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The video tutorial from Cohere AI explains the concepts of word and sentence embeddings, fundamental components of large language models. It highlights that language models aim to enable computers to understand and process human language, which is inherently based on words, while computers can only work with numbers. To bridge this gap, word embeddings transform words into numerical representations, and sentence embeddings do the same for sentences, ensuring the numerical associations reflect contextual similarities. This process is automated and typically performed by neural networks rather than humans, as the models analyze the context in which words and sentences appear to adjust their representations accordingly, leading to impressive outcomes.