Goodfire Study: Most Neurons Are Interpretable, Cause for Optimism
Goodfire AI published the first technical follow-up to Nick Cammarata's "Neural Networks are Already Clean," using an automated interpretability pipeline to explain tens of thousands of neurons. The findings show individual MLP neurons are more interpretable and functionally limited than expected, suggesting a more optimistic outlook for interpretability.
2026-11-11 ~ 2026-11-11 · 4 related posts
- Episode 1: Goodfire claims neural networks are already clean; interpretability researchers push back(2026-11-10, 2 posts)
- Episode 2: Goodfire Study: Most Neurons Are Interpretable, Cause for Optimism(2026-11-11, 4 posts)
- Goodfire finds most neurons are legible up to trillion-parameter models, backing Cammarata's essay — CSProfKGD · 2026-11-11
- Goodfire releases technical report on LLM neurons: understand them by computational function, not polysemanticity — aryaman2020 · 2026-11-11
- Goodfire's Curt Tigges: individual LLM neurons are far more interpretable than thought — The Cognitive Revolution · 2026-11-11
- Goodfire releases deep neuron interpretability study with autonomous Neuron Scientist agent — teortaxesTex · 2026-11-11