# Markov Text Systems

**Track:** 3D, Shaders & AI Intuition — Creative Coding — the existing 50
**Framework / surface:** p5.js
**Level:** Intermediate
**Prerequisites:** Hash Maps & Lookup, Typography & Text Systems

**In one line:** Generate text by which word tends to come next — ancestor of language models.

## Theory, aesthetics & inspiration

A Markov system predicts the next word from the recent past alone, treating language as a chain of probabilistic transitions. The idea is Andrey Markov's, who studied such dependent sequences in the early twentieth century; Claude Shannon turned it toward language in A Mathematical Theory of Communication (1948), generating eerily plausible English from letter and word statistics. The aesthetic is one of recombination — familiar fragments reassembled into uncanny, half-sensical drift, kin to the literary cut-up. Though crude beside modern systems, the Markov chain is their direct ancestor: every contemporary language model is, at heart, a vastly richer answer to the same question of what tends to come next.