What is neural machine translation and how does it work?

What is neural machine translation and how does it work?

Neural machine translation (NMT) is a type of AI that uses neural networks to translate text from one language to another. It learns from vast amounts of data to improve accuracy.

How is NMT different from traditional translation methods?

Unlike traditional methods that rely on rule-based systems or phrase-based translation, NMT uses deep learning to understand context and produce more fluent translations.

Can you give me an example of how NMT translates a sentence?

Sure! For instance, if you input 'Hello, how are you?' in English, an NMT system might translate it to 'Hola, ¿cómo estás?' in Spanish, capturing the meaning and context.

What are the advantages of using NMT?

NMT offers several advantages, including improved fluency, better handling of context, and the ability to learn from new data, making it more adaptable.

Are there any limitations to NMT?

Yes, NMT can struggle with idiomatic expressions, low-resource languages, and may require significant computational power.