CHRIS HAY

IDEAS · SYSTEMS · OBJECTS / LONDON · 2026

THE CONNECTED RECORD

Ask
the work.

Find the question. Follow the work. Return to the source.

Search scope
map memoryLARQLFFN graphoperator knowspredictive localitycontext reconstructingMCPHow many episodes?

1 THREAD · 4 SYSTEMS · 5 NOTEBOOK ENTRIES · 2 QUESTIONS · 241 FILMS · 235 CHAPTERS

Search the authored text, its questions and refusals, and the films around it. Drafts keep their status. Chapters identify a topic and a time; only the 2 indexed transcripts provide spoken passages, and their automatic captions are unreviewed. This edition retrieves sources rather than generating an answer. Explore what is connected ↗

4 RESULTS FOR “FFN graph

AUTOMATIC CAPTIONS / 7:26

LLMs Are Databases - So Query Them

geographic neighbors as well. So, let's go a little bit raw here. That was a pretty clean view. Let's look at the feedforward network underneath the hood there. Again, everything we're looking at is the FFN, which is really the knowledge store where all of the data stored. Attention is slightly different. We'll talk about that later. But if I do something like show features, and again we'll limit it to layer 26. Feature two is really

ORIGINAL SOURCE

AUTOMATIC CAPTIONS / 8:44

LLMs Are Databases - So Query Them

stores that within the weight? So, basically, a feature is a single column in the FFN. It's one gate vector that decides when it fires, and one down vector that decides what it outputs. Gate times down. That is basically the edge. So, it's an edge in the graph. And the gate is a direction in the residual stream. I'm not going to go into too much detail of what a residual stream is. I've

ORIGINAL SOURCE