It’s churn because every new model may or may not break strategies that worked before.
Nobody is designing how to prompt models. It’s an emergent property of these models, so they could just change entirely from each generation of any model.
Nobody is designing how to prompt models. It’s an emergent property of these models, so they could just change entirely from each generation of any model.
I would quibble that there is a modicum of design in prompting; RLHF, DPO and ORPO are explicitly designing the models to be more promptable. But the methods don’t yet adequately scale to the variety of user inputs, especially in a customer-facing context.
My preference would be for the field to put more emphasis on control over LLMs, but it seems like the momentum is again on training LLM-based AGIs. Perhaps the Bitter Lesson has struck again.
People are trying to design how to prompt, but it’s very different in both implementation and result than designing a programming language or a visual language, ofc.