Research · Updated 17 Oct, 12:31 am IST

Post explains how transformer layers act as memory stores

Why it matters for readers: It shows why models sometimes forget details and how researchers think about improving recall.

The post models linear layers, MLPs and self-attention as memory stores that differ in recall capacity.1
It introduces the interference-to-signal ratio as a key quantity that limits how many memories a store can hold.1
From this intuition the author derives heuristics for memory capacity and how different layers improve recall.1
The post uses a real-world example — an assistant named Astra recalling board game rules — to show practical recall behavior.1

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