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This video discusses word and sentence embeddings, which are essential for large language models. These embeddings enable computers to understand and process language, as they convert words into numerical representations. Each word is linked to a list of numbers, similar to how sentences are represented. This conversion is not manually done by humans, but rather through complex models like neural networks. The model analyzes context, bringing words and sentences closer together based on their usage in similar contexts. Ultimately, this technique produces impressive results in language comprehension.