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concepts → Architecture

Architecture

Multilayer perceptron

timeless4 connectionsdraft

stacked neuron layers that can bend a boundary no single perceptron could

Where it sits

The prism has six jobs across and eight layers down. Its primary cell islearn × L1. Hatched cells cannot exist — a GPU does not learn, an institution does not infer.

What must come first — and what it unlocks

Left to right is reading order, derived from the prerequisite_of edges. Nothing here is hand-ordered: the diagram is the graph.

Hidden layerMultilayer perceptronnothing depends on it yet — a leaf in the reading order

Before it: Hidden layer

What kind of thing it is — and what it is made of

It is made of: Hidden layer.

How it goes wrong — and what answers that

known failure modes
Vanishing gradientin a deep stack the learning signal fades to nothing before it reaches the bottom

Where to read it

The chapter that introduces it, and any chapter that uses it again.

19Learning from Blameact 5 · The Connectionist Turn

Where it comes from

paperLearning Representations by Back-Propagating ErrorsDavid Rumelhart, Geoffrey Hinton, Ronald Williams · 1986
bookDeep LearningIan Goodfellow, Yoshua Bengio, Aaron Courville · 2016

Every connection

All 4 edges touching this node, grouped by relation family — the sections above are highlights from this list. Colours match the relation families inthe atlas.

Structure · 1
has as a partHidden layerMechanism
Order · 1
requiresHidden layerMechanism
Lineage · 1
improves onPerceptronMechanism
Failure · 1
fails byVanishing gradientFailureMode

This page is a projection of one node in src/data/concepts.ts. It has no prose file of its own — 230 declared edges produce all 236 of these pages. Edit an edge and both endpoints change.