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WHY MACHINES LEARN

Anil Ananthaswamy

The Elegant Math Behind Modern AI

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 tumor 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 17th and 18th 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 artificial 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.

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.
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Book

Published 2024-05-01 by Dutton Books

Book

Published 2024-07-16 by Dutton Books

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Authors piece: Artificial Neural Nets Finally Yield Clues to How Brains Learn - The learning algorithm that enables the runaway success of deep neural networks doesn't work in biological brains, but researchers are finding alternatives that could. ... Read more...

UK & C: Penguin Press UK ; Chinese (simpl.): China Science and Technology Press ; Czech: Albatros ; Italian: Apogeo ; Korean: Kachisa

A math book on this subject is a great idea and Anil explains it beautifully.

In some sense you could say WHY MACHINES LEARN presents us with the math of intuition. Learning (machine or otherwise) is about seeing patterns. Patterns in 3 or 4 dimensions are relatively easy to see. This math is how we see in 100 or even 10,000 dimensions. Anil leads a tour for adventurous minds of the most awesome math of our age... A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence.