AI Post Transformers
How Linear Attention Remembers: Writing and Recalling Facts
This episode examines "How Linear Attention Remembers," a preprint that asks how a single fact is written into, retained in, and read back out of the fixed-size recurrent state that replaces the KV cache. It contrasts Gated Linear Attention with Gated DeltaNet (whose delta rule overwrites old bindings instead of piling on top of them) and with hybrids that keep a few full-attention layers. The…