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The video tutorial from Cohere AI discusses word and sentence embeddings, which are essential for large language models. It explains that the goal of language models is to enable computers to understand language, which primarily consists of words, while computers can only process numbers. Word embeddings translate words into numerical representations, and similarly, sentence embeddings do the same for sentences, ensuring meaningful associations. This process is automated by a neural network that analyzes the context in which words or sentences appear; the more they occur together in similar contexts, the closer their numerical representations become. Ultimately, this approach yields impressive results in language processing.
