This record documents the authors' original hypothesis and first exploratory run exactly as performed, together with the raw output data and the simulation source code. It does not claim a resolution of the black hole information paradox. Taking two ideas from the authors' WERR decision engine, the treatment of error a...
This record documents the authors' original hypothesis and first exploratory run exactly as performed, together with the raw output data and the simulation source code. It does not claim a resolution of the black hole information paradox. Taking two ideas from the authors' WERR decision engine, the treatment of error a...
Abstract: Modern automated computing systems increasingly deploy Large Language Models (LLMs) to resolve runtime operational triage, incurring prohibitive latency (>100–500 ms), severe memory allocation (>4–8 GB VRAM), and high thermodynamic dissipation. Extending the foundational theory of Mandelbrot Fractal Neural Sy...
Abstract: Modern automated computing systems increasingly deploy Large Language Models (LLMs) to resolve runtime operational triage, incurring prohibitive latency (>100–500 ms), severe memory allocation (>4–8 GB VRAM), and high thermodynamic dissipation. Extending the foundational theory of Mandelbrot Fractal Neural Sy...
Mandelbrot Fractal Neural Synthesis: Zero-Storage Procedural Weight Derivation and Non-Linear Decision Boundaries What's New in Version 2.0 (Major Revision & Q1 Readiness) Systems Trade-Off Framing: Reframed the central research question from raw parameter fitting to fundamental systems architecture: trading determinis...
Mandelbrot Fractal Neural Synthesis: Zero-Storage Procedural Weight Derivation and Non-Linear Decision Boundaries What's New in Version 2.0 (Major Revision & Q1 Readiness) Systems Trade-Off Framing: Reframed the central research question from raw parameter fitting to fundamental systems architecture: trading determinis...
