Combines maximum math density + unified compression architecture +
hippocampus engram consolidation (Tomé 2024) + tabula plena insight
(Live Science 2024: hippocampus starts full slate, prunes to sparse).
Key insight: hippocampus starts tabula plena (densely wired, hyperconnected)
and prunes to sparse structured during maturation. Compression does the
same: start with maximum math density (full Unicode 1,114,112 codepoints +
custom glyphs + omniversal chirality) and prune via FAMM delays,
OAC gates, radius-ratio quantization, gain tests to minimal representation.
FAMM pruning model: uniform delays (young hippocampus) → preshaped delays
based on eigenvalue spectra → sparse structured delays (mature hippocampus).
10 compression gain sources: tabula plena pruning (90-99% of Unicode unused),
FAMM delay pruning (10-20% context efficiency), OAC gate pruning (2-5%
bloat avoidance), radius-ratio quantization, gain test pruning, shear matrix
pruning (15-30% structured regions), topological skeleton (50-150MB vs 1GB),
math notation density, repeat encoding, erans entropy.
Estimated 15-25% reduction vs current Hutter best + navigable capability.
14 encoding/decode stages. Archive format HFC1 with 16 sections.
13 keeper phrases. Core: Don't start blank. Start full, then prune.
