Part 1: The Foundations of Large Language Models (LLMs)

This part provides you with an introduction to LLM architecture, including the anatomy of a language model, transformers and attention mechanisms, Recurrent Neural Networks (RNNs) and their limitations, and a comparative analysis between transformer and RNN models. It also explains decision making in LLMs, LLM response generation, challenges and limitations in LLM decision making, and advanced techniques and future directions.

This part contains the following chapters:

• Chapter 1, LLM Architecture
• Chapter 2, How LLMs Make Decisions