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The video tutorial from Cohere AI discusses word and sentence embeddings, essential components of large language models. These embeddings enable computers to process language by converting words and sentences into numerical representations, allowing for better understanding and processing of language. The process is not manually done by humans; instead, it relies on complex neural networks that analyze context. By examining how words appear together, the model optimizes their numerical associations, leading to improved results in language tasks. Ultimately, word and sentence embeddings play a critical role in the functioning of language models.
