Conbini Wars – Map of Japanese convenience store ratios
conbini.kikkia.dev
conbini.kikkia.dev
[1] https://ja.wikipedia.org/wiki/%E3%83%89%E3%83%9F%E3%83%8A%E3...
https://en.wikipedia.org/wiki/%C5%BBabka_(convenience_store)
The homepage of google.com is also localized. I remember noticing that even when requesting and getting the English locale, the tooltip for the doodle was still in my region's language... wahey!
Makes you wonder if universal translators ever become the norm people will still bother to learn foreign language.
And there's just some passages of literature that you can't translate. Or rather, you can but it just doesn't work, simply because the target language doesn't let you structure or rhyme in the same way as the source language. Every language has a potential for generating unique literature simply because each language has a unique vocabulary + sentence structure.
I don’t think it would be fair to differentiate it though. The point of the map is to show popularity / reach of each of the bigger brands.
My personal favorite is probably Family Mart, because they have multiple very delicious vegan rice balls to choose from.
I’ve actually been interested in that data for a back burner project for some years now.
Where I stayed, you could go to a store and from there see the next one already.
You cant search or change language
Idk what is the goal here, but maybe some analysis with graph would be better, like who has the most territory or something like that? You also might need to disclosure how you got this data
https://github.com/kikkia/ConbiniWars/commit/b8ea5e5a9351c23...
As an aside, we used to use the term “code smell” back in the day when trying to trace the source of problems in an app. The “smell” would tend to lead you to the bad code.
It doesn’t guarantee this is purely AI generated. It’s just weird, and when held up to the rest of the git repos of the last two years, it gives the appearance of AI generated.
The “slop” part is debatably unfair still, but having an app be AI generated tends to mean little effort was put into the up front requirements analysis before a selection of functionality made.
Again, just generalizations on my part. If it makes you feel better, I’m working on an AI generated app to quantify the amount of times someone’s work is dismissed as “AI slop” so I can present a case to the moderation team to get the HN guidelines updated to discourage ONLY calling something slop without any evidence of it.