03433cam a2200481 i 4500 23494348 BJBSDDR 20250701092029.0 a|||||r|||| 00| 0 ta 240110s2024 nyua 001 0 eng 2024000738 9780593185742 (hardcover) 0593185749 (hardcover) 9780593185759 (ebook) DLC eng rda DLC eng pcc Q 325.5 A533w 2024 006.3/1 Ananthaswamy, Anil 41769 Why machines learn : the elegant math behind modern AI / Anil Ananthaswamy. New York : Dutton, 2024. 464 pages : illustrations ; 24 cm text txt rdacontent unmediated n rdamedia volume nc rdacarrier Includes bibliographical references and index. Desperately seeking patterns We are all just numbers here.. The bottom of the bowl In all probability Birds of a feather There's magic in them matrices The great kernel rope trick With a little help from physics The man who set back deep learning (not really) The algorithm that put paid to a persistent myth The eyes of a machine Terra incognita "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"-- Provided by publisher. Machine learning. Aprendizaje automático. 11301 Aprendizaje automático (Inteligencia artificial) 16131 Deep learning (Machine learning) Aprendizaje profundo 42994 Artificial intelligence. Inteligencia artificial 2016 Mathematics. Matemáticas 6152 7 cbc orignew 1 ecip 20 y-gencatlg lcc BK 123268 123268 0 0 lcc 0 0 HU BJB BJB HU 2025-04-30 0 Q 325.5 A533w 2024 00000189317 2025-04-30 00:00:00 1 BK