US EditionThe Sequence Opinion #667: The Superposition Hypothesis And How it Changed AI Interpretability
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The Sequence Opinion #667: The Superposition Hypothesis And How it Changed AI Interpretability
Mechanistic interpretability—the study of how neural networks internally represent and compute—seeks to illuminate the opaque transformations learned by modern models. At the heart of this pursuit lies a deceptively simple question: what does a neuron mean? Early efforts hoped that neurons, particularly in deeper layers, might correspond to human-interpretable concepts: edges in images… Source
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