Introduction to LLM
This page provides an easy-to-understand guide on LLMs (Large Language Models) from basics to applications for AI enthusiasts.
Chapter 8 — Adversarial Attacks on Models
Eighth post of the LLM Primer VII walkthrough. Adversarial examples in NLP (HotFlip, TextFooler), model extraction (Tramèr et al., Carlini et al.), and the defensive strategies for API-boundary abuse.
2026-05-17
Chapter 16 — Cost-Cutting Strategies in Production
Sixteenth and final post of the LLM Primer VI walkthrough. Intelligent model routing, context compaction, async batch APIs, and semantic caching — plus a look ahead to Volume VII on AI Security.
2026-05-08
Chapter 14 — Token Economics and API Pricing
Fourteenth post of the LLM Primer VI walkthrough. The input-vs-output token asymmetry, the hidden cost of conversation history, and the invisible reasoning tokens that quietly rewrite the daily bill.
2026-05-06
Chapter 9 — Training at Scale
Ninth post of the LLM Primer II walkthrough. How data preprocessing quietly shapes everything that follows, the mathematics of mini-batch learning and parallelism, and the surprisingly subtle question of how to keep a training run numerically stable across thousands of GPUs.
2026-03-11
6.1 Introducing Open-Source Tools and APIs
A preview from Chapter 6.1: Explore Hugging Face, OpenAI, Google Cloud Vertex AI, and Azure Cognitive Services—leading tools to bring LLMs into your projects.
2024-10-04