Visual representation of how embedding vectors and positional encodings are added to include word meaning and position context.

This image shows the mathematical operation of adding a word’s embedding vector to its corresponding positional encoding. The result is a combined vector that retains both the semantic meaning of the word and its position in the sentence. This operation is foundational in transformer architectures for contextual understanding of sequences.

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