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803b96754a
Claude Code's demo proves the conservation law with measured bytes: - k=0: total=102,252 (model=440, tape=101,812) - k=1: total=85,534 (sweet spot) - k=3: total=557,169 (model=501,392 ate the savings) - xz: total=35,492 (tiny amortized decoder) As prediction improves (k↑), tape shrinks but model explodes. The sum is conserved. The weird machine moves bits between columns, never reduces the total. One real win: frozen model + arithmetic coder = sub-xz on tape alone (amortized). But the model is on the invoice. Ship it for Hutter = lose. This permanently gates: - 'Turing-complete weird machine beats unpredictability' = FALSE - '583x GW compression' = zero-noise artifact (1.5x at realistic SNR) - '16D braid adds value over LPC' = FALSE (ties at 30dB, loses at 20dB) - 'Generation beats prediction' = FALSE (generation = prediction, sum conserved) The honest map: every approach tried loses to established coders (xz on text, LPC on signals). The polynomial stays a GCCL receipt. The pipeline's real value is formal verification + anti-smuggle framework, not compression ratio. |
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| .. | ||
| adversarial_review | ||
| build_logs | ||
| concept_map | ||
| diagrams | ||
| first_principles | ||
| fundamental_math | ||
| refactor | ||
| research | ||
| reviews | ||
| ARCHITECTURE.md | ||
| CLAIMS_STATUS.md | ||
| cmix_epigenetic_analysis.md | ||
| FIX_DESIGN.md | ||
| generate_porting_candidates.py | ||
| generate_project_map.py | ||
| generate_research_stack_usage_map.py | ||
| GLOSSARY.md | ||
| GLOSSARY_ALLOWLIST.md | ||
| GOORMAGHTIGH_SPECTRAL.md | ||
| gw_compression_honest_result.md | ||
| PROJECT_MAP.json | ||
| PROJECT_MAP.md | ||
| research_stack_usage_graph_thumb.png | ||
| review_findings.md | ||
| SPECTRAL_CODEBOOK_ANALYSIS.md | ||
| SPECTRAL_CODEBOOK_GENERATOR.md | ||
| THEOREM_STACK.md | ||
| weird_machine_conservation_law.md | ||
