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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 can only handle numbers. Word embeddings convert words into numerical representations, associating each with a list of numbers. Similarly, sentence embeddings map sentences to corresponding numerical lists meaningfully. This process is not manually carried out by humans; instead, it is performed by complex models, usually neural networks. These models analyze context, bringing related words and sentences closer together, leading to impressive results in language processing.
