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The video discusses word and sentence embeddings, which are crucial for large language models. Language models aim to help computers understand and process language, but since computers work with numbers, word embeddings convert words into numerical representations. Each word is associated with a list of numbers, and similarly, sentence embeddings represent sentences as lists of numbers in a meaningful way. This mapping is not done manually; rather, it is accomplished by complex neural networks that analyze context. When two words frequently appear together, their embeddings get closer in numerical space, leading to effective semantic representations. The process results in significant advancements in language understanding.
