A dual framework built to be attacked: A background-independent metriplectic field theory and a real-time, zero-training emergent neural runtime.
Sponsor my work and research to unlock private adversarial packages, raw compute logs, and unreleased runtimes.
I build "zero-trust" auditable physics and cognition systems that can be proven wrong with clear instructions on how to do so.
Justin K. Lietz is the founder of Neuroca and leads the Void Dynamics Model (VDM), an independent research program with two tracks.
The first is a physics framework that treats experiments like software releases: predictions are preregistered, time-stamped, and cryptographically signed before any results are collected, with clear pass/fail gates and public contradiction reports when something breaks.
The second is a zero-training cognitive runtime that explores how “conservation vs. dissipation” style dynamics can produce stable, adaptive behavior in sparse, event-driven neural graphs. VDM is built to be reviewable and reproducible, and Justin actively seeks skeptical external reviewers and independent reruns.
- Who is this work best for? Researchers who value reproducibility and clean falsification.
- What can you do with it? Reproduce runs, audit gates, or stress-test the strongest claims.
- What makes it trustworthy? Preregistration, explicit pass/fail thresholds, and failure reports by default.
If you only remember one thing: VDM prioritizes falsifiable, repeatable evidence over narrative and makes the ability to fail quickly an advantage.
Included with the publications are adversarial Jupyter notebooks, SymPy scripts, and rigorous Lean 4 packages explicitly designed to attack each claim directly and mercilessly in each of the associated Zenodo packages for your convenience as a skeptical reviewer.
Attempts to disprove the work of Neuroca, Inc. and our affiliated researchers are highly encouraged. If your critique successfully falsifies any of our findings and we are able to verify your results, we will publish a formal follow-up paper confirming your criticisms, officially conceding the original claims, and giving you full credit for the correction.
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