Publishing details
Pub Date Jul 16, 2024, Dutton (Penguin Random House).
For publishing issues, please contact: Grace Layer, Associate Editor, glayer@penguinrandomhouse.com
For publicity: Emily Canders, Asst. Director of Publicity, Dutton (Penguin Random House), ecanders@penguinrandomhouse.com
Overview
Why Machines Learn explains the mathematical underpinnings of modern AI, from Rosenblatt’s perceptrons (1958) to today’s deep neural networks, with pitstops along the way to understand the seminal algorithms that have made machine learning the force it is today.
For Running Errata, Click Here.
If you find an error in WHY MACHINES LEARN, please use the form below to notify me.
PRAISE
“Some books about the development of neural networks describe the underlying mathematics while others describe the social history. This book presents the mathematics in the context of the social history. It is a masterpiece. The author is very good at explaining the mathematics in a way that makes it available to people with only a rudimentary knowledge of the field, but he is also a very good writer who brings the social history to life.”
—Geoffrey Hinton, deep learning pioneer, Turing Award winner, former VP at Google, and Professor Emeritus at University of Toronto
PRAISE / REVIEWS CONTD…
“After just a few minutes of reading Why Machines Learn, you’ll feel your own synaptic weights getting updated. By the end you will have achieved your own version of deep learning—with deep pleasure and insight along the way.”
—Steven Strogatz, New York Times bestselling author of Infinite Powers and professor of mathematics at Cornell University
“If you were looking for a way to make sense of the AI revolution that is well underway, look no further. With this comprehensive yet engaging book, Anil Ananthaswamy puts it all into context, from the origin of the idea and its governing equations to its potential to transform medicine, quantum physics—and virtually every aspect of our life. An essential read for understanding both the possibilities and limitations of artificial intelligence.”
—Sabine Hossenfelder, physicist and New York Times bestselling author of Existential Physics: A Scientist’s Guide to Life’s Biggest Questions
“Why Machines Learn is a masterful work that explains—in clear, accessible, and entertaining fashion—the mathematics underlying modern machine learning, along with the colorful history of the field and its pioneering researchers. As AI has increasingly profound impacts in our world, this book will be an invaluable companion for anyone who wants a deep understanding of what’s under the hood of these often inscrutable machines.”
—Melanie Mitchell, author of Artificial Intelligence and Professor at the Santa Fe Institute
“Generative AI, with its foundations in machine learning, is as fundamental an advance as the creation of the microprocessor, the Internet, and the mobile phone. But almost no one, outside of a handful of specialists, understands how it works. Anil Ananthaswamy has removed the mystery by giving us a gentle, intuitive, and human-oriented introduction to the math that underpins this revolutionary development.”
—Peter E. Hart, AI pioneer, entrepreneur, and co-author of Pattern Classification
“Anil Ananthaswamy’s Why Machines Learn embarks on an exhilarating journey through the origins of contemporary machine learning. With a captivating narrative, the book delves into the lives of influential figures driving the AI revolution while simultaneously exploring the intricate mathematical formalism that underpins it. As Anil traces the roots and unravels the mysteries of modern AI, he gently introduces the underlying mathematics, rendering the complex subject matter accessible and exciting for readers of all backgrounds.”
—Björn Ommer, Professor at the Ludwig Maximilian University of Munich and leader of the original team behind Stable Diffusion
“[An] illuminating overview of how machine learning works.”
—Kirkus Reviews