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@AnneliesGamble

@AnneliesGamble on X

1 capture, most recent first. Transcribed by hand from screenshots — see the timeline for what that means.

@AnneliesGamble

— web clipping, 2,740 words — published 2026-06-16

What's worth reading off a brain

![Image](https://pbs.twimg.com/media/HK9DZhRaEAAZqha?format=jpg&name=large) We can read every weight in a large language model and still can’t really say what the model is doing. Why then would tracing every connection in a brain, a far harder problem, tell us anything we couldn’t get more cheaply somewhere else? It sounds like a reason not to bother mapping brains at all. [@AdamMarblestone](https://x.com/@AdamMarblestone) thinks it’s the […]

Summary by Claude Opus 5

Annelies Gamble's interview with Adam Marblestone (Convergent Research) on why mapping a connectome isn't the futile exercise that reading every weight of an LLM would be. The argument: in an AI system the design lives in code *outside* the weights, while a brain has no outside — architecture, learning signals and reward functions all have to be built physically into cells. So the target is the steering subsystem, not the cortex's learned weights, and cell-type diversity piling up in hypothalamus and brainstem is the evidence. Bears directly on brain_graph_1's load-bearing-wiring thesis.

Full text not reproduced here — kept as What's worth reading off a brain.md in Nathan's clippings archive.