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Disagree. Some examples. If I have an LLM in a video game that generates NPC dialog, I might want to feed more information to the prompt based on things my cha
by devmunchies 4y ago
Disagree. Some examples.
If I have an LLM in a video game that generates NPC dialog, I might want to feed more information to the prompt based on things my character has done in the game so the NPC dialogue is more relevant to me.
Maybe I want to inject the user’s location or the current weather in Sunnyvale, CA for the specific query. Or maybe I want to inject that the user is currently at Disneyland.
Maybe the user really likes a specific tv show and I want to let the model know that. Or maybe the specific TV show was DMCA’d by an IP owner and I need to put that in the prompt.
Do I need to detect that the user is below 13 yrs old and use a different prompt (or a different model altogether)?
Maybe I want the model to only ever respond with JSON without the user needing to specify. It needs to be clarified in the prompt with no way for the user to override it.
Models can be simplified to: input to output. Prompt engineering will be engineering the inputs.
- mncharity 4y agoAnother example. Someone has yet another new programming language. Expected infrastructure was github, website with docs, editor/IDE integration, community repo, slack/mailinglist, etc. "Now" it's also a "chatoverflow" capable of answering "how do I ...?" and "translate this <code in popular language>". What does a MVP training set for this look like? Can translation be pushed to permit assimilating "batteries" from similar languages? What does the infrastructure for that look like? Does this mean a half century of agonizingly slow language evolution is about to state change?
- seydor 4y agoBy the time you have finished writing the job description for this prompt engineer, you have your prompt ready.