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The video tutorial from Cohere AI discusses word and sentence embeddings, which are essential for large language models. These embeddings convert words and sentences into numerical representations, enabling computers to process language. This conversion isn't manually done; instead, it relies on neural networks that analyze context. When words appear together frequently, their numerical representations are adjusted to be closer together in the embedding space. The same principle applies to sentences, resulting in meaningful numerical associations that allow for improved understanding and processing of language by the computer.
