LLM Primer I How Generative AI Works by Sho Shimoda (.ePUB)
File Size: 17.4 MB
LLM Primer I How Generative AI Works: A Clear and Practical Guide to the Foundations of Large Language Models by Sho Shimoda
Requirements: .ePUB reader, 17.4 MB
Overview: Artificial Intelligence (AI) is no longer experimental. Large Language Models now write code, summarize research, power chat systems, and reshape entire industries. Yet most explanations remain either overly academic or frustratingly superficial. This book is different. LLM Primer is a clear, technically grounded guide for engineers, technical product managers, advanced beginners, and curious professionals who want to truly understand how large language models work — not just how to use them. This book is one volume in the LLM Primer series by Sho Shimoda. Each volume is designed to stand on its own, and together they cover foundations, systems engineering, and governance of Large Language Models. You will not find hype, vague metaphors, or hand-waving explanations. Instead, you will build real understanding from first principles. Every concept is introduced intuitively first, then explored more deeply. Technical terms are clearly defined. Examples are concrete and practical. Mathematical ideas are explained in plain language before any formal detail appears. This book assumes you know basic programming, but not Deep Learning. This book is written for anyone who has encountered large language models and wants to understand what is actually happening inside them. That audience has grown dramatically. It now includes general readers who are curious about the technology quietly reshaping their work, students encountering the topic for the first time, managers who have to make decisions about tools they did not build, and engineers who want a durable mental model rather than a list of tips. You do not need a technical background to read this book. Some mathematical ideas appear in the book, because probability, optimization, and geometry are how these systems are built. Where math matters, the text uses it. Where math can be explained in ordinary sentences without losing the point, the sidebars do so. You do not need to remember calculus to read this book, and you should not feel disqualified if an equation looks unfamiliar; the surrounding explanation will carry you through.
Genre: Non-Fiction > Tech & Devices
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