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This video tutorial from Cohere AI explains word and sentence embeddings, essential components of large language models. Language models aim to enable computers to understand and process human language, which consists of words, while computers inherently process numbers. Word embeddings convert words into numeric vectors, and sentence embeddings do the same for sentences. This conversion is not manually created but performed by a neural network that analyzes context. When two words appear together in similar contexts, their numeric representations are adjusted to be closer together. This process results in highly effective language comprehension capabilities, delivering impressive outcomes.
