Why Do Neural Networks Contain Legible Neurons? A Theory Finally Arrives
anshulkundaje · x · 2026-10-16
David Klindt opened a thread on a fundamental question: how did we get so lucky as to find meaningful neurons inside neural networks? A theory now exists.
Context from Nick Cammarata: interpretability may be the most important scientific problem today — alignment is unsolvable without knowing what we're building. Early mechanistic interpretability work at OpenAI left him pessimistic, as networks looked like arbitrary tangled knots; OpenAI's first large-scale automated interpretability project found only 2% of neurons legible.
With modern agentic tools the picture flips: in models up to trillions of parameters, the vast majority of neurons are legible and their circuits tractable — evidence that networks are not fundamentally inscrutable.
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