This started with Addition Under Pressure, where I gave Claude Code and Codex the same prompt: train the smallest possible transformer that can do 10-digit addition with at least 99% accuracy. Claude Code came back with 6,080 parameters and Codex came back with 1,644. The community has since pushed this dramatically lower.
Quadtree-based image compression formats and level-of-detail systems all work this way. Satellite imagery, terrain rendering, and geographic information systems use quadtree decomposition to serve data at varying resolutions: zoomed out, you see large coarse blocks; zoomed in, you see fine-grained tiles. The same principle extends to three dimensions (octrees) for volume rendering and 3D spatial indexing.
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