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This video tutorial discusses word and sentence embeddings, which are fundamental to large language models. Language models aim to enable computers to understand and process language, but since language consists of words and computers handle numbers, embeddings serve as a bridge. Word embeddings map each word to a numerical list, while sentence embeddings do the same for sentences. This mapping is performed by neural networks that analyze the context of words and sentences, positioning similar ones closer together in the numerical space. Ultimately, this approach yields impressive results in language processing.
