What Google Translate can tell us about vibecoding

https://ingrids.space/posts/what-google-translate-can-tell-us-about-vibecoding/

by todsacerdoti • 1 year ago

288 171 1 year ago

dr_dshiv2• 1 year ago

In my limited experience, LLMs can have issues with translation tone — but these issues are pretty easily fixed with good prompting.

I want to believe there will be even more translators in the future. I really want to believe it.

alganet6• 1 year ago

easily fixed with good prompting

Can you give us an example of a typical translation question and the "good prompting" required to make the LLM consider tone?

simonw4• 1 year ago

There was a great thread about that here four months ago: https://news.ycombinator.com/item?id=42894215#42897856

darvinyraghpath• 1 year ago

Fascinating thought piece. While I agree with the thrust of the piece: 'that llms can't really replace engineers', unfortunately the way the industry works is that the excuse of AI, however grounded in reality has been repurposed as a cudgel against actual software industry workers. Sure eventually everyone might figure out that AI can't really write code by itself - and software quality will degrade.. But unfortunately we've long been on the path of enshitification and I fear the trend will only continue. If google's war against its own engineers has resulted in shittier software - and things start break twice a year instead of once - would anyone really blink twice?

tartoran• 1 year ago

Maybe AI can't replace engineers but it surely can apply downward pressure on engineers' salaries.

lodovic2• 1 year ago

I don't believe that. Software has become so expensive in the last decade, that only very large enterprises and venture capitalists were still building custom applications (ymmv). LLMs make it cheaper and faster to create software - you don't need these large teams and managers anymore, just a few developers. Smaller companies will be back in the game.

krackers• 1 year ago

This seems like a terrible comparison since Google Translate is completely beat by DeepL, let alone LLMs. (Google Translate almost surely doesn't use an LLM, or at least not a _large_ one given its speed)

Ninjinka• 1 year ago

For Google's Cloud Translation API you can choose between the standard Neural Machine Translation (NMT) model or the "Translation LLM (Google's newest highest quality LLM-style translation model)".

https://cloud.google.com/translate/docs/advanced/translating...

DeepL also has a translation LLM, which they claim is 1.4-1.7x better than their classic model: https://www.deepl.com/en/blog/next-gen-language-model

ethan_smith• 1 year ago

Google Translate has actually been using neural machine translation since 2016 and integrated PaLM 2 (a large language model) in 2023 for over 100 languages, though DeepL does still outperform it in many benchmarks.

AndroTux• 1 year ago

That’s absolutely not the point of this article. The point was that people said, once Google Translate was introduced, that translators would lose their jobs. Just like people say the same thing about developers with LLMs nowadays. The point is: they didn’t, and they won’t.

DeepL is not part of that point. Yes, maybe eventually, developers will lose their jobs to something that is an evolution of LLMs. But that’s not relevant here.

resoluteteeth2• 1 year ago

The point was that people said, once Google Translate was introduced, that translators would lose their jobs. Just like people say the same thing about developers with LLMs nowadays. The point is: they didn’t, and they won’t.

Translators are losing their jobs now though. Google translate wasn't very good for Japanese so a lot of people assumed that machine translation would never be a threat, but deepl was better to the point where a lot of translation moved to just cleaning up it's output and current state of the art llms as of the last six months are much better and can also be given context and other instructions to reduce the need for humans to clean up the output. When the dust settles translation as a job is probably going to be dead.

tkgally7• 1 year ago

... a translators’ and interpreters’ work is mostly about ensuring context, navigating ambiguity, and handling cultural sensitivity. This is what Google Translate cannot currently do.

Google Translate can't, but LLMs given enough context can. I've been testing and experimenting with LLMs extensively for translation between Japanese and English for more than two years, and, when properly prompted, they are really good. I say this as someone who worked for twenty years as a freelance translator of Japanese and who still does translation part-time.

Just yesterday, as it happens, I spent the day with Claude Code vibe-coding a multi-LLM system for translating between Japanese and English. You give it a text to be translated, and it asks you questions that it generates on the fly about the purpose of the translation and how you want it translated--literal or free, adapted to the target-language culture or not, with or without footnotes, etc. It then writes a prompt based on your answers, sends the text to models from OpenAI, Anthropic, and Google, creates a combined draft from the three translations, and then sends that draft back to the three models for several rounds of revision, checking, and polishing. I had time to run only a few tests on real texts before going to bed, but the results were really good--better than any model alone when I've tested them, much better than Google Translate, and as good as top-level professional human translation.

The situation is different with interpreting, especially in person. If that were how I made my living, I wouldn't be too worried yet. But for straight translation work where the translator's personality and individual identity aren't emphasized, it's becoming increasingly hard for humans to compete.

lukax• 1 year ago

Try Soniox for real-time translation (interpreting). With the limited context it has in real-time, it's actually really good.

https://soniox.com

Disclaimer: I work for Soniox.

dr_dshiv2• 1 year ago

I’ve been looking for that! Thanks

felipeerias• 1 year ago

It is hard to convey just how important it is to be able to provide additional context, ask follow-up questions, and reason about the text.

I live in Japan. Almost every day I find myself asking things like “what does X mean in this specific setting?” or “how do I tell Y to that specific person via this specific medium?”.

Much of this can be further automated via custom instructions, so that e.g. the LMM knows that text in a particular language should be automatically translated and explained.

tkgally7• 1 year ago

It is hard to convey just how important it is to be able to ... ask follow-up questions, and reason about the text.

Great ideas. I'll think about adding those features to the system in my next vibe-coding session.

What I automated in the MVP I vibe-coded yesterday could all be done alone by a human user with access to the LLMs, of course. The point of such an app would be to guide people who are not familiar with the issues and intricacies of translation so that they can get better translations for their purposes.

I have no intention to try to commercialize my app, as there would be no moat. Anyone who wanted to could feed this thread to Claude, ask it to write a starting prompt for Claude Code, and produce a similar system in probably less time than it took me.

aidenn0• 1 year ago

I'm bad with names, so for any Japanese literature, I need to take notes; it's not unusual to see one character referred to by 3 names. Then you might have 3 characters that are all referred to as Tanaka-san at different points in time.

numpad04• 1 year ago

Maybe we should stop using advanced and somewhat hand-wavy vocabulary like "context" for that. The thing is that the prompt has to be long enough.

The word "potatoes" in context of a specific 500-page book has little ambiguity. Same word but extracted out of the same book and fed to a translator(human or machine) in isolation would be much more ambiguous. You probably don't need the whole book, but the solution space do reduce as you give translators more out of the content or how it's used in the original as well as in other parts of translations.

It's similar to how GPS works. With one satellite, your location is precise as "on Earth, I guess". It gets more precise as you add more satellites that further and further reduce margins of errors.

bboygravity• 1 year ago

You just created the software for a profitable business. People would use that and pay for it.

bugtodiffer• 1 year ago

but it is easy to build a competitor

jiehong• 1 year ago

The problem with LLMs for translation is when they refuse to do so if the topic being translated isn’t following their policies, even if the context shows it’s fine here.

It can be as simple as discuss one’s own religion

Jensson• 1 year ago

You can just turn that off, at least on Googles model.

Alex-Programs4• 1 year ago

I made a tool which translates sentences as you browse, for immersion[0]. I solved this by giving the model a code (specifically, "483") to return in any refusal. Then, if I detect that in the output, I fail over to another model+provider.

I also have a few heuristics (e.g. "I can't translate" in many different languages) to detect if it deviates from that.

It works pretty well.

[0] https://nuenki.app

Alex-Programs4• 1 year ago

I've ended up doing a lot of research into LLM translation, because my language learning tool (https://nuenki.app) uses it a lot.

I built something kinda similar, and made it open source. It picks the top x models based on my research, translates with them, then has a final judge model critique, compare, and synthesise a combined best translation. You can try it at https://nuenki.app/translator if you're interested, and my data is at https://nuenki.app/blog

tkgally7• 1 year ago

Very nice! Thanks for the links.

tanvach• 1 year ago

Very neat, love how there’s a formality level selection! Google translate has such bad tendencies to use very formal language (at least when translating into Thai) that it’s almost useless in real life. Some English to Thai examples I tried so far have been quite natural.

boredhedgehog• 1 year ago

What's your approach for dealing with a text too long for an ordinary context window? If I split it into chunks, each one needs some kind of summary of the previous ones for context, and I'm always unsure how detailed they should be.

tkgally7• 1 year ago

I haven’t developed an approach to it yet. In my tests yesterday, I did run into errors when the texts were too long for the context windows, but I haven’t tried to solve it yet.

As a human translator, if I were starting to translate a text in the middle and I wanted my translation to flow naturally with what had been translated before, I would want both a summary of the previous content and notes about how to handle specific names and terms and maybe about the writing style as well. When I start working on the project again tomorrow, I’ll see if Claude Code can come up with a solution along those lines.

f38zf5vdt2• 1 year ago

It's funny -- I independently implemented the same thing (without vibe coding) and found it doesn't actually work. When I ended up with was a game of telephone where errors were often introduced and propagated between the models.

The only thing that actually worked was knowing the target language and sitting down with multiple LLMs, going through the translation one sentence at a time with a translation memory tool wired in.

The LLMs are good, but they make lot of strange mistakes a human never would. Weird grammatical adherence to English structures, false friend mistakes that no one bilingual would make, and so on. Bizarrely many of these would not be caught between LLMs -- sometimes I would get _increasingly_ unnatural outputs instead of more natural outputs.

This is not just for English to Asian languages, even English to German or French... I shipped something to a German editor and he rewrote 50% of the lines.

LLMs are good editors and suggestors for alternatives, but I've found that if you can't actually read your target language to some degree, you're lost in the woods.

crazygringo• 1 year ago

That doesn't match my experience at all. Maybe it's something to do with what your prompts are asking for or the way you're passing translations? Or the size of chunks being translated?

I have been astounded at the sophistication of LLM translation, and haven't encountered a single false-friend example ever. Maybe it depends a lot on which models you're using? Or it thinks you're trying to have a conversation that code-switches mid-sentence, which is a thing LLM's can do if you want?

jedberg• 1 year ago

You give it a text to be translated ... and then sends that draft back to the three models for several rounds of revision, checking, and polishing.

Interesting. Curious if you modeled the cost of that single translation with the multiple LLM calls and how that compares to a human.

tkgally7• 1 year ago

I had Claude Code write a module that monitored the incoming and outcoming token counts and display the accumulated costs. A Japanese-to-English translation that yielded about a thousand words in English cost around US$0.40.

I didn't double-check the module's arithmetic, but it seems to have been in the ballpark, as my total API costs for OpenAI, Anthropic, and Google yesterday--when I was testing this system repeatedly--came to about eight dollars.

A human translator would charge many, many times more.

djaychela• 1 year ago

creates a combined draft from the three translations

How is this part done? How are they chosen/combined to give the best results? Any info would be appreciated as I've seen this sort of thing mentioned before, but details have been scant!

tkgally7• 1 year ago

The combination, compilation, and evaluation process was designed by Claude Code and I haven’t examined or evaluated it closely yet. Here is the log of a session I did just now, after a few more hours of vibe-polishing the program:

https://www.gally.net/temp/20250619translationprogramtrace/i...

The Anthropic servers seem to have been overloaded, but if you read through the above it should give you an idea of how the program is currently doing that synthesis. If you want the code as it stands now (a single HTML file), feel free to email me. My website is linked from my profile page.

Casteil• 1 year ago

It then writes a prompt based on your answers, sends the text to models from OpenAI, Anthropic, and Google, creates a combined draft from the three translations, and then sends that draft back to the three models for several rounds of revision, checking, and polishing.

RIP global power consumption

philsnow• 1 year ago

The distinction between what people typically imagine a translator's job is and the reality reminds me of pixar movies being "localized" instead of just translated (green beans on a plate in the Japan release instead of broccoli because that's the food that Japanese kids don't like).

Lacking cultural context while reading translated texts is what made studying history finally interesting to me.

few• 1 year ago

Another infamous example is Brock's "jelly filled donuts" in pokemon https://knowyourmeme.com/memes/brocks-jelly-doughnuts

amake• 1 year ago

It's important to distinguish that from the Pixar thing.

First, the Pixar thing was green pepper, not green beans: https://www.businessinsider.com/why-inside-out-has-different...

Second, the Pixar one is not "mere" translation; it is full localization because they changed the visual to match the "textual" change.

The Pokemon one is where the change was limited to the "text". The translator's heart might have been in the right place (it would depend on how integral to the story it is that the item is onigiri) but didn't have the authority to make the full breadth of changes needed for such adaptation to be successful.

falcor842• 1 year ago

Is that beans example a real thing? If so, I would hate for my kids to be subjected to that. The best thing about watching films from another country is that you're exposed to the culture of that foreign place and learn about how it's different from yours - I don't see why we'd try to localize away the human experience as if these differences don't exist.

the_af3• 1 year ago

Same. I don't understand why people want (them and their kids) to be isolated from other cultures. If you're watching a movie set in Japan, India or China, have it be about their culture. If there's something you or your kids don't understand, make an effort to learn about it (and the green peas thing seems trivial to understand).

Netflix also does something absurd with their subtitles. I was watching "The Empress" (which is set in the Austro-Hungarian Empire) with German language and English subtitles. I like listening to the real actors' voices, and learning the sounds and cadence of the language. So the characters speak in Italian for a while (subtitles say "[speaking in Italian]", and when they switch back to German the subtitles clarify.. "[in English]". The fuck, Netflix? Surely the viewer of this show understands they didn't speak in English in the Austro-Hungarian empire, so why write it's English? What the hell is Netflix even trying to achieve here? Seems robotic: "us = English speakers, therefore everyone's default must be English"?

infecto• 1 year ago

I understand the sentiment and agree but for me there is a line and I am not sure Inside Out meets the threshold for exposing culture. The changes are too minor to me in a children’s film that it has little impact. Broccoli to peppers is not a deep enough change. Now if the film had a Chinese new year celebration in it and they switched it entirely to a western new year celebration I would think that is a pretty drastic change that does hide cultural changes.

ktosobcy• 1 year ago

Erm... yeah, cool and whatnot but: 1) in case of pixar those are just animations that are mostly "generic" (or in fairyland) hence adapting them to the local nuance to pass some idea makes sense 2) as a Pole that had to be basically "brainwashed" by US made movies - while being exposed to other cultures is great, being firehose-fed by "dream factory" was IMHO one of the worst thing that happened to "post-commie" countries.

dlisboa• 1 year ago

Localization is more important than you might think.

My wife worked for a company that helped provide teaching content for schools throughout Brazil. They'd interview teachers all over the country and one of the complaints from teachers in isolated communities was that they had to use the same textbooks as other places in Brazil without any regard to their own situation.

They reported that many examples for starting math for kids featured things like "strawberries" or "apples", things the kids had never seen or maybe heard. So now they needed to abstract over what is a "fruit" and a "countable object" as well as whatever the example was trying to teach. Teachers reported less engagement and it was more work for them to adapt it to local relevance.

Try to teach kids about vegetables in the US midwest and use green beans and Bok Choy as an example, for instance. It doesn't make sense.

sodality23• 1 year ago

This article is spot on about a lot of things. One thing I think it fails to address is this:

I feel confident in asserting that people who say this would not have hired a translator or learned Japanese in a world without Google Translate; they’d have either not gone to Japan at all, or gone anyway and been clueless foreigners as tourists are wont to do.

The correlation here would be something like: the people using AI to build apps previously would simply never have created an app, so it’s not affecting software development as a career as much as you first expect.

It would be like saying AI art won’t affect artists, because the people who would put in such little effort probably would never have commissioned anyone. Which may be a little true (at least in that it reduces the impact).

However, I don’t necessarily know if that’s true for software development. The ability to build software enabled huge business opportunities at very low costs. I think the key difference is this: the people who are now putting in such low effort into commissioning software maybe did hire software engineers before this, and that might throw off a lot of the numbers.

MarkusQ2• 1 year ago

Conversely, it may create jobs. Why? Because the more elephants you have in your parade, the more jobs there are for folks to walk behind them with a broom and bucket. For decades we've seen tools that "let users write their own software" and every one of them has driven up the demand for people to clean it up, make it scale, make it secure, or otherwise clean up the mess.

sodality23• 1 year ago

Also true! But that world is one where the vast majority of time is spent cleaning up slop code, so if there's a general shift towards that, I think that still changes the job in a significant way. (I don't have extensive history in the industry yet so I may be wrong here)

scuff3d2• 1 year ago

CAD, Matlab, and Altium made electrical and mechanical engineers more valuable, not less.

The work got easier, so what we do got more complex.

camillomiller2• 1 year ago

This has been a stable source of business for a while in my niche.

candiddevmike• 1 year ago

I think you could extrapolate it and say folks are primarily using GenAI for things they aren't considered a specialist in.

steveBK123• 1 year ago

Google translate is a good example too in terms of better-than-nothing to the completely uninitiated, helpful to someone with a little knowledge, and obviously not a replacement for a professional. That is - the more you know, the more you see its failures.

I know enough Japanese to talk like a small child, make halting small talk in a taxi, and understand a dining menu / restaurant signage broadly. I also have been enough times to understand context where literal translation to English fails to convey the actual message.. for example in cases where they want to say no to a customer but can't literally say no.

I have found Google Translate to be similarly magical and dumb for 15 years of traveling to Japan without any huge improvements other than speed. The visual real-time image OCR stuff was an app they purchased (Magic Lens?) that I had previously used.

So who knows, maybe LLM coding stays in a similar pretty-good-never-perfect state for a decade.

sodality23• 1 year ago

So who knows, maybe LLM coding stays in a similar pretty-good-never-perfect state for a decade.

I think this is definitely a possibility, but I think the technology is still WAY too early to know that if the "second AI winter" the author references never comes, that we still wouldn't discover tons of other use cases that would change a lot.

jf• 1 year ago

The visual real-time image OCR stuff was an app they purchased (Magic Lens?) that I had previously used.

Word Lens, by Quest Visual

https://en.wikipedia.org/wiki/Quest_Visual

Miraste• 1 year ago

I think you're right, AI art and AI software dev are not analogous. The point of art is to create art. There are a lot of traditions and cultural expectations around this, and many of them depend on the artist involved. The human in the loop is important.

Meanwhile, the point of software development is not to write code. It's to get a working application that accomplishes a task. If this can be done, even at low quality, without hiring as many people, there is no more value to the human. In HN terms, there is no moat.

It's the difference between the transition from painting to photography and the transition from elevator operators to pushbuttons.

tptacek2• 1 year ago

The reasonable concern people have about AI eliminating coder jobs is that they will make existing coders drastically more productive. "Productivity" is literally defined as the number X of people required to do Y amount of stuff.

I'm not sure how seriously people take the threat of non-coding vibe-coders. Maybe they should! The most important and popular programming environment in the world is the spreadsheet. Before spreadsheets, everything that is today a spreadsheet was a program some programmer had to write.

simonw4• 1 year ago

I'm still optimistic that the net effect of making existing programmers drastically more productive is that our value goes up, because we can produce more value for other people.

alganet6• 1 year ago

everything that is today a spreadsheet was a program some programmer had to write

That is incorrect, sir.

First, because many problems were designed to fit into spreadsheets (human systems designed around a convenient tool). It is much more likely that several spreadsheets were _paper_ before, not custom written programs. For a lot of cases, that paper work was adapted directly to spreadsheets, no one did a custom program intermediate.

Second, because many problems we have today could be solved by simple spreadsheets, but they often aren't. Instead, people choose to hire developers instead, for a variety of reasons.

bgwalter2• 1 year ago

I'm currently getting two types of ads on YouTube: One is about how the official Israeli Gaza humanitarian efforts are totally fine and adequate (launched during the flotilla with Greta Thunberg).

The other is about an "AI" website generator, spamming every video at the start.

I wonder what kind of honest efforts would require that kind of marketing.

15123123• 1 year ago

yeah I think the case for AI art is very different. I see major brands, even those who has been very generous with artist commission like McDonald Japan. is now using AI art instead.

imiric• 1 year ago

The correlation here would be something like: the people using AI to build apps previously would simply never have created an app, so it’s not affecting software development as a career as much as you first expect.

I don't think the original point or your interpretation is correct.

AI will not cause a loss of software development jobs. There will still be a demand for human developers to create software. The idea that non-technical managers and executives will do so with AI tools is as delusional as it was when BASIC, COBOL, SQL, NoCode, etc. were introduced.

AI will affect the industry in two ways, though.

First, by lowering the skill requirements to create software it creates a flood of vibe coders competing for junior-level positions. This dilutes the market value of competent programmers, and makes entering the software industry much more difficult.

A related issue is that vibe coders will never become programmers. They will have the ability to create and test software, which will improve as and if AI tools continue to improve, but they will never learn the skills to debug, troubleshoot, and fix issues by actually programming. This likely won't matter to them or anyone else, however, but it's good to keep in mind that theirs is a separate profession from programming.

Secondly, it floods the software market with shoddy software full of bugs and security issues. The quality average will go down causing frustration for users, and security holes will be exploited increasing the frequency of data leaks, privacy violations, and unquantifiable losses for companies. All this will likely lead to a rejection of AI and vibe coding, and an industry crash not unlike the video game one in 1983 or the dot-com one in 2000. This will happen at the bottom of the Trough of Disillusionment phase of the hype cycle.

This could play out differently if the AI tools reach a level of competence that exceeds human senior software engineers, and have super-human capabilities to troubleshoot, fix, and write bug-free software. In that case we would reach a state where AI could be self-improving, and the demand for human engineers would go down. But I'm highly skeptical that the current architecture of AI tools will be able to get us there.

carlosjobim• 1 year ago

As long as the person you are talking or writing to is aware that you're not a native speaker, they will understand that you won't be able to follow conventions around polite languages or understand subtle nuances on their part. It's really a non issue. The finer clues of language are intended for people who are from the same culture.

devnullbrain2• 1 year ago

All this is not to say Google Translate is doing a bad job

Google Translate is doing a bad job.

The Chrome translate function regularly detects Traditional Chinese as Japanese. While many characters are shared, detecting the latter is trivial by comparing unicode code points - Chinese has no kana. The function used to detect this correctly, but it has regressed.

Most irritatingly of all, it doesn't even let you correct its mistakes: as is the rule for all kinds of modern software, the machine thinks it knows best.

simonw4• 1 year ago

That doesn't sound like a problem with Google Translate, it sounds like a problem with Google Chrome. I believe Chrome uses this small on-device model to detect the language before offering to translate it: https://github.com/google/cld3#readme

devnullbrain2• 1 year ago

Archived in 2024

numpad04• 1 year ago

IMO, it's still not too late and it'll never be too late to split and reorganize Unicode by languages - at least split Chinese and Japanese. LLMs seem to be having issues acquiring both Chinese and Japanese at the same time. It'll make sense for both languages.

The syntaxes aren't just different but generally backwards, and, it's just my hunch but, they sometimes sound like they are confused about which modifies word which.

jjani2• 1 year ago

It's only a matter of time before they have an LLM both 1. cheap 2. fast 3. good enough that they'll replace Google Translate's current model with it. I'd be very surprised if they'd put more than 1 hour of maintenance into Translate's current iteration over the last 12 months.

NicuCalcea• 1 year ago

While it's just anecdotal evidence, I have translator friends and work has indeed been drying up over the past decade, and that has only accelerated with the introduction of LLMs. Just check any forum or facebook group for translators, it's all doom and gloom about AI. See this reddit thread, for example: https://www.reddit.com/r/TranslationStudies/comments/173okwg...

While professionals still produce much better quality translations, the demand for everything but the most sensitive work is nearly gone. Would you recommend your offspring get into the industry?

tossaway0• 1 year ago

I imagine even for professional teams with clients that need proper translations, LLMs have made it so one person can do the work of many. The difference between the quality of former automatic translations and LLM translations is huge; you couldn't rely on auto translation at all.

Now a professional service only needs a reviewer to edit what the LLM produces. You can even ask the LLM to translate in certain tones, dialects, etc. and they do it very well.

neilv• 1 year ago

Some additional things that translators do (which I recall from a professional translator friend, put in my own words):

* Idioms (The article mentions in passing that this isn't so much a difficulty in Norwegian->English, but of course idioms usually don't translate as sentences)

* Cultural references (From arts, history, cuisine, etc. You don't necessarily substitute, but you might have to hint if it has relevant connotations that would be missed.)

* Cultural values (What does "freedom" mean to this one nation, or "passion" to this other, or "resilience" to another, and does that influence translation)

* Matching actor in dubbing (Sometimes the translation you'd use for a line of a dialogue in a book doesn't fit the duration and speaking movements of an actor in a movie, so the translator changes the language to fit better.)

* Artful prose. (AFAICT, LLMs really can't touch this, unless they're directly plagiarizing the right artful bit)

yieldcrv• 1 year ago

This is like the worst comparison since generative AI is far better at conversational translation than google translate

LLM’s will tell you idioms, slang, and the point behind it

You can take a screenshot of telegram channels for both sides of a war conflict and get all context in a minute

In classic HN fashion I’m sure I missed the point, ok translators are still in demand got it.

Google Translate has been leapfrogged by the same thing that allows for “vibecoding”

noname120• 1 year ago

The article starts with a giant straw man and miscaracterisation, not sure that I want to read the rest of the article at this point

BergAndCo• 1 year ago

Literally the first example is an outright lie.

At the dinner table a Norwegian is likely to say something like “Jeg vil ha potetene” (literally “I will have the potatoes”, which sounds presumptuous and haughty in English). Google Translate just gives the blunt direct translation.

"To will" means "it is my will", i.e. to want to, which became the future tense in English. In Norwegian is still means "want", and Google Translate indeed translates it as "I want the potatoes." If you translate the rising (pleading) intonation on "potatoes", you then have an unwritten "please?", i.e. "I want the potatoes?...", which is passable English.

Most businesses think AI code is "good enough", and that machine translation is "good enough", which tanks the entire industry because there is now more supply than demand. He says there are still plenty of translator jobs, but then justifies it as because "it’s inadvisable to subsititute (sic) Google Translate for an interpreter at a court hearing." Meaning, the thing taking away all the tech jobs temporarily (unchecked mass-migration) is the same thing keeping keeping him employed temporarily.

ryao3• 1 year ago

At the dinner table a Norwegian is likely to say something like “Jeg vil ha potetene” (literally “I will have the potatoes”, which sounds presumptuous and haughty in English) where a brit might say “Could I please have some potatoes?”.

I find “I will have the potatoes” to be perfectly fine English and not haughty in the slightest. Is this a difference between British English and American English?

jvanderbot2• 1 year ago

When ordering, "I will have" sounds reasonable.

When asking someone to pass them to you, just imagine them turning to you, looking you in the eye, and asserting "I will have the potatoes" like it's some kind of ultimatum. Yes, that is strange.

roxolotl• 1 year ago

It’s such an anachronistic statement I laughed out loud reading your comment. I even was taught that you can’t pass things mid air. You place the potatoes down between each person required to pass them to the person who wants them.

noobermin• 1 year ago

Americans are extremely polite, and American English is replete with niceties in everyday speech. It's funny, having been a tourist abroad, it's only living in a significantly non American country for a few years that lead me to realise this. I even lived in another country albeit a former US colony for ten years and didn't even notice it there given American influence.

I stopped saying, stuff "I would like a latte today" or more Midwestern (could I get a latte today etc) in singapore because people would just get confused. Same with being too polite when recieving things. There's ways to be polite but it usually involves less words because anything else confuses people.

sudahtigabulan• 1 year ago

could I get a latte today actually

To me (non-American) the above sounds like sarcasm, not politeness. Adding "today" and/or "actually" could mean you've had it with their delays.

I like to joke that Americans always seem to find ways to get offended by innocuous things, but in this case the joke is on me.

rr808• 1 year ago

Maybe its a NY thing I was shocked when I heard people in restaurants saying "I want...". Growing up outside the US "want" is a very impolite word. People in US are polite but direct, usually English/Irish people are much less direct.

danpalmer4• 1 year ago

Americans are extremely polite

Having grown up in the UK and living in Australia, I do not find Americans polite. To me, politeness is "please", "thank you", "may I have", etc, whereas "I would like a latte today" reads to me as a demand. In context it's fine (it stands out a bit but not in a problematic way), it's not particularly rude, but in general just stating your desires is not considered polite in my experience in UK/AU.

There are some other parts of American English that may be considered polite, I notice a lot of US folks addressing me as "sir" for example, but this sort of thing comes off as insincere or even sarcastic/rude.

I know this is how people communicate so they don't really bother me, I'm used to them and accept that different people have different expectations. I also understand that Americans might believe they are being polite and consider me to be rude, but I think this is why blanket statements like "Americans are extremely polite" are just missing so much cultural nuance.

SoftTalker2• 1 year ago

It would also depend on the tone of voice and even body language used.

koala_man• 1 year ago

I'm Norwegian and concluded that she meant when ordering, such as for a choice of potatoes or pasta.

This makes sense since the context is translation for tourism.

Otherwise, the normal, casual way would be "kan du sende potetene?" i.e. "could you pass the potatoes?", lit. "can you send the potatoes?"

(This assumes it wasn't physically possible to simply reach across people to grab it yourself with what's known as "the Norwegian arm")

jezzamon• 1 year ago

I was thinking about this comparison recently along a slightly different axis: One challenge when working with translations (human or machine translations) as that you can't vet whether it's correct or not yourself. So you just have to either trust the translation and hope it's the best. It's a lot easier to trust a person than a machine, though I have had someone message me once to say "this translation of your article is so bad I feel like the translator did not put in a serious attempt"

It's similar to vibe coding where the user truly doesn't know how to create the same thing themselves: You end up with output that you have no way of knowing it's correct, and you just have to blindly trust it and hope for the best. And that just doesn't work for many situations. So you still need expertise anyway (either yours or someone else's)

stevage• 1 year ago

Well no, you can run the output. That gives you some measure of correctness.

danpalmer4• 1 year ago

No I think the original comment is correct. You need to be able to evaluate the result.

The goal of software is not to compile and run, it's to solve a problem for the user when running. If you don't know enough about the problem to be able to assess the output of the program then you can't trust that it's actually doing the right thing.

I've seen code generated by LLMs that runs, does something, and that the something would be plausible to a layperson, but that I know from domain knowledge and knowing the gotchas involved in programming that it's not actually correct.

I think the comparison with translation is a very apt one.

eurleif• 1 year ago

You can kinda validate machine translation by doing a circular translation, A->B->A. It's not a perfect test, but it's a reasonably strong signal.

ruszki• 1 year ago

I’m learning German, and I quite often use this test. Google Translate fails this most of the times. This is true even between Hungarian and English. The difference with the latter one is, that I can properly choose between the options given to me, if there are, without translating it back. Especially, that that passed many times when it gave terrible translations.

So this test fails many times, and even when not, the translation is still usually not good. However, when you don’t care about nuances, it’s still fine usually. And also translation seems to be better if the text is larger. Translating a single word does almost always fail. Translating a whole article is usually fine. But even there it matters what you translate. Translating the Austrian subreddit fails quite often. Sometimes completely for whole large posts. Translating news is better.

numpad04• 1 year ago

Round tripping is definitely better than nothing, but it lets through a lot of "engrish" errors with multi-meaning words and with implied perspectives. Cape as in clothing and cape as in pointy seasides, general as in military rank vs general as in generic, etc.

e.g. "Set up database as: [read replica]" and "Database setup complete: [a replica was loaded.]" may translate into a same string in some language.

vasco• 1 year ago

So you just have to either trust the translation and hope it's the best. It's a lot easier to trust a person than a machine

Only because you think the machine will be incorrect. If I have a large multiplication to do it's much easier to trust the calculator than a mathematician, and that's all due to my perception of the calculator accuracy.

autobodie• 1 year ago

"Behold the impeccable nuance of my opinion"

Kiro• 1 year ago

I see claims from one side that “I used $LLM_SERVICE_PROVIDER to make a small throwaway tool, so all programmers will be unemployed in $ARBITRARY_TIME_WINDOW”, and from the other side flat-out rejections of the idea that this type of tool can have any utility.

No, the one side is saying that all their code is written by LLMs already and that's why they think that. In fact, I would say the other side is the former ("it works for throwaway code but that's it") and that no-one is flat-out rejecting it.

banq• 1 year ago

LLM=Google Translate +Context

DidYaWipe• 1 year ago

Hopefully it tells everyone to never use this douchey term again.

camillomiller2• 1 year ago

> For what it’s worth, I don’t think it’s inconceivable that some future form of AI could handle context and ambiguity as well as humans do, but I do think we’re at least one more AI winter away from that, especially considering that today’s AI moguls seem to have no capacity for nuance, and care more about their tools appearing slick and frictionless than providing responsible output.

Fantastic closing paragraph! Loved the article

Seanambers• 1 year ago

Prompting and context solves this.

nottorp3• 1 year ago

There was a fun one on OSNews:

https://www.osnews.com/story/142469/that-time-ai-translation...

yoden• 1 year ago

Machine translation is a great example. It's also where I expect AI coding assistants to land. A useful tool, but not some magical thing that is going to completely replace actual professionals. We're at least one more drastic change away from that, and there's no guarantee anyone will find it any time soon. So there's not much sense in worrying about it.

A very similar story has been happening in radiology for the past decade or so. Tech folks think that small scale examples of super accurate AIs mean that radiologists will no longer be needed, but in practice the demand for imaging has grown while people have been scared to join the field. The efficiencies from AI haven't been enough to bridge the gap, resulting in a radiologist _shortage_.

Workaccount22• 1 year ago

Just a note on the radiologist part, the current SOTA radiology AI is still tiny parameter CNN's from the mid-late 2010's running locally. NYT ran an article a few weeks about this, and the entire article uses the phrase "A.I.", which people assume means ChatGPT, but really can refer to anything in the last 60 years of A.I. research. Manually digging revealed it was an old architecture.

We don't know yet how a modern transformer trained on radiology would perform, but it almost certainly would be dramatically better.

TechDebtDevin• 1 year ago

That wouldnt be that much different than current CNN/labeling methods used on medical imaging. Last time I got a ct scan the paperwork had the workstation specs and the models/nueral network techniques used.

demosthanos• 1 year ago

We don't know yet how a modern transformer trained on radiology would perform, but it almost certainly would be dramatically better.

Why? Is there something about radiology that makes the transformer architecture appropriate?

My understanding has been that transformers are great for sequences of tokens, but from what little I know of radiology sequence-of-tokens seems unlikely to be a useful representation of the data.

ptx2• 1 year ago

Do you still have the links to what you dug up manually?

throwaway2037• 1 year ago

    > Machine translation is a great example. It's also where I expect AI coding assistants to land. A useful tool, but not some magical thing that is going to completely replace actual professionals.

I can say from experience that machine translation is light years ahead of 15 years ago. When I started studying Japanese 15 years ago, Google Translate (and any other free translator) was absolutely awful. It was so bad, that it struggled to translate basic sentences into reasonable native-level Japanese. Fast forward to today, it is stunning how good is Google Translate. From time to time, I even learn about newspeak (slang) from Google Translate. If I am writing a letter, I regularly use it to "fine-tune" my Japanese. To be clear: My Japanese is far from native-level, but I can put full, complex sentences into Google Translate (I recommend to view "both directions"), and I get a reasonable, native-sounding translation. I have tested the outputs with multiple native speakers and they agree: "It is imperfect, but excellent; the meaning is clear."

In the last few years, using only my primitive knowledge of Japanese (and Chinese -- which helps a lot with reading/writing), I have been able to fill out complex legal and tax documents using my knowledge of Japanese and the help of Google Translate. When I walk into a gov't office as the only non-Asian person, I still get a double take, but then they review my slightly-less-than-perfect submission, and proceed without issue. (Hat tip to all of the Japanese civil servants who have diligently served me over the years.)

Hot take: Except for contracts and other legal documents, "actual professionals" (translators) is a dead career at this point.

Alex-Programs4• 1 year ago

Also, Google Translate is really not a particularly good translator. It has the most public knowledge, but as far as translators go it's pretty poor.

DeepL is a step up, and modern LLMs are even better. There's some data here[0], if you're curious - DeepL is beaten by 24B models, and dramatically beaten by Sonnet / Opus / https://nuenki.app/translator .

[0] https://nuenki.app/blog/claude_4_is_good_at_translation_but_... - my own blog

rstuart4133• 1 year ago

Hot take: Except for contracts and other legal documents, "actual professionals" (translators) is a dead career at this point.

Quote from article:

it turns out the number of available job opportunities for translators and interpreters has actually been increasing.

p3rls• 1 year ago

I just posted that Google is translating words that should be translated like "bastard" in foreign pop music (in this case, a member of the most popular boy band in the world, BTS) as racial slurs like the n-word. This is pretty much the worst case error scenario for a translation service.

https://kpopping.com/news/2025/Jun/17/Google-Translation-of-...

It's amazing more people aren't talking about this stuff, how incompetent do you have to be to allow racial slurs in translation, especially with all the weights towards being pro-diversity etc that already exist?

Just more enshittification from ol Sundar and the crew

insane_dreamer• 1 year ago

I've done freelance translation in two different language pairs, for 20 years (mostly as a side thing). A few thoughts on this:

- Google Translate has always been garbage for professional translation work, which is why human translators have been needed.

- LLMs can write in a way that sounds native (at least in English), which is something that ML translation software was bad at. They can also understand context to some degree and can adopt tones. This is a huge leap forward that makes it suitable for a large majority of translation work _between common language pairs_ (Hindi to Thai is probably safe).

- The vast majority of translation work is commercial in nature, and most cases, "decent" is good enough. Cost is prioritized over occasional mistakes. Prices have been falling for years already. Many agencies now pay peanuts because they expect you to use AI and "just" do some light proofreading. Except that often the "light proofreading" was actually "heavy editing" that often took more work than translating from scratch. It's not worth it.

- Do not lump translators and interpreters together when discussing this subject. Interpreters aren't going away and their job is much more difficult to replace with AI (for a variety of reasons). What they do is very different than translators (some do both of course).

- There are some exceptions to "decent is good enough", where: 1) context/localization is critical (a major advertising campaign), 2) accuracy of the message is critical (a government pronouncement), 3) linguistic excellence is critical (a novel). This may be the most visible parts, but also a very small fraction of the overall market.

My conclusion is that translators won't disappear altogether but their ranks will shrink considerably.

voxleone• 1 year ago

>For what it’s worth, I don’t think it’s inconceivable that some future form of AI could handle context and ambiguity as well as humans do,

Absolutely! AI might get better at context, but there's still no substitute for a seasoned dev who’s had to untangle a 2 a.m. deployment gone wrong. As for vibe coders — hey, good vibes are great, but they won’t refactor a legacy monolith on their own.

coolpool• 1 year ago

I've just launched https://www.verbascan.com/ — it does context-aware photo translations. Still early (doesn’t ask questions yet), but even at this stage, it's clear how much better the results are when intent and nuance are factored in. Would love any feedback if you give it a try.

rehearsalsj• 1 year ago

shebeurb• 1 year ago

What Google Translate can tell us about vibecoding

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