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And yet prompts can be optimized.
by Xmd5a 2y ago
And yet prompts can be optimized.
- AlexeyBrin 2y agoYou can optimize a prompt for a particular LLM model and this can be done only through experimentation. If you take your heavily optimized prompt and apply it to a different model there is a good chance you need to start from scratch. What you need to do every few months/weeks depending of when the last model was released is to reevaluate your bag of tricks. At some point it becomes a roulette - you try this, you tray that and maybe it works or maybe not ...
- Xmd5a 1y agoStumbled upon this in another thread: https://ai-analytics.wharton.upenn.edu/generative-ai-labs/research-and-technical-reports/tech-report-prompt-engineering-is-complicated-and-contingent/ https://ai-analytics.wharton.upenn.edu/generative-ai-labs/re... My point still holds that it is optimizable though (https://github.com/zou-group/textgrad https://github.com/zou-group/textgrad, https://arxiv.org/abs/2501.16673 https://arxiv.org/abs/2501.16673) >Subjects develop elaborate "rain dances" in the belief that they can influence the outcome. Not unlike sports fans superstitions. Anybody tuning neural weights by hand would feel like this.