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This video tutorial from Cohere AI discusses word and sentence embeddings, which are essential for large language models. The goal of these models is to enable computers to understand and process language, which they do by converting words into numerical representations. Word embeddings assign a list of numbers to each word, while sentence embeddings do the same for sentences, based on contextual relationships. This process is automated by a neural network rather than manual human association. By analyzing the context in which words appear together, the model brings related words and sentences closer together in numerical space, leading to effective language processing outcomes.