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This video tutorial from Cohere AI explains word and sentence embeddings, which are crucial for large language models. The goal of language models is to enable computers to understand and process language, transitioning from words to numbers. Word embeddings translate individual words into numerical representations, while sentence embeddings do the same for sentences. This process is not manually curated but performed by complex neural network models that analyze context—bringing related words and sentences closer together in the embedding space. Ultimately, this yields impressive outcomes in natural language processing.
