The base models are eerie. People have done some amazing creative work with them, but I honestly think the base models are so disconcerting as to effectively force nearly every R&D lab out there to run to instruction tuning and otherwise avoid having to work with base models.

I think it's so frustrating and uncanny valley and alien dealing with the edge cases of the good, big base models that we're missing a lot of fun and creative use cases.

The performance hit from fine-tuning is what happens when the instruct tuning and alignment post-training datasets distort the model of reality learned by the AI, and there are all sorts of unintended consequences, ranging from full on Golden Gate Claude levels of delusion to nearly imperceptible biases.

Robopsychology is in its infancy, and I can't wait for the nuanced and skillful engineering of minds to begin.