Why does a chatbot utilizing a Markov chain exhibit incoherence more readily than one using a transformer network?

💡 Explanation

Markov chains determine the next word based only on the preceding n words, rather than considering the overall context; therefore, coherence suffers due to the lack of long-range dependencies. Transformers use attention mechanisms to relate words across the entire input, allowing better coherence rather than just local relationships.

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