attention conservation notice: incredibly rough scratchpad of ideas

"You are GPT-3", revised: A long-form GPT-3 prompt for assisted question-answering with accurate arithmetic, string operations, and Wikipedia lookup. Generated IPython commands (in green) are pasted into IPython and output is pasted back into the prompt (no green). pic.twitter.com/CFVkufPjhf

— Riley Goodside (@goodside) October 17, 2022

there is a meta business to {interior}.ai; exterior of building, landscaping, car interiors, fabric / clothing. Any object that can be highly customized there is a SaaS for them around SD. https://t.co/hpByA7Kdhm

— nikete (@nikete) October 23, 2022

Prompt engineering can be loosely thought of as providing the context that shapes the interface between a model and the task. Prompt engineering may be a transient phenomenon a la “advanced/cyborg/centaur” chess. A market structure for improvements to the interface between models and the world is still generically valuable, even if human crafted prompts dissapear.

How to compose prompts? Are the useful meta prompts? How stable are prompts accross models? what does that correlate to?

What market structures are expressive enough? can be understood? can be incnetive compatible?