How LLMs Actually Work
Summary
This interactive visual guide explains how large language models are built, from data collection and tokenization to pre-training, base model behavior, and post-training improvements. It covers core concepts like SFT, RLHF, LLM psychology, and RAG, and provides an end-to-end pipeline for transforming raw text into a conversational assistant. The piece emphasizes the probabilistic nature of token-based generation and includes live demonstrations and interactive tools.