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This video 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 is inherently composed of words, whereas computers operate with numbers. Word embeddings convert words into numerical representations, while sentence embeddings do the same for sentences, ensuring meaningful associations. Importantly, this process is automated through neural networks that analyze context; words that appear together in similar contexts are positioned closer in numerical space. The outcome is a powerful mechanism for language understanding in AI.
