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concepts → Architecture

Architecture

Graph neural network

decade4 connections

a network shaped like a mesh — information travels along edges instead of everywhere at once

Where it sits

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

Evidence: benchmark.

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.

nothing comes first — this is a starting pointGraph neural networknothing depends on it yet — a leaf in the reading order

Where to read it

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

64Simulating the Worldact XIV · AI for Science

Where it comes from

paperLearning Skillful Medium-Range Global Weather ForecastingLam et al., Google DeepMind · 2023
paperScaling Deep Learning for Materials DiscoveryMerchant et al., Google DeepMind · 2023

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.

Flow · 4
is used byNeural weather modelModel
is used byGraphCastSystem
is used byMaterials discoveryTask
is used byGNoMESystem

This page is a projection of one node in src/data/concepts.ts. It has no prose file of its own — 521 declared edges produce all 340 of these pages. Edit an edge and both endpoints change.