Live data from Hacker News

Flowrite: Turn short lists of facts into well-written emails

flowrite.com

51–56 of 56 posts

Re: Flowrite: Turn short lists of facts into well-written emails

#52
post #5

This is an interesting interface for a sophisticated machine learning model. The user input is a moderately structured prompt (a line-delimited list of facts) and the output is text crafted for a particular medium (email). This could be extended to support output for other mediums, such as Blog posts or social media updates. It does drive me slightly crazy that this system JUST INJECTS NOISE. You provide it with conc…

I think text written by models should be properly marked as such. It's too cheap to generate and doesn't have a reputation to defend.

So the first thing I would do with the message would be to put it into a model to detect artificial text, before deciding if I want to see it.

Re: Flowrite: Turn short lists of facts into well-written emails

#53
post #11
post #5

This is an interesting interface for a sophisticated machine learning model. The user input is a moderately structured prompt (a line-delimited list of facts) and the output is text crafted for a particular medium (email). This could be extended to support output for other mediums, such as Blog posts or social media updates. It does drive me slightly crazy that this system JUST INJECTS NOISE. You provide it with conc…

If the example is correct, it's injecting more than fluff and flourish. It injected "After weeks of hard work" , which doesn't seem supported by anything in the input, and probably sets the wrong tone. Certainly it was at least many months of work prior to launch.

Or is it? Huggingface model fine tuned in 3 weeks? Maybe the model knows what it's saying. /s

Re: Flowrite: Turn short lists of facts into well-written emails

#54
post #28
post #7

Can it turn a well written email into a short list of facts? That seems more useful.

I think that'd be a much harder thing to do well. You'll have a lot of false negatives. Missing nuances in complex sentences can change the meaning significantly whereas when adding extra words to a list of facts as long the words are pretty neutral meaning-wise you'll be fine.

Haha, text summarisation has been a traditional NLP task for ages. Google Scholar has 16,000 results just from the last year.

More leads: https://paperswithcode.com/task/text-summarization

Post reply on HN