Modern large language models operate on tokens (letters, words, or punctuation) rather than just an alphabet, predicting the odds of the next token given a string of prior tokens—but unlike simple Markov chains they use 'attention' to decide which prior tokens matter, allowing context like 'blood' and 'mitochondria' to disambiguate that 'cell' means biology rather than a prison.