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This video tutorial from Cohere AI explains the significance of word and sentence embeddings in large language models. It highlights that while language consists of words, computers only process numbers. Word embeddings convert words into numerical lists, while sentence embeddings do the same for sentences, ensuring the representations are meaningful. This process is automated by a computer, usually a neural network, which examines context. When two words frequently appear together in similar contexts, the model brings their embeddings closer in the numerical space. The end result is a sophisticated understanding of language, leading to impressive outcomes in natural language processing.
