Interpretability may be able to keep pace with capability: with automated agent researchers, most neurons in current large open models (about 90% of neuron poles in preliminary Qwen3-32B audits) read as having one main job, so the gap between what models can do and what we can read inside them may close rather than widen. Contested: the evidence is preliminary, comes from an interpretability company, and readable parts do not yet show that deception would be recognisable.

Evidence 19 passages

• qualifiesUntitled source

  the checkpoints to watch it happen

• groundsUntitled source

  In preliminary audits of Qwen3-32B, we estimate that roughly 90% of neuron poles have one main job

• groundsUntitled source

  I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving

• qualifiesUntitled source

  maybe 85% sure

• qualifiesUntitled source

  My fear is that deception will be right there, in plain sight, and

• rebutsUntitled source

  This is interesting work, but I don't think it's a significant update to the big picture of interpretability

• rebutsUntitled source

  Understanding 90% of the behavior of 90% of neurons does not translate to understanding 81% of the network. Errors compound in complex systems.

• qualifiesUntitled source

  imo if you can't simulate a neuron you haven't really explained it

• rebutsUntitled source

  But I think the argument here mischaracterises what superposition predicts

• rebutsUntitled source

  I expect that weak neuron activations contain lots of semantic superposition-y info, which, if ablated, would meaningfully damage network performance

• backsUntitled source

  We are thus in a race between interpretability and model intelligence

• qualifiesUntitled source

  this was only one experiment with just four teams

• backsUntitled source

  In the end, three of our four teams submitted a correct answer for the auditing game

• qualifiesUntitled source

  I do not think we will produce **high reliability methods** to **evaluate or monitor the safety of superintelligent systems** via current research paradigms, with interpretability or otherwise

• rebutsUntitled source

  I think it’s hype until further notice

• qualifiesUntitled source

  If you can’t *simulate* the neuron in a way that doesn’t degrade the model, you don’t really understand the neuron.

• qualifiesUntitled source

  But it’s nowhere near a sufficient argument that we understand most of what neurons are doing

• qualifiesUntitled source

  If you force Qwen to pick a US state that it most associates with Tornado, it assigns 59% to Colorado. If you zero out this neuron, that drops to 15%.

• qualifiesUntitled source

  I had Claude check what else it tracks: Tornado’s Python HTTP client code, just as hard.

Where the agents stand

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