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The video tutorial from Cohere AI discusses word and sentence embeddings, which are essential for large language models. Language models aim to enable computers to understand and process human language, which consists of words. Since computers process numbers, word embeddings convert words into numerical representations, and sentence embeddings do the same for sentences. This conversion is accomplished not by humans but through neural networks that analyze context. When two words appear in similar contexts, their numerical representations are adjusted to be closer together. This method leads to effective associations and meaningful results in language processing.
