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Comment by starpilot | Hacker News Reader

I compressed "I am going to work outside today," then put the compressed output in Google Translate. Google translated the Chinese characters back to English as "raccoon."

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I think the Chinese text that comes out confuses Google translate. I took the whole first sentence of Hamlet's soliloquy which compressed to 䮛趁䌆뺜㞵蹧泔됛姞音逎贊 and plugged that into Google Translate. It came back with "Commendation." The reverse translation is 表彰

I hit the reverse button again, and got "recognition" which translated back to 承认 which finally got into a closed loop to recognition and back to the same Chinese text.

It's not Chinese text, it's an arithmetic-coded stream of bits mapped so the bits fall within the range of some codepoints. It's basically a variant of base64 except for Unicode.

(Side note: aren't these codepoints very expensive to encode in UTF-8? It seems there must be a lower-valued range more suited to it)

It's probably similar to this: https://pieroxy.net/blog/pages/lz-string/index.html

Check the 'How does it look?' section.

Yeah I don't understand why it's using CJK, the page claims:

> each compressed character holds 15 data bits by using the CJK and the Hangul Syllables unicode ranges.

In UTF-8 these characters take 3 bytes each. Which makes it less space efficient than base64 (60% overhead vs 33% overhead).

The CJK/Hangul scheme has more information per character but I'm not sure where that matters.

It's so that the output uses printable characters, that's all. The raw output would actually just be random bits, or at least something approximating random bits if GPT-2 is as good as we hope it is.

Yes, I understand. But base64 is the bog standard solution for encoding arbitrary binary data as printable characters.

So I'm just wondering why you would use something more obscure, less space efficient, and not ascii compatible.

Because it will impress uneducated people with how much smaller (in terms of screen real estate) the resulting message is.

EDIT: Ohhh, I know, and because twitter cares about characters. So you can use this to put essays into tweets.

The page for base32768 has some efficiency charts for different binary to text encodings on top of different UTF encodings, as well as how many bytes you can use them to stuff in a tweet. Depends on where you're going to house the data, I guess.

https://github.com/qntm/base32768

In addition to being 94% efficient in UTF-16 (!), this reveals some additional reasons why one might want to optimize for number of characters: fitting as many bytes as possible into a tweet which is bounded in the number of characters not bytes.

This is Chinese characters mixed with Korean characters and this is pretty much never done by humans. It is analogous to mixing English and Heiroglyphics and typing out some gibberish with both.

The author might as well have included the rest of the Unicode range including Arabic, Emoji, and math symbols.

For more fun enter "I am going to work outside today" compress, delete the second character and decompress, the result is... "I know what you're thinking –"

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