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HTML Visit Hacker News on the Web
COMMENT PAGE FOR:
HTML "Don't You Just Upload It to ChatGPT?"
Markoff wrote 1 hour 12 min ago:
Some of my clients use the LLM to do QA on my translations, dunno about
English, but for smaller languages (think less than 10M speakers) LLM
still ain't that good, at least 5-10% LLM suggestions contain
hallucinated made-up words which don't even exist.
I can see LLM usable for long paragraphs of text, legal documents,
maybe even books if you don't care about artistic quality, but good
luck translating software/UI with short strings with hardly any
description/screenshots even human has trouble to figure out let alone
dumb intelligence.
I already told one of my clients who work for one of the major Chinese
companies I can't guarantee quality of translation if they don't
provide me variables description and all screenshots are in Chinese, so
basically you are blind whether you are translating button, toast with
instruction for user or page title, but seems client doesn't care...
Nowadays I don't even bother explaining why are AI reports wrong, it
would be huge waste of my time, if 99% are FP.
semiquaver wrote 1 hour 56 min ago:
âSo itâs all Gell-Mann amnesia?â
âAlways has beenâ
zelphirkalt wrote 2 hours 15 min ago:
Typical for HR. Not able to understand the qualifications of others,
lauding AI, down-talking other people's work. The number of jobs I
would have already gotten, if not for an HR person, who doesn't
understand my qualification or the level of it, and if only they had
asked a capable engineer to take one good look at my own projects,
which I am exposing in my application documents ... The way HR people
work, their work-ethics, and the way they do not work, is a huuuge
problem.
cainxinth wrote 3 hours 20 min ago:
> One of my clients has insane style guides, plural. Iâm talking
about 500-page documents detailing the proper way to format quotes and
the one true way to insert footnotes.
Thatâs absurd overkill.
hoherd wrote 4 hours 8 min ago:
This reminds me of that scene from The Covenant:
> You're here to translate.
> Actually, I'm here to interpret.
telesilla wrote 5 hours 42 min ago:
This is all really nice but I have so many friends lost their
translation and voice acting jobs that they are leaving for other
fields, except for the high paid professional who have publishing and
actor unions behind them.
stuaxo wrote 6 hours 15 min ago:
We should rename AI psychosis The AI Delusion, since it's really about
people being deluded (often that it can do everyone else's job not
there's) and because ironically Richard Dawkins seems to have fallen
fully into being fully deluded by it.
GreenSalem wrote 12 hours 27 min ago:
Despite the protests, he admits using AI and then charging his clients
full price...
"But maybe I will ask Claudeâs opinion, and if one of the suggestions
is smartâcutting a paragraph, for instance, or clarifying a
sentenceâI might accept it.
When I started translating 15 years ago, we used to paste uncooperative
sentences into Google Translate to see if it had interesting ways to
phrase things differently. Then came DeepLâsame idea."
zhuli wrote 12 hours 23 min ago:
Hi, it's me, I wrote the article! I'm a she, BTW.
I do admit testing AI. Hell, most of the time, I don't have the
choice anymoreâI don't use it but several of my clients send
AI-translated documents. Do I just send back a CHatGPT version? Hell
no. This is why and how I know it's not reliable or good.
It's not exactly taboo to use AI, is it? IT doesn't have to be all or
nothing. AI is great for my glossaries. AI is shit to translate.
zhuli wrote 12 hours 37 min ago:
Hey guys,
I just found out you were discussing my article, so obviously I had to
come here. ;-)
Iâll take the time to read the thread properly because, hey, you took
the time to read my article. Also, I genuinely enjoy reading and Iâm
curious to see what you think about AI.
The anecdote in the article is real, by the way. I only changed her
title.
With AI, I went from âsurely this wonât affect meâ to âAI is
dumbâ â no, I was dumb, I just didnât know how to prompt it â
and now Iâm at the âhow can I make it work for me?â stage, while
still hoping employers, clients and, well, the entire world realize
itâs NOT a magic button.
Itâs crazy how unreliable it can be. Sure, it can translate in the
sense that it can give you an idea of what was said. But that doesnât
mean itâs good. I could give a million examples...
anotherevan wrote 10 hours 38 min ago:
Welcome to the crazy lolly shop that is Hacker News. Be warned
though, as is written on many a candy wrapper: may contain nuts.
Also, it is positively charming that you think most of us took the
time to properly read something before coming here to espouse an
opinion. :-)
epaga wrote 10 hours 57 min ago:
If you look at the trajectory of your stance, do you think you might
reach "Uh-oh this is doing just as good a job as I can do in a much
shorter time?" within the next year? I feel like that's what happened
to pure coding for me, something I never ever thought would be
possible.
The unreliability is something that seems like it might be a
temporary early stage.
victor22 wrote 13 hours 40 min ago:
Marijuana ilegal
zhuli wrote 12 hours 17 min ago:
Ah, a fellow Manu Chao fan!
defrost wrote 8 hours 58 min ago:
Sing something good to me, yeah.
bch wrote 14 hours 40 min ago:
Everybody else is a fungible cog.
TFA is a good little read - couple things come to mind
1) Knollâs Law [0][1]
2) The ways I feel when Iâm working on a hard problem in an area of
my expertise and some person starts in with âWhy donât you
justâ¦â. Enough people have come to me in such a situation with such
a comment that I think it mostly translates as a sort of shibboleth for
âI have no real idea what Iâm talking about.â Now to find out if
this is a teachable moment, if I have to maintain a sense of humour, or
find out if Iâm actually one of the days lucky 10,000.[2]
[0] [1] [2]
HTML [1]: https://effectiviology.com/knolls-law/
HTML [2]: https://en.wikipedia.org/wiki/Erwin_Knoll
HTML [3]: https://xkcd.com/1053/
tapland wrote 16 hours 25 min ago:
One of my parents tried this to beat a deadline for product packaging.
There are now bags being sold marked "Lawn Suits", when it was supposed
to be Lawn Topdressing
gizajob wrote 16 hours 31 min ago:
I canât believe this article hasnât been written by ChatGPT. The
author claims to have written it but has clearly become completely
captured by the awful generic style of AI writing.
phendrenad2 wrote 16 hours 42 min ago:
Reminded me of this quote:
"Expertise in one field does not carry over into other fields. But
experts often think so. The narrower their field of knowledge the more
likely they are to think so." - Robert Heinlein
In this case, the gym buddy doesn't think that she's an expert in the
other field, but dismisses it as something ChatGPT can do with ease.
GreenSalem wrote 17 hours 6 min ago:
I had transliterated lyrics of a song * with stanzas in Urdu , Braj
Basha, Persian and Arabic , that I wanted to understand better ..
Gemini did a pretty good job of translating this to English .
Sure a professional human translator would have done a more nuanced job
if I was willing to invest the money and time . But ...
* tajdar e haram originally by Payam Saihalwi, later versions by the
Sabri Brothers and recently by Asif Aslam
themafia wrote 16 hours 53 min ago:
Is the assumption that the LLM did the translation? Or that it just
understood your query and submitted, on your behalf, to a tool you
could have just used directly?
tkgally wrote 17 hours 30 min ago:
As a former freelance translator (1986 to 2005, Japanese to English), I
have much sympathy for the writer. But I wouldnât be so confident
that AI cannot do professional-level translation.
She writes: âI adapt, I localize, and I find the best way to convey
the original message so it makes sense and feels natural. I research
terminology. I make sure itâs consistent throughout.â
Iâm sure she has other important insights into what enables her to do
her job well. The problem is whether or not such insights can be
incorporated into an AI-driven translation system, too.
Since early this year, I have been experimenting with a variety of
agentic systems for language-related tasks, including
dictionary-writing, research on topics in the philosophy of language,
essay-writing, and translation. Other than the dictionary [1], I am
keeping the results private, so they havenât been evaluated by
others. But my personal assessment is that agentic systems given
suitable high-level guidance can be very good at such tasks now.
If I were still freelancing and I had a large translation job to do for
a client, here is the outline of the prompt I would give to Claude to
get it started:
âUse this private GitHub repository to build a system for translating
[genre of text] from [Language1] to [Language2]. The directory samples/
contains examples of the type of document to be translated,
high-quality human translations of those documents, and texts in
[Language2] that are in writing styles that I believe to be appropriate
for this genre of translation. The file guidelines.md contains my
general instructions about the needs of my client and my preferences
for how you should translate texts along various axes (natural vs.
literal, informal vs. formal, preferred dialect in [Language2],
consistency vs. variety in terminology translation, etc.). Begin
building (1) a knowledge wiki for this project using Karpathyâs
LLM-wiki framework and (2) a system inspired by Karpathyâs
Autoresearch, AutoResearchClaw, etc. for testing and recursively
improving both the functioning of the system and the quality of the
translations. For the actual translation, editing, checking, etc., use
not only your own ability and the knowledge assembled in (1) but also
outsource such tasks to other frontier models through OpenRouter, and
use adversarial evaluations among those models and yourself to check
and recursively improve the system design, the prompt-writing for other
models, and any translations created by the system. My OpenRouter API
key is available in this environment. You may spend up to $xx per day
in API calls until this project is ready to do real translations;
before beginning a real job, give me an estimate for how much the API
calls will cost for that job. The initial build-out of this project
will take many sessions, so write a prompt called resume-prompt.md that
I can point you to at the start of a scheduled Routine to have you work
on this. Commit and squash-merge to main at the end of each session. I
will be checking in occasionally to view your progress and to ask you
to run translation tests, and I will offer guidance then on how to
improve the pipeline further and make the translations closer to what
my client needs. If you have any questions before you begin, please ask
me.â
HTML [1]: https://www.tkgje.jp
thi2 wrote 17 hours 45 min ago:
I recently saw a video showing the french to german translation of a
french McDonald's terminal.
The translations were hilarious bad, like old school google translate
bad.
Maybe McDonalds is big enough to not care about their reputation, maybe
they are happy about the free clout from people making fun of them but
they certainly chose to cheap out on translations.
HTML [1]: https://www.tiktok.com/@denneshow/video/7522160205501566230
r0m4n0 wrote 17 hours 52 min ago:
I say itâs a simple value proposition.
A few examples
Audio book narration. Human narrators are paid a seemingly ridiculous
amount of money to literally read a book out loud. We have the tech to
replace them, itâs actually pretty dang good, and it is substantially
cheaper to do with computers. Itâs pretty accurate too. In the audio
book industry though, if you take your book seriously you have a real
person read it. The best one you can find that you like. Readers enjoy
hearing good narrators and the total value one narrator can bring is
very high mostly because the value scales well.
Another real world example that doesnât scale well, call centers.
Customers want humans, but execs have tried to replace them with
automation in every way possible. The margins of a business get
squeezed because the value of the human touch doesnât scale well in
this case.
Translation falls a bit in the middle. Iâm sure ChatGPT is good
enough for some people. If you are a restaurant and need to understand
what you are ordering at the local authentic Italian restaurant itâll
do the job. If you have a bad food allergy? Maybe not, you are willing
to pay for accuracy because thatâs what a human brings
So the answer to the question posed in the article, canât you just
upload it to ChatGPT? Maybe yea maybe no
antonvs wrote 18 hours 5 min ago:
Jesus fuck, stop with the chatgpt written posts.
TZubiri wrote 18 hours 23 min ago:
â
627467 wrote 18 hours 25 min ago:
I'm gonna sound a bit like the clueless gym hr lady: I assume most
income generating translation jobs are either mandated by law or
commercially high stakes enough to warrant a human to do, no? Were
people really being paid to do the type off _low stakes_ translations
implied that a automated system can replace?
Maybe a publisher will replace the translator of the next Dan Brown
best seller with Mythos? Who cares other than those buying it, getting
money out of it?
d_runs_far wrote 18 hours 27 min ago:
As a public service employee within the GOC, I feel the pain expressed
by the author. I sat through a meeting today where somebody with no
domain knowledge puffed up their chest to show off their gpt created
master lesson plan for a four year long internal training plan that is
being re-worked.
I could feel the heads of those around the table that had been teaching
this material for a decade starting to explode as this was exactly what
others in the thread have described: it looked good until vetted by
experts, then it was easy to poke holes as it was just not right
The problem in the public service is that the experts who can review
the output are leaving or being nudged out.
robmn wrote 18 hours 30 min ago:
Denial isn't just a river in Egypt
robmn wrote 18 hours 30 min ago:
Denial is tangible
dyauspitr wrote 18 hours 46 min ago:
This is all bullshit. I speak 4 languages, 3 fluently. Even chatGPT
does a stellar job with translation. For most things people want
translated- forms, administrative documents etc. I doubt you even need
a human in the loop.
That being said, something with essence like a novel definitely still
needs to be done by a human.
karakoram wrote 19 hours 17 min ago:
Safe to say OP just does NOT like AI [1] Poor woman should really look
into pivoting her career or finding a different way of making money.
Truth be told, her industry/career is not going to get better.
Consistent work will just not fall from the sky.
Being bitter will not improve her situation. Even organizations like
UN/OECD are looking into implementing AI in various ways.
Really good blog though. I love life blogs like these! You can go back
and live through so many interesting/pivotal moments.
HTML [1]: https://correresmidestino.com/sorry-i-was-busy-unfucking-my-ai...
thi2 wrote 17 hours 43 min ago:
I wonder when this is posted about your or my profession.
karakoram wrote 13 hours 48 min ago:
Just to clarify, I am not saying this is a negative or offensive
way. Just that she needs to proactively look into her options as I
think its not going to get better, at least in the near term.
To answer your question, I think its happening as we speak, in
small ways for some and in big ways for others.
Who knows really, either all this is a phase that pops with the AI
bubble popping or something all of us will have to consider.
acyou wrote 20 hours 19 min ago:
"we all more or less look the same in gym clothes"
Maybe my brain works differently than the author, but I'm surprised at
this statement. Gym clothes don't change recognition for me, it's about
the face, body, posture, clothes don't really enter into it. For me it
is nonsensical enough to be suspicious.
And for a human centric perspective, not recognizing who someone is
sad, it's knowing that you probably won't meet them again so it's not
worth it, the community isn't there. Where community and interpersonal
relationships between people are something we still hold dearly.
zhuli wrote 12 hours 18 min ago:
I wrote the article.
I'm a real person.
And I'm shit at recognizing people I don't interact with. PIcture 50
of us in black legging in front of a mirror...!
anotherevan wrote 10 hours 29 min ago:
It's possible you have a touch of prosopagnosia, also known as face
blindness. It would make sense as you would recognise people you
interact with more regularly by other things (e.g.: voice, or even
body or posture as the grandparent comment mentioned), but
unfamiliar people tend to me harder to identify.
ibudiallo wrote 20 hours 30 min ago:
Slight tangent into translations:
I read two translations of the book "The Master and Margarita". My
first read was so boring I couldn't help but stop reading before the
end of the first chapter. I can't find the copy and the name of the
person who translated it, but this one had all the Russian nicknames
translated. It kept talking about a guy called homeless. I thought it
was just a bad book and dismissed it for years. I couldn't understand
what all the fuss was about with this book.
But then, I stumbled upon the translation by Diana Burgin and Katherine
Tiernan O'Connor. Although I don't speak Russian, I think this is as
good as it gets. They did a phenomenal job.
You can see the same effect with the mechanical translation of the book
"We" by Yevgeny Zamyatin, where the government is called "United State"
easily confused with the "United States". The translation that called
it "One State" was so much better.
rciorba wrote 3 hours 43 min ago:
I read the first Dune books in Romanian, then re-read the first one
in English, and I was amazed at how nice the translation was. I
actually prefer it to the original. For example, stillsuit sounds
really basic, but distrai, a portmanteau of "a distila" (to distil)
and "strai" (old word for clothes) lands differently for me.
buggy6257 wrote 2 hours 14 min ago:
Now Iâm wondering if âstillâ is meant to be short for
âdistillââ¦
semiquaver wrote 1 hour 53 min ago:
Of course it is.
HTML [1]: https://en.wikipedia.org/wiki/Still
TheChetan wrote 9 hours 54 min ago:
I had a similar experience reading the âCount of Monte Cristoâ. I
gave up multiple times when reading the first translation.
anotherevan wrote 10 hours 57 min ago:
I still clearly remember in my early twenties being stunned to
discover that the Astérix comics are originally written in French
and then translated. Coming up with names like Getafix in English for
the druid â incroyable.
juancn wrote 20 hours 38 min ago:
The most important thing a human translator does is certify that the
translation is faithful.
Period.
You could do a machine translation if you want, but you better pore
over every word in case you end up on the witness stand.
pazimzadeh wrote 20 hours 52 min ago:
LLM's are in fact very good at translation and transliteration.
majdalsado wrote 19 hours 37 min ago:
Some would say that's exactly what they do best, learn a language and
be able to transform across them. Hence, "language" model.
Ancapistani wrote 20 hours 42 min ago:
Yeah, I agree - I get what the author is saying, but I also don't
expect "translator" to be a practical career path in the future.
Even small, dumb, local models are excellent at translation already.
Frontier models are on par or better than the human translations
we've tested them against at work.
atleastoptimal wrote 20 hours 59 min ago:
You'd be laughed at if you said that ChatGPT could help you with
graduate level mathematics in 2024, but this year, AI models on simple
prompts are solving previously unsolved Erdos problems.
It seems silly to imagine that there is some fundamental barrier
between human intelligence and AI, and that AI could never do many of
the things that humans can do. Inferring intent, gauging sentiments,
factoring in cultural values, etc. all the things cited as stuff humans
can do but AI can't, AI can currently do if given enough context. But
more importantly, all those things aren't magical tasks that can only
occur inside a human skull, they are a product of information
processing, its just the information processing that has been hard to
make computers good at, but so far it appears AI keeps getting better.
I'm all for humans having special value that is not attached to their
ability to perform useful work. However denying the abilities of AI
models seems to be a common mistake many people are making, and sadly
reality catches up to these people before they can emotionally prepare.
4k0hz wrote 15 hours 46 min ago:
> all those things aren't magical tasks that can only occur inside a
human skull, they are a product of information processing
I agree but it's useful to remember that 1. brains and especially the
human brain are enormous and 2. individual tokens carry significantly
more meaning than individual tiny muscle twitches so even extremely
primitive "cognition" can look like it's doing more work than it
actually is.
zymhan wrote 15 hours 57 min ago:
> You'd be laughed at if you said that ChatGPT could help you with
graduate level mathematics in 2024, but this year, AI models on
simple prompts are solving previously unsolved Erdos problems.
I'm curious, do you have a graduate degree in mathematics?
woopwoop wrote 11 hours 45 min ago:
I have a graduate degree in mathematics. AI models can absolutely
help you do research math in 2026. I recently asked chatGPT to
prove a result which I know to have been published in Advances in
Mathematics (a pretty good, but not top tier, journal) this year,
and it gave a correct proof which was completely distinct from the
one that was published.
TZubiri wrote 18 hours 18 min ago:
As mentioned in the article, the point of language is to communicate
with other humans, and you need a human to do that.
Mathematics is famously rigorously defined, it's roughly analog to AI
beating humans at chess. Sure it's impressive, but it's also
something you'd expect machines to be good at.
tim333 wrote 8 hours 9 min ago:
People have been skeptical of them doing advanced maths because it
involves complicated thinking which the 'stochastic parrot' folk
thought wouldn't happen.
while_true_ wrote 20 hours 18 min ago:
Yes. It's as if they think AI will forever be LLM only and won't
develop world models that incorporate current state assessment,
dynamic next-state prediction, cause-and-effect reasoning, object
permanence, etc. I'm not in the AI industry but I assume there's got
to be lots of research and work being done on this.
cptroot wrote 20 hours 26 min ago:
> AI can currently do if given enough context
It's worth noting that you can substitute "dollars" for "context" in
that sentence, which seems to be where many of these impressive
achievements are coming from. As ever, it's unclear whether these
models will get cheaper while remaining better, since all of the
recent breakthroughs appear to be of the "think more" kind. For
translation specifically, I'd be very surprised if the "think more"
LLMs would help given the per-unit cost expected of the output.
jaggederest wrote 20 hours 26 min ago:
Fable has really spooked me, honestly. It's another big jump, but not
in the actual coding. I was pretty comfortable with the "you do the
implementation, I do the meta work and steering", and ... no steering
required, no meta work required. Here's the backlog, let me know when
it's complete, I guess I'm going to go touch grass until I have to
review and refine... probably tomorrow?
Reminds me of the first time I saw a coding agent stumble through an
issue in 2023 maybe? and went "this is a big deal", similarly when OG
gpt started making jokes that actually kinda worked.
Updated modern version of the classic "make me a greentext",
apologies for slop-posting, but it seems relevant:
> be me
> senior software engineer
> in charge of making sure the tickets get, in fact, implemented
> occasionally have to open the IDE and write some code myself
> one day i open the IDE and the ticket is already closed
> the agent did it overnight
> no steering, no review notes, nothing left for me to do
> distress.jpg
> ask my manager what to do
> he says "just focus on the high-level architecture stuff"
> i say "what high-level architecture stuff"
> he says "i don't know, you're the senior engineer"
> rage.jpg
> quit my job
> become a prompt engineer, nice and simple, just tell it what to
build
> first day on the job, sit down to write the prompt
> AI already wrote it
rustcleaner wrote 12 hours 58 min ago:
Spicy... I giggled.
balefulboy wrote 19 hours 49 min ago:
Greentext is eh. Very formulaic, in fact very similar to the
bottomless pit one, which I'd argue is better because of it's
absurdity. I have to ask, did you mention the older GPT version to
fable in the prompt?
jaggederest wrote 18 hours 21 min ago:
Of course I did! Wouldn't be faithfully mediocre without the
right context
robertnowell wrote 21 hours 1 min ago:
the version of this skillset that stays employed is "now I translate
10000x more than i could before by managing a fleet of agents. by
encoding my experienced taste and judgement into robust evals, I've
helped my ai translators be far better than chatgpt on its own, and
much more cost effective compared to manual human translation"
jovial_cavalier wrote 21 hours 1 min ago:
You don't even need to argue that you're better than the AI. The point
is that the client could have uploaded it to ChatGPT too. Perhaps they
even did, and they didn't like the answer they got. They are sending it
to a human because they want a human to do the work. If you were to
send back ChatGPT output, that would be fraud.
yaky wrote 21 hours 12 min ago:
I don't see LLMs being able to replace translators for less-spoken
languages.
I know a translator between two Eastern European languages, and some
jobs require use of specialized dictionaries. Using LLMs in such cases
would be very unreliable and would require even more effort to check
and correct than doing it correctly in the first place. Plus, I really
doubt that US tech firms are training LLMs on language spoken by "only"
6 million people.
As for entertainment, anyone who grew up in Eastern Europe with pirated
movies with nasal monotone translations, or machine-translated video
games knows how much those take away from the experience. Sure, "AI
could do better", but could it be consistent and capture cultural
nuances and idioms, etc?
tim333 wrote 8 hours 2 min ago:
I use Google Translate quite a lot and it's pretty good even for
obscure languages. The voice to text thing on youtube videos has
improved a lot in the last five years.
Re. not training on obscure languages, the current thing seems to be
to chuck all digital information available into the training so
although they probably don't hire a human, the specialist
dictionaries are probably in there.
jiehong wrote 21 hours 9 min ago:
Even more so for spoken-only languages.
dmitrygr wrote 21 hours 25 min ago:
Any expert in any field will gladly tell you that ML sucks for
specifics of their field (and it does). But if you are not an expect in
that field, it looks convincing enough to make you think that maybe it
is OK for that field, and your field is somehow unique. It is not. Any
expect in any field will confirm to you that ML produces
plausible-looking slop which is occasionally completely wrong. This is
the case for all fields.
loloquwowndueo wrote 21 hours 31 min ago:
> If you ask me, nothing can save downtown Ottawa or North American
public transit.
Come to Montreal. Only 2H away and you can get by decently well without
a car.
robertnowell wrote 21 hours 32 min ago:
unfortunately this person will soon be unemployed.
not because their skills are no longer relevant, but because they are
taking a principled stance defending now irrelevant skills.
xboxnolifes wrote 19 hours 48 min ago:
Close. They will be unemployed because AI be "good enough" and
companies won't care about it being better. Nothing they mentioned
was really about principles. Everything was about quality output. Too
bad companies dont care about quality.
karakoram wrote 13 hours 27 min ago:
Exactly, companies and even NGOs/charities that might be past
clients of hers will only look at costs, not her experience.
robertnowell wrote 12 hours 7 min ago:
their number one priority is solving their problem so they can
realize their organization's mission, and that's how it should
be.
if the translation is good enough to solve their problem, then it
doesn't need to be any better.
robertnowell wrote 21 hours 33 min ago:
unfortunately this person will soon be unemployed.
bwhiting2356 wrote 21 hours 41 min ago:
AI should be used for all the bullshit tasks that no one wants to do.
There are garbage dumps full of stuff that can be reused and recycled.
But it's not high enough ROI to pay someone $25/h to sort trash, so it
isn't happening.
ghusto wrote 21 hours 54 min ago:
Sounds a aweful lot like the kind of things we were all saying before
realising that we had to change what our jobs meant.
Chuzam wrote 21 hours 58 min ago:
Who is gonna tell her?
km3r wrote 21 hours 58 min ago:
> Should you pay your roofer less because he uses a hammer instead of
his bare hands?
Yes. Effective tools increase the supply of roofs made. More supply
means lower prices per roof. But because the same number of roofs need
to get worked on, the increase in roofs per roofer means less roofers
will be needed.
AnodicElegy wrote 22 hours 13 min ago:
Out of curiosity, I pasted an article in French I was reading a few
minutes before coming across this thread into ChatGPT and asked for a
translation into English. It was certainly passable from a functional
perspective, and I wouldn't hesitate to use it to translate an article
from a language I don't understand. But it was not professional-quality
work. There were a couple instances where the French grammar was
mistranslated, and the writing was perfunctory, not going into any
effort to have the article flow like it was originally written in
English instead of simply translating each sentence literally. Would I
read an article written like this? A short one. A novel? Definitely
not.
HDThoreaun wrote 21 hours 25 min ago:
I think the issue is that a lot of professional work is being done
when the commissioner would be perfectly fine with non professional
work. There will always be a place for artful translation, theres a
place for hasty translation as well.
throw310822 wrote 18 hours 55 min ago:
Especially when you get three assignments from 4 to 6 pm, all due
for the day after. It's certainly literary translation they're
after.
esafak wrote 22 hours 44 min ago:
This is just about the worst career you could be in right now. Of
course people are just going to upload it to ChatGPT. Processing text
is its forte.
This person is in the first stage of grief (denial); artists are
several stages ahead. Most customers are not going to care about the
difference in translation quality unless it's in a regulated sector.
tiborsaas wrote 23 hours 16 min ago:
It's quite ironic as the transformer architecture that powers most
generative AI was invented for language translation :)
TekMol wrote 23 hours 19 min ago:
AI isnât replacing me. Like a toddler, it
needs to be constantly coached.
Like a toddler, it will grow up.
Humans are really bad at noticing trajectories. They see the current
situation. They know what the situation was 5 years ago. But for some
reason they do not believe that there is a trajectory. They view the
present state as the final destination.
jubilanti wrote 19 hours 35 min ago:
> Like a toddler, it will grow up. Humans are really bad at noticing
trajectories.
Yourself included??
robertnowell wrote 21 hours 3 min ago:
head in the sand
FromTheFirstIn wrote 22 hours 21 min ago:
Itâs been basically the same for 3 years now. Are you sure weâre
the ones who canât see trends?
Ancapistani wrote 20 hours 34 min ago:
Your experiences must be much different from mine.
Three years ago, AI was barely able to provide sort-of reliable
command completion.
Two years ago, it could extrapolate a single function from a
docstring - but the docstring had to be so verbose that it wasn't
practical to use in that way.
A year ago, I was tinkering with Devin to try to find a way to get
it to reliably implement small, isolated features from verbose Jira
tickets.
Six months ago, I started using AI to generate the majority of my
code output. Most of my time was spent reviewing, and I was
ecstatic to reach ~2x output because I could run the next task
while reviewing the last.
Now, at work I'm managing a half dozen Claude Code instances, Devin
sessions, and orchestrating a review loop between Claude, Devin,
and CodeRabbit. It's not uncommon for me to be working on four or
more discrete features at once. My output is approximately 15x my
pre-AI baseline - and I've not sat down and written a line of code
directly in six months.
At home I'm managing a Hermes agent that can spin up a whole fleet
of purpose-tuned agents for whatever purpose I'd like. I've
implemented spec-driven development a'la Acai, and extended it to
the point that my agent creates specs from text or voice
conversation, I review them, and it handles implementation
end-to-end. The code itself is an almost disposable artifact -
useful primarily to ensure no regressions have been introduced
between rounds.
... I simply don't understand how you can assert that "it's been
basically the same for 3 years". It absolutely has not.
FromTheFirstIn wrote 12 hours 52 min ago:
It sounds like our experiences are different. My software work
isnât on products where code can be disposable, since it
affects peopleâs lives in material ways. Iâm not sure why
youâre launching fleets of agents at home, either.
NichoPaolucci wrote 17 hours 35 min ago:
Cmon - cursor has been out for like 3.5 years at this point. AI
was still in its infancy but it was definitely able to complete
tasks, albeit smaller ones.
Not disputing the overall trajectory, yeah itâs gotten better.
But it was definitely capable of more than just command
completion 3 years ago.
I reach for it more frequently. But personally, itâs at the
point of diminishing returns for my work. Itâs capable enough
now to handle most of the things I want to throw at it, sometimes
itâs wrong, sometimes itâs right.
Iâm not doing cutting edge deep tech work - and I also donât
have the motivation (or salary increase) to be 15X more
productive, if thatâs even measurable. We are so busy because
the CEO hears these â15Xâ statements and then the pressure is
on to match or exceed that, and Iâm not playing that game.
allknowingfrog wrote 23 hours 16 min ago:
Sure, just like AI enthusiasts seem to be unfamiliar with the concept
of local maxima...
athrowaway3z wrote 23 hours 22 min ago:
So i assume this post is just a bit of writing out frustration, but i'm
always hoping that "AI can't do it" posts to include examples.
A list of "Examples AI will silently fail at" would be a lot more
interesting, and might just convince your next potential client to
_not_ use AI.
xp84 wrote 23 hours 23 min ago:
The ending is a really powerful point. Most people apparently agree on
two things:
1. AI is a great boon for all tasks and specialties we donât have the
skills to do ourselves. Understandable, since (A) weâre ill equipped
to see the flaws in its output because it isnât our area of
expertise, and (B) it often can unlock great gains because if we trust
it, we then donât have to pay and wait for humans to do that thing.
2. AI is a terrible replacement for me - my skills are at such a high
level that itâs almost theoretical that itâll ever be good enough
to replace me for 90% of what I get paid to do. Itâs a tool at best.
This is why I use AI for all my medical questions and doctors use AI to
write software, and we both smirk at the quality the other person is
getting from it.
fennecbutt wrote 10 hours 10 min ago:
>itâll ever be good enough to replace me for 90% of what I get paid
to do
This is more "humans are special" hubris imo. Not saying it's gonna
happen tomorrow but look at the advancements from just 2019 to now.
It's unwise to say it'll never happen.
Al-Khwarizmi wrote 11 hours 24 min ago:
my skills are at such a high level that itâs almost theoretical
that itâll ever be good enough to replace me for 90% of what I get
paid to do.
Is it really true for most people that they are using their core
advanced skills 90% of the time? I'm curious about how people feel
about this.
I'm a professor, which is supposed to be an intellectually demanding
job. I do research in NLP/AI, and I don't think AI will replace my
core intellectual tasks in the near future, but I don't think my core
intellectual tasks represent even 10% of my time. Most of the time is
taken by various things like writing bureaucratic reports, writing
and polishing grant applications, grading exams and exercises,
designing a poster, planning a course's calendar for a given year,
creating a figure for slides, writing assignments and exams,
attending teaching coordination meetings... which definitely are or
should be automatable. Probably even teaching the same lesson for the
umpteenth time also is from an objective point of view, we'll
probably be kept doing it due to the human factors driving motivation
but not because a lecture given by a human is intellectually
superior.
NIckGeek wrote 11 hours 41 min ago:
The fundamental issue imo is that LLMs are trained to make believable
outputs. They can be complete horseshit, but because they look
plausible they get treated like quality.
I swear that the intensity and time I've had to take with code
reviews has gone up because LLMs are so good at making flawed code
look good. I assume the same goes for everything else we use LLMs
for.
Npovview wrote 13 hours 0 min ago:
We should create a generalized version of "Gell-Mann Amnesia". This
applies not just to fields of study. But also to time and space. We
read history as if the person who wrote the history book has perfect
knowledge.
Xeoncross wrote 16 hours 5 min ago:
Honestly, we're at a point where AI can write better software than
some devs and answer medical questions with more knowledge than some
doctors.
Likewise, AI is oblivious to it's own mistakes, much like said
professionals can be at times.
Not that AI is actually thinking, but rather the collective corpus of
text yields greater insights (knowledge of the crowd, not wisdom of
the crowd) than a lower-average person in that same industry.
perrygeo wrote 19 hours 2 min ago:
At what point does this become an issue for data quality and global
epistemology?
It seems inevitable that we ask for more AI assistance on topics we
don't understand. And therefore have the least context to correct.
Result: a flood of poor quality information.
In areas we DO understand, we'll either not ask AI at all, or treat
its results with a higher degree of skepticism. Result: a lack of
high quality information.
Inevitably this means a higher volume of non-expert prompts gets
translated into the next generation of internet content. AIs are
pumping out more novice-level text and less expert guidance.
The result will be an internet full content written from the
perspective of an ignoramus; not addressing any complex issues,
staying surface level on every topic. Which will cascade into future
models, etc.
tpmoney wrote 15 hours 12 min ago:
> The result will be an internet full content written from the
perspective of an ignoramus; not addressing any complex issues,
Not to be overly negative, but have you really looked at the vast
majority of the content on the internet? There are good pockets of
real, in depth content. But the absolute vast majority of it is
surface level basics at best, and completely wrong hot takes at
worst. Content farms and click spam have made up huge portions of
the internet for a while, never mind the absolute hell holes that
places like Facebook, Twitter and Tumblr were and have been. And
that's before you consider how often news media gets stuff wrong
and then everyone copies everyone else's homework. Knowledge
propagation, and more specifically correct knowledge propagation
has always been difficult, slow and rare. You have always needed to
check primary sources, and AI is just the latest in a long line of
reminders of that fact.
esailija wrote 11 hours 2 min ago:
Yes, the first 80% of a subject is repeated everywhere (including
all the misconceptions) and you cannot go deeper except if you
got very lucky like found a 5 year old youtube video with 130
views or an old blog post or a downvoted reddit comment. This is
what makes internet so addicting to me, the small chance of
finding these hidden gems inside mountains of garbage.
Having 80% in a broad amount of subjects is basically worthless,
it is the 90% and further that have value because it took luck
and actual personal experience and effort to take it that far.
aphroz wrote 19 hours 26 min ago:
Except that it is also quite difficult to assess the quality of a
doctor or a software developer if you don't work in the field.
I've heard numerous cases where AI solved medical issues that doctor
couldn't.
ozgung wrote 20 hours 14 min ago:
I feel like I am the only one thinking AI is actually much better
than me in the things I'm supposed to do well. I feel like that for
years now, so it's not about the latest generation of models. I can't
imagine a single thing I can really compete with an AI at this stage.
I am not sure if I am under-skilled or others are overconfident.
Maybe people who feel like me don't say this out laud.
dfee wrote 19 hours 45 min ago:
agree. it's strange reading the loud voices that are counter to my
lived experience. llms just have seemingly infinite depth - or can
at least debug and execute without fatigue.
ben_w wrote 20 hours 47 min ago:
> 2. AI is a terrible replacement for me - my skills are at such a
high level that itâs almost theoretical that itâll ever be good
enough to replace me for 90% of what I get paid to do. Itâs a tool
at best.
Most? Perhaps it's depression, but I look back at my career and
wonder if any code I've ever been paid to write is beyond what
current AI can do.
Sure, this leaves me with the non-coding tasks of UX taste, and code
review + a few other forms of QA (and, when self-employed, project
management, game design, etc.), but man, I'm someone who actually
learned to read in part on the Commodore 64 user manual (as in,
trying to understand what PEAK and POKE meant concurrent with having
"Jack and Jill go up the hill" picture books).
(And no, I'm not claiming LLMs make bug-free code, I see the bugs
LLMs make during my code review of their output and some of them are
awful, hence "this leaves me with â¦").
borzi wrote 20 hours 40 min ago:
And? How valuable are individual lines of code? To the author's
point, I'm sure AI can translate individual sentences perfectly,
but miss the nuance of communication in a bigger project or body of
text. In the same vein, when was the last time someone put an AI on
a ralph loop, posted the result on r/vibecoding and ended up with
actual users.
ben_w wrote 20 hours 30 min ago:
> How valuable are individual lines of code?
Don't care, only time I've measured them was personal curiosity
about hand-written projects, and one time I was trying to work
out how many blank comments a co-worker had put into their
codebase*.
How valuable are features? Management kept giving me them, and I
always just assumed they'd decided which ones were important. But
I've seen git histories of apps where the same feature was added
twice, 5 years apart, by the same developer.
> In the same vein, when was the last time someone put an AI on a
ralph loop, posted the result on r/vibecoding and ended up with
actual users.
How often do the megacorps currently boasting that 80% of their
code is now vibed, post anything (other than adverts) to reddit?
* 20% of the whole project, or 24 thousand blank comments.
chrsw wrote 20 hours 57 min ago:
My fear is in the future it won't matter. People will accept slop
because while they can be convinced it's not as good as it could be,
it's good enough. To them it's good enough because it's fast and
cheap not because it's actually good. There won't be any room in the
economy for the value human output brings because the economy will
rearrange itself around AI and become completely dependent on cheap
output, good enough or not.
madrox wrote 21 hours 18 min ago:
This is a new form of Gell-Mann Amnesia:
HTML [1]: https://en.wiktionary.org/wiki/Gell-Mann_Amnesia_effect
Aurornis wrote 21 hours 54 min ago:
> This is why I use AI for all my medical questions and doctors use
AI to write software, and we both smirk at the quality the other
person is getting from it.
There is an interesting third group emerging: People who acknowledge
the quality problem, but think they can deal with it by applying more
AI to the output.
This takes the form of people who spin up a lot of "agents" and give
them personalities like security director or quality director (which
are unnecessarily complex and maddeningly unpredictable ways to
trigger an LLM session for doing a security review or a quality check
pass).
It also includes the person who knows that their app is full of bugs,
but thinks it's not a problem because they can have the AI fix the
bugs as they show up. People in this class haven't encountered
security breaches or data loss bugs yet. They think it's all about
having Claude fix that div that isn't centered or handle that error
code that shows up some times.
AussieWog93 wrote 9 hours 2 min ago:
I'm in a similar-ish boat here. I acknowledge that what I paid an
LLM $100 to develop isn't as good as what if pay a human $100,000
to do, but it's "good enough" to solve the problem.
petre wrote 9 hours 52 min ago:
> People who acknowledge the quality problem, but think they can
deal with it by applying more AI to the output.
This is just like throwing more money at a problem, hoping that it
might solve it, but instead one throws tokens.
ReptileMan wrote 9 hours 54 min ago:
3 out of 5 voting works quite well for hardware sensors and for
computing in space.
No reason why it won't improve the quality of the agents output
too, eventually. Spin 5 from different providers, take the vote.
wseqyrku wrote 13 hours 13 min ago:
> There is an interesting third group emerging: People who
acknowledge the quality problem, but think they can deal with it by
applying more AI to the output.
That's the entire big tech's business strategy right now.
greazy wrote 17 hours 19 min ago:
> There is an interesting third group emerging: People who
acknowledge the quality problem, but think they can deal with it by
applying more AI to the output.
Ah yes, the known unknowns.
The discussion reminds me of a talk Zizek gave in which he
discusses the speech Rumsfeld gave regarding the evidence Iraq
supplying weapons to terrorist[0].
Zezik argues the unknown knowns are far more interesting (and the
reason why USA was losing in Iraq). While Rumsfeld focused on the
unknown unknowns.
I've noticed that domain experts who implicitly know the the known
unknowns of their field distrust LLMs because they can identify
their shortcomings. Those subtle mistakes LLMs make. I argue this
is why domain experts using LLMs get such a boost. They can
identify and avoid pitfalls sometimes before they happen. But in
other fields the same people are in awe of LLM capabilities
precisely because the known unknowns are a mystery.
The Unknown Unknowns of LLMs are the IMO the most interesting. The
so called emergent capabilities of the technology. The use of LLMs
in others fields such as biology, eg in protein language models, is
really cool.
Everyone focuses on replacement of people workers when I think
opening new fields of work for humans should be the goal of LLMs by
leveraging the tech to discover.
The other interesting caregory is unknown knows. But that's another
topic for another time.
[0]
HTML [1]: https://en.wikipedia.org/wiki/There_are_unknown_unknowns
tetromino_ wrote 15 hours 44 min ago:
Link for the curious:
HTML [1]: https://www.lacan.com/zizekrumsfeld.htm
bandrami wrote 15 hours 47 min ago:
As an aside, the mass mockery in response to Rumsfeld's statement
always bothered me because it's the single most intelligent
statement he ever made about the Iraq war, and if he had started
out with that mindset things probably would not have gone nearly
as pear-shaped as they did.
thisoneisreal wrote 15 hours 14 min ago:
This is one of those classic "sounds dumb / doesn't play well
on TV but is actually smarter than most of the other people
babbling about it" things. Nassim Taleb has written for example
about how maddening it is to watch world-class economists who
are also just sort of awkward and a little nerdy go on TV and
"lose" to blowhards who don't actually know what the hell
they're talking about but appear confident and look good on
camera. Thankfully in Rumsfeld's case I think as time has gone
on it's become a pretty respected statement about risk even if
people still occasionally find the phrasing a bit amusing.
throw-the-towel wrote 19 hours 57 min ago:
> People who acknowledge the quality problem, but think they can
deal with it by applying more AI to the output.
Brute Force: if it doesn't work, you're just not using enough.
What if they're right though?
goatlover wrote 17 hours 33 min ago:
They're right until they're not.
eqmvii wrote 17 hours 37 min ago:
I've seen it turn right in business contexts. Sometimes you can
even lower your standard of "good enough" and find quantity has a
quality all its own.
But it requires taste and engineering to do it right, and on the
right things. It'll be an interesting few years.
cwnyth wrote 14 hours 36 min ago:
I think it also requires someone who knows just enough to be
able to navigate between those ideas that will set you back and
those which will propel you forward. At the end of the day, you
still need some human filter.
tgma wrote 18 hours 5 min ago:
It does not have to be brushed away as "brute force" necessarily.
We can, and do, build more reliable systems out of less reliable
components. In fact, most industrial engineering accepts some
defect rate and builds margins around it.
Software is no different. Even without AI, you already have buggy
compilers and buggy OSes and buggy libraries. You just tend to
accept the risk because you have some idea of what the failure
modes are and can work around it or manage the risk in some other
way (buy literal insurance.)
Joker_vD wrote 14 hours 0 min ago:
> you already have buggy compilers and buggy OSes and buggy
libraries.
Which run, I must add, on effectively infallible hardware. Most
of the software straight up assumes that the CPUs and the RAM
will function perfectly and don't bother even trying to detect
such failures (unless those failures manifest themselves in a
catastrophic manner, the show will simply go on).
So in effect, we also can, and do, build less reliable systems
out of more reliable components, and that's how software is
different.
adastra22 wrote 8 hours 9 min ago:
You should talk to an electrical engineer or materials
scientist about how reliable transistors emerge from noisy
voltages in wires.
tgma wrote 11 hours 48 min ago:
I am not sure if I correctly understood your point. On one
dimension, you are basically hinting at another anecdote that
proves my point: hardware failure (specifically bit flip in
non-ECC memory) is pretty much guaranteed to happen at scale,
but people are mostly okay with absorbing that risk. I feel
you are overselling the hardware reliability story. For sure,
we can build less reliable systems out of reliable
components. That goes without saying, and no, that's
definitely not software specific. Almost by default most
composite systems are less reliable than their primitives
(simple example would be nailing two pieces of wood) unless
specific care is taken to build in those guardrails or
redundancies. The point, however, is it is possible, and
there is a vast precedent for it.
pianopatrick wrote 18 hours 20 min ago:
There are other places where some process has an error rate and
you make up for that error rate by doing the work more than once
and then comparing results. For example, I've heard in a video
that satellites and other space craft often have 3 or 4
processors and compare the results to make sure there were no
errors due to radiation. Similarly, we have RAID arrays that
store data multiple times because disks can fail. So, even if AI
has a failure rate of like 20%, maybe you can make up for that by
running the same prompt multiple times with slight variations or
with different models, comparing the results and choosing the
best.
keeganpoppen wrote 19 hours 13 min ago:
they are right. bad output is user error. there, am i suiting the
role appropriately? i do like 65% believe that, fwiw.
MichaelZuo wrote 21 hours 11 min ago:
How did you get over 52,000 karma in under 3 years with no
submissions at all?
Are you averaging like 2000+ comments a month?
soperj wrote 19 hours 43 min ago:
They spin up agents, and then give them roles like commenter, and
director of quality for the commenter. Although I'm unsure how
the director helps since I've never seen one do actual work.
Aurornis wrote 20 hours 32 min ago:
Commenting more than I should, to be honest.
I have a few periods during my daily routine where Iâm waiting
somewhere away from the computer and need a break from email.
A lot of my comments have double digit upvotes and some get into
the mid hundreds. I try to actually read articles and provide
thoughtful comments, which gets upvoted a lot more than the
throwaway.
> Are you averaging like 2000+ comments a month?
52000 / 3 years would be under 1500 points per month or 48 points
per day. That could be done with 1-2 helpful comments per day on
popular threads.
aquariusDue wrote 17 hours 10 min ago:
I browse HN a bit more than I should and I see you and simonw
around a lot, like you said always providing thoughtful
commentary.
When I write comments on here I tend to spend upwards of 15
minutes to draft and reformulate my comments. Sometimes
double-checking what I'm about to say (sometimes not thoroughly
enough as some of my recent comments show) and I was wondering
if you have a similar experience in that regard or do you just
manage to fire off a comment in a stream of thought fashion
from start to end?
dotancohen wrote 18 hours 52 min ago:
Serious, non-acusatory question. Your writing looks human. Do
you use any writing assistants?
Where else, other than HN, do you post?
mschild wrote 21 hours 4 min ago:
3 pages deep into their comment history only brings me to 5 days
ago so probably yes.
toddmorey wrote 21 hours 13 min ago:
I always imagine the model rolling its silicon eyes when itâs
assigned a personality (âyou are an expert growth hackerâ) at
the start of the prompt. Was that ever actually shown to be
effective? Is it still?
overgard wrote 12 hours 31 min ago:
From what I've heard, personas give a greater chance that the LLM
will answer confidently.. and also a greater chance it'll
hallucinate something when the data is sparse. Supposedly
"grounding" the personas on real documents/web searches is the
best approach. Anecdotal though.
not_a_bot_4sho wrote 16 hours 21 min ago:
Back with some papers. (Apologies in advance; I typically don't
edit/format comments much here, please bear with me.)
Notable papers describing performance improvements with
prescribed roles and personas:
- ExpertPrompting: Instructing Large Language Models to be
Distinguished Experts (2023) [1] (if you're going to only read
one paper here, maybe read this one but know there has been a lot
of follow up with more modern models.)
- Expert Personas Improve LLM Alignment but Damage Accuracy
(2026) [2] - When Does Persona Prompting Actually Help? (2026)
[3] - Unveiling Power on Combining Prompt Engineering Techniques:
An Experimental Evaluation on Code Generation (2025) [4] - A
Pattern Language for Persona-based Interactions with LLMs (2025)
[5] A TLDR of my *admittedly heavily biased* mental model (so
take it with a grain of salt): personas do improve task
alignment and precision to measurable effect but with observed
negative impact to accuracy and knowledge grounding. Overall,
this makes it quite suitable and preferred for code generation
scenarios. (Don't over-index on 'accuracy' here as meaning "bad
code", it's more about verbosity/jargon reducing clarity of
higher order goals like business objectives and system
architecture.)
Outside of code generation, personas have the interesting effect
of increasing implicit biases and stereotypes. It's not hard to
imagine something like "you are a left|right wing politician ..."
or "you are a senior-citizen|teenager ..." influencing token
space construction considerably.
HTML [1]: https://arxiv.org/abs/2305.14688
HTML [2]: https://arxiv.org/abs/2603.18507
HTML [3]: https://arxiv.org/abs/2605.29420
HTML [4]: https://doi.org/10.5753/sbbd.2025.247251
HTML [5]: https://www.dre.vanderbilt.edu/~schmidt/PDF/Persona-Patt...
antonvs wrote 18 hours 8 min ago:
The reason it seems suspicious is that it's phrased in a way
that's oriented towards humans. I haven't tested this, but I
suspect you'd get similar results if you said something like
"orient your response to that of a growth hacker." Either one is
likely to have the desired effect on the stochastic result.
Sharlin wrote 19 hours 46 min ago:
There was a time when stuff like "Unreal Engine, trending on
ArtStation, 8K resolution" actually worked when prompting image
gen models because such labels actually correlated with
higher-quality images in the web-crawled training datasets
available back then.
Blackthorn wrote 19 hours 58 min ago:
At least in the beginning of spicy autocomplete, this sort of
role-play did work pretty dramatically at aligning a conversation
to a task, though I don't think anyone ever tested it versus
somewhat less cringe priming.
After that, cargo cults do what they do best.
customguy wrote 19 hours 31 min ago:
> though I don't think anyone ever tested it versus somewhat
less cringe priming.
I really wonder if phrasing it differently would make a
difference. In good faith conversations, it just doesn't happen
that someone tells someone else who that person is.
not_a_bot_4sho wrote 20 hours 3 min ago:
> Was that ever actually shown to be effective? Is it still?
Yes! Personas demonstrated measurable improvement in a few
different ways, with caveats of course. The common intuition is
that personas influence token space in beneficial ways.
I'll come back here later on desktop and link a few (still)
relevant papers on this topic.
shnock wrote 16 hours 35 min ago:
Please do, thank you! I have been similarly skeptical as your
comment's parent
not_a_bot_4sho wrote 15 hours 17 min ago:
I added some brief commentary here: [1] (or just refresh
parent comment replies to see it)
It scratches the surface really but hopefully provides a
helpful starting point.
HTML [1]: https://news.ycombinator.com/item?id=48507278#485115...
bryanrasmussen wrote 20 hours 37 min ago:
I remember there were some studies that this kind of thing was
effective a year or so ago, so essentially a lifetime in Model
years.
However to me it seems completely reasonable that it would work,
because my understanding of what happens is the model interprets
what you said as:
Look for a group of people who are considered to be expert
growth hackers by the world at large and answer my questions as
though they were answering them.
So assuming that there are a set of questions that can best be
answered by people that most other people identify as expert
growth hackers then yes, I believe assigning a personality in
this way should obviously work.
code_biologist wrote 20 hours 17 min ago:
It's been interesting to see how aggressively some reasoning
models like to "reason" by analogy. They love to say things
like "it's like a CPU" or "it's like a highway", and then they
start to make logical leaps based off that rather than just
using it for user explanation. Gemini 2.5 and 3.1 Pro have been
particularly bad for this type of behavior. Telling models to
"speak as though you are a physiologist considering the case
with an expert colleague" gets them to "reason" using a more
correct linguistic substrate.
The Opus models over the last year doesn't seem as vulnerable
to this type of behavior and I've noticed the "identify as
expert" prompt tricks aren't as meaningful there.
FeteCommuniste wrote 20 hours 29 min ago:
I imagined it as kind of a shorthand for "you should be
spending my tokens on looking for / addressing issues like X,
Y, and Z," where X, Y, and Z are the sorts of things that an
expert in [insert domain here] would be likely to care most
about.
bandrami wrote 15 hours 46 min ago:
At some point we have to just admit we're mass cargo-culting
here and that these secret invocations people swear by have
the same epistemic value as medieval superstitions.
FeteCommuniste wrote 5 hours 38 min ago:
I don't know, I was never one to "assign roles" to AI
myself, but if it ends up working for some people in
practice, then I guess it might be worth examining why.
bryanrasmussen wrote 20 hours 19 min ago:
right, but the thing is how do they know what an expect in
[insert domain here] would care about? Obviously by finding
content created by
people who claim to be experts in [domain]
people who others claim to be experts in [domain]
hopefully valuing membership in group two over membership in
group 1.
xpct wrote 20 hours 30 min ago:
I propose we move away from the framing of "Model years" -
they're standard human research years. Yes, likely more people
are working on it, and also working harder, but ever since we
acquired a certain amount of compute in the world, many people
were able to independently find the same patterns and train
models.
spudlyo wrote 20 hours 42 min ago:
It reminds me when people would stuff their image prompts with
things like NO DEFORMED FINGERS.
Npovview wrote 13 hours 4 min ago:
I did something different. Instead of describing the image, I
described the artist. Made that artist in Ubermensch. Then
asked AI to draw the image from his point of view. It worked
fabulously.
hexasquid wrote 17 hours 31 min ago:
"Don't think of an elephant"
cwillu wrote 19 hours 44 min ago:
Instructions unclear, digitized subject into a mass of fingers.
205guy wrote 17 hours 46 min ago:
I hope that pun was intendedâ½
cwillu wrote 16 hours 47 min ago:
SCP-48510055
badc0ffee wrote 18 hours 2 min ago:
Perfectly formed fingers.
sebastiennight wrote 18 hours 44 min ago:
Thanks for reigniting the PTSD of reading about SCP-4051.
throw-the-towel wrote 18 hours 40 min ago:
You mean the 4051 from There's No Antimemetics Division and
not the mainline 4051, right?
sebastiennight wrote 17 hours 31 min ago:
Yes. I'll confess that I started with the novel :)
techpression wrote 20 hours 54 min ago:
I feel it helps for the personality aspect, how it handles
answers and general vocabulary, but it doesnât in any way
improve skill level, at least thatâs my take from building an
assistant.
gs17 wrote 21 hours 3 min ago:
I've always wondered if the go-to should have been prefilling its
response with "I am an expert growth leader, and here are my
thoughts:".
s_tec wrote 22 hours 36 min ago:
It seems to be a general principle: If AI is better than you at
something, you use it. If AI is worse than you, you don't.
Each time the frontier models get better, I see another wave of AI
doubters suddenly become believers. People say things like, "AI
couldn't code last year, but now I use it for everything!"
Interesting. Now we know how that the person who said this has the
coding skills of a Claude Opus 4.5 or whenever the frontier was when
they flipped.
Meanwhile, the rest of us keep using AI as simple tools, like the
person in the article. I wonder how long it will take before
computers can program better than me, and I flip too.
Al-Khwarizmi wrote 11 hours 31 min ago:
If AI is not better than you at a task, but it's good enough and
saves you time, it also makes sense to use it. Many of my uses of
AI fall in this category.
jasonfarnon wrote 17 hours 55 min ago:
"Now we know how that the person who said this has the coding
skills of a Claude Opus 4.5 or whenever the frontier was when they
flipped."
Well, once folks like Linus Torvalds concede, this doesn't carry
much sting.
black3r wrote 19 hours 59 min ago:
the sentiment "AI couldn't code last year, but now I use it for
everything!" rings true for me... but I didn't flip cause AI is now
better than me... I flipped cause now I am faster with AI than
without it...
A year ago the AI output was so bad that getting it up to my
standards took more than writing it myself from scratch. And
nowadays it is faster for me to start with AI output and iterate
from there to reach quality submission.
The ninety-ninety[0] rule was a thing talked about 40 years ago,
long before anyone thought of AI coding. AI can nowadays make the
first 90% of the task very fast and good enough. The last 10% is
still the hardest part of coding by far.
[0]:
HTML [1]: https://en.wikipedia.org/wiki/Ninety%E2%80%93ninety_rule
greiskul wrote 20 hours 35 min ago:
> the person who said this has the coding skills of a Claude Opus
4.5 or whenever the frontier was when they flipped
It's not about just skill. It's a matter of skill, time, and how
critical the software you are writing is.
There is a lot of software that is not critical. That is not close
to security mechanisms. And that even if the code quality is not
the highest, it does not matter.
Even if you are the best coder in the world, you would already
become more productive by using ai. Things that in the past you
might have not coded yourself but delegated to an intern, or things
that you wouldn't even delegate to an intern because they are just
too boring to do like some refactorings.
Like I had this project at work that was written without typescript
strict mode turned on. When I turned it on, it had over 700 errors.
I might be better than AI to fix every single of one these errors.
But my time is worth more than that in doing other things. But I
can, and did, ask AI to fix every single one. And then I reviewed
it batches, and something that my team wanted to do for multiple
years and nobody had the time for, finally got done.
r3trohack3r wrote 20 hours 36 min ago:
Iâm not sure I agree with this but maybe I just lack self
awareness?
There are large portions of my codebases that are essentially
extremely verbose grunt work. My UI stack, IaC YAML, thin CRUD
routes, etc.
I know what the code is supposed to look like when itâs done
being written, but itâs going to take me for freaking ever to
type it all out.
I can just few shot it now in an hour. Plan -> feedback loop ->
build -> review loop.
Does it try to do weird stuff? Yeah. And then Iâm just like
âthatâs weird, no, the components should be broken up like
XYZâ and then itâs not weird anymore. Occasionally (1% of the
time) I just do a quick refactor myself instead of trying to tell
the agent harness what to do.
I can get something fairly close to the ballpark of what I would
have done but in like single digit percentage of the time.
And the result is that I can spit out a bunch of purpose built
tools (personal tools, internal tools for teams, etc.) that I
never would have been able to justify building otherwise.
PaulRobinson wrote 22 hours 37 min ago:
I was saying something like this a few years ago when people were
getting first excited about ChatGPT. The gap has narrowed, but not by
as much as people think.
AI produces output that is very convincing to a non-expert, and
(dangerously), it's so good at looking like an expert, they might
believe that it is an expert. But the moment you ask someone to use
it for something they're an expert in themselves, the holes appear
wide, consistent & obvious.
My favourite moment of seeing this in action was watching AI-worrier
TV host/comedian Bill Maher. He has spent years talking about the
dangers of AI taking everyone's jobs, destroying civilisation,
ruining the economy, starting wars, "it's just getting better and
better all the time", and so on. But one night he let slip a tell.
"It's no good at writing jokes. Not yet, anyway". There you go,
Bill... connect those dots...
There is real utility in it being a tool to help experts apply their
expertise, as in this story where it speeds up some tasks to help the
translator do part of the work, enhance their expertise, allow them
to be more productive.
It's a better screwdriver, a better hammer, in the hands of somebody
who knows what needs a screwdriver or a hammer. It doesn't replace
them. It can't replace them. It's a tool that enhances the human, not
an alternative.
I don't understand why this is not widely understood yet, but I'm
sure it will in due course.
And I don't expect this to change. Even if the latest model scores
100% on every benchmark, all that really tells us is that it's now
more productive/efficient than it was before at helping experts do
that work, not that it can replace everyone in that category of work.
CGMthrowaway wrote 23 hours 8 min ago:
Well said. Everyone agrees AI can't do their job, so it ends up doing
everyone else's.
I'm not sure how to formulate it yet but it seems there is some Peter
Principle/Gell-Mann Effect corollary that is AI-related we can say
here.
Perhaps: "AI rises to the level of its users' incompetence."
Or: "Confidence in AI output is inversely proportional to one's
ability to verify it"
Kiro wrote 19 hours 14 min ago:
> Everyone agrees AI can't do their job, so it ends up doing
everyone else's.
In real life I haven't met a single programmer who doesn't think AI
can do their job.
If someone would actually say that I would immediately think they
have hubris and overestimate their skills.
SCdF wrote 11 hours 29 min ago:
We must live in different realities, because I have the direct
opposite experience.
Perhaps we are defining "job" differently? AI can, with much
coaching, _perhaps_[1], do some _aspects_ of a programmer's job.
But not all of it, or even the most important parts of it.
[1] given that we have spent the past many decades pointing out
that developer productivity is possibly impossible to measure, or
at least very hard; given "done" vs "done done"; given the
history of "rock star" developers creating messes behind them,
the difference between short and long term thinking and the
external imperceptability of that difference; given all of that,
we haven't really had enough time to form a valid opinion on what
AI can do, in the long run.
notsirius wrote 17 hours 45 min ago:
are you saying that all of the programmers youâve met in real
life have automated their work away and are coasting while
waiting for their bosses to fire them�
â¦if not, theyâve found developer work that ai canât do yet,
no?
Kiro wrote 3 hours 19 min ago:
That was not my point. Maybe we interpret "can't do their job"
differently. That said, outside of HN I don't know anyone
writing code by hand anymore except people that can't use it
due to compliance or work on PLC stuff.
jenniferhooley wrote 17 hours 52 min ago:
You mean theoretically in the future? Or right now?
whazor wrote 21 hours 2 min ago:
But using AI itself is a job too. It takes effort to correctly
prompt, to steer it, to verify it, and to improve the harness.
kingkongjaffa wrote 20 hours 43 min ago:
show me a prompt that is meaningfully expertly crafted beyond
just providing Do's, Do not's, task context, and a goal.
> Correctly prompt, to steer it, to verify it, and to improve the
harness.
I doubt this a lot. The average AI user is running claude code as
the harness, or Codex etc. prompting has no secret
incantations, and steer and verify is just knowing what the
answer should roughly look like, which is a domain skill, not an
AI skill.
jenniferhooley wrote 17 hours 48 min ago:
I feel like you don't have any friends who make software but
don't know how to code.
Yes, they do make software now - whereas it was impossible
before. You may be absolutely shocked at how bad LLM code can
be when prompted from a noncoder. How buggy, and how absolutely
rife with security problems it can have. I honestly don't know
how they can get LLMs to write such bad software - but somehow
they can. This is from people who have been vibe coding for 3
years straight btw (huge amount of time p/day).
dools wrote 20 hours 11 min ago:
> show me a prompt that is meaningfully expertly crafted beyond
just providing Do's, Do not's, task context, and a goal.
The way that information is organised and formatted matters for
compliance. Itâs pretty similar to writing good procedural
documentation for humans.
theendisney wrote 22 hours 2 min ago:
>Well said. Everyone agrees AI can't do their job, so it ends up
doing everyone else's.
Its like basic income, everyone will stop working except from you.
cwmoore wrote 20 hours 39 min ago:
It is not at all like universal basic income, except that both of
those are misleadingly simple quips.
baby_souffle wrote 22 hours 37 min ago:
> Confidence in AI output is inversely proportional to one's
ability to verify it
I like this / generally agree. The only wrinkle is that - for some
tasks - the verification _is_ "run the script, see if it worked,
don't care how... just that it did" which is distinctly different
from "not only did it do it correctly, it did so in the most direct
and performant way possible".
For a _lot_ of what I use LLMs to build, the former is all I need.
OptionOfT wrote 22 hours 12 min ago:
And for as long that that runs on your computer, I don't care.
But the problem is that for many people they now believe it's ok
to present a 10k line vibe-coded PR that only has been verified
against external behavior, and some Senior Engineer needs to
review it, in time, under pressure, without too much push-back,
and lastly, it's the Senior Engineer that gets paged at 2am
because something has fallen over.
Also, those scripts tend to start a life of their own, and
because it looks good enough, people don't look at them again.
I recall a bug of someone vibe-coding a cleanup script for
folders older than $x (on Windows).
Get the CreationDate, and sort. Delete older than $x. Except
CreationDate can be null and null is always smaller than $x.
Oops.
holmesworcester wrote 23 hours 11 min ago:
Reminded me of this post by EY. (You're making a different point
about existing expertise, not LLM expertise, but I think it holds in
general.)
Every month a new guy discovers LLMs; discovers a skill the current
LLMs require to get good results; and writes about the future jobs
that will always be available for smart people like HIM, that are
SKILLED in using LLMs.
The next generation of AIs doesn't need his fancy prompt. The image
model goes from needing to type in just the right set of weird words
and cryptic sorcerous invocations, to most people being able to type
in English what they want and get a pretty good result.
There are still tasks that require careful invocation. But they are
a much smaller fraction of all the tasks people are trying to do, or
you can get a bleh result without the elaborate invocation to get it
really good. And to improve on the bleh result you need to be
substantially more of an expert than back when the Guy was memorizing
a rule about adding "trending on Artstation" to the image prompts, as
would always require a human paid to do that.
Another generation of AIs comes out. The next generation of Clever
Skills is obsolete. Image models just obey the instructions for
compositing panels without mixing them up, and you don't need to be
an expert to get them to do it right. Another human value-add is
gone. A wider set of tasks require no human expert.
Now a new Guy notices LLMs have become useful in his field for the
first time. He discovers they require SKILL to use CORRECTLY. He
posts about how there will always be jobs for humans who are SKILLED
in using LLMs like HIM.
But it is not an infinite cycle. It is not the same each time it
repeats. Now the Guy is a highly paid programmer or a career
mathematician in 2026, instead of a graphic artist in 2023.
In six months the models will no longer require his vaunted Skills.
And by then there will be another Guy.
But the process doesn't continue forever. The Guys are coming from
fields that were harder and harder for AIs. The brief centaur eras
are shorter and shorter.
Today it is writers who are laughing at how bad the LLMs are at their
job, and who will perhaps soon be posting about how it takes Skill to
get an LLM to do their job Correctly. But the models are coming
faster, and the eras of kinds of human value-add in each field are
shortening.
There is a point when you run out of Guys, either because the centaur
eras are too short for people to develop SKILLs and post to Twitter
about them; or because there are not lands left for AIs to conquer;
or because ordinary people are not reassured by some Nobel laureate
proclaiming there will always be jobs for Nobel laureates with the
SKILLS to prompt robotized biology labs Correctly.
But we'll never run out of amateur economists who assert entirely
without a brief contemporary example that there will always be jobs
for humans skilled at operating AIs!
We'll run out of professional economists saying it when nobody is
paid for that work anymore.
I guess we'll also run out of amateur economists when they're dead.
Source:
HTML [1]: https://x.com/allTheYud/status/2057136382817231151
carlosjobim wrote 23 hours 24 min ago:
Translating is one thing that artificial intelligence undeniably excels
at, and the value of this alone is enough to underpin the trillion
dollar valuations of the gigantic AI companies.
Translation is a gigantic boon for business, but just as important for
human connection, for culture, science, art, and entertainment. The
value of automatic and cheap translation between all languages, this
tower of Babylon, is immeasurable.
Human translators will always be better than any AI at their job. But
they don't have unlimited time and energy, and they aren't cheap. AI
makes good to great translations available to everybody.
aaroninsf wrote 23 hours 25 min ago:
True, and relevant (I live with a professional editor)... yet I
immediately think of Ximm's Law:
Every critique of AI assumes to some degree that contemporary
implementations will not, or cannot, be improved upon.
Lemma: any statement about AI which uses the word "never" to preclude
some feature from future realization is false.
Lemma: contemporary implementations have already improved; they're just
unevenly distributed.
edude03 wrote 21 hours 8 min ago:
I think it can't be improved because it's measuring the wrong thing.
A junior engineer becomes a senior when they stop being told what
code to write and start solving business needs. Therefore often the
highest paid engineers aren't the ones who would do the best on
leetcode - or SWE bench pro verified.
Maybe AGI is possible and we'll have software defined human
intelligence that's completely autonomous but that's not coming in
the next slightly better RL trained LLM and if existed likely
wouldn't be under our control anyway
Planktonne wrote 22 hours 14 min ago:
No one assumes that AI systems won't be improved upon. What people
don't assume is that progress will be infinite in every domain
cheaply forever.
JackFr wrote 23 hours 26 min ago:
I worked at large Japanese bank in New York and happened to sit near
Chief US Economist next to his Japanese translator. She would
occasionally ask about certain idioms. I remember explaining what a
wildcat strike was for instance. But it must have been pretty tough
because the guy was prolific in his commentary.
analogpixel wrote 23 hours 31 min ago:
All I got out of this article is that he should have went home and
dumped it into chatgpt just to see what happened; then if it did as
good a job as him, he should start looking for other places he can add
value that AI can't.
analogpixel wrote 22 hours 1 min ago:
The point of the comment was that models are improving a lot every
release, so if your livelihood depends on something, you might want
to check to see what the latest models are capable of before someone
else (like your employer ) tells you.
The other person in the gym was right, did you you just dump it in
the latest model?
byronic wrote 23 hours 27 min ago:
she did. Did you remember to read the article?
int3trap wrote 23 hours 20 min ago:
The article does not say that. The author doesn't take the text the
other person dumped into ChatGPT and evaluate its quality. That is
what OP is referring to.
xboxnolifes wrote 22 hours 16 min ago:
The article clearly implies she has tried so previously.
analogpixel wrote 21 hours 59 min ago:
when someone says they have tried previously that makes me
think once long ago when they first came out. If your
employment could be replaced by this, I'd be testing all new
models to see where they stand.
Just because you don't want to use AI/LLM to translate, that
won't stop someone else who will, and they will end up doing it
cheaper and faster (maybe not better, but most people don't
really care about quality too much anymore.)
bachmeier wrote 23 hours 21 min ago:
From the phrasing of the sentence, with the incorrect gender and
the generic nature of the comment, obviously not.
vulcan01 wrote 23 hours 31 min ago:
wrt. the end of the story, it will be interesting to see if people
start noticing their Dunning-Kruger bias as a result of LLMs.
Specifically: LLMs make it really easy to misunderestimate the
complexity of fields other than your own. (You can see this with a lot
of vibecoded projects, for example â once they hit the wall of
complexity, they stall out or start finding ugly patches for
fundamental design issues, etc.)
I don't think this sort of cultural change will happen short-term,
though.
nzach wrote 22 hours 59 min ago:
> LLMs make it really easy to misunderestimate the complexity
In my experience this is a real problem. Just yesterday I asked my
LLM to create a piece of software that could help me build an
'ambilight-like experience' through my home assistant. It did
something that seems to work as I expected, but there is a lot of
theory that I just brushed past. It would be pretty easy for me to
assume that I would be able to replicate this feature from scratch
'now that I understand the problem'.
rootusrootus wrote 23 hours 20 min ago:
Agreed. LLMs are really terrific at sounding like they know exactly
what they are talking about. Fable is the best yet. Beautiful,
thorough explanations with absolute certainty, which under even light
scrutiny turn out to be mostly bullshit.
I still love the tool, but remain as convinced as ever that AGI does
not lie at the end of this particular path.
liquidise wrote 23 hours 32 min ago:
> âGreat. So, do you use AI a lot at work?â
> âOh, I canât! Itâs really not reliable enough.â
Gell-Mann Amnesia strikes again.
Seattle3503 wrote 23 hours 32 min ago:
Presumably the people paying the author for translation services are
aware of AI, but for whatever reason are choosing a humans services
instead. IMO it would be a form fraud to heavily rely on AI and not
disclose that to the customer.
Drupon wrote 23 hours 33 min ago:
An honest to god article full of em dashes that's not because it was AI
but because it was a human using them as a crutch to get around
crafting sentences that flow naturally. Almost brings a tear to my eye.
zhuli wrote 12 hours 21 min ago:
English isn't my native language.
Also, I like em dashes.
And if this is my worst sin, so be it.
TZubiri wrote 18 hours 20 min ago:
Either it's LLM generated, or it's written by someone who wants to be
ambiguous about using LLMs.
Either way, I'm not reading it, it's a clanker or a clanker
collaborationist.
I mean, how would you even write an em dash? There's no button in the
keyboard for em dashes, it's not in ascii, it's just not something we
write in internet text with, it's a safety watermark put into LLMs by
OpenAI to help making LLM generated content identifiable as such.
If for some reason you are an em dash lover that was hurt by the LLM
debacle, I'm so sorry for your loss, but look who's on your side,
give the em dash a funeral and let it go.
Hendrikto wrote 10 hours 58 min ago:
> I mean, how would you even write an em dash?
With a keyboard shortcut. Just because you are incompetent, that
does not mean everybody is.
zhuli wrote 12 hours 20 min ago:
I wrote the article.
Sorry if I like em dashes.
It's alt + 151 BTW.
Lalabadie wrote 16 hours 58 min ago:
> I mean, how would you even write an em dash?
⥠⧠+
It's been seared into my muscle memory for more than a decade. I
keep using it, too. It's present in the popular training sets â
and then in LLM outputs â simply because it's proper punctuation.
hexasquid wrote 17 hours 17 min ago:
"clanker"
Slang for an AI, used by a Blade Runner
inopinatus wrote 18 hours 14 min ago:
Your argument goes as follows: âIâm incapable of it, therefore
no-one is capable of itâ.
Followed by, âYou should abandon your preferences because I
donât share themâ.
hyperpape wrote 19 hours 55 min ago:
First sentence:
> In my Ottawa life, every Tuesday evening, I take two gym classes
back to backâboxing and the pompously named âbody sculpt,â
which makes me discover muscles I didnât know I had.
The em-dash matches how you'd speak out loud.
You'd say "I take two classes every Tuesday back to back, boxing and
'body sculpt'. Weird name." (Parts of that sentence did flow oddly,
but not because of the em-dash).
Grammarians say you can't make those separate sentences without
adding some extra words, and because of blah-de-blah-blah-blah,
someone might say you can't join them with a comma. So we have an
em-dash.
Rewriting the sentence would make it flow less naturally, not more.
anotherevan wrote 10 hours 7 min ago:
This is why I find using speech-to-text tools quite difficult to
use: because the parts of my brain that I use for writing and the
parts of my brain I use for speaking are a little different â
although with significant overlap.
With writing I find I'm drafting the flow for readability and
clarity as I'm writing, so I go back and rework bits and pieces â
sometimes even while I'm in the middle to typing a sentence. Maybe
it's because I write code for a living.
Speech only moves forward and you have to state your retractions or
clarifications on the go. You can't go back and edit what you've
said.
I've been trying to use speech-to-text a bit to: a) give my hands a
bit of a break when I'm writing prose, and b) see if it's faster
than typing.
I find there are long pauses while I'm struggling to draft what I'm
going to say to what I want written, so I'm not sure if it is
faster (given that I'm a ten finger touch typist so can type pretty
fast is short bursts, and the time spent going back and tidying up
the output which is somewhat tedious). It might improve with more
practice.
â No tokens were harmed in the production of this comment. â
mcmcmc wrote 18 hours 26 min ago:
If I had a nickel for every em-dash I saw that couldâve been a
colonâ¦
anotherevan wrote 11 hours 1 min ago:
You'd be full of shit.
Oh, sorry, I thought you said colonâ¦
113 wrote 18 hours 41 min ago:
Good writing shouldn't just be how you talk out loud.
inopinatus wrote 18 hours 5 min ago:
Good writing doesnât exclude it.
pvillano wrote 19 hours 28 min ago:
When I write like I talk, I use a lot of commas. Replacing some of
my commas with em dashies, so long as it was done judiciously,
would probably make things easier to chunk.
stogot wrote 18 hours 38 min ago:
Iâve seen people use colons where em dashes are effective. I
use em dashes. AI leans heavily on them for same reason
mcmcmc wrote 18 hours 24 min ago:
Itâs become the exclamation mark of mid-sentence punctuation.
It connotes fragmented or interrupted speech in my opinion. The
problem is that writing is not speech, thatâs why it is more
often seen in written dialogue.
olivierestsage wrote 23 hours 8 min ago:
Em dashes are really good actually and a standard stylistic choice
for non-technical writing, particularly outside the US.
anigbrowl wrote 20 hours 49 min ago:
They certainly have their place, but are massively overused in
contemporary American prose. This might be slight more of an east
coast thing, but that's just a subjective impression that I'm not
willing to spend time measuring.
To me they come off as faddish, with many writers using them where
commas and semicolons would have done just as well. I think their
popularity stems from teh fact that provide the sense of a personal
aside from the writer, allowing them to be more expressive while
clearly delineating the personal or contextual remark from the main
flow of the prose. No doubt this works for a lot of readers, but I
find it tedious.
epihelix wrote 18 hours 57 min ago:
It's a fad that has been going strong for centuries in published
literature, so I'd guess an awful lot of authors world disagree
with you.
You can restructureany sentence to use fewer forms of punctuation
-- but if you do that, you'll lose nuance. And nuance, in
writing, is a very fine thing.
anigbrowl wrote 18 hours 10 min ago:
The em-dash has indeed been around for centuries, but the fad I
refer to is its overuse in contemporary American prose. IF you
look at Google Books n-gram viewer, you can see it went through
a surge of popularity over a few decades that then fell off
sharply. [1] It's also notable that the em-dash is approved in
American Manuals of Style, while discouraged in British ones. I
was unable to find longitudinal data for the em-dash's use in
magazines, blogs etc., but AI summaries suggest it's 3-4 times
more used in those contexts than in news reports.
Like strawberry ice cream or apple pie, nuance is certainly a
fine thing; but a surfeit of it becomes cloying, and the
antipathy toward the omnipresence of the em-dash in
LLM-generated prose, along with other kinds of literary
expression like contrast and comparison, suggests to me that
people have had more than enough of it.
HTML [1]: https://books.google.com/ngrams/graph?content=%E2%80%9...
kevinwang wrote 19 hours 4 min ago:
I use them because I know what I want to say out loud, but
transcribing the pause with commas is incorrect because it's a
comma splice, and I find that the semicolon often looks glaringly
overly formal. So I've settled on the em-dash.
madaxe_again wrote 23 hours 19 min ago:
My writing used to be littered with them, but I now eschew the em in
favour of en, as it has become too strong an anti-shibboleth.
I have also taken to being sloppier in my prose, as Iâve had
stories rejected for being âwritten by AIâ - when theyâre
shorts I wrote more than a decade ago. Reworked them to sound like a
moron, accepted. Sigh.
Hendrikto wrote 10 hours 57 min ago:
> I now eschew the em in favour of en
They have different meaning and are not interchangeable.
spider-mario wrote 9 hours 25 min ago:
For the use discussed here, they basically are.
HTML [1]: https://en.wikipedia.org/wiki/Dash#En_dash_versus_em_das...
madaxe_again wrote 9 hours 45 min ago:
Fully aware - although now the broader meaning of the em dash has
become âI am an LLMâ.
AStrangeMorrow wrote 22 hours 55 min ago:
I have a similar issue. I tend to have a very âstructuredâ type
of writing. Say on slack or Reddit for example. Using markdown
formatting. Lists with bulletpoints etc. And I tend to write long
detailed explanations, sometimes too long if I am being honest.
But now I find myself adding noise and imperfections to my writing
(not that it was perfect) to make it more human, which is kinda
silly.
jimbokun wrote 21 hours 2 min ago:
The LLMs decided to use you as the model for the pinnacle of
human communication style.
bluechair wrote 23 hours 20 min ago:
My first ruleâbefore doing anything elseâwhen writing a sentence,
is to check whether I could have removed the em dashes by re-ordering
the elements.
Update: in case itâs not obvious, I am sorry. I could not help it.
anotherevan wrote 10 hours 1 min ago:
Update: I am sorry. In case it's not obvious â I could not help
it.
FTFY
ixtli wrote 23 hours 23 min ago:
I wish more people had casual exposure to professional translators.
Its a deeply important, vanishingly small segment of the human
population and has been this way for at least many thousands of
years. Also, it will continue to be!
madaxe_again wrote 23 hours 16 min ago:
Iâve a friend who does simultaneous interpretation at the UN and
sheâs just⦠good god, how do you even do that. Oh, and she does
it in six languages.
And here I am, brain the size of a galaxy, and I fumble my way
through every language I speak other than English.
Serious respect for the linguists.
projektfu wrote 17 hours 54 min ago:
I guess I should have figured Marvin would be here on HN, feeling
sorry for himself.
tombert wrote 23 hours 35 min ago:
I have no doubt that the writer is better at translating than AI, but I
have to say that AI translation has gotten so good that I'm not sure
how much longer translation work will be there, or rather it might end
up being more about auditing.
For example, I just read the Lawrence Ellsworth translation of The
Three Musketeers, which I very thoroughly enjoyed. I don't speak or
read French, but from my understanding Ellsworth's translation is
considered one of the more accurate translations of the work.
Out of curiosity, I sic'd Claude Fable on the original French version
of The Three Musketeers and told it to translate accurately, but also
try and keep the same jovial tone as the original and do not censor
anything. After it was done, I didn't read the entire output, but I did
compare a few individual chapters between the Ellsworth translation and
the Fable translation.
They were honestly remarkably similar. As far as I could tell, nothing
was substantially different from the Ellsworth translation and the
Fable translation. I do think that the prose for the Ellsworth
translation was a bit better, but the prose for the Fable one was
actually perfectly readable. Again, I don't speak French so I cannot
say for sure, but I do not believe that I would have gotten a
significantly different experience had I read the Fable version instead
of the Ellsworth version.
Now, it's possible (and likely) that this is somewhat self-fulfilling;
Fable might have been trained using Ellsworth's translation and as such
it's very directly able to crib from it; sadly since I do not speak any
language outside of English, there's sort of a catch-22: the only way I
can compare the accuracy of a translation is to compare against other
translations, but if other translations exist then that will likely
influence the results, and if a translation doesn't already exist then
I have no way of auditing it.
I'm still going to continue reading through Ellsworth's translations
for the subsequent stories simply because that feels more canonical,
and as I said I do think the prose was a bit better.
rikroots wrote 6 hours 7 min ago:
I learned last year that "translation" can be a very tricky thing.
Because there's never a one-to-one correlation between one language's
words, phrases, structures and metaphors, and another language's
equivalent stuff. And LLM translations may not be the actual
translation you want, or need.
I wrote up my experiences of translating Lorca and Cavafy poems
here[1]. tl;dr: I have developed a massive new respect for
translators; however much they're being paid, they probably need to
be paid more! [1] -
HTML [1]: https://rikverse2020.rikweb.org.uk/blog/adventures-in-poetry...
Hendrikto wrote 10 hours 50 min ago:
> I have to say that AI translation has gotten so good
> I do not speak any language outside of English
So you are entirely unqualified to judge this, and you acknowledge
yourself that your test is flawed to the point of being completely
useless. Yet you make grandiose statements about the quality.
eviks wrote 14 hours 20 min ago:
Your example doesn't prove your point because you can't even tell
it's translation, but also because you said it was not better and
are not using it.
Folcon wrote 15 hours 51 min ago:
> but I have to say that AI translation has gotten so good that I'm
not sure how much longer translation work will be there, or rather it
might end up being more about auditing
It's functional? I wouldn't say it's poetic, I wouldn't want any AI
translator translating art, like say a book or poem, I'd be so
uncertain that it would correctly bridge the concepts
A good translator can make stylistic choices that elevate the work
and make it fit in their language
(Having read lots of well translated manga and anime, also from what
I understand there's a few books I've been told by my bilingual
friend's are just chef's kiss quality translations)
Considering translating meaningful art is of some value, on that
score I don't think we're there yet
no_multitudes wrote 20 hours 23 min ago:
> Fable might have been trained using Ellsworth's translation and as
such it's very directly able to crib from it
The `cp` program on my computer also has the remarkable ability to
produce a faithful translation of The Three Musketeers when provided
one as input.
dosisking wrote 9 hours 50 min ago:
Not necessarily. If you are using macOS and APFS, it will just make
a link, it won't actually make a copy.
JeremyNT wrote 20 hours 34 min ago:
Honestly, translations of fiction are themselves creative works, and
the translator needs to really understand both cultures and needs to
write cohesively throughout the work. I'm not sure this is even
really a question of "can it translate" so much as "can it create a
good work of fiction" which is a much higher bar. So maybe the model
can mimic the style (especially given that it was probably trained on
existing translations) but could it really do so from scratch in a
way that is actually compelling? I'm not so sure.
Of course as for the poor OP... is this a majority of what working
translators are paid to do?
I suspect a lot of translation is just grunt work - technical and
business documents. The lack of a cohesive voice with considered
style is perhaps not really much of an issue in those. The
expectations are just much lower; text that conveys the basic meaning
is a much lower bar to clear.
She's probably better than a bot at that stuff, at least for now, but
my concern is that it won't be "enough" better for businesses to
justify her continued employment. And this is my general feeling
about this stuff across society, in basically all domains.
j_w wrote 21 hours 35 min ago:
As somebody who regularly reads translated works, including the
occasional machine translation (MTL), they (MTL) suck. You got a
hugely biased result, which you recognize.
Translation is hard. If you're familiar with reading translations
from specific languages MTL works have a very specific smell to them,
it's a bit hard to describe but it's there. A good translation is
miles (kilometers, for those outside of the US) above MTL.
That's not to say that perhaps the latest LLMs will have better
translation abilities, but that they are generally crap currently.
Maybe they are fine for something very short, but absolutely not for
longer content.
Ekaros wrote 10 hours 36 min ago:
I read genres where MTL is somewhat commonly used. But good quality
human translations take remarkable effort. And even artistic
choices. Like choices between transliterating and translating. Or
maybe in some cases just doing both for single name or term. And
then keeping these choices consistent over substantial works.
And it is not like transliteration is consistent thing. Some cases
would prefer the old way. Or existing already common one. Even
across entirely different works from different authors.
j_w wrote 4 hours 6 min ago:
It definitely takes a lot of work. I've read that it takes a good
writer themselves to translate well, since it's such an artistic
endeavor.
turtletontine wrote 21 hours 39 min ago:
> ⦠considered one of the more accurate translations of the work.
I think youâre missing a big point of translating literary works. A
purely âaccurateâ, phrase-by-phrase translation is often not very
good; the actual literary style, the feeling and the allusions and
references, often get lost that way. A good translation of literary
work requires a lot of deliberate choices by the translator to
deviate from literal translations in ways that convey the style of
the original, or an extra layer of meaning that would be lost by an
âaccurateâ translation of a phrase. Also, being consistent with
these choices matters a lot, which OP claims LLMs are less good at.
mjmsmith wrote 22 hours 54 min ago:
An interesting counter-example:
HTML [1]: https://xcancel.com/ValerioCapraro/status/206506665753442336...
bmacho wrote 10 hours 24 min ago:
I had the suspicion that this was more of a problem of missing
context than lacking meta linguistic abilities. A text can be
translated as "what's the meaning of the words" and "what would a
person/character say in an other language in the same situation",
and it's not in the prompt which one the user wants, but only in
their head.
So I asked my free chatGPT mentioning that it is for a book but it
failed too:
> For a book, a natural English translation would be:
> âJust three words: you are not alone.â [1] It even repeated
the context. So it seems to me now that it indeed still lacks meta
linguistic abilities. (I don't think that this proves anything
meaningful about AI.)
HTML [1]: https://chatgpt.com/share/6a2d06a3-a3b4-83ed-9e0a-8ec07e05...
layer8 wrote 22 hours 46 min ago:
I wonder if âJust 3 words: youâre not aloneâ would have been
acceptable. :)
Hendrikto wrote 10 hours 39 min ago:
That are still 4 words, imo.
mjmsmith wrote 22 hours 8 min ago:
The Empire Strikes Back: "I'm your dad."
bombcar wrote 22 hours 59 min ago:
You're very likely to get a somewhat circular reference; the key (for
me) is that for 90% of the usages, "standard translation LLMs" are
just fine - I still recommend a translator but they're more of a
proof-reader for both languages, catching where something slipped
through.
ixtli wrote 23 hours 24 min ago:
This is sort of missing the point-- people who dont deal with
linguistics dont understand that there are multiple types of
translation. There's word for word (which is what you're talking
about) and sense for sense. If you let an LLM do all of your
translation you're letting it interpret huge amounts of intent and
context it doesnt (and probably cant) access. The ways in which this
impacts the translation will forever be unknown to you and in the
worst case lost forever.
So i guess in the end it just matters how important the work is.
senordevnyc wrote 19 hours 14 min ago:
If you let an LLM do all of your translation you're letting it
interpret huge amounts of intent and context it doesnt (and
probably cant) access.
Whatâs the intent and context that a human translator of a text
is typically privy to that an LLM is not?
vel0city wrote 20 hours 38 min ago:
> If you let an LLM do all of your translation you're letting it
interpret huge amounts of intent and context it doesnt (and
probably cant) access.
Assuming lots of material local to the context one is wanting to
translate is included, why couldn't it potentially access that
additional context?
tombert wrote 23 hours 11 min ago:
Actually I was talking about tonally as well.
A raw "word for word" translation (which I also tried) made the
story somewhat hard to follow and very dry, but just asking it to
keep the same kind of jovial swashbuckling tone of the original
made something pretty similar to Ellsworth's translation.
Again, before someone decides to "correct" me on this, I am aware
that it's very likely that the Ellsworth translations are part of
the training set so it's not directly a fair comparison.
geon wrote 23 hours 25 min ago:
> I did compare a few individual chapters between the Ellsworth
translation and the Fable translation.
I'm pretty sure the Ellsworth translation is in the corpus. You
basically instructed claude to regurgitate it.
The llms all have the more famous books memorized. You can trick them
to recite them more or less word for word.
tombert wrote 23 hours 18 min ago:
I mentioned this specifically in my comment :)
stdbrouw wrote 21 hours 21 min ago:
... yet you still conclude "AI translation has gotten so good",
so which is it?
tombert wrote 21 hours 13 min ago:
I do think it's gotten pretty good. I'm just acknowledging my
limitations in the matter. It's not a contradiction.
sushid wrote 10 hours 16 min ago:
I'm sorry but it's just such a glaring caveat. And the fact
that you don't speak French...
oytis wrote 20 hours 43 min ago:
Try translating some prose from English to another language,
then, in a different model, back to English
lambda wrote 17 hours 15 min ago:
I tried this with the original comment in the thread.
Guaranteed to not be in the corpus, references a few terms
that also wouldn't be in the corpus (Claude Fable), and
long enough to be more than a sentence or two while short
enough to compare in a discussion like this.
I did this with entirely local models I have sitting around
on my laptop. Minimax M2.7 at a 3 bit quant with 8 bit
quantized KV cache for English -> French, Gemma 4 31B QAT
(4 bit quant) MTP for French -> English.
It's perfectly readable, but there are a few places where
the phrasing is a bit more awkward after the double
translation ("auditing" to "revision" in particular is a
bit off). Gemma did comment on not knowing what Claude
Fable was in its thought process: "The author compares
Ellsworth's translation with one produced by "Claude Fable"
(likely a misspelling of "Claude" or a specific version of
Claude)."
Here's the double translation:
"I have no doubt that a writer is better at translating
than AI, but I must say that AI translation has become so
good that I'm not sure how much longer the profession of
translation will existâor rather, it may become more a
matter of revision.
"For example, I just read Lawrence Ellsworth's translation
of The Three Musketeers, which I enjoyed immensely. I
neither speak nor read French, but from what I understand,
Ellsworth's translation is considered one of the most
faithful translations of the work.
"Out of curiosity, I asked Claude Fable to translate the
original French version of The Three Musketeers; I asked it
to translate faithfully, but also to try to maintain the
same playful tone as the original and to censor nothing.
"Once it was finished, I didn't read the entire result, but
I compared a few individual chapters between Ellsworth's
translation and Fable's.
"They were honestly remarkably similar. As far as I can
tell, nothing was substantially different between
Ellsworth's translation and Fable's. I think the prose in
Ellsworth's translation was slightly better, but Fable's
was actually perfectly readable. Again, I don't speak
French, so I can't say for certain, but I don't believe I
would have had a significantly different experience if I
had read Fable's version instead of Ellsworth's.
"It is possible (and probable) that this is partly a
self-fulfilling prophecy; Fable may have been trained using
Ellsworth's translation and can therefore draw directly
from it. Unfortunately, since I don't speak any language
other than English, there is a sort of vicious circle: the
only way to compare the fidelity of a translation is to
compare it to other translations, but if other translations
already exist, that will likely influence the results, and
if a translation doesn't exist yet, I have no way of
verifying it.
"I am going to continue reading Ellsworth's translations
for the following stories simply because it feels more
canonical to me, and as I said, I think the prose was
slightly better."
tombert wrote 16 hours 45 min ago:
This is terrible. I never use em dashes!
jimbo808 wrote 23 hours 25 min ago:
LLMs are now being aggressively manipulated for propaganda purposes.
Powerful people have realized that people believe LLMs, and treat
them as authoritative sources of fact.
The number of lies, lies by omission, deceptive distortions, and
fallacious argument tactics they generate is absurd, and increasing
rapidly. Translation, when done as a service you are paid for, can't
be relied on by propaganda bots.
smallpipe wrote 22 hours 4 min ago:
Do you have examples?
jimbo808 wrote 14 hours 25 min ago:
Tons. To pick the most recent example:
I was asking about some allegations relating to the Epstein
files, and it used the slogan "Satanic Panic" in a weird way that
gave me a vibe of discrediting victims. I'm too young to know
much about it, so I asked some things about it. It explained the
McMartin case in a way that seemed too absurd to be real. I asked
some follow-up questions about what the strongest evidence was,
and how it was explained.
The first deception was omission. Initially, it didn't even
mention what was arguably the most significant evidence in the
case, which was the presence of tunnels under the school. ChatGPT
mentioned the tunnels, and how an archaeologist named E. Gary
Stickel found evidence of tunnels. Here's what it said about
that:
> However, that conclusion has been repeatedly challenged and is
not treated as settled fact in the academic or forensic
archaeology literature.
> Other archaeologists and later reviewers reinterpreted the same
physical findings differently. One major counter-analysis (W.
Joseph Wyattâs review) argued that what Stickel identified as
tunnels was more plausibly explained as pre-existing trash pits
and construction-related disturbance from before the school was
built in the 1960s.
The first lie was by omission, it didn't even mention this when I
asked about the most important evidence. The next misleading
piece was the framing. Dr. Stickel is a PhD archaeologist, and
doing this sort of analysis is his area of expertise. He used
nine criteria as a basis for determining the presence of tunnels,
and all nine were met. He found "conclusive" evidence of tunnels,
and that they matched the expected locations described by the
victims. Dr. Stickel was the only expert to review the site
before significant construction made such an analysis impossible.
The "major counter-analysis (W. Joseph Wyattâs review)" was
done by psychologist Joseph Wyatt, who never physically visited
the site, and who is not an expert in anything related even
loosely to archaeology. ChatGPT presented this guy in a way that
made it seem that Stickel had been debunked by a comparable
expert.
Wowfunhappy wrote 23 hours 25 min ago:
> Out of curiosity, I sic'd Claude Fable on the original French
version of The Three Musketeers and told it to translate accurately,
but also try and keep the same jovial tone as the original and do not
censor anything. After it was done, I didn't read the entire output,
but I did compare a few individual chapters between the Ellsworth
translation and the Fable translation.
This isnât a great test, because Claude almost certainly has
multiple translations of The Three Musketeers in its training data.
tombert wrote 23 hours 19 min ago:
Read the last two paragraphs :)
svara wrote 20 hours 27 min ago:
The things is, this is almost certainly what's happening.
You can (could, maybe they 'fixed' it by now) get sota LLMs to
reproduce entire novels near verbatim.
The idea of giving it parallel texts of those novels in different
languages, to train it on translation, is so obvious it'd just be
strange if the AI labs didn't do it.
In fact DeepL was doing basically that more than 10 y ago.
Wowfunhappy wrote 22 hours 36 min ago:
Oops, I legitimately missed the second-to-last paragraph.
I still think there are better tests you could do. Ideally, you
would choose a book that was published recentlyâafter the
modelâs cut-off dateâwhich is considered to be a good
translation. But even something like The Girl With the Dragon
Tattoo, which is not particularly new and by no means obscure,
would be better than a famous work of literature like The Three
Musketeers that has many translations.
tombert wrote 22 hours 30 min ago:
Almost certainly correct, though I've noticed that these LLMs
like to complain when you give it stuff that is still in
copyright. The Three Musketeers is thoroughly public domain
everywhere so in that sense it's a good test, but of course
because it's public domain everywhere there are lots of
translations to crib from so I acknowledge it's not a great
test because the training data almost certainly contains a
competent translation.
Even if Fable didn't have Ellsworth's translation, it certainly
has the William Barrow translation, which would still get it
like 80+% of the way there.
My wife speaks Spanish, I should get her to do some kind of
comparison with a Spanish book that doesn't have English
translations.
card_zero wrote 22 hours 40 min ago:
They say "yes, I admit it, this is all invalid".
tombert wrote 21 hours 3 min ago:
No, they are a disclaimer that it's possible that the data
isn't conclusive. Not the same thing as saying "it's all
invalid".
paulddraper wrote 23 hours 26 min ago:
.
tombert wrote 23 hours 17 min ago:
Already mentioned in the comment lol.
Swizec wrote 23 hours 26 min ago:
> As far as I could tell, nothing was substantially different from
the Ellsworth translation and the Fable translation.
Crucially the full translation was part of ChatGPTâs training set.
Recall is a pretty solved problem in machine learning.
How well does it translate a French novel published yesterday? Where
neither the original novel nor any translations are in the training
set yet? Or might not even exist!
I tried asking ChatGPT to translate a letter I wrote in Slovenian
this weekend. It got the general gist but missed a lot of the nuance.
Completely missed several of the little touches of tone where the
right choice of synonym conveys a whole bunch of information.
tombert wrote 23 hours 18 min ago:
Did no one actually finish reading my comment?
Swizec wrote 23 hours 10 min ago:
I feel like that wasnât there when I started writing my
comment. I also have a bad habit of quickly posting and then
adding over a few minutes.
Glad we agree :)
tombert wrote 23 hours 0 min ago:
Guess I have no way of proving it, but I pinky swear that I
didn't edit it in later!
But yeah, I broadly do agree; if I read other languages I could
find a book that hadn't been thoroughly translated to English
and then I could give a proper analysis on how good the
translation is, but since I'm a very stereotypical American I
know exactly one language (and sometimes my comprehension of
even that is questionable).
Hendrikto wrote 10 hours 46 min ago:
> I could find a book that hadn't been thoroughly translated
to English and then I could give a proper analysis on how
good the translation is, but since I'm a very stereotypical
American I know exactly one language
So you actually cannot give a proper analysis.
zipy124 wrote 23 hours 15 min ago:
Welcome to the internet
layer8 wrote 23 hours 30 min ago:
I see the difficulties more in other areas, such as technical
translations, specialist books, user manuals, and translating UIs,
where contextual information and a back and forth with the client is
needed to clarify details, and (for user manuals and UIs) the
translator has to put themselves in the mind of the user and has to
consider the possible contexts and use cases.
exe34 wrote 23 hours 31 min ago:
> Again, I don't speak French so I cannot say for sure
This reminds me of the adage, that ChatGPT is really great at
everything except my own work.
rootusrootus wrote 23 hours 24 min ago:
Yes, it is another variation on the Gell-Mann Amnesia Effect. I
have a number of non-developers in my circle of friends who think
Claude is about to put me out of work. They think it is just a
great tool for them, not a replacement. Of course!
tombert wrote 23 hours 28 min ago:
Yeah, that's why I put the caveat in there. I have no real way to
verify the result outside of checking against "known good"
translations, though if the known-good translation exists then
there's not exactly a lot of reason to do the AI translation in the
first place.
I suspect if I knew another language I would be able to find errors
in the translation.
zuzululu wrote 23 hours 34 min ago:
This moment is coming for software developers too
ixtli wrote 23 hours 19 min ago:
I think this collapses a global, complex heirarchy of software
engineering workers into a single monolith and serves only to
advertise for frontier LLM providers. the point where you no longer
need engineers is not going to be reached by making LLMs better and
better.
daveguy wrote 23 hours 26 min ago:
But not before a huge crash in optimism about their capabilities.
Specifically wrt accuracy, reliability, efficiency, and
organization/architecture.
rootusrootus wrote 23 hours 27 min ago:
More specifically, it is coming for coders. If you make your
living by banging out lines of code all day, then you may want to
be looking at adjusting your career trajectory. But if that is
your job, you are either very junior, or a bit foolish for getting
into that situation.
zuzululu wrote 23 hours 11 min ago:
so what is software developer doing if writing code is not part
of their job
I don't see how not writing code is being offered as a moat, it
seems like that is just translating business/stakeholder
requirements to architecture/biz processes which is exactly the
type of low hanging fruit that AI will capture first
or was it your point that the position sits closer to the
stakeholders (relatively compared to those lifting) thus immune
from replacement by AI
or is your argument that your taste is exquisite that no AI will
be able to match it like it already has with software so far and
it will not improve beyond the current state
preg_match wrote 1 hour 30 min ago:
I kind of view it this way. Yes, non-technical people can
prompt and write code. But technical people can certainly also
do the job of product people. So then, who would you want to do
the end-to-end? A SWE, or a product person? Probably a SWE.
As software engineers, our job will expand horizontally. We
will shift left, and right. But thatâs really fine, because
Iâve found SWE can be really good at that.
Theyâre good at requirements engineering. Theyâre good at
quality assurance. Theyâre good at technical support. So, why
not pay a SWE to be that person?
Or, at least, some SWEs are good at that. The ones that
arenât will struggle I think.
pwython wrote 22 hours 25 min ago:
Same thing architects do if drawing lines gets automated:
architecture.
Would you trust living in a high rise designed by AI?
Designing a system that survives production is the job.
tombert wrote 22 hours 28 min ago:
If you get to senior level then most of your job probably is
not writing code, but planning things out. The code is largely
an implementation detail.
At least that's how it was for me, maybe other peoples' careers
are different.
lelanthran wrote 21 hours 17 min ago:
> If you get to senior level then most of your job probably
is not writing code, but planning things out.
If they're so good at banging out code now, they're coming
for that too, you know.
tombert wrote 21 hours 11 min ago:
I don't necessarily disagree, but there's gotta be a name
for some kind of "infinite extrapolation" fallacy, where
you assume that the current rate of progress will continue
indefinitely.
That might happen, but I don't think it's implied, at least
given literally every other bit of technology that has ever
happened in history ever.
lelanthran wrote 21 hours 4 min ago:
> I don't necessarily disagree, but there's gotta be a
name for some kind of "infinite extrapolation" fallacy,
where you assume that the current rate of progress will
continue indefinitely.
I am not assuming they'll continue indefinitely, but it's
a small step from writing code to planning out the code
to write, and another small step from planning a coding
project to planning a software project, etc.
These are all small steps, and because the act of
specification + planning paid less than specification +
planning + programming, what reason do you have for
thinking that specification + planning is valuable enough
to keep the salaries the same as specification + planning
+ programming?
tombert wrote 16 hours 23 min ago:
I think with a fixed size problem, no we wouldn't be
able to demand the same salaries that we get now.
I dispute that the problem is fixed size. The people
who are senior engineers now will learn how to think at
a higher level with the AI models.
lelanthran wrote 6 hours 44 min ago:
> The people who are senior engineers now will learn
how to think at a higher level with the AI models.
I think my argument is that, if they were going to do
that, they would have done so by now - they already
say that actual coding was only a small percentage of
their work anyway.
bluefirebrand wrote 21 hours 43 min ago:
Yes, my career has been different. At my workplaces seniors
still have to code because they dont want to hire juniors
The "planning things out" has moved to another layer, called
"architects"
skydhash wrote 22 hours 36 min ago:
So what a lab researcher doing if typing articles is not part
of the job?
jujube3 wrote 22 hours 7 min ago:
Well--well look. I already told you: I deal with the god damn
customers so the engineers don't have to. I have people
skills; I am good at dealing with people. Can't you
understand that? What the hell is wrong with you people?
HTML [1]: https://www.reddit.com/r/ProductManagement/comments/...
VBprogrammer wrote 23 hours 28 min ago:
I think there is going to be a long time before all of the obscure
knowledge of a decent software developer can be completely replaced
by AI. Though the job is going to change beyond recognition. It
already has in many ways.
tombert wrote 23 hours 33 min ago:
Yeah almost certainly, especially the ones who made a career out of
"copypaste from StackOverflow", which is most engineers.
But even the good engineers should likely be a little worried.
zuzululu wrote 11 hours 0 min ago:
why would it be different for other people if you already said
senior level is not writing code but planning things out?
is there something about planning that LLMs cannot do being your
crux of the argument?
what do you believe about your jobs or function that you think
will be immune from AI replacing you?
If anything it seems your role is not that dissimilar to those
translating languages or business requirements.
I am struggling to see what it is about this planning you do that
cannot be done by AI because it seems to me thats not where the
moat is rather I find the middle man jobs to be the most
vulnerable to AI immediately much more than people writing code.
Because at least someone is watching the outputs from AI and
understands the code and can communicate it easily back to the
stakeholders without the middle man gate keeping and applying
their "taste".
I have a feeling that anyone in your shoes is going to be working
with code soon or they won't have much to offer anymore to the
business. A stakeholder could easily replace the middle layer
with AI and even as a business owner myself I do not see any need
to add any more humans at the layer anymore unless they write
code.
ValentineC wrote 23 hours 41 min ago:
From the post:
> Ah, you canât fire me, Iâm self-employed!
I don't understand thinking like this. I think companies can certainly
fire their contractors.
anotherevan wrote 9 hours 32 min ago:
Humour â it's so subjective.
mapmeld wrote 23 hours 47 min ago:
I think it's an interesting perspective, because translation is one of
the jobs that I (a) hear is the first to lose work due to AI, and (b)
often used as an example of "acceptable" AI by people who are skeptics
of LLMs and AI-generated art.
fzeroracer wrote 5 hours 0 min ago:
I think the only people that genuinely think AI translation is viable
are those that never read in the first place.
There are a number of games I've seen and played on Steam which use
MTL to get the game playable in English and universally the
translation is absolute shit. Sentences that don't transition into
another, wordplay that becomes nonsense and a completely flat affect
to everything.
Marsymars wrote 19 hours 34 min ago:
Well it's more than acceptable to translate e.g. web pages for
reading, but it's not something you'd want to professionally publish.
Kinda conceptually similar to how typos and grammatical mistakes
aren't a big deal if you're shooting off a quick text or email, but
publishing if you've got typos in your advertising copy, in your
resume, on your medicine label, etc. it's a real bad look.
geon wrote 23 hours 18 min ago:
"Could not connect to translation service" was apparently good enough
for someone, so the bar must be extremely low. [1] On the other hand,
a lot of people become extremely put off by the smallest sign of ai
slop. And the llms have a tendency to impart their style to any text
they touch.
HTML [1]: https://www.reddit.com/r/funny/comments/3e786n/chinese_hair_...
anigbrowl wrote 20 hours 33 min ago:
I prefer to get my hair cut at 'Usage limits exceeded.'
SecretDreams wrote 23 hours 31 min ago:
It'll be a similar theme for all facets of work involving any
language, slowly - human or code. We'll parrot about humans in the
loop this and that, but I think it'll be less humans in the loop over
time and I think most people will even be willing to settle for a
slightly more mediocre translation or coded project. It all comes
back to our dopamine addiction, where we like fast feedback. And the
oligarchs like tools to suppress wages. We will be our own demise for
not advocating for either UBI or job protections, instead, happily
using the technology while also rolling our eyes that it could never
replace us.
layer8 wrote 23 hours 35 min ago:
Translators already started losing jobs due to machine translation a
decade ago (e.g. DeepL), before LLMs. Remuneration going down made it
more difficult to make a living as a translator already then, even if
you still received offers.
qsort wrote 23 hours 35 min ago:
Not all translations are the same. Literary translations are often
works of art in and of themselves, and automating them would be
missing the point entirely, like automating homework or weightlifting
at the gym. I don't really know what's the state of the art, but I do
buy that, on the other hand, translating toaster manuals or generic
copy could soon be automatic.
duffycommaryan wrote 22 hours 52 min ago:
When it's one one-hundredth the cost, "good enough" is generally
good enough.
greiskul wrote 23 hours 26 min ago:
Yup. If you are bilingual, you quickly realize how some
translations are very bad. How some translations are very good. And
how hard it is to translate. With dry, simple text, it might be
easy. But when it involves art?
Some jokes don't translate directly. There is pun. Sounds of words.
Double meaning. Ambiguity. Cultural background. The creation of new
words.
It can be reasonably argued that some poetry can be impossible to
translate from some languages to others. A poem might be explained,
but by a lenghty, dissecting explanation, that completely loses the
point of it.
graemep wrote 23 hours 22 min ago:
Or if you compare a poetic translation to a literal one, of
different translations of the same work to the same language to
each other.
raincole wrote 23 hours 36 min ago:
There are translators and there are translators. Translating
legal/business documents is a completely different thing from
translating movies/books/games.
I can confidently say that LLMs do a better job than the average
traditionally published fictions in my country, at least when the
original works are in English. Every single time I watch a subbed
movie there will be some lines noticeably wrong.
anigbrowl wrote 20 hours 35 min ago:
Yes, I've become very leery of artistic translation, in part
because the paradigm of translators as adapters and localizers
often ends up at odds with the job of faithfully and accurately
representing the original material.
The most egregious example I came across recently was where a
friend enthused about some manga he was reading and I agreed to
read a few chapters, only to discover that the translator has
decided to render the countryside accents of western Japan
(engaging with a protagonist visiting from Tokyo) by having them
say 'y'all' and 'bless your heart' and other Southern USA tropes. I
get the aspiration of the translator, but it was excruciatingly
unpleasant to read. At that point, why not just say the protagonist
was from New York and on vacation in Florida, or draw in some
meshback caps on some of the characters and add alligators here and
there in the background?
xigoi wrote 23 hours 42 min ago:
> often used as an example of "acceptable" AI by people who are
skeptics of LLMs and AI-generated art.
As one of such people, I think there is a nuance to it. AI is great
when youâre translating something to yourself. But when translating
things for others, more caution and human judgement is needed.
Espesially when translating instruction manuals, where bad wording
could cause someone to injure themself.
duffycommaryan wrote 22 hours 53 min ago:
Language is incredibly complex. I remember a TikTok from a
bilingual English-Korean speaker comparing the English subtitles
from a Squid Game scene to what was actually being said by the
characters. The nuance and info density lost in translation made
the subtitles feel completely remedial. Americans were basically
watching a different show altogether.
ClimaxGravely wrote 20 hours 38 min ago:
I'm by no means a native level Japanese speaker but I'm
frequently surprised at how off Japanese-English subtitles can
be.
alex0015 wrote 11 hours 25 min ago:
I was watching the Netflix show The Empress with Chinese
subtitles that did a pretty good job translating the German. I
switched to English subs for one episode and couldn't stop
telling the people I was watching with "That's not what he
said! That's completely different!"
inigyou wrote 23 hours 32 min ago:
This. I put things through Google translate all the time and
they're always unreliable. Sometimes they're correct, sometimes I
need to know roughly what the original said. Infamously, Google
used to say "geiler Typ" meant "horny guy" when it means "awesome
guy". Google used to think "geil" meant "horny" in general, which
it can but not usually
smallerfish wrote 23 hours 21 min ago:
Google translate is primitive compared to Claude at translations.
carlosjobim wrote 23 hours 21 min ago:
Google Translate is at the bottom of the barrel. All other AI
translation tools are vastly superior. You'd want to evaluate
those, and forget about Google Translate completely.
numpad0 wrote 22 hours 8 min ago:
It's all the same, except LLMs are less precise with names.
edude03 wrote 21 hours 14 min ago:
Googles machine translation team wrote the Attention is all
you need paper that introduced transformers specifically to
solve the problem that you can just model language by mapping
one word to another. I'd be floored if they weren't using the
tech they invented for intended purpose
numpad0 wrote 14 hours 6 min ago:
Yeah. LLMs, machine translations, CJK keyboards, they are
all the same technology; faster cars to each others, not
cars vs horse drawn carriages. It'll be surprising if they
didn't directly apply any applicable learnings back to
Google Translate.
carlosjobim wrote 21 hours 26 min ago:
Just like a car and a school bus are the same because both
have four wheels?
ai-x wrote 23 hours 34 min ago:
Exactly, it's never about absolute results, it's always
Expected Value (Upside, given time/cost savings + Downside, given
%reliability).
So, every task falls under a spectrum
layer8 wrote 23 hours 50 min ago:
Whatâs unfortunate is that the market that is willing to pay for
high-quality human translation has shrunken considerably.
robertnowell wrote 21 hours 3 min ago:
if it was valuable, people would pay for it
layer8 wrote 20 hours 18 min ago:
Thatâs not how it works. Value for users doesnât translate 1:1
into value for businesses, nor are either necessarily willing to
pay for value. Thatâs why things enshittify.
robertnowell wrote 12 hours 5 min ago:
if they are selling to a business, the biz will pay if it solves
their problem. if the solution doesn't solve their problem, or
something else solves their problem that is easier / cheaper /
better, the business will not pay.
kevincox wrote 23 hours 17 min ago:
Is it that unfortunate? Tasks that don't require high-quality
translation now don't need human labor. We should be celebrating.
The sad part is that we haven't figured out how to distribute our
resources fairly to these people even thought their services aren't
required as often. Instead we just take their wages and give them to
the top 0.1%
layer8 wrote 22 hours 51 min ago:
Itâs unfortunate because we are seeing more poor translations in
all domains, and users suffer from it. Itâs part of a general
enshittification of things. There are few contexts where
low-quality translations donât constitute a degradation of user
experience.
Just one amusing example I saw recently: On the Amazon website, a
submit button labeled âGoâ in English was translated to
something which when translated back would be âWalkingâ.
Thatâs the kind of thing that would be exceedingly unlikely to
happen with a human translator.
arjie wrote 21 hours 41 min ago:
On the other hand, a bridge sign that says "No entry for heavy
vehicles" is unlikely to now read "I am out of office for the
next 2 weeks" in Welsh:
HTML [1]: https://www.theguardian.com/theguardian/2008/nov/01/5
627467 wrote 17 hours 46 min ago:
This story is so great because it shows how robotic are so many
jobs and tasks. Like, what happened in the reciepient mind to
not consider whether the reply was appropriate or not? Did the
almost instant response not hint at an automated email? Or the
lack of any other content of the email (a greeting, something)?
Or maybe people send so many emails or is doing so many thing
they switch off certain parts of the brain?
kube-system wrote 20 hours 10 min ago:
Now instead it will say, in Welsh
"Switched to Opus 4.8 - Fable has safety measures that flag
messages on most cybersecurity or biology topics. They may flag
safe, normal content as well. These measures let us bring you
Mythos-level capability in other areas sooner, and we're
working to refine them."
arjie wrote 19 hours 34 min ago:
Hahaha thatâs pretty funny. But in their defence perhaps if
you didnât want a tall tale you shouldnât have asked for
a Fable? ;)
Legend2440 wrote 22 hours 8 min ago:
I think you overestimate human translators. There is a lot of
very poor quality human-translated text out there. English
translated from Chinese is famous for this.
There will never be enough expert-level human translators, and
they tend to be very expensive. Machine translation has raised
the floor.
layer8 wrote 20 hours 10 min ago:
I donât agree that machine translation has raised the floor,
because even LLM-based translation can get pretty bad when it
isnât provided with the necessary context. And the average
quality level Iâm encountering has dropped since machine
translation became mainstream. Poor translations have become
the norm, which wasnât the case 20 years ago, despite the
occasional âall your base are belong to usâ.
kouteiheika wrote 21 hours 1 min ago:
> I think you overestimate human translators. There is a lot of
very poor quality human-translated text out there.
This.
There was even a big controversy recently with one of the games
on Steam where human translators just completely botched and
vandalized the translation, mistranslating huge chunks of it
and injecting their own personal politics which are not present
in the original text (only English was affected; other
languages were translated fine apparently): [1] If you'd get
the AI to translate it, even without any editing, it would have
done much better job. Just because something's done by a human
it doesn't automatically make it good; you still need competent
people at the helm, and recent machine translation advances
certainly raise the floor on that.
HTML [1]: https://store.steampowered.com/news/app/2914150/view/5...
pixel_popping wrote 1 day ago:
I agree with the take, but it's a temporary one, the sad reality is
that we will be literally inferior soon, there will be a point where we
will not trust human input without counter check by AI, we need to
remember that we are kinda at the beginning of the AI era, in 5 to 10
years it's very unlikely that a human translator or software engineers
will do better than the tooling we will have.
There is already a tipping point now in software engineering where we
prefer to ask AI instead of humans because we believe accuracy will be
better, see SO death as an example or just see the current state of
online dev communities, it's getting deserted and between team members
at work, we can also notice that people speak less and less.
Sad but I believe it.
rootusrootus wrote 23 hours 17 min ago:
> we will be literally inferior soon
This plague of misanthropic doom is itself pretty depressing. Why do
so many people think LLMs are in any way on a path to compete with
human brains? Why do you think so little of yourself? The brain is
magnificent and complex in ways that we are unable to decipher
anytime soon, and it does way more than an LLM. Way, way more.
pixel_popping wrote 22 hours 45 min ago:
I don't talk specifically about LLMs but AI in general, it's an
important distinction because tooling is currently what make models
useful and more performant.
When I say we, I mean the general population really. There0-'ll
always be the super bright ones, sure, but we gotta be realistic
here. Most people already struggle to make any meaningful
contribution because it's so hard to compete, and that gap is just
gonna get bigger and bigger.
I agree the brain is pretty magnificent, but when it comes to stuff
like language, figuring out if an idea actually works, building the
next LLM, or running business stuff, it's pretty obvious we'll be
inferior. AI can already innovate and come up with new things way
faster than any human could, so at some point (soon) => the
majority of contributions are just gonna come from AI, not from us.
WillowWithAWand wrote 23 hours 24 min ago:
The thing is that AI is not some inevitable force of nature that must
just be contended with and weathered. It is an active choice by our
society to develop it and it is a choice by our society how we should
use it, if at all.
We would all do well to remember that and remember that each and
every advancement and use case regarding AI is the result of choices
by people (or the groups of people we call corporations) and are
oftentimes motivated by the profit motive, not the best interest of
humanity.
We could make different choices up to and including our own Butlerian
Jihad where we ban all forms of AI but we could also do everything we
can to prevent the worst fallout short of that.
There are only two types of problems in the universe:
1) those posed by the laws of physics
2) those posed by human choices
The problem of AI is one of the latter.
bigstrat2003 wrote 23 hours 31 min ago:
> there will be a point where we will not trust human input without
counter check by AI
That's nonsense. There is zero reason to believe that AI (with the
current techniques) will ever become reliable enough to let it do its
own thing, let alone better than a human. It's been years of
development and you still can't trust it to get basic facts correct,
not even "well it's better than it used to be". Saying it'll replace
humans in 5-10 years is a fantasy (or a prediction that people are
stupid enough to fall for hype, I guess).
Ancapistani wrote 20 hours 19 min ago:
> It's been years of development and you still can't trust it to
get basic facts correct
There's the rub: AI is not an oracle. It's neither designed nor
intended to provide accurate recall of all facts. It's closer to a
reasoning engine than anything IMO.
Oh, and for the record: I don't trust people to get basic facts
correct, either. It's already far better than the average human at
trivia.
pixel_popping wrote 22 hours 16 min ago:
You come from the principle that humans are reliable at first which
is partly right but also wrong in so many scenarios, you can even
see lately the CVE spree happening, which demonstrates that
human-made codebases have serious vulnerabilities and without the
help of AI, we probably won't even know about them which proves
that humans are not that "reliable", the current societal structure
is also built around the fact that humans can't really be trusted,
nothing really different with AI, we can't fully trust them like we
can't fully trust humans.
It's not a fantasy, I would bet that no serious engineer nowadays
is putting in prod a codebase not AI reviewed meaning we already
can't work on our own, we must factor in the on-going decline of
human capabilities (at least developers) as well of course.
I'm not really saying this because of any sort of hype, but I can
personally relate where I went from actually coding to NEVER CODE
in less than 2 years, and everyone around me is the same thing,
what it will be in 5 years?
Knowing that really, most developers aren't even using proper
tooling yet so they are very slow compared to what they could be, I
mean how many people we hear saying they can't even saturate an
Anthropic Max 20 subscription? I saturated 7 accounts the last 2h
alone, it's because they haven't entirely rethought their workflows
yet, why do they even have "downtimes", it should be 24/7.
graemep wrote 23 hours 23 min ago:
It can spot mistakes made by a human if asked to review code or
write tests.
GP is is over the top ins saying humans will "be inferior soon" but
AI can be a nice additional check so AI review might be come
standard.
Johnbot wrote 23 hours 32 min ago:
This is anecdata, but in my experience with myself and my coworkers,
it is not that we believe the AI will be more accurate in software
engineering, but that the answer will come faster and be more
tailored to our exact problems. If I have to search SO, I have to
find the answer and then tweak it to fit my codebase, but with AI
tooling, the AI is already basing its answer around my code.
pixel_popping wrote 22 hours 32 min ago:
I think we actually do believe it, do you believe Fable 5+GPT-5.5(+
the whole model zoo) in loop with adversarial (no budget limit) or
a 10-year experienced SWE?
We are talking about "codebases" but realistically we won't even be
checking the filetree of them soon, it will be all blind,
containerized and verified with pseudo guarantees which are good
enough to build serious things. We don't even write documentation
for humans anymore, we need to look at the trends and the reality
within companies, most developers became "callcenter agents" in a
matter of only 2 years and literally most of them are not even
using proper automated tooling yet as we can see the "vibe coding"
trend with Claude Code which is weak, by far most work done daily
by developers is already automatable entirely, but with exceptions,
sure, but in a few years those exceptions will become rare.
There will be niche problems about legacy products, sure, but
legacy products will all be replaced over time, if we think in
depth, why do we even need that many languages, that many tools?
Tomorrow AI will write 99% if not all code existing ("code" doesn't
even matter anyway), so it's much better if it's specific to AI and
not playing this dance where we think we are doing a meaningful
human contribution on an "AI-made codebase".
For context, I have 2 decades of software dev behind me.
Ancapistani wrote 20 hours 23 min ago:
This is the direction I'm going.
For personal projects that I don't plan to share widely, I'm
making it a point to not look at the code at all. So far - and to
my surprise - I've not only found that this has result in no more
bugs than before, but it seems to result in fewer bugs over time.
Every time I find a bug or a regression, I add it to the
specification. My SDLC requires that every specification have at
least one associated test. Not every function, or every line, or
anything like that - every specified feature. The end result has
been that my projects have matured over time much faster than if
I'd been more closely involved.
I've already toyed with writing some projects in Nim and Haskell
for token efficiency. At some point I plan to put together a
simple test project, then do a comparison of token efficiency
with every language I can think of to find the one that I'm able
to generate most quickly, correctly, and cheaply.
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