Leaving aside the gimmicks in some of these examples, it is a fact that when you need to communicate quantitative information machine generated text is a great solution. Our company builds analytics and dashboards for fund managers and traders (the people who manage most pension funds). Infographics and charts only go so far; eventually, the user has to extract the key information, or communicate it with a colleague, which means verbalizing.

[ShowHN:] We built our report generation system (in Haskell) that can create a custom report for every portfolio or market index, and can be tuned to the user's risk profile. We've released a public version that anyone can use for free that covers most global indices and sectors:

https://apps.otastech.com/morningreport?listtype=marketindex...

In our experience, the turns of phrase that initially give the impression that the text has been written by a human quite quickly become irritating noise. Our users need to absorb information quickly and accurately, and comprehension is aided by adhering to a standard structure and avoiding figurative language.