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The arguments for not limiting yourself to prompt engineering are compelling, but I wouldn't call the whole practice snake oil. Fundamentally, it's about learni
by TheAceOfHearts 3y ago
The arguments for not limiting yourself to prompt engineering are compelling, but I wouldn't call the whole practice snake oil. Fundamentally, it's about learning to communicate your desires and requirements effectively.
There's definitely a fair number of simple tricks with existing models which drastically improve output quality. It's usually simple things like making requirements explicit, e.g. "generate a few foo" vs "generate 5 foo". The single most effective phrase I've picked up has been to tell the model that whatever is being output was written by an expert. But a lot of my experimentation has been dealing with generating and exploring fantasy ideas.
- olddustytrail 3y ago> Fundamentally, it's about learning to communicate your desires and requirements effectively. Yes, that's how you get the most bang for your buck, if you'll excuse the expression...
- BoorishBears 3y agoThe article is silly: LLMs are autoregressive. Dismissing prompting is dismissing one of the biggest value propositions of RLHF in that you can affect future output in a steerable way using natural language. Meanwhile the SOTA model in question didn't support fine tuning until last month, still only supports SFT, and costs significantly more than the base model. The fact the article concludes with "hire us" says it all: great marketing strategy with the title though.
- toddmorey 3y agoI would call this article a bit of snake oil. It’s basically an ad. And you are right—it’s amazing how well the “you are an expert in…” has worked when added to a prompt.
- gverrilla 3y agoexactly, that's all it is: an ad.