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This video tutorial from Cohere AI discusses word and sentence embeddings, which are essential components of large language models. Language models aim to enable computers to understand and process human language, which is inherently composed of words, while computers operate using 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 process is not manually curated but is performed by complex neural networks that analyze contextual relationships. When words or sentences appear together in similar contexts, the model learns to bring their numerical representations closer, ultimately producing effective results in language understanding.
