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This video tutorial discusses word and sentence embeddings, which are fundamental to large language models. Since computers process numbers, word embeddings convert words into numerical representations, linking each word to a list of numbers. Similarly, sentence embeddings do this for sentences, ensuring the numerical representation makes semantic sense. This process is not manually done but is achieved through complex neural networks, which analyze context. When two words frequently appear in the same context, their numerical representations are adjusted to be closer together. This context-driven approach results in significant advancements in language processing capabilities.
