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This video tutorial from Cohere AI discusses word and sentence embeddings, which are essential for large language models. The purpose of language models is to enable computers to understand and process human language. Since language consists of words but computers operate using numbers, word embeddings convert words into numerical representations. Similarly, sentence embeddings transform sentences into numerical lists that retain semantic meaning. This process is not manually done by humans; rather, it is performed by complex models like neural networks. These models analyze context, positioning words and sentences closer together based on their usage, ultimately leading to effective numerical representations that yield impressive results.
