아닐 아난타스와미  | Penguin Books

45,100원  | 20250828  | 9781802060867

“걸작” 2024년 노벨 물리학상 수상자 제프리 힌턴 강력 추천 AI가 구현하는 놀라운 세상을 떠받치며 미래를 만들어갈 핵심 수학! 2024년 챗GPT의 마법 같은 등장은 빠르게 모두의 관심사를 장악했다. AI가 길을 찾아주고, 음악을 추천하고, 그림을 그려주고, 문서를 정리해주는 수준에서 도약하여 정보를 “스스로” 찾아서 알려주고 질문에 “생각해서” 대답하는 수준에 이른 것처럼 보였기 때문이다. 과연 AI는 진짜 생각하는 기계가 된 것인가? AI로 인해서 우리 사회는 어떻게 달라지고, 우리의 삶은 또한 어떻게 될 것인가에 대한 장밋빛 기대와 어두운 우려가 공존하고 있다. 과학저술가 아닐 아난타스와미의 이 책은 오늘날의 AI를 있게 한 알고리즘을 구성하는 핵심 수학을 상세하게 살펴봄으로써 기계 안에서 어떤 과정이 작동하고 있는지를 선명하게 제시한다.

 | Penguin Publishing Group

20,300원  | 20250826  | 9780593185766

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.

아닐 아난타스와미  | Dutton

38,320원  | 20240716  | 9780593185742

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.