If you don’t know the language then you shouldn’t be involved in the translation at all… The current process requires both the translators and the proof-readers to know the language.

As long as you can verify it is an accurate translation

Unless the process has changed in the last decade, article translations are a multi-step process, which includes translators and proof-readers. It’s easier to get volunteer proof-readers than volunteer translators. Adding AI for the translation step, but keeping the proof-reading step should be a great help.

But you could probably also have used Google translate and then just fine tune the output yourself. Anyone could have done that at any point in the last 10 years.

Have you ever used Google translate? Putting an entire Wikipedia article through it and then “fine tuning” it would be more work than translating it from scratch. Absolutely no comparison between Google translate and AI translations.

Deep learning did not shift any paradigm. It’s just more advanced programming. But gen AI is not intelligence. It’s just really well trained ML. ChatGPT can generate text that looks true and relevant. And that’s its goal. It doesn’t have to be true or relevant, it just has to look convincing. And it does. But there’s no form of intelligence at play there. It’s just advanced ML models taking an input and guessing the most likely output.

Here’s another interesting article about this debate: https://ourworldindata.org/ai-timelines

What we have today does not exhibit even the faintest signs of actual intelligence. Gen AI models don’t actually understand the output they are providing, that’s why they so often produce self-contradictory results. And the algorithms will continue to be fine-tuned to produce fewer such mistakes, but that won’t change the core of what gen AI really is. You can’t teach ChatGPT how to play chess or a new language or music. The same model can be trained to do one of those tasks instead of chatting, but that’s not how intelligence works.

See the sources above and many more. We don’t need one or two breakthroughs, we need a complete paradigm shift. We don’t even know where to start with for AGI. There’s a bunch of research, but nothing really came out of it yet. Weak AI has made impressive bounds in the past few years, but the only connection between weak and strong AI is the name. Weak AI will not become strong AI as it continues to evolve. The two are completely separate avenues of research. Weak AI is still advanced algorithms. You can’t get AGI with just code. We’ll need a completely new type of hardware for it.

https://www.lifewire.com/strong-ai-vs-weak-ai-7508012

Strong AI, also called artificial general intelligence (AGI), possesses the full range of human capabilities, including talking, reasoning, and emoting. So far, strong AI examples exist in sci-fi movies

Weak AI is easily identified by its limitations, but strong AI remains theoretical since it should have few (if any) limitations.

https://en.m.wikipedia.org/wiki/Artificial_general_intelligence

As of 2023, complete forms of AGI remain speculative.

Boucher, Philip (March 2019). How artificial intelligence works

Today’s AI is powerful and useful, but remains far from speculated AGI or ASI.

https://www.itu.int/en/journal/001/Documents/itu2018-9.pdf

AGI represents a level of power that remains firmly in the realm of speculative fiction as on date

That would be a danger if real AI existed. We are very far away from that and what is being called “AI” today (which is advanced ML) is not the path to actual AI. So don’t worry, we’re not heading for the singularity.