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This video tutorial discusses word and sentence embeddings, which are essential for large language models. The goal of language models is to help computers understand and process language, which is typically comprised of words. Since computers operate using numbers, word embeddings transform words into numerical representations by associating each word with a list of numbers. Similarly, sentence embeddings do the same for sentences. This process is not performed by humans; instead, it is handled by a neural network that analyzes context. Words or sentences that appear together in similar contexts are moved closer together in this numerical space, leading to effective results in understanding language.
