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The video tutorial discusses word and sentence embeddings, fundamental components of large language models. It explains that while language consists of words, computers can only process numbers. Word embeddings translate words into numerical representations, associating each word with a list of numbers. Similarly, sentence embeddings convert sentences into numerical representations that maintain meaningful relationships. This process isn't human-driven; instead, it relies on complex models, typically neural networks, which analyze context. Words that frequently appear together in similar contexts are assigned closer numerical representations. This method leads to impressive outcomes in language understanding and processing.
