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The video tutorial discusses word and sentence embeddings, essential components of large language models. These embeddings transform words and sentences into numerical representations, allowing computers to process language. The process is automated by a neural network, which analyzes context to position words that frequently appear together closer in the numerical space. This method applies the same logic to sentences, resulting in significant and effective representations of language. Ultimately, the tutorial highlights how this approach enables advanced understanding and processing of language by machines.