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The video tutorial discusses word and sentence embeddings, fundamental components of large language models. These embeddings help computers understand and process language by converting words and sentences into numerical representations. Each word is associated with a list of numbers, as is each sentence, but this process is automated and performed by neural networks. The model analyzes context; when two words frequently appear together, their numerical representations are positioned closer in the embedding space. This approach allows for meaningful associations between words and sentences, ultimately leading to impressive language processing results.
