Modern AI scaling has a hidden physical limit: The Noise Floor. I reverse-engineered the 'Signal Explosion' that occurs in 100+ layer networks, where unconstrained data streams amplify by 3,000x, leading to catastrophic training failure and the '12k-Step Crash.' This forensic audit dissects the Manifold-Constrained Hyper-Connections (mHC) and the Birkhoff Polytope math required to quiet the 'Neural Screech' and stabilize the trillion-parameter frontier
The mathematical cornerstone of the modern world—the Identity Mapping Property—is being quietly eroded by unconstrained architectural complexity. I forensic-audited the "Residual Stream Divergence" (RSD) that occurs when deep models forget their original intent, leading to "Logic Rot" and the liquidation of multimillion-dollar training budgets. This manifesto defines the Manifold-Constrained implementation required to lock neural identity at the silicon level
Widening the residual stream was meant to accelerate intelligence, but unconstrained Hyper-Connections (HC) triggered a 3,000x signal explosion that vaporized millions in compute. I forensic-audited the ByteDance 'HC' Tragedy to identify the '12k-step crash' and define the mHC Standard—the geometric safety cage that prevents signal integrity collapse in the 1,000-layer frontier
Focusing on FLOPs is a lethal strategic error. Infrastructure leaders who measure success by raw operation counts are ignoring the "Memory Wall"—the physical limit where data movement costs liquidate all theoretical compute gains. This forensic audit dissects why unoptimized architectures like unconstrained Hyper-Connections (HC) increase memory access costs by 400% and defines the mHC Standard for I/O efficiency.