Markov Chains are the Original Language Models

Explores Markov chains as a mathematical foundation for text prediction and autocomplete systems, contrasting them with modern large language models. Demonstrates how probabilistic state transitions can model word sequences using matrix operations, with a practical implementation in Rust compiled to WebAssembly. Covers the mathematical theory behind transition matrices, probability calculations, and text generation techniques.