Why Machines Learn The Elegant Math Behind Modern Ai By Anil Ananthaswamy
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Why Machines Learn
'An invaluable companion for anyone who wants a deep understanding of what’s under the hood of often inscrutable machines' Melanie Mitchell 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 discoveries in chemistry, biology and physics - the study of genomes, extra-solar planets, even the intricacies of quantum systems. We are living through a revolution in artificial intelligence that is not slowing down. This major shift is based on simple mathematics, some of which goes back centuries: linear algebra and calculus, the stuff of eighteenth-century mathematics. Indeed by the mid-1850s, a lot of the groundwork was all done. It took the development of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see all around us today. In this enlightening book, Anil Ananthaswamy explains the fundamental maths behind AI, which suggests that the basics of natural and artificial intelligence might follow the same mathematical rules. As Ananthaswamy resonantly concludes, to make the most of our most wondrous technologies we need to understand their profound limitations - the clues lie in the maths that makes AI possible.
Why Machines Learn
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 if someone gets bail. They now influence developments and discoveries in chemistry, biology, and physics—the study of genomes, extrasolar 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 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.
The Man Who Wasn't There
*Nominated for the 2016 PEN/E.O. Wilson Literary Science Writing Award* *An NBC News Notable Science Book of 2015* *Named one of Publishers Weekly's Best Books of 2015* *A Book of the Month for Brain HQ/Posit Science* *Selected by Forbes as a Must Read Brain Book of 2015* *On Life Changes Network’s list of the Top 10 Books That Could Change Your Life of 2015* In the tradition of Oliver Sacks, a tour of the latest neuroscience of schizophrenia, autism, Alzheimer’s disease, ecstatic epilepsy, Cotard’s syndrome, out-of-body experiences, and other disorders—revealing the awesome power of the human sense of self from a master of science journalism. Anil Ananthaswamy’s extensive in-depth interviews venture into the lives of individuals who offer perspectives that will change how you think about who you are. These individuals all lost some part of what we think of as our self, but they then offer remarkable, sometimes heart-wrenching insights into what remains. One man cut off his own leg. Another became one with the universe. We are learning about the self at a level of detail that Descartes (“I think therefore I am”) could never have imagined. Recent research into Alzheimer’s illuminates how memory creates your narrative self by using the same part of your brain for your past as for your future. But wait, those afflicted with Cotard’s syndrome think they are already dead; in a way, they believe that “I think therefore I am not.” Who—or what—can say that? Neuroscience has identified specific regions of the brain that, when they misfire, can cause the self to move back and forth between the body and a doppelgänger, or to leave the body entirely. So where in the brain, or mind, or body, is the self actually located? As Ananthaswamy elegantly reports, neuroscientists themselves now see that the elusive sense of self is both everywhere and nowhere in the human brain.