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This video tutorial from Cohere AI discusses word and sentence embeddings, essential components of large language models. It explains that language models aim to enable computers to understand and process human language, which consists of words, while computers operate with numerical data. Word embeddings convert words into numerical lists, and sentence embeddings do the same for sentences, forming meaningful representations. This process is not manually conducted by humans but is performed by complex models like neural networks that analyze context. When two words frequently appear together, their numerical representations are adjusted to be closer, leading to effective and insightful results.
