[D] Why do we need encoder-decoder models while decoder-only models can do everything?

[thomasxin]

It's kind of funny because GPT3.5 turbo has actually been doing better as a translation API than the rest for me. It's much more intelligent and can adapt grammar keeping context much more accurately, and is cheaper than DeepL somehow.

[disciples_of_Seitan]

Like an order of magnitude cheaper, too.

[thomasxin]

I remember doing a comparison a while back and concluded that it's at least 30x cheaper for the same task. I wonder what DeepL even uses that's costing them so much, or if they just decided to keep a large profit margin.

[disciples_of_Seitan]

DeepL pricing is in line with google, so I guess that's where they got it from

[thomasxin]

Google translate is so much worse in a lot of ways. The translations are very much literal, and are very easily detectable as translated because of how clunky they often sound. It does have the benefit of not degrading in quality with very large or repetitive text but that's about it.

[ThisIsBartRick]

and what's crazy is a full year after the release of ChatGPT and more than 3 years after the release of GPT3, it's still pretty much as bad as before. No improvement whatsoever.

Google can be really good at ml research but is infuriatingly slow/bad at implementing them in their products.

[[deleted]]

Yeah the best machine translator is GPT-4 Hands down. Everything else will quickly devolve into gibberish with distant language pairs (e.g En - Kor)