How Well Can Large Language Models Translate?

Introduction

In a possible future, it is envisioned that with sufficient data and training, language pairs could be efficiently translated by light language models. These models, when trained on vast amounts of data and scaled to large sizes, could provide a level of generic translation quality for top languages like English, Spanish, Chinese, French, and German. This advancement could potentially extend to the top 20 or even 50 languages over time. Despite the promise of such developments, the primary hurdle lies in the cost associated with deploying these large models. While models like GPT4 may offer enhanced translation capabilities, their high cost may render them impractical for widespread translation use.

Keywords:

Language translation, large language models, data training, generic translation quality, cost efficiency, GPT4

FAQ:

1. What is the potential future outlook for language translation using large language models?
2. What are the primary challenges in deploying large language models for translation purposes?
3. How do cost considerations impact the practicality of utilizing advanced models like GPT4 for translation tasks?
4. Which languages are initially expected to benefit from improvements in translation quality through large language models?