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Category: Technical Terms
Self-attention helps AI understand how different parts of input relate to each other, even when they're far apart.
When processing "The cat that lived next door was friendly," self-attention connects "cat" with "was friendly" despite the words in between. It calculates how much each word should pay attention to every other word.
This happens for all words simultaneously, making processing much faster than older methods.
Self-attention is the core mechanism in transformer models like GPT and BERT. It's what makes modern language AI so good at understanding context and relationships.
Without self-attention, AI couldn't handle long texts or complex sentence structures effectively.
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