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Other comments in this thread do a good job explaining the differences in the Markov algorithm vs the transformer algorithm that LLMs use.

I think it's worth mentioning that you have indeed identified a similarity, in that both LLMs and Markov chain generators have the same algorithm structure: autoregressive next-token generation.

Understanding Markov chain generators is actually a really really good step towards understanding how LLMs work, overall, and I think its a really good pedagogical tool.

Once you understand Markov generating, doing a bit of handwaving to say "and LLMs are just like this except with a more sophisticated statistical approach" has the benefit of being true, demystifying LLMs, and also preserving a healthy respect for just how powerful that statistical model can be.



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