A source: https://www.facebook.com/watch?v=1070577474204753

ok, so basically im very smol

BoJack, stop. You are all the things that are wrong with you! It’s not the alcohol, or the drugs, or any of the shitty things that happened in your career, or when you were a kid! It’s you! Alright? It’s you. Fuck, man. What else is there to say?

The source and more photos: https://zbiory.mnk.pl/en/catalog/530266

A source: https://www.metmuseum.org/art/collection/search/544088 (currently in The Metropolitan Museum of Art in NY)

During the Late Period and Ptolemaic times mongooses were represented in bronze statuettes such as this one, standing, forepaws raised, atop small bronze boxes. The pose of raised paws signifies the animal’s adoration of the sun god when he rises in the morning. Some scholars have identified these animals as otters rather than mongooses.

In myth, mongooses were particularly attached to the goddess of Lower Egypt Wadjet, whose cult was centered in Buto, in the northern Delta.

A source: https://www.tiktok.com/@star_boi_blue/video/7352184824850926879

A good summary:

Source: https://twitter.com/selimyaman_/status/1772172937073709293

Actual paper on the impact of ChatGPT on adjectives: https://arxiv.org/abs/2403.07183

A source: https://www.tiktok.com/@juliahoran13/video/7347870106644466990

An article on Wikipedia: https://en.wikipedia.org/wiki/Operation_Cat_Drop

I’ve added BÉPO and AZERTY (some letters I had to keep below). I think that BÉPO actually has an interesting pattern:
https://imgur.com/a/uupLDMJ

The site has tooltips showing letter percentages:
https://deykun.github.io/diffle-lang/fr?p=about-language

Peak for other languages: English - 9, Spanish - 10, Polish - 12, German - 13

A source: https://www.britishmuseum.org/collection/object/E_Am-7498

Textile fragment; cotton plain weave ground with paired warps; camelid supplementary weft patterning; feline figure; cream and black.

Oh no: https://www.sadanduseless.com/cat-taxidermy/

There were some comments on Reddit suggesting that cutting the dataset at 15 and removing 40% of words was not the best move. I have locally built a version with the limit set to 30.

For the interested:
https://imgur.com/a/Rz7Cw6x

The paper: https://www.frontiersin.org/articles/10.3389/fcell.2023.1339390/full

I only have a prespellechecked list of words from here: http://www.aaabbb.de/WordList/WordList_en.php

Thanks. It should read prefers-color-scheme. I have dark mode by default, but it’s also possible to set dark/light mode too.

To clarify, it is not the total number of words but rather the number of unique words considered. Imho a million of unique words is okay. A bigger concern for me would be that words on Wikipedia can be overly specific.

A source: https://deykun.github.io/diffle-lang/de?p=about-language (It has tooltips displaying percentages for other letters)