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This video tutorial from Cohere AI explains word and sentence embeddings, fundamental components of large language models. Language models aim to enable computers to understand and process human language, which consists of words that computers can only interpret numerically. Word embeddings convert words into lists of numbers, while sentence embeddings do the same for sentences, ensuring contextual relevance. This process is automated by neural networks, which analyze the context in which words or sentences occur. As similar words or sentences appear together, their numeric representations are adjusted to be closer, leading to effective language understanding and impressive results.
