Live Architecture Pareto
Efficiency Pareto
Holographic Distributed Computing (HDC) obeys a fundamentally different scaling regime. Memory capacity scales with dimension D, not parameter count.
Retrieval Speedup
1000×
Via constant-time holographic lookup
Scaling Exponent
0.50α
vs Chinchilla's 0.34 — steeper gains
Sequence Update
O(1)
Constant regardless of sequence length
Memory Footprint vs Sequence Length
Real-time simulation Transformer O(N²) Catalyst O(1)
FLOPs vs Loss @ 10²¹ Compute
Live Results| Architecture | Loss ↓ | FLOPs ↓ | Update |
|---|---|---|---|
| Transformer (Baseline) | 2.10 | 1.0 × 10²¹ | O(N·T²) |
| Mamba-3 (ICLR 2026) | 2.05 | 7.0 × 10²⁰ | O(N·T) |
| CHT (Ours) | 1.98 | 4.0 × 10²⁰ | O(T·D) |
| QHN (Ours) | 1.92 | 2.0 × 10²⁰ | O(D log D) |
| FRN (Ours, K=50) Best | 1.85 | 5.0 × 10¹⁹ | O(D·K) |