What is the difference between AI language models and traditional rule-based language processing systems?
Rule-based language processing systems use hand-coded rules to analyze and understand language. On the other hand, AI language models use statistical models and machine learning algorithms to learn patterns and relationships in language data. 

AI language models have the advantage of being able to learn from vast amounts of data and understand the nuances of language in a more sophisticated way than rule-based systems. However, they may also be more difficult to interpret and debug than rule-based systems, which can make them more challenging to use in certain applications.