HackerTubewatch
Surprise me
Frame from Can GPT-4 translate literature? Plays via YouTube's privacy-enhanced embed

Can GPT-4 translate literature?

Tom Gally
Talks
YouTube
Cited on HN 4 times, 2023–2025, never outright recommended score 0
Years with an HN recommendation, 2007–2026

Cited as an expert's first-hand evidence that GPT translation is near human quality for distant language pairs.

Tom Gally, a former professional translator and University of Tokyo professor, discusses in March 2023 whether GPT-4 and similar models could translate literary and popular fiction. He gives his assessment of Japanese-to-English quality.

“the basic quality of the translation [from Japanese to English] is as good as a human might do” (HN, 2023)

4 citations · Talks · partly dated

4 Hacker News comments

From the HN archive; up to 20 kept per video, favoring different commenters. Recommendations first.

@bumbledraven Mar 2023 Cites it
on HN thread ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks
Read more
Are you giving it multiple paragraphs to translate at once so that it has enough context for a good translation? If so, would you mind sharing a sample input and output that you found unsatisfactory? In "Can GPT-4 translate literature?" (Mar 18, 2023) [ [this video] ], Tom Gally, a former professional translator and current professor at the University of Tokyo, said: > …the point is, to my eye at least, the the basic quality of the translation [from Japanese to English] is as good as a human might do, and with some relatively mild editing by a sensitive human editor, it could be turned into a novel that would be readable and enjoyable.
Professional translator says GPT-4 Japanese-English is near human quality
@og_kalu Sep 2023 Cites it
on HN thread
>about machine translation and looked at some results of translating between English and French. It was difficult to find any fault with the translation. This has never been the case for distant language pairs till GPT. That is a pretty big change. [this video]
Evidence GPT translation is strong for distant language pairs
@og_kalu Sep 2023 Cites it
on HN thread
>but nobody in the very well funded translation industry has a GPT powered translation engine for the key reason that it's not ready for production. Translator for 20 years talking about using GPT for Japanese-English. [this video] [link]
Translator of 20 years on using GPT for Japanese-English
@tkgally Feb 2025 Cites it
on HN thread Notes on OpenAI o3-mini
Read more
As I explained in a sister comment, it is not possible to rate translation quality objectively, as opinions and positions about what constitutes a good translation vary. But in my tests of reasoning models since the release of o1-preview, they have not seemed as reliable as the straight nonreasoning versions of ChatGPT, Claude, or Gemini. The translation process itself usually doesn’t seem to require the kind of multistep thinking those reasoning models can be good at. For more than a year, regular LLMs, when properly prompted, have been able to produce translations that would be indistinguishable from those of some professional translators for some types of translation. General-purpose LLMs are best for translating straight expository prose without much technical or organization-specific vocabulary. Results are mixed for texts containing slang, dialogue, poetry, archaic language, etc.—partly because people’s tastes differ for how such texts should be translated. Because most translators are freelancers, it’s hard to get a handle on what impact LLMs have been having on their workloads overall. I have heard reports from experienced translators who have seen work drop off precipitously and have had to change careers, while others report an increase in their workloads over the past two years. Many translation jobs involve confidential material, and some translators may be hanging onto their jobs because their clients or employers do not allow the use of cloud-based LLMs. That sa
Author of the talk commenting on LLM translation quality

Video list and Hacker News comment labels from HackerTube (prompted by @karpathy), released under ODC-By 1.0, built on the open-index/hacker-news archive. Hacker News data is provided by Y Combinator; comments remain the work of their authors. Video titles, channel names and thumbnails belong to their creators and are shown via YouTube. HackerTube Watch is an unofficial edition. Data export of 2026-10-31.

Keyboard shortcuts

/
Search
j k
Next / previous video
r
Surprise me
l
Like (video page)
w
Watch later (video page)
?
This help
Esc
Close