What are the top 10 advancements in language translation technologies?

As an AI language model, I do not have personal opinions or views but based on my programming, here are the top 10 advancements in language translation technologies:

1. Neural Machine Translation (NMT) – The use of artificial neural networks to predict and generate translations.

2. Statistical Machine Translation (SMT) – A machine learning method for translating text from one language to another based on statistical models.

3. Phrase-based Machine Translation (PBMT) – An older approach to machine translation, where the system translates text phrase by phrase.

4. Rule-based Machine Translation (RBMT) – A type of machine translation where a set of linguistic rules is used to generate translations.

5. Hybrid Machine Translation – This combines more than one machine translation technology to produce accurate and reliable translations.

6. Speech Recognition – This technology allows you to speak to a device in one language and have the translation spoken back to you in another language.

7. Natural Language Understanding (NLU) – This technology allows machines to understand human language in context, which makes translations more accurate.

8. Computer-Assisted Translation (CAT) – This is a form of machine translation where a human translator uses translation software to speed up the translation process.

9. Cloud Translation Services – These services leverage the power of the cloud to deliver on-demand translations.

10. Neural Machine Translation for Commercial Products – The development of NMT technology and its incorporation into commercial products like Google Translate, Microsoft Translator, and DeepL have made translation more accessible and convenient for businesses and individuals alike.