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This video tutorial from Cohere AI discusses word and sentence embeddings, which are essential for large language models. Language models aim to enable computers to understand and process human language, which consists of words, but computers handle numerical data. Word embeddings convert words to numerical representations, while sentence embeddings do the same for sentences. This process is not manually done by humans but rather by complex neural networks that analyze context. When words frequently appear together, the model adjusts their numerical representations to be closer, thereby achieving meaningful associations. The result is a powerful way for computers to understand language.
