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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 stor

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

ImHereToVote 3y ago
Google Translate simply doesn't use a GPU for translation. It's as easy as that. There is a huge jump in cost associated with using the GPU.
- dartos 3y ago
  What are you even talking about? 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.
  - ImHereToVote 3y ago
    No... I mean LLM's use a GPU. Hence why the cost is different. 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.
    - trashtester 3y ago
      You have it backwards. For any given amount of compute needed, GPU's are a lot cheaper than CPU's. But GPU's can't run all the code you can run on a CPU. 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.
- imurray 3y ago
  Google translate uses TPUs, and has done since they swapped to neural models: https://cloud.google.com/blog/products/ai-machine-learning/an-in-depth-look-at-googles-first-tensor-processing-unit-tpu https://cloud.google.com/blog/products/ai-machine-learning/a...
anon1094 3y ago
If you try to translate anything more than a single sentence with Google Translate you get looks of confusion. It's too literal. GPT-4 is much more natural.
- snapcaster 3y ago
  Yeah i used GPT-4 instead and it worked perfectly every single time
londons_explore 3y ago
> 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.
- yau8edq12i 3y ago
  Where did you get this number from?
- snapcaster 3y ago
  Yeah I guess so? I don't work there no explanation for why it's unuseably bad for one of the most popular languages in the world
hnfong 3y ago
It's kind of perplexing how Google Translate has not improved at all (apparently), given that the "transformer" paper ("Attention is all you need") that kickstarted this whole LLM thing was published by Google(rs) intended for translation (between English and French)... 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....

ImHereToVote 3y ago

Google Translate simply doesn't use a GPU for translation. It's as easy as that. There is a huge jump in cost associated with using the GPU.

dartos 3y ago
What are you even talking about? 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.
- ImHereToVote 3y ago
  No... I mean LLM's use a GPU. Hence why the cost is different. 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.
  - trashtester 3y ago
    You have it backwards. For any given amount of compute needed, GPU's are a lot cheaper than CPU's. But GPU's can't run all the code you can run on a CPU. 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.
imurray 3y ago
Google translate uses TPUs, and has done since they swapped to neural models: https://cloud.google.com/blog/products/ai-machine-learning/an-in-depth-look-at-googles-first-tensor-processing-unit-tpu https://cloud.google.com/blog/products/ai-machine-learning/a...

anon1094 3y ago

If you try to translate anything more than a single sentence with Google Translate you get looks of confusion. It's too literal. GPT-4 is much more natural.

snapcaster 3y ago
Yeah i used GPT-4 instead and it worked perfectly every single time

londons_explore 3y ago

> 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.

yau8edq12i 3y ago
Where did you get this number from?
snapcaster 3y ago
Yeah I guess so? I don't work there no explanation for why it's unuseably bad for one of the most popular languages in the world

hnfong 3y ago

It's kind of perplexing how Google Translate has not improved at all (apparently), given that the "transformer" paper ("Attention is all you need") that kickstarted this whole LLM thing was published by Google(rs) intended for translation (between English and French)... 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....