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This video from Cohere AI explains word and sentence embeddings, which are essential for large language models. Language models aim to help computers understand and process language, but since computers can only handle numbers, word embeddings translate words into numerical vectors. Similarly, sentence embeddings convert sentences into numerical forms. This process is not manually done but is achieved through complex models like neural networks, which analyze context. When two words frequently appear together in similar contexts, their numeric representations are adjusted to be closer together, resulting in meaningful associations. This leads to impressive outcomes in language processing.
