Anil Ananthaswamy, "Why Machines Learn: The Elegant Maths Behind Modern AI" (Dutton, 2024)

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Welcome to the New Books Network.

**Gregory McNabb** (1:34)
Welcome to the New Books Network. I'm your host, Gregory McNabb, and I'm excited to be joined by Anil Ananthaswamy, the author of Why Machines Learn, The Elegant Maths Behind Modern AI. The book was published by Dutton in 2024 Anil is an award-winning science writer and a former staff writer and deputy news editor for New Scientist. He holds a bachelor's in technology from IIT Madras and a master's of science in intellectual engineering from the University of Washington. He worked as a distributed system software engineer at Silicon Valley in the 1990s before transitioning to journalism. He is the author of several popular science books, including The Man Who Wasn't There, which was long listed for the Penn EO. Wilson Literary Science Writing Award. He was a 2019-2020 MIT Knight Science Journalism fellow, and the recipient of the Distinguished Alumn Award, the highest award given by IIT Madras to its graduates, for his contributions to science writing. For those who follow AI, Jeffrey Hinton labels his book a masterpiece. For those who are unfamiliar with Professor Hinton, that's about as high praise as one can hope for, and it is certainly warranted. I selected Why Machines Learn because it offers a deep dive into the problems, development of the math behind AI and more importantly how AI learns. While there is some math involved, Anil does a wonderful job of walking the reader through the formulas at a patient pace and highlighting the key concepts behind the submerging and powerful technology. The structure of the book is both chronological and thematic, in the sense that Anil charts the key contributions over time, as well as how each genre of mathematics contributes to the algorithms of AI.
Hello, Anil, thank you for joining me today to discuss your book.

**Anil Ananthaswamy** (3:16)
Hi, Greg. It's my pleasure to be on this podcast. Thank you very much.

**Gregory McNabb** (3:21)
Anil, why did you write Why Machines Learn and who is the target reader?

**Anil Ananthaswamy** (3:27)
So, the book began more as a project, wherein I was teaching myself machine learning. So what had happened was, once I transitioned from being a software engineer to being a journalist, for the longest time, I didn't write about technology. I didn't want to write about technology. I was more interested in writing about physics and neuroscience. And sometime about six or seven years ago, I noticed that more and more stories were coming my way, which had some element of machine learning.
And so whenever I would interview the scientists involved, I think the software engineer in me would perk up and say, hang on, this is something I could be doing because I have a software background. So when you mentioned during the intro that I did a fellowship at MIT, so my project for that fellowship was basically trying to teach myself deep learning and machine learning. And I went back to school, literally sat in a, you know, in CS101 classes that I don't think they're called 101 in MIT, but nonetheless, I was sitting with these teenagers learning Python and PyTorch and stuff like that. And at this point, I wasn't thinking about a book. I was just thinking about learning, enough deep learning and machine learning so that I could be a better journalist. But at some point, I think as I was learning the math, it struck me that there is something very beautiful about the math. So the desire to actually then write about the math and tell the story of how this field has come about, that desire was born and that's what led to the book.