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It's great at summarization and translations.
Might want to rethink the summarization part.
AI also hasn’t made any huge improvements in machine translation AFAIK. Translators still get hired because AI can’t do the job as well.
Thank you for pointing that out. I don't use it for anything critical, and it's been very useful because Kagi's summarizer works on things like YouTube videos friends link which I don't care enough to watch. I speak the language pair I use DeepL on, but DeepL often writes more natively than I can. In my anecdotal experience, LLMs have greatly improved the quality of machine translation.
So basically this study concludes that Llama2-70B with basic prompting is not as good as humans at summarizing documents submitted to the Australian government by businesses, and its summaries are not good enough to be useful for that purpose. But there are some pretty significant caveats here, most notably the relative weakness of the model they used (I like Llama2-70B because I can run it locally on my computer but it's definitely a lot dumber than ChatGPT), and how summarization of government/business documents is likely a harder and less forgiving task than some other things you might want a generated summary of.
Please share any studies you have showing AI is better than a person at summarizing complex information.
If it wasn't clear, I am not claiming that AI is better than a person at summarizing complex information.
My bad for misunderstanding you.
LLMs are TERRIBLE at summarization
Downvoters need to read some peer reviewed studies and not lap up whatever BS comes from OpenAI who are selling you a bogus product lmao. I too was excited for summarization use-case of AI when LLMs were the new shiny toy, until people actually started testing it and got a big reality check
Until it makes shit up that the original work never said.
The services I use, Kagi's autosummarizer and DeepL, haven't done that when I've checked. The downside of the summarizer is that it might remove some subtle things sometimes that I'd have liked it to keep. I imagine that would occur if I had a human summarize too, though. DeepL has been very accurate.
LLMs are especially bad for summarization for the use case of presenting search results. The source is just as critical of information for search as the information itself, and LLMs obfuscate this critical source information and combine results from multiple sources together...
tl;dr?
Translates Sumerian texts.