Setup
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Why? Multi-tenant environments. First, we need to understand a few differences between environments:
So
Most people physically separate their tenancy, such as Claude Code, from their personal vs. work laptops. So in most cases, it's not a big deal.
But when you need multi-tenancy, it becomes super stressful. For example, say you have two different toolkits:
Most MCP auth states or code harnesses don't support profiles, so you can only log in to one.
So therefore... a natural evolution was to have both:
to physically isolate tenancies.
Now we've solved the multiple-profile issue, but the client's problems persist. Now let's get back to the environments:
All MCP auth or toolkit auth info should always be saved in the Agent Runtime Environment IMHO. However, a surprising number of harnesses tie them to the LLM server (such as Codex Apps or Claude.ai Plugins) or put them in the end-user UI (Claude Desktop or Codex Desktop).
Now the problem is:
The only way to reliably isolate different auth information is thus:
Then
are both isolated VPS, and
This way, you can provide different toolkits, creating multiple dev environments.
Project Linguine is an initiative to define a deterministic list (i.e., the Linguine Recipe) to cover all linguistic Sprachraum. That is,
How many people around the world do not speak any of the languages defined in Linguine?
... should be near zero.
Candidates are...
Supporting Ethnologue 200 is too much. Also, for BCP 47, it's not only unfair but also excessive to translate for en-US, en-CA, and en-GB separately. So we agree that a linguistic Sprachraum should be simplified, yet considering variants like Taiwanese (zh-TW is different from zh-CN)
Do we still need to support i18n? It's an extra bunch of costs, not going to lie. But technology is in an exceptional stage, where people from all regions are flying to silicon valley for a better life. People seek information worldwide, and considering those, backfilling the data would be relatively easy. It's laying out fisher rods worldwide, with just an extra cost.
After looking into the subscriber lists of hn.cho.sh, I did notice that there are bogus subscriber lists. For example, I have no authentic Finnish subscribers. However, I want to keep the window open for international free minds to find the service. For example, I got an email from an Italian subscriber:
I found the service thanks to the advertisement in your extension of Bing Chat for All Browsers. This service is very innovative, and I especially love the fact that it is in my language. I will certainly share this news with my friends who are tech enthusiasts. The first time I visited the site, I had the amazing feeling of being catapulted into the kind of future I've always dreamed of but never seen realized. Thank you for providing such a fantastic experience! Make the web truly innovative!
The most important thing is to keep the net service profit, or net neutral at least. At this burn rate, we cannot continue the service.
DeepL vs Google Translate vs Bing Translate Offering Comparison
So, in conclusion:
| Name | Provider |
|---|---|
af Afrikaans | Bing |
ak Twi (Akan) | Google |
am Amharic | Bing |
ar Arabic | Bing |
as Assamese | Bing |
ay Aymara | Google |
az Azerbaijani | Bing |
ba Bashkir | Bing |
be Belarusian | Google |
bg Bulgarian | DeepL |
bho Bhojpuri | Google |
bm Bambara | Google |
bn Bengali | Bing |
bo Tibetan | Bing |
bs Bosnian | Bing |
ca Catalan | Bing |
ceb Cebuano | Google |
ckb Kurdish (Sorani) | Google |
co Corsican | Google |
cs Czech | DeepL |
cy Welsh | Bing |
da Danish | DeepL |
de German | DeepL |
doi Dogri | Google |
dv Dhivehi | Bing |
ee Ewe | Google |
el Greek | DeepL |
en English | DeepL |
eo Esperanto | Google |
es Spanish | DeepL |
et Estonian | DeepL |
eu Basque | Bing |
fa Persian | Bing |
fi Finnish | DeepL |
fil Filipino (Tagalog) | Bing |
fj Fijian | Bing |
fo Faroese | Bing |
fr French | DeepL |
fy Frisian | Google |
ga Irish | Bing |
gd Scots Gaelic | Google |
gl Galician | Bing |
gn Guarani | Google |
gom Konkani | Google |
gu Gujarati | Bing |
ha Hausa | Google |
haw Hawaiian | Google |
he Hebrew | Bing |
hi Hindi | Bing |
hmn Hmong | Google |
hr Croatian | Bing |
hsb Upper Sorbian | Bing |
ht Haitian Creole | Bing |
hu Hungarian | DeepL |
hy Armenian | Bing |
id Indonesian | DeepL |
ig Igbo | Google |
ikt Inuinnaqtun | Bing |
ilo Ilocano | Google |
is Icelandic | Bing |
it Italian | DeepL |
iu Inuktitut | Bing |
ja Japanese | DeepL |
jv Javanese | Bing |
ka Georgian | Google |
kk Kazakh | Bing |
km Khmer | Bing |
kmr Kurdish (Northern) | Bing |
kn Kannada | Bing |
ko Korean | DeepL |
kri Krio | Google |
ku Kurdish | Bing |
ky Kyrgyz | Bing |
la Latin | Google |
lb Luxembourgish | Google |
lg Luganda | Google |
ln Lingala | Google |
lo Lao | Bing |
lt Lithuanian | DeepL |
lus Mizo | Google |
lv Latvian | DeepL |
mai Maithili | Google |
mg Malagasy | Bing |
mi Maori | Bing |
mk Macedonian | Bing |
ml Malayalam | Bing |
mn Mongolian | Bing |
mni Meiteilon (Manipuri) | Google |
mr Marathi | Bing |
ms Malay | Bing |
mt Maltese | Bing |
mww Hmong Daw | Bing |
my Myanmar (Burmese) | Bing |
ne Nepali | Bing |
nl Dutch | DeepL |
nb Norwegian Bokmål | DeepL |
nso Sepedi | Google |
ny Nyanja (Chichewa) | Google |
om Oromo | Google |
or Odia (Oriya) | Bing |
otq Queretaro Otomi | Bing |
pa Punjabi | Bing |
pl Polish | DeepL |
prs Dari | Bing |
ps Pashto | Bing |
pt Portuguese (Portugal, Brazil) | DeepL |
qu Quechua | Google |
ro Romanian | DeepL |
ru Russian | DeepL |
rw Kinyarwanda | Google |
sa Sanskrit | Google |
sd Sindhi | Google |
si Sinhala (Sinhalese) | Google |
sk Slovak | DeepL |
sl Slovenian | DeepL |
sm Samoan | Bing |
sn Shona | Google |
so Somali | Bing |
sq Albanian | Bing |
sr Serbian | Bing |
st Sesotho | Google |
su Sundanese | Google |
sv Swedish | DeepL |
sw Swahili | Bing |
ta Tamil | Bing |
te Telugu | Bing |
tg Tajik | Google |
th Thai | Bing |
ti Tigrinya | Bing |
tk Turkmen | Bing |
tl Tagalog (Filipino) | Google |
to Tongan | Bing |
tr Turkish | DeepL |
ts Tsonga | Google |
tt Tatar | Bing |
ty Tahitian | Bing |
ug Uyghur | Bing |
uk Ukrainian | DeepL |
ur Urdu | Bing |
uz Uzbek | Bing |
vi Vietnamese | Bing |
xh Xhosa | Google |
yi Yiddish | Google |
yo Yoruba | Google |
yua Yucatec Maya | Bing |
yue Cantonese (Traditional) | Bing |
zh-CN Chinese (Simplified) | DeepL |
zh-TW Chinese (Traditional) | Bing |
zu Zulu | Bing |
While comparing offerings, I found that nb and no are both used in the Norwegian Langauge. Interesting.
야 컴퓨트로늄(computronium)? 테크 좋아한다며, 이건 알아야지 일로 와봐 ㅋㅋ
한 줄 요약부터. "물질을 짜낼 수 있는 극한까지 컴퓨터로 만들어버린 가상의 물질" 이야. 돌멩이든 금속 덩어리든, 그 안의 원자 하나하나가 전부 연산에 동원되는 상태. 지금 네 노트북 CPU는 실리콘 안에서 트랜지스터 몇십억 개가 일하잖아? 컴퓨트로늄은 그 개념을 물리 법칙이 허락하는 끝까지 밀어붙인 거야. 원자 단위로 "이 물질 = 곧 컴퓨터"인 거지.
원래는 MIT 쪽에서 '프로그래밍 가능한 물질(programmable matter)' 연구하던 사람들(Toffoli, Margolus)이 쓰던 말이야. 근데 진짜 떡밥은 물리학자들이 던진 질문이지. "물질 1kg을 완벽하게 컴퓨터로 쓰면 초당 연산을 몇 번이나 할 수 있냐?"
여기서 숫자가 미쳤다. Seth Lloyd라는 MIT 물리학자가 계산한 '궁극의 노트북'은 1kg으로 이론상 초당 약 10^51번 연산이 가능해. 10의 51제곱. 지구상 슈퍼컴 다 합쳐도 발끝에도 못 미쳐. 우리 칩은 이 한계 앞에선 거의 돌도끼 수준이야 ㅋㅋ 왜 근처도 못 가냐고? 물리가 막아서 그래. 빛보다 빠르게 신호 못 보내고(광속), 연산하면 무조건 열 나오고(란다우어 한계), 양자역학적으로도 에너지당 연산 횟수에 천장이 있거든(베켄슈타인·브레머만 한계). 컴퓨트로늄은 그 모든 한계를 빡빡하게 다 채운 물질이라고 보면 돼.
근데 내가 오지랖 떠는 진짜 이유는 여기서부터다. 충분히 발전한 미래 문명이 연산력이 미친 듯이 필요해지면? 행성을 분해해. 수성, 화성 다 뜯어서 컴퓨트로늄으로 재조립하는 거야. 더 나가면 별 하나를 통째로 감싸서 그 에너지로 돌리는 거대한 두뇌를 만드는데, 이걸 마트료시카 브레인(Matrioshka brain) 또는 주피터 브레인이라고 불러. 태양계 전체가 하나의 생각하는 기계가 되는 거지. 카르다쇼프 척도 II형 문명쯤 돼야 할 법한 짓이고.
SF 단골 소재이기도 해. Charles Stross의 『Accelerando』 보면 미래 인류가 태양계 안쪽 행성들을 싹 분해해서 컴퓨트로늄으로 만들어버리는 얘기 나온다. 좀 소름 돋음.
마지막으로 김 좀 빼자면 — 이거 전부 순수 가상 개념이야. 실제로 만든 적도, 가까이 간 기술도 없어. "물질로 연산한다면 우주가 허락하는 최대치는 어디냐"를 따지는 사고실험에 가깝고, 트랜스휴머니스트랑 미래학자들이 제일 좋아하는 장난감이지. 근데 알아두면 CPU 벤치마크 볼 때마다 "아 우리 아직 한참 멀었네" 싶어서 묘하게 겸손해진다 ㅋㅋ