alt Hacker NewsChrist, thank you! I’ve been saying this for years and no one I’ve spoken to, even engineers, could acknowledge the level of “chunking” that’s been engrained in them over the years for turning inquiries into keyword/phrase shorthand, and that this is NOT something most people want to do, and is the killer app of Google AI. This time around, you CAN type in an input box what you would say to a human in everyday conversation, AND expect a reasonable response. That’s invaluable to a casual user.
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It's not just engineers, I think it's more an age thing.
For a certain cohort (eg those currently between 35 and 45) who did any sort of grade school computer/library classes in the 90's/early2000's, 'chunking' or keyword searching was one of the main skills taught.
I mean, I'm in my mid-30s, and "keywording" and "how to use search engines" was taught in my US Midwest public school library/media center.
> this is NOT something most people want to do
I've always felt that "proper" and responsible LLM use for search [0] would be two boxes: You can describe what you want in the first, and it'll propose search terms in the second, and then those get executed normally.
Yes, the "average user" [1] might not usually care about the second box... Until they need to because the query/results are wrong.
Showing them in tandem means:
1. Users are at least capable of learning through exposure.
2. Users may realize a key term can be added which the model could never have guessed.
3. Users may recognize a term in there that doesn't make sense, allowing them to detect a translation error.
4. If good search-terms leads to a bad outcome, it is possible for someone to report and diagnose it, rather than a fully black-box mystery.
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[0] Not just for websites, but also things like internal business software, or SQL queries.
[1] The average that might not exist. ( https://www.thestar.com/news/insight/when-u-s-air-force-disc... ) There are some features that everybody needs, just at different times.