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This video tutorial from Cohere AI focuses on word and sentence embeddings, which are essential for large language models. These embeddings allow computers to understand language by converting words and sentences into numerical representations, enabling processing. Rather than human-assigned values, this conversion is performed by complex neural network models that analyze context. When two words appear in similar contexts, the model moves their numerical representations closer together, fostering meaningful associations. As a result, both word and sentence embeddings yield impressive outputs, enhancing language processing capabilities in artificial intelligence.
