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This video tutorial discusses word and sentence embeddings, essential components of large language models. Language models aim to enable computers to understand and process language, which consists of words, while computers handle numbers. Word embeddings convert words into numerical representations, and sentence embeddings do the same for sentences, ensuring meaningful associations. This process isn't manual; it's achieved through complex neural networks that analyze context. When words or sentences appear together in similar contexts, the model adjusts their numerical representations to reflect their relationship, resulting in impressive outcomes in language understanding and processing.
