Scott investigates the correlation between intelligence and neuron count, exploring various theories before suggesting that more neurons allow for less polysemantic (overlapping) representations of concepts.
Longer summary
Scott explores why intelligence correlates with neuron count across species, humans, and AI models, despite this correlation not being immediately intuitive. He examines various hypotheses about how having more neurons could help with complex pattern-matching tasks like IQ tests. After discussing several possibilities including pattern storage and matching, he settles on polysemanticity as a potential explanation: fewer neurons means each neuron must encode multiple concepts, reducing precision. The post concludes with insights from an expert suggesting that larger neural networks (biological or artificial) can better approximate complex functions and maintain multiple hypotheses simultaneously.
Shorter summary