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This video tutorial from Cohere AI explains the concepts of word and sentence embeddings, which are fundamental to large language models. Language models aim to enable computers to understand and process language, which consists of words, by converting these words into numerical representations. Word embeddings associate each word with a list of numbers, while sentence embeddings do the same for sentences. This conversion is performed by a computer, typically using a neural network model, rather than human interpretation. The model analyzes the context in which words and sentences appear, bringing similar items closer together numerically, resulting in effective representations that yield impressive outcomes.
