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The video tutorial discusses word and sentence embeddings, crucial components of large language models. These embeddings help computers understand and process language by converting words into numerical representations. Each word is linked to a list of numbers, and similarly, sentences are associated with numerical lists in a meaningful way. This conversion is achieved not through human intervention, but by a neural network that analyzes context. When two words appear together in the same context, the model adjusts their numerical association to bring them closer. This process yields impressive results in language understanding.
