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In this video tutorial, the topic of word and sentence embeddings, essential for large language models, is discussed. Language models aim to help computers understand and process language, which is inherently composed of words, while computers process numerical data. Word embeddings convert words into numerical representations, and sentence embeddings do the same for sentences. This process isn't manually performed; it relies on computers, typically neural networks, to understand context. When two words or sentences appear in a similar context, their numerical representations are adjusted to reflect that closeness. This leads to effective language understanding and processing results.
