are programmed to act intelligently and why AI is less fearful than we sometimes predict it will be.