While temperature can mix things up a little, we’ll quickly start to see how the depth of LLM output is tied to the depth of LLM input — and people’s prompts are not all that varied and deep at the end of the day.

We’ll start to notice signatures to each generation of model in its responses to tiringly common prompts — especially in stuff like blog spam, homework essays, email punchups, casual fiction, etc

There are certain poles that it gravitates to that end up reading like verbal tics or lazy ideas, and those will be more obvious as we begin to get inundated with generated content.

Careful prompt work can evade those poles and tics, but most people won’t have the skill or drive to bother with that.