Why Machines Learn

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 tumour is cancerous, or deciding whether someone gets bail. They now influence developments and discoveries in chemistry, biology, and physics—the study of genomes, extra-solar 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 artifical 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.

Table of Contents

Chapter 1: Desperately Seeking Patterns  

Chapter 2: We Are All Just Numbers Here…  

Chapter 3: The Bottom of the Bowl  

Chapter 4: In All Probability  

Chapter 5: Birds of a Feather  

Chapter 6: There’s Magic in Them Matrices  

Chapter 7: The Great Kernel Rope Trick  

Chapter 8: With a Little Help from Physics  

Chapter 9: The Man Who Set Back Deep Learning (Not Really)  

Chapter 10: The Algorithm That Put Paid to a Persistent Myth  

Chapter 11: The Eyes of a Machine  

Chapter 12: Terra Incognita

Review

“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

“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 inspiring introduction to the mathematics of AI.”

—Arthur I. Miller, author of The Artist in the Machine: The World of AI-Powered Creativity

“[An] illuminating overview of how machine learning works.”

—Kirkus Reviews

About the Author

Anil Ananthaswamy is an award-winning science writer and 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 long-listed 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.