21–30 of 127 posts
I still find it amazing how LLM translation capabilities are an almost accidental feature. Yet they still managed to leapfrog decades of research and billions of investment dollars in traditional machine translation.
Didn't "Attention Is All you Need" bill transformers primarily as a translation model?
It looks like the main takeaway is that Claude 3 (Opus) is a lot better at low resource language pairs compared with other LLMs and Google Translate. While this is not as important for the typical english usage of Google Translate it promises way better usage of LLMs as simple translators for languages with fewer speakers or just less data available.
Get 4 years of multicultural students @ universities that focus on language studies. Feed LLM's the translation exercises. Record the sessions with the teachers and professors. Let the students revise. Repeat. Let LLM's learn the nuances and perspectives by following students through their evolution. Build LLMs that want to learn from students and not the other way around. Let the LLMs discuss it all with each other at human speeds and let the crowd moderate the conversations.
Yeah this is old news. When i was in China last year google translate seemed to literally never work (looks of confusion trying to do basic interactions in stores). GPT-4 worked perfectly every time, I think google translate might be another soft abandoned project from google
There are 100+ people working on Google translate and associated stuff (the mobile apps, the serverside stuff, etc). I guess they're all asleep.
Google Translate is just terrible anyway. The other day I was using it to read some difficult Kanji and found that it didn't recognize は as being "wa" in certain places, which is something you learn in like your second or third Japanese lesson. And of course it was useless for the Kanji too.
One of the best yet unplanned features of them imo.
I still find it amazing how LLM translation capabilities are an almost accidental feature. Yet they still managed to leapfrog decades of research and billions of investment dollars in traditional machine translation.
Orders of magnitude more energy necessary though.
I still find it amazing how LLM translation capabilities are an almost accidental feature. Yet they still managed to leapfrog decades of research and billions of investment dollars in traditional machine translation.
Orders of magnitude more energy necessary though.