Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.