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This video tutorial explains word and sentence embeddings, which are essential for large language models. These embeddings translate words and sentences into numerical representations that computers can process. Since language consists of words and computers only understand numbers, word embeddings link each word to a numerical vector, while sentence embeddings do the same for sentences. Importantly, this process is not manually done by humans; instead, it is performed by a neural network that analyzes context. When two words appear in similar contexts, their embeddings are adjusted to be closer together. This results in meaningful numerical representations and impressive outcomes in language understanding.
