Google Translate迎来20周年,其发展依赖多次技术飞跃。2006年部署基于万亿词训练的5-gram语言模型,实现质量突破;2016年转向深度神经网络,结合Sequence-to-Sequence模型和TPUs,性能提升30-80倍、延迟降低15-30倍,使大规模服务成为可能;近期集成Gemini模型进一步优化。这些进步均基于前沿研究,每次都为翻译质量带来显著提升。作为Google机器学习工作的初始实验,Google Translate最常见翻译短语如“thank you”体现了其连接全球用户的使命。
Google Translate is turning 20! 🎉. There are 20 fun facts and tips in the thread below.
Translate is one of my favorite Google products because it brings us all closer together!
I've been involved with a couple of things over the years. The first was our deployment of the initial system in 2006, which provided a huge leap forward in quality because it used a much larger 5-gram language model trained on trillions of words of text (indeed, probably the first trillion token language model training in the world: paper has some nice heads showing scaling-law-like quality improvement from scaling to more data/compute).