There are 100+ people working on Google translate and associated stuff (the mobile apps, the serverside stuff, etc). I guess they're all asleep.
As a sibling mentioned it's probably something about cost, but given the narrow domain and the performance of smaller models on translation tasks, I'm surprised they're still doing the same old thing in 2024....
GPT-4 is much more natural.
You don’t just “use a gpu.” Software doesnt get better by magically throwing it at a gpu. Moreover you can’t just run any old software on a gpu, it has to be built for it.
Even then, the gpu is just a speed increase, not a magical make better box.
That’s like saying any random text editor would be a better translator if they ran on GPUs.
EDIT: google also literally builds its own acceleration hardware, suggesting that they can’t afford GPUs (which they already own for GCP) for google translate is weird.
Changing Google Translate to use an LLM would become much more expensive for Google.
This is why you see a different cost structure for using "AI". LLM's can't realistically use the CPU for anything serious.
The reason models that use GPU's cost more to run, is that they tend to be A LOT more compute intensive. However, if you run the inference for the same models on CPU, they will be both much more expensive than on GPU's (or on specialized tensor silicon) and also slower.