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This video tutorial from Cohere AI discusses word and sentence embeddings, which are essential components of large language models. Language models aim to enable computers to understand and process human language, which consists of words, while computers can only work with numbers. Word embeddings translate individual words into numerical representations, while sentence embeddings do the same for entire sentences, ensuring that the associations make sense contextually. This process is not manually done by humans; instead, it relies on complex neural network models that analyze context. Words that frequently appear together become numerically closer, leading to highly effective results in language understanding.
