I'm writing this in English.

[ddelemeny@mastodon.xyz]

@hongminhee @silverpill How do you think translators shape or maintain your abilities in a foreign language, as opposed to research and experimentation ?

[hongminhee@hollo.social]

@julian@activitypub.space Thank you for saying this. The ActivityPub development community being Euro-America-centric isn't just a cultural observation. It shapes what gets built, what use cases are considered, and whose needs are treated as edge cases. Language is a big part of that, and I'm glad the point landed.

And yes, apparently the chardet post found its audience. I was not expecting that particular piece to take off, but I'll take it!

[julian@activitypub.space]

@hongminhee@hollo.social do you think your writing skills will improve with continued reading of the LLM-reflected translations, to the point where you may no longer need it?

[phnt@fluffytail.org]

@hongminhee @silverpill Maybe consider writing posts in both languages, Korean and English. Multi-language posting on the protocol side is in its early infancy and basically does not exist, but you at least don't seem to have the arbitrary character limit on posts that a certain blue elephant has. It might not be a bad idea to take advantage of that. Even if the english part is slightly broken, there is still the possibility of defaulting to a translation.

Not sure how that would hold up in reality, but it seems like a reasonable option to me, even though translators in $current_year are getting worse instead of better in general. Google Translate is barely usable now.

[hongminhee@hollo.social]

@ddelemeny@mastodon.xyz @silverpill@mitra.social I relate to the immersion argument, and I think it's part of why I avoided machine translation for so long—not out of principle, but because the output wasn't worth learning from. Older MT between Korean and English produced something closer to a word-by-word skeleton than actual language. You couldn't look at it and think: oh, that's how a native speaker would put it. It was more like a scaffold you had to tear down before building anything.

LLMs are different enough that I've had to revise that instinct. The output is often genuinely idiomatic, and when I read a phrase that lands exactly right, there's a recognition that functions a lot like learning—the same feeling as encountering a sentence in a book and thinking: I'll remember that. I do find myself absorbing expressions that way, probably more than I would have expected.

That said, I think your point holds at the edges. For shorter writing I still work without assistance, partly for practical reasons and partly because I notice the difference when I don't. So I suspect I'm arriving at something similar to what you're describing, just from the other direction—using the tool for longer texts while trying to keep the muscle from atrophying entirely on shorter ones.

The dynamic you mention with German and Korean is interesting too. Korean was my concern about English; I imagine the lack of immersion shapes the experience in ways that are hard to compensate for with tools alone.

[hypolite@friendica.mrpetovan.com]

@lain_7 It would be the case if these tools weren't aggressively integrated in everything we use. If there's a murky water tap in your city, then it's up to the users to appropriately filter the output for safe consumption. Now if the murky water tap is forcibly installed in every household because the city received bribes for it, then the responsibility shifts from individual users to the murky water tap provider. Even if users can get somewhat safe water from adequate filtration.

[hongminhee@hollo.social]

@julian@activitypub.space I actually just addressed something close to this in a reply up the thread—might be worth a read!

[hongminhee@hollo.social]

@phnt@fluffytail.org Multilingual posting is something I've actually been thinking about and experimenting with already. I'm building a fediverse platform for software developers called Hackers' Pub, where I've been prototyping exactly this kind of feature. My other project, @hollo@hollo.social, is where I post from right now, and I'd like to bring something similar there eventually—the main obstacle is that most fediverse platforms don't properly render multilingual posts even when they receive them—the protocol already supports it via contentMap, but implementations like Mastodon tend to pick one language arbitrarily rather than presenting all of them.

Outside the fediverse, my blog already works this way: each post is written in multiple languages (Korean, Japanese, and English), not as translations filed separately but as the same post published in all three. It's a pattern I find natural given how I actually think and write across languages.

On Google Translate: I stopped using it for Korean–English a long time ago, for the same reasons you'd expect. These days I mostly use Kagi Translate, which is LLM-based and noticeably better for distant language pairs. The gap between that and older MT is stark enough that I think “machine translation” has started to mean two quite different things depending on which generation of tools you're talking about.

[ddelemeny@mastodon.xyz]

@hongminhee @silverpill Thank you for replying with care, your POV is really interesting.
Have you read the Reg's article about semantic ablation that was shared around some time ago ?

https://www.theregister.com/2026/02/16/semantic_ablation_ai_writing/

This may be part of why other commenters allegedly found a negative difference in your writing using MT, and a concern I have about building fluent writing skills. MT (and autocomplete) collapse possibilities into an average, that's probably correct enough but also probably low entropy.

[julian@activitypub.space]

@hongminhee@hollo.social thanks, good answer :smile:

I would wonder then that maybe you might end up sounding like an LLM, then. Best interject some of your own style later on :wink:

[hongminhee@hollo.social]

@ddelemeny@mastodon.xyz That's a useful framing, and the article is worth reading. The concern about entropy collapse is real—I've seen it happen when native speakers run their own writing through a model and get something smoother but somehow emptier back.

My situation is a bit different, though. The high-entropy original is in Korean. The LLM's job is to carry that across, not to sand it down. Whether it succeeds is a fair question, but the direction of the process matters. I'm not polishing a draft into blandness; I'm trying to get something that exists in one language to exist in another without losing its shape.

Anyway, this has been a genuinely interesting exchange. Thank you for the link.

[hongminhee@hollo.social]

@julian@activitypub.space Yeah, that's why I'm still writing short words myself. My accent won't go anywhere!