Why Machines Learn: The Elegant Math Behind Modern AI (First Edition)

Ananthaswamy, Anil

ISBN 10: 0593185749 / ISBN 13: 9780593185742

Published by Dutton, New York, 2024

About this Item

New York: Dutton, 2024. First edition, first printing stated. Hardcover. Black over black paper-covered boards with red spine lettering. Fine in a fine dust jacket. Publisher's original price intact on jacket flap ($32.00). Comes with archival-quality mylar dust jacket protector. A tight, clean, unread copy. Octavo, 465 pages including index. This book explores the mathematical foundations of modern artificial intelligence, showing how concepts such as linear algebra, calculus, and probability underlie today s machine learning breakthroughs and questioning whether the same math connects artificial and natural intelligence. Anil Ananthaswamy is a science journalist and author of "The Edge of Physics" and "Through Two Doors at Once," noted for making complex scientific ideas accessible to general readers. This is his fourth book.

Seller Inventory # Nonfiction-Sale-AI

Bibliographic Details

• Title: Why Machines Learn: The Elegant Math Behind Modern AI (First Edition)
• Publisher: Dutton, New York
• Publication Date: 2024
• Language: English
• ISBN 10: 0593185749
• ISBN 13: 9780593185742
• Binding: Hardcover
• Edition: 1st Edition
• Condition: Fine
• Dust Jacket Condition: Fine
• Seller catalogs:
  • Technology

About this title

Synopsis

A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence

Machine learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumor is cancerous, or deciding if someone gets bail. They now influence developments and discoveries in chemistry, biology, and physics—the study of genomes, extrasolar planets, even the intricacies of quantum systems. And all this before large language models such as ChatGPT came on the scene.

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning, while suggesting intriguing links between artificial and natural intelligence. Might the same math underpin them both?

As Ananthaswamy resonantly concludes, to make safe and effective use of artificial intelligence, we need to understand its profound capabilities and limitations, the clues to which lie in the math that makes machine learning possible.

About the Author

Anil Ananthaswamy is an award-winning science writer and a former staff writer and deputy news editor for New Scientist. He is the author of several popular science books, including The Man Who Wasn’t There, which was longlisted for the PEN/E. O. Wilson Literary Science Writing Award. He was a 2019-20 MIT Knight Science Journalism Fellow and the recipient of the Distinguished Alum Award, the highest award given by IIT Madras to its graduates, for his contributions to science writing.