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fri20dec7:00 pmfri8:30 pmWHY MACHINE'S LEARN7:00 pm - 8:30 pm(GMT+05:30) Event Type Talk

Event Details

The Elegant Math Behind Modern AI

Anil Ananthaswamy

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.
“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
 

Anil Ananthaswamy is an award-winning science writer and former staff writer and deputy news editor for the London-based New Scientist magazine. He is a 2019-20 MIT Knight Science Journalism fellow. He has been a guest editor for the science writing program at the University of California, Santa Cruz, and organizes and teaches an annual science writing workshop at the National Centre for Biological Sciences in Bengaluru, India.

 

He is a freelance feature editor for PNAS Front Matter. He writes for regularly for New Scientist, Quanta, Scientific American, PNAS Front Matter and Nature, and has contributed to Nautilus, MatterThe Wall Street Journal, Discover and the UK’s Literary Review, among others.

 

His first book, The Edge of Physics, was voted book of the year in 2010 by UK’s Physics World, and his second book, The Man Who Wasn’t There, was long-listed for the 2016 Pen/E. O. Wilson Literary Science Writing Award.  His most recent book, Through Two Doors at Once was named one of Smithsonian's Favorite Books of 2018 and one of Forbes's 2018 Best Books About Astronomy, Physics and Mathematics. His latest book, Why Machines Learn: The Elegant Math Behind Modern AI, was published in July 2024.

 

Anil trained as an electronics and computer engineer at IIT-Madras (BTech) and the University of Washington, Seattle (MSEE), and worked as a distributed systems software engineer and architect before switching to writing. He studied science journalism at UC Santa Cruz. Of late, he has retrained in aspects of machine learning and deep neural networks, during his stay at MIT as a Knight Fellow and via eCornell, Cornell University’s online program. He was awarded the Distinguished Alumnus Award by IIT-Madras, for his contributions to science writing.

 

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Time

December 20, 2024 7:00 pm - 8:30 pm(GMT+05:30)

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