[rdiddly]

Anyone have a real-world use case for something like this? I must admit I'm having trouble thinking of any that aren't essentially deceptive. Because in my little biased world, I have no need of "text" per se, and what value any text has to me is closely linked to the fact that it came from a human.

[zawerf]

Machine learning researchers aren't working on language modeling because they want to enable fake news.

They are working on it because it improves all downstream NLP tasks. See: http://ruder.io/nlp-imagenet/. BERT, Elmo and XLNet all fall under this use case.

For example if you're trying to recognize speech or translate some text, it helps a lot if you can start off producing something that is statistically grammatical even if the content is nonsense.

[csande17]

One use case I've seen is autocomplete -- people have used GPT-2 to build things like TabNine[1] and Write With Transformer[2].

[1]: https://tabnine.com/

[2]: https://transformer.huggingface.co/

[taf2]

I imagine summarization being a usecase