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This video tutorial from Cohere AI explains word and sentence embeddings, fundamental components of large language models. Language models aim to help computers understand and process human language, which consists of words. Since computers only handle numbers, word embeddings convert words into numerical representations, associating each word with a list of numbers. Similarly, sentence embeddings achieve this for entire sentences. The process is automated, typically using a neural network that analyzes contextual relationships; words that appear together in similar contexts are represented with closer numerical values. This context-driven approach leads to effective results in language processing.
