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This video tutorial from Cohere AI explains word and sentence embeddings, crucial components of large language models. It highlights that language models aim to enable computers to understand language, which is inherently composed of words, while computers process numbers. Word embeddings convert words into numerical representations, associating each word with a list of numbers. Similarly, sentence embeddings do the same for sentences. This conversion is not performed manually; instead, it's achieved through complex neural networks that analyze context. When words or sentences share similar contexts, the model brings their numerical representations closer together, leading to compelling outcomes in language processing.
