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This video from Cohere AI discusses word and sentence embeddings, fundamental components of large language models. Since computers can only process numbers, word embeddings convert words into numerical lists, while sentence embeddings do the same for sentences in a meaningful way. This conversion is not manually created but is achieved through neural networks that analyze context. When two words appear together in the same context, the model adjusts their numeric representations to bring them closer together. This process results in effective and coherent language understanding by the computer, enabling it to analyze language more naturally.
