AI article
Is transformer attention really a Hopfield network?
Community description: Someone in a thread says attention is just a Hopfield network, and the next reply runs with it: so...
Dev.to | Sep 19, 2026 | Edward Izgorodin
Automated excerpt
The update rule of their modern Hopfield network is ξ_new = X softmax(β Xᵀξ). The update becomes softmax(QKᵀ/√d_k)V, which is scaled dot-product attention. A Hopfield state updates by attending over stored patterns and returning their weighted blend.
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