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The video tutorial discusses word and sentence embeddings, which are essential for large language models. These embeddings transform words into numerical representations, allowing computers to process language. Each word is associated with a list of numbers, and sentences are treated similarly, capturing their meaning in a numerical format. This process is accomplished by a neural network, which examines the context in which words or sentences appear. By doing so, it brings related words and sentences closer together in the numerical space. The tutorial emphasizes that this encoding is performed by computers, not humans. The result is a powerful method for enabling machines to understand language effectively.