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This video tutorial from Cohere AI discusses word and sentence embeddings, fundamental components of large language models. Language models aim to enable computers to understand and process language, which consists of words, while computers operate with numbers. Word embeddings convert words into numerical representations, associating each word with a list of numbers, while sentence embeddings do the same for sentences. This process is not manually done; rather, a computer, typically using a neural network, analyzes context. When two words appear together in similar contexts, their numerical representations are adjusted to be closer. Ultimately, this method yields impressive results in language understanding.
