Idea Space as Rugged Landscape

Innovation can be modeled as exploration of a multi-dimensional solution space where each position has an uncertain value, like searching for gold mines across terrain with unknown deposits.

The landscape is “rugged” because it has multiple local optima. Gradient-following (iteratively improving a single idea) gets stuck at local peaks. Broad exploration across distant regions increases the probability of finding the global maximum.

This framing explains why diversity matters structurally, not just aesthetically. In a rugged landscape, the expected value of your best idea increases with the variance of your idea pool. Clustering around one region guarantees mediocrity even if that region is reasonably good.

The metaphor also clarifies the AI limitation: models trained on human outputs learn the statistical center of idea distributions. They generate competent ideas from well-explored regions but struggle to reach the unexplored edges where breakthrough value lives.

Related: 05-atom—ai-diversity-deficit, 05-atom—cot-diversity-effect