My intuition given the rapid, informal developments of agent-type systems is that this is obvious insofar as the initial dataset was formed from a huge hidden "

My intuition given the rapid, informal developments of agent-type systems is that this is obvious insofar as the initial dataset was formed from a huge hidden "data cleaning" task that was human evolution and society. This isn't really that interesting of a claim and is it clear that it holds if you simply loop the LLM back onto the data cleaning task itself as a critic to the new training set? Is this what the author would classify as fine tuning? Another question is what is the interpretation of the output of an LLM generation when unprompted? Isn't that always effectively garbage when there's not a deliberate bias in the training set?