Attention in transformers, visually explained | Chapter 6, Deep Learning

3Blue1Brown's visual explanation of the attention mechanism in transformer neural networks. This video covers query, key, and value matrices, how attention scores are computed, multi-head attention, and the intuition behind why attention enables transformers to model long-range dependencies. It is the clearest visual explanation of the core mechanism underlying every major language model. AICI recommends it to anyone who encounters "attention" in AI documentation and wants to understand what it actually means — not as metaphor, but as computation.

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