As artificial intelligence and cognitive computing have gained interest in recent years, a lot of the attention has been on varieties of classifier systems. Classifier systems look for patterns to establish a given probability that a thing is of a certain type. Simple rules and actions can then be run based on this classification. To understand how generative techniques can take AI to the next level, it is important to understand their basics. The classic area of interest is still one of the most interesting: natural language. This series explores letter correlation and simple language statistics for AI, word analysis and N-grams in a variety of practical applications, and using Markov Chains to generate language from letter correlation matrices and N-grams.