- cross-posted to:
- technology@lemmy.ml
- technology@lemmy.world
- cross-posted to:
- technology@lemmy.ml
- technology@lemmy.world
In similar case, US National Eating Disorder Association laid off entire helpline staff. Soon after, chatbot disabled for giving out harmful information.
LLMs has the potential to do so much more. It’s actually capable of doing significant work.
I see it some kind of a generic text processor.
For example, say you got 1000s of news articles in different languages (like English, Chinese, Thai, etc), and you want to find articles mentioning Liverpool football club. You also want a brief summary describing the context LFC is mentioned, and whether it’s positive or negative. It should write the output in a CSV format so it’s easy to view it in Excel.
This can easily be done with LLMs. Just requires some pipeline so you can feed the LLM lots of news articles. Sure, it will do some errors, but this is something that previously required a skilled natural language processing engineer.