Word and sentence embeddings are the bread and butter of LLMs. They are the basic building block of most language models, since they translate human speak (words) into computer speak (numbers) in a way that captures many relations between words, semantics, and nuances of the language, into equations regarding the corresponding numbers.
Sentence embeddings can be extended to language embeddings, in which the numbers attached to each sentence are language-agnostic. These models are very useful for translation and for searching and understanding text in different languages.