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This video tutorial discusses word and sentence embeddings, fundamental components of large language models. Language models aim to enable computers to understand and process human language, which consists of words, while computers work with numbers. Word embeddings convert words into numerical representations, creating a numerical association for each word. Sentence embeddings serve a similar purpose for sentences. These embeddings are generated by neural networks, not through human intervention; the models analyze word and sentence contexts to position similar words and sentences closer together in numerical space. Ultimately, this process leads to impressive outcomes in natural language processing.