Translation models are systems designed to convert text from one language to another. They analyze the structure and meaning of sentences in the source language and generate equivalent sentences in the target language. These models can be rule-based, statistical, or neural, with neural models currently being the most advanced due to their ability to learn from vast amounts of data. Neural translation models, such as those used in Google Translate, utilize deep learning techniques to improve accuracy and fluency. They consider the context of words and phrases, allowing for more natural translations. This technology has significantly enhanced communication across different languages and cultures.