Mechanistic interpretability breakthrough: most neurons understood in trillion-parameter models
dair_ai · x · 2026-10-16
dair-ai amplifies a new interpretability writeup claiming we "can now understand most neurons in models up to trillions of parameters," with the authors arguing the outlook for mechanistic interpretability "may be far better than we thought." The accompanying visualization maps the ConvNeXt residual stream across layers, tracing how image locations for animal faces, red patches, text/signs, grass, and sky cluster or diverge from the first layer to the last stage — a concrete look at how internal representations organize.
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