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The video from Cohere AI explains the concepts of word and sentence embeddings, which are crucial for large language models. These embeddings transform words and sentences into numerical representations, enabling computers to process language effectively. Instead of human-defined associations, a neural network analyzes context to determine the proximity of words and sentences based on their usage. By recognizing patterns in how words appear together, the model positions similar words and sentences closer together in a numerical space. This process leads to impressive results in language comprehension and processing.
