Understanding LLMs Through Math: The Inner Workings of Large Language Models
Understanding LLMs Through Math: The Inner Workings of Large Language Models: The Mathematical Foundations Behind How Machines Understand Language (Learning LLM Book 2) by SHO SHIMODA
English | September 17, 2025 | ISBN: N/A | ASIN: B0FRM54SCS | 176 pages | EPUB | 1.53 Mb
English | September 17, 2025 | ISBN: N/A | ASIN: B0FRM54SCS | 176 pages | EPUB | 1.53 Mb
Understanding LLMs Through Math: The Inner Workings of Large Language Models
Unlock the mathematics that power today’s most advanced AI.
In this in-depth guide, Shohei Shimoda—CTO of ReceiptRoller and former CEO of transcosmos' Technology Institute—demystifies how large language models (LLMs) like GPT truly work, from a mathematical and systems-level perspective.
Whether you're an engineer, researcher, or AI enthusiast, this book offers a rare bridge between theory and real-world application. You’ll learn:
- How vector spaces and linear algebra form the basis of embeddings
- The role of probability, entropy, and loss functions in language prediction
- What self-attention really computes—and how it powers the Transformer architecture
- The training pipeline: from data preprocessing to mini-batch learning
- The computational trade-offs of scaling models, and how to optimize efficiency
- Ethical and societal challenges posed by LLMs—and how to address them