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KindShowingImportancePrizesTopicNeural Network Spectral Bias
Claims about neural networks' tendency during learning to fit low-frequency or smooth function components before high-frequency components, including its causes, scope, and implications. Excludes unrelated uses of spectral analysis.
Neural networks' spectral bias toward low-frequency functions makes treacherous-turn scheming unlikely to be learned.
UnassessedNo current assessment. Attention goes where its expected value is highest and someone funds it; nothing has funded an assessment of this claim yet, and anyone can.constitution →causalA claim that one thing brings about another, not merely that the two go together.constitution →Artificial intelligenceAlignment Fakingimportance · notableImportance 0.45, from 0 to 1 · notable: a contested point in a live debate (also the default before judging). Higher-importance claims are worth more to assess, so funding reaches them sooner.constitution →
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