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This video tutorial from Cohere AI explains word and sentence embeddings, which are essential for large language models. Language models aim to enable computers to understand human language, made up of words, while computers process numbers. Word embeddings translate words into numerical representations, associating each word with a list of numbers, and sentence embeddings do the same for sentences. This process is executed by computers, typically through complex neural networks, that analyze context. When words or sentences appear together in similar contexts, the model brings their numerical representations closer together, leading to effective and meaningful results in language understanding.
