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This video tutorial by Cohere AI explains word and sentence embeddings, essential components of large language models. Language models aim to help computers understand and process human language, which consists of words, but computers only handle numbers. Word embeddings convert each word into a list of numbers, while sentence embeddings do the same for sentences, ensuring semantic meaning is preserved. This process is not manually assigned by humans; instead, it is achieved by a neural network that learns from context. By analyzing which words and sentences appear together, the model brings similar terms closer in the numerical representation, leading to effective language processing results.
