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We don't have to do that to communicate with humans because they're aren't one-shot. Humans ask followup questions like "Polish as in people from Poland, or pol
by ketralnis 4y ago
We don't have to do that to communicate with humans because they're aren't one-shot. Humans ask followup questions like "Polish as in people from Poland, or polish as in rubbing until it's shiny?". Or they know you both work for a translation company and you don't talk about shinifying objects very often.
If you did have to send google-esque one shot queries to humans you'd probably settle on short hand like "polish shiny" or you'd opt to use "poland" specifically to avoid it. For most known-ambiguous terms you'd do this, the same way we say out loud "M as in Mancy" because we know the sound of the letter can be ambiguous sometimes. We have lots of these in English that you use all of the time without knowing it. In a smaller audience the local language gets even more specific, you probably disambiguate people with your friends like "programmer Bob, not carpenter Bob". It's not at all crazy that we'd develop another local language for communicating with computers even if that's not a traditional programming language
- Xelynega 4y agoExcept we do that for humans and it's still not really relevant to language models. If I were talking to a python programmer I could assume they knew what a for loop was, so could phrase a question requiring the context of one differently than I would for the layperson. Just like if I were designing inputs to one language model I could assume it's capabilities that are different from another. I don't think it's relevant to the performance of language models for that same reason though, we already have to design out queries with the thing being queried in mind so I don't see why we wouldn't for llms.
- selfhoster11 4y agoI’ve been able to make ChatGPT ask for follow-up clarifications if it’s unsure about the meaning of something. I didn’t explore this further, but the ability is right there and can be triggered with the right prompt text.