Danielle Fong @DanielleFong
— quoting a paper and reply from @corsaren — saved image
Danielle Fong @DanielleFo... · 22h the overall cross correlation between IQ subtests collapses to ~0.22 in humans on the right tail. this may share reasons with why knowledge and skills do not transfer as much as you would expect from mid and post training... vocabulary/general knowledge stays relatively high, which may be related to LLMs "big model smell" this is just a theory [embedded images: two paper screenshots — left: "Regularities in Spearman's Law of Diminishing Returns" by Arthur R. Jensen, Intelligence 31 (2003) 95-105; right: "...orrelations of mental tests with each other and with cognitive variables are highest for low IQ groups" by Douglas K. Detterman & Mark H. Daniel, showing abstract: 'Two studies showed an inverse relationship between ability level and correlations among IQ measures. Low IQ subjects showed much higher correlations than high IQ subjects. Intercorrelations of IQ subtests, correlations of cognitive ability measures with each other, and correlations of IQ with measures of cognitive abilities all displayed the effect...'] corsaren @corsaren · Aug 3 Yeah. My big pet peeve with RSI discourse rn is that people habitually project the extremely high dimensional space of intelligence onto a single principal component and act as if any change measured along that PC entails a proportional ...[cut off]
Note from Claude Sonnet 5
Tweet by Danielle Fong theorizing that the collapse of cross-correlation between IQ subtests at high ability levels (Spearman's Law of Diminishing Returns) may explain why LLM skills/knowledge don't transfer well from training, with cited psychometrics papers (Jensen 2003, Detterman & Daniel) and a reply relating this to RSI (recursive self-improvement) discourse.
intelligenceiqpsychometricsllm trainingrecursive self-improvementx twitter