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The video discusses word and sentence embeddings, which are fundamental to large language models. These embeddings convert words and sentences into numerical representations, enabling computers to process language. While humans do not manually associate words with numbers, a neural network analyzes the context of words appearing together to create these embeddings. The model adjusts the representations based on context, bringing similar words and sentences closer together in the numerical space. This process leads to effective language understanding and processing by computers, resulting in impressive outcomes in language tasks.
