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The video tutorial discusses word and sentence embeddings, which are essential for large language models. Language models aim to help computers understand and process human language, which consists of words, while computers deal with numbers. Word embeddings convert words into numerical representations, associating each word with a list of numbers. Similarly, sentence embeddings do this for sentences. This process is not manually done but is performed by a neural network that analyzes context; words appearing together in a similar context are positioned closer in the numerical representation. This method leads to impressive outcomes in language processing.
