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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 help computers understand and process language, which consists of words, while computers can only handle numbers. To bridge this gap, word embeddings convert words into numerical representations, while sentence embeddings do the same for sentences. Importantly, this process is not performed by humans but by a computer, typically using a neural network model. The model analyzes the context in which words and sentences appear together, gradually bringing similar terms and sentences closer in their numerical representation, resulting in significant and insightful outcomes.
