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// bridge system
useState()→Model Weights·Event Propagation→Forward Pass·Array.map()→Tensor Operation·React diff→Loss Function L = Σ(y−ŷ)²·transition-duration→Learning Rate η·CSS clamp()→σ(x) Activation·Re-render cycle→Training Epoch·Event bubbling→Backpropagation ∂L/∂w·useCallback→Gradient Caching·Promise.all()→Batch Inference·Redux store→Weight Matrix·DevTools profiler→Loss Landscape·useState()→Model Weights·Event Propagation→Forward Pass·Array.map()→Tensor Operation·React diff→Loss Function L = Σ(y−ŷ)²·transition-duration→Learning Rate η·CSS clamp()→σ(x) Activation·Re-render cycle→Training Epoch·Event bubbling→Backpropagation ∂L/∂w·useCallback→Gradient Caching·Promise.all()→Batch Inference·Redux store→Weight Matrix·DevTools profiler→Loss Landscape·
Bridges/Backbone networks
Structural Bridge

Shared component libraries
=
Backbone networks

Neon Protocol // Bridge #32
The connection

Both provide reusable feature extraction that multiple downstream tasks build on. A shared UI library serves multiple apps; a backbone CNN serves multiple vision tasks.

Why "Structural"?

Structural bridges share the same architecture or pattern, even though the domains differ.

Frontend concept
Shared component libraries
View in glossary
ML concept
Backbone networks
View in glossary
Related bridges in Neon Protocol
canvas.getImageData()=Image tensors
Identity
CSS blur() / SVG filters=Convolution kernels
Structural
getBoundingClientRect()=Bounding boxes
Identity
debounce()=Non-Max Suppression
Structural
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