“This book is the ultimate explainer… What I love most is how [Ananthaswamy] threads history into the equations. You get why these methods matter, how they were discovered, and why they’ve stuck around. I felt like I was part of the journey, not just staring at some abstract formula. If you’re curious about how machines learn but feel like math is a wall you can’t climb, this book is your ladder. Highly recommended.”
Helen Edwards, The Artificiality Institute
In Why Machines Learn, acclaimed science writer Anil Ananthaswamy presents a narrative-driven journey through the mathematics powering the modern artificial intelligence revolution. With clarity and depth, he unpacks how centuries-old mathematical principles, such as linear algebra, calculus, and probability, form the backbone of today’s machine learning systems, from image recognition algorithms to large language models like ChatGPT.
Designed for the curious executive or forward-looking leader, the book reveals how foundational concepts evolved through key historical milestones. Readers gain insight into how AI now drives decision-making in finance, medicine, and criminal justice, while also reshaping the frontiers of scientific research in fields like genomics and quantum physics.
Ananthaswamy’s strength lies in making the complex accessible.
Without oversimplifying, he draws intuitive connections between abstract math and its real-world applications, offering a toolkit of understanding that empowers professionals to engage meaningfully with AI-driven innovation. His exploration also invites reflection on a provocative question: could the same mathematics that drives artificial intelligence also underpin the mechanisms of natural intelligence?
For CIOs and technology leaders, Why Machines Learn offers both a foundational education and a strategic lens. It’s an essential read for anyone seeking to comprehend AI’s promise, and its limitations, through the clarity of its mathematical core.
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