Anil Ananthaswamy
Author. Speaker. Educator.
Keynotes, workshops and moderated conversations for corporations that need to understand how AI actually works — from the author of Why Machines Learn.
Machine Intelligence
Made Clear
Testimonials From Corporate Executives
“An enthralling, enchanting, and enlightening workshop. Your ability to bring clarity and energy to complex ideas left a lasting impression.”
Deepak Bhatia
CTO & SVP, The Hershey Company
Full-day ML/AI workshop
“Several engineers (me included) who’ve shipped AI products for years had multiple aha moments… Anil is a rare polymath and a brilliant teacher.”
Santhosh Kumar
CTPO, cult.fit, Bangalore, India
Two-day ML workshop
The Book
Why Machines Learn
A history of ideas and an accessible tour of the mathematics — linear algebra, calculus, probability and optimization — that makes modern AI possible. The foundation for every keynote and workshop (Dutton, Penguin Random House, 2024).
“A masterpiece.” Geoffrey Hinton, Nobel laureate
Top 5 Best AI Books of 2024, The Information
Also by Anil: Through Two Doors at Once (2018) · The Man Who Wasn’t There (2015) · The Edge of Physics (2010, Physics World Book of the Year)
Anil Ananthaswamy spent a decade working on distributed systems before turning to science journalism. He became deputy news editor at New Scientist and writes for Quanta, Scientific American, Nature and others.
He has since spent years embedded with the researchers shaping AI — at the Simons Institute, UC Berkeley, Princeton and the Heidelberg Institute for Theoretical Studies — and now teaches AI and Machine Learning at IIT Madras.
He’s the author of four acclaimed books, including Why Machines Learn: The Elegant Math Behind Modern AI
An Engineer’s Mind, A Journalist’s Ear.
Watch Talks / Listen to Podcasts
South Park Commons India
Why Machines Learn: The Future of Intelligent Machines
The ideas that took machine learning from the perceptron to today’s frontier — and what they tell us about where it goes next
International Centre for Theoretical Sciences
From LLMs to LRMs: The Rise of Reasoning Models
How large language models became large reasoning models, and what is — and isn’t — happening inside them.
Machine Learning Street Talk
The Elegant Math Behind Machine Learning
A long-form conversation on the mathematical intuitions behind neural networks and modern AI.
TED Talk: Where Does Your Sense of Self Come From?
A scientific look at the self, drawing on neuroscience and the stories of people whose sense of self has been altered.
IIT-Madras,
Professor of Practice
Simons Institute,
UC Berkeley
Science Communicator-at-Large
MIT
2019-20 Knight Science
Journalism Fellow
Author / Journalist
Why Machines Learn
Bylines: Quanta, Nature, Scientific American, New Scientist, and more
Rigor for experts.
Clarity for everyone else.
An electrical engineer and former software engineer turned award-winning science journalist, Anil brings the intuition and the math behind modern AI to boardrooms, engineering teams and public stages.
Keynotes
From the perceptron to today’s reasoning models — what these machines can do, where they fail, and why the difference matters for your organization.
Workshops & Training
One- and two-day intensives for engineering and leadership teams on the theoretical underpinnings of machine learning — the ideas beneath the products you ship.
Moderated Conversations
On-stage interviews with leading researchers, informed by two decades of reporting — most recently with Yoshua Bengio at the AI Impact Summit, India 2026.
