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Prompt engineering is rapidly becoming just a way to squeeze better, predictable performance out of crappier, cheaper models. If your app or feature is powered
by rrrrrrrrrrrryan 3y ago
Prompt engineering is rapidly becoming just a way to squeeze better, predictable performance out of crappier, cheaper models.
If your app or feature is powered by an LLM, why pay for the state-of-the-art LLM when you can get comparable performance out of a cheaper one with a little bit of prompt engineering?
Over time, as the models themselves improve, prompt engineering may become less important. I already think it's largely unimportant for day-to-day one off things.
- minimaxir 3y agoPrompt engineering benefits models of all sizes, even the 70B ones.
- EvgeniyZh 3y agoIndeed, I'd expect more capable models to be less amenable to prompt engineering, but even if it is true it's quite possible out best models are not past "prompt engineering efficiency peak" yet. It is also fairly hard to quantify (I was thinking about some naive approaches to do that during our work on BIG-Bench [1] but I couldn't think of something robust enough), so I don't think we will even be able to say we are past this peak until much later. [1] https://github.com/google/BIG-bench/issues/801 https://github.com/google/BIG-bench/issues/801