Introduction to LLM
This page provides an easy-to-understand guide on LLMs (Large Language Models) from basics to applications for AI enthusiasts.
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Chapter 5 — Position, Order, and Sequence Structure
Fifth post of the LLM Primer II walkthrough. How transformers acquire a sense of order — from the original sinusoidal encoding to relative position to RoPE — and a striking final view that ties the whole apparatus to Fourier analysis.
2026-03-07Chapter 4 — The Transformer Architecture: Inside the Engine of Modern AI
Chapter 4 of the LLM Primer I series. A tour of the Transformer block — how self-attention, positional encoding, and stacked layers combine to produce the architecture every modern LLM is built on. Includes a clear explanation of why scaling Transformers works, and what it costs.
2026-02-21