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This video tutorial by Cohere AI discusses word and sentence embeddings, essential components of large language models. The primary goal of language models is to enable computers to understand and process language, which involves converting words into numerical representations. Word embeddings associate each word with a list of numbers, while sentence embeddings do the same for sentences in a meaningful way. This process is automated and not reliant on human input; instead, it employs complex neural network models that utilize context. Words that frequently appear together in the same context are positioned closer together in the embedding space, resulting in impressive and insightful outcomes.
