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The video tutorial explains word and sentence embeddings, which are essential for large language models. These embeddings convert words and sentences into numerical representations, allowing computers to process language. While humans could associate meanings with numbers, this is accomplished by neural networks that analyze context. When words frequently appear together, their numerical representations are adjusted to be closer in value. This process applies to sentences as well, resulting in meaningful embeddings that enable computers to understand and process language effectively.
