What's the advantage of doing this, versus becoming good at context management and RAG? I always found trained knowledge unreliable, given that it is lossy by construction.
Or think about an extreme case: an LLM that is trained on almost nothing combined with great RAG and context.
You can call it "technical pedantry", but what you actually meant is "precision and logic". Which is relevant to make a connection. Your new fallacy is called "ad hominem", btw.
And there is one more logical fallacy hidden in your message: training an LLM on a lot of data is not the same thing as then relying on that lossy data once training is done.