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The video discusses word and sentence embeddings, essential for large language models, which enable computers to understand and process language. Since language consists of words, and computers only process numbers, word embeddings convert words into numerical representations, associating each word with a list of numbers. Similarly, sentence embeddings provide numerical representations for sentences in a meaningful way. This process is not manual; rather, it is performed by a neural network that analyzes context. When two words appear together in similar contexts, the model moves their numerical representations closer together. This context-based approach leads to impressive outcomes in language processing.
