^ to me it’s really a stretch that someone could read that and think “markov chains are practically an llm!”
They’re pretty limited, and everyone working on building LLMs knows about them and has probably used them at some point.
They both generate tokens/words on probabilities, but it’s hard to understate how much simpler of a probability model a Markov chain is compared to an llm.
You’ve stated that markov chains have a limited use as a simple chat bot. How do you improve an mc so that it can perform other tasks, like classification, summarization, question answering, complex text parsing, text matching, etc, etc?
The language modeling done in llms has an open pathway to scaling and improving on this statistical model, and it’s incredible to me that this is still opaque to people. I don’t believe that llms are a path to intelligence, but I can certainly recognize that they’re going to emerge as a sophisticated and very useful productivity tool.