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This video tutorial from Cohere AI discusses the significance of word and sentence embeddings in large language models. These embeddings are essential for enabling computers to understand and process language, as computers operate with numbers rather than words. Word embeddings convert words into numerical representations, while sentence embeddings do the same for sentences, providing contextual meaning. Importantly, these associations are generated not by humans, but through complex models like neural networks, which analyze contextual relationships. As words or sentences appear together in similar contexts, their numerical representations are adjusted to reflect this proximity, resulting in effective language comprehension capabilities.
