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This video from Cohere AI explains word and sentence embeddings, which are essential for large language models. Language models aim to enable computers to understand and process language, which is inherently made of words, whereas computers only work with numbers. Word embeddings convert words into numerical representations, and sentence embeddings do the same for sentences. This process is automated by computers, typically using complex neural networks. Rather than humans associating words with numbers, the model analyzes context; if two words frequently appear together, their numerical representations are adjusted to be closer. This results in effective and meaningful embeddings for both words and sentences.
