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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 language, which consists of words that need to be transformed into numbers for processing. Word embeddings map each word to a list of numbers, while sentence embeddings do the same for sentences. This mapping is not done manually; instead, it is executed by a neural network that analyzes context. When words appear together in similar contexts, the model brings their numerical representations closer together, ultimately yielding impressive results in language comprehension.
