3 ms·

> LLM translation is shit Compared to who? Compared to a professional with a language degree, with a feel and love for both languages and an understanding of t

> LLM translation is shit Compared to who? Compared to a professional with a language degree, with a feel and love for both languages and an understanding of the subject area, LLM translation is shit, no question. But such professionals don't get hired by startups to localize their websites, too expensive. When comparing to paid- by-the-word contractors who do website localization, I am not so sure that LLM is worse - because in practice too many biologically-human-localized websites and apps are translated horrifically.

applfanboysbgon 2mo ago
My experience with dirt cheap contractors you're talking about is that they simply throw what you put into Google Translate / an LLM themselves. So yes, strictly speaking, doing that yourself is better than paying someone else to do it for you. But it's not better than hiring a real professional, so let's not pretend it is. It is what it is: cheap. Be up front about that. And I think using machine translation, and being honest about it, is completely understandable for some tiny startup that just wants their website localized. I think it is completely and totally unacceptable for a language learning application, though.
- stuess 2mo ago
  The point I'm making isn't (in life or in this blog post) that LLMs do a better job than humans. My point is that LLMs can get pretty close with the right context, and in some circumstances they can build context better than the typical human translator would. Most CAT tools do vet for ML/LLM translations these days, so "cheap" human translation is mostly ML-assisted and human-edited, but my entire point is that they're not to blame, the majority of translation fails happens because of the lack of context, not because the human didn't try. It's about setting the site and l10n infrastructure out in a way that gives them the freedom to translate in the way that makes most sense for their language without being forced into "English in a costume". It is unfortunately a fact that one can be both things: a startup and a language learning app. But my entire point wasn't about LLMs vs. humans, it was about laying out the architecture in a way that enables great l10n, whether we do that with LLMs today or humans tomorrow once we can afford it.
  - applfanboysbgon 2mo ago
    > The point I'm making isn't (in life or in this blog post) that LLMs do a better job than humans. Your literal headline claim is that LLMs are better than humans. With a caveat attached, sure, but you're immediately setting the tone with that. > It is unfortunately a fact that one can be both things: a startup and a language learning app You know what you do in that case? Teach the languages you know! It's arrogant and greedy beyond belief to think you have any ability or right to "teach" people 58 languages. If you were genuinely interested in helping people learn and not making a quick AI startup cash grab, you'd start with the language pair you're most fluent in, then if that has any success, slowly expand your offerings once your concept is proven, hiring more people as you can. Of course, such a rational business as that probably doesn't sound as juicy as "we used AI to SOLVE TRANSLATION" to the investors you're hoping to attract...
stuess 2mo ago
My point here is exactly that, as a startup, there's l10n that we can afford and l10n that's perfect. Could a human that has plenty of time to build context, browse the website, think about and learn our product do a better job at transcreating? They sure would. But the reality for us (and many other startups) is that the options are no l10n and locking people who don't speak English (well) out of our product or having one that we - at least - do our best to make feel pretty native. We also built a version in Simple English. (I wrote an article sharing that process, too: https://reelang.com/open-startup/blog/how-to-build-a-simple-english-version-of-your-website https://reelang.com/open-startup/blog/how-to-build-a-simple-...) There is also a reality that coding agents do have the ability to build more context than the average human translator with the average tooling like Smartcat or Weglot would.

applfanboysbgon 2mo ago

My experience with dirt cheap contractors you're talking about is that they simply throw what you put into Google Translate / an LLM themselves. So yes, strictly speaking, doing that yourself is better than paying someone else to do it for you. But it's not better than hiring a real professional, so let's not pretend it is. It is what it is: cheap. Be up front about that. And I think using machine translation, and being honest about it, is completely understandable for some tiny startup that just wants their website localized. I think it is completely and totally unacceptable for a language learning application, though.

stuess 2mo ago
The point I'm making isn't (in life or in this blog post) that LLMs do a better job than humans. My point is that LLMs can get pretty close with the right context, and in some circumstances they can build context better than the typical human translator would. Most CAT tools do vet for ML/LLM translations these days, so "cheap" human translation is mostly ML-assisted and human-edited, but my entire point is that they're not to blame, the majority of translation fails happens because of the lack of context, not because the human didn't try. It's about setting the site and l10n infrastructure out in a way that gives them the freedom to translate in the way that makes most sense for their language without being forced into "English in a costume". It is unfortunately a fact that one can be both things: a startup and a language learning app. But my entire point wasn't about LLMs vs. humans, it was about laying out the architecture in a way that enables great l10n, whether we do that with LLMs today or humans tomorrow once we can afford it.
- applfanboysbgon 2mo ago
  > The point I'm making isn't (in life or in this blog post) that LLMs do a better job than humans. Your literal headline claim is that LLMs are better than humans. With a caveat attached, sure, but you're immediately setting the tone with that. > It is unfortunately a fact that one can be both things: a startup and a language learning app You know what you do in that case? Teach the languages you know! It's arrogant and greedy beyond belief to think you have any ability or right to "teach" people 58 languages. If you were genuinely interested in helping people learn and not making a quick AI startup cash grab, you'd start with the language pair you're most fluent in, then if that has any success, slowly expand your offerings once your concept is proven, hiring more people as you can. Of course, such a rational business as that probably doesn't sound as juicy as "we used AI to SOLVE TRANSLATION" to the investors you're hoping to attract...

stuess 2mo ago

My point here is exactly that, as a startup, there's l10n that we can afford and l10n that's perfect. Could a human that has plenty of time to build context, browse the website, think about and learn our product do a better job at transcreating? They sure would. But the reality for us (and many other startups) is that the options are no l10n and locking people who don't speak English (well) out of our product or having one that we - at least - do our best to make feel pretty native. We also built a version in Simple English. (I wrote an article sharing that process, too: https://reelang.com/open-startup/blog/how-to-build-a-simple-english-version-of-your-website https://reelang.com/open-startup/blog/how-to-build-a-simple-...) There is also a reality that coding agents do have the ability to build more context than the average human translator with the average tooling like Smartcat or Weglot would.