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The video explains word and sentence embeddings, essential components of large language models. These embeddings convert words and sentences into numerical representations, enabling computers to process language. Since language consists of words and computers handle numbers, word embeddings map each word to a list of numbers, while sentence embeddings do the same for sentences. This process is not manually managed; instead, a neural network analyzes context by positioning words and sentences that frequently occur together closer in numerical space. This context-driven approach yields impressive results in understanding and processing language.
