The deep learning revolution - Info and Reading Options
By Terrence J. Sejnowski
"The deep learning revolution" was published by The MIT Press in 2018 - mau, it has 342 pages and the language of the book is English.
“The deep learning revolution” Metadata:
- Title: The deep learning revolution
- Author: Terrence J. Sejnowski
- Language: English
- Number of Pages: 342
- Publisher: The MIT Press
- Publish Date: 2018
- Publish Location: mau
“The deep learning revolution” Subjects and Themes:
- Subjects: ➤ Social aspects - Big data - Artificial intelligence - Machine learning - Data mining - COMPUTERS / Database Management / Data Mining
Edition Specifications:
- Pagination: x, 342 pages
Edition Identifiers:
- The Open Library ID: OL26977607M - OL19764607W
- Online Computer Library Center (OCLC) ID: 1004086901
- Library of Congress Control Number (LCCN): 2017044863
- ISBN-13: 9780262038034
- ISBN-10: 026203803X
- All ISBNs: 026203803X - 9780262038034
AI-generated Review of “The deep learning revolution”:
"The deep learning revolution" Description:
The Open Library:
How deep learning-from Google Translate to driverless cars to personal cognitive assistants-is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
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