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This video tutorial from Cohere AI explains word and sentence embeddings, which are essential for large language models. Language models aim to enable computers to understand and process language, but since computers only process numbers, word embeddings convert words into numerical representations. Each word is associated with a list of numbers, and similarly, sentence embeddings represent sentences with numbers in a meaningful way. This process is not manually done; instead, it is carried out by a neural network that analyzes context. When two words appear in similar contexts, their numerical representations get closer together, enhancing the model’s performance in understanding language patterns.
