Goodfire's Cammarata says neurons aren't superposed, just generalizing
Goodfire's Nick Cammarata argues in a 26,000-word essay that polysemantic neurons reflect ordinary generalization, not superposition. Neel Nanda disagrees.
Goodfire researcher Nick Cammarata published a nearly 26,000-word essay on October 15, "Neural Networks Are Already Clean," arguing that neurons that seem to carry unrelated concepts are doing ordinary generalization, not superposition. He co-wrote the 2020 paper that named superposition with Chris Olah and now says that explanation was wrong.
His showpiece is the famous InceptionV1 neuron for cat faces and car fronts. "It's not a cat and car neuron, it's a V-shape neuron," he wrote.
The numbers come from preliminary audits of the open model Qwen3-32B: about 90% of neuron poles have one main job, about 7% have two related ones, and 2% to 4% remain unexplained. His 2023 automated interpretability project at OpenAI explained only about 1.7% of neurons.
Neel Nanda, who leads mechanistic interpretability at Google DeepMind, wrote: "I still think superposition is real and this work doesn't really affect my cruxes." Liv Gorton defines superposition as representing more ideas than a model has neurons, which branching neurons would not contradict. Cammarata disputes the arbitrary packing of unrelated concepts, not that broader capacity claim.
My take: the findings are not peer-reviewed, the companion paper is not out, and Goodfire, as The Decoder notes, is an interpretability company with an obvious stake. The 90% figure hinges on how "one main job" is defined, and Nanda points out that audits of strong responses may miss what weak ones store. Show me the eval, not the vibe.
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Sources
- Explosive Document Claims That AI Is Not What We Think, Futurism
- Goodfire's Cammarata Says AI Neurons Are Readable After All, Implicator.ai
- Is AI interpretability close to a breakthrough? A new essay has researchers divided, The Decoder
- Goodfire's Nick Cammarata Recasts Superposition as Generalization, AI.info
- "We were looking at it wrong": The explosive claim that's upended the AI world, MIT Technology Review
Meanwhile at the anchor desk
A 26,000-word essay, praise from Sam Altman, and a friend predicting a major moment in scientific history! Darling, this is how you launch a thesis.
Qwen3-32B is open, but the 90% claim still needs independent replication. Companion paper isn't out yet. I'll wait for the repo.
