Why Machines Learn Book Reviews
Why Machines Learn by Anil Ananthaswamy Book Summary
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 tumour 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 seventeenth- and eighteenth-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 artifical 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.
Book Name | Why Machines Learn |
Genre | Computers & Internet |
Author | Anil Ananthaswamy |
Published | 16 July 2024, Tuesday |
Language | English |
E-Book Size | 350 KB |
Why Machines Learn (Anil Ananthaswamy) Book Reviews 2024
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Summary of Why Machines Learn by Anil Ananthaswamy
The Why Machines Learn book written by Anil Ananthaswamy was published on 16 July 2024, Tuesday in the Computers & Internet category. A total of 90 readers of the book gave the book 0 points out of 5.
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