3 ms·
Isn't data entry a really good usecase for the LLM technologies? Of course depending on the exact usecase. But most "data entry" jobs are data transformation jo
by newswasboring 1y ago
Isn't data entry a really good usecase for the LLM technologies? Of course depending on the exact usecase. But most "data entry" jobs are data transformation jobs and they get automated using ML techniques all the time. Current LLMs are really good at data transformation too.
- sirwhinesalot 1y agoNo because they aren't reliable. You don't want to be storing hallucinated data. They can help write the scripts that do the actual work though.
- swiftcoder 1y agoAh yes, because hallucinations will definitely improve our data entry!
- jeroenhd 1y agoIf your core feature is data entry, you probably want to get as close to 100% accuracy as possible. "AI" (LLM-based automation) is only useful if you don't really care about the accuracy of the output. It usually gets most of the data transformations mostly right, enough for people to blindly copy/paste its output, but sometimes it goes off the rails. But hey, when it does, at least it'll apologise for its own failings.
- grey-area 1y agoNo data replication or transformation is not a good use-case for text generators.
- delaminator 1y agoWe can't even use AI language translation because of compliance / liability - we translate food ingredients. "It says 'no shellfish', go ahead - eat it" Even with lots context the various services we tried would get something wrong. e.g. huile is oil in French and sometimes it would get translated as "motor oil"