What if intelligence does not need training, backpropagation, or massive stored datasets?

This video introduces the Void Dynamics Model (VDM): a unified research program connecting theoretical physics, Phase Calculus, and a zero-training cognitive runtime that self-structures in real time.

This is the broad entry point:

- what VDM is

- why it claims intelligence may not require training

- how Phase Calculus fits in

- how the Cognitive Runtime works

- where the physics framework enters

- where to find the papers, code, notebooks, and public research archive

VDM is organized into three connected branches:

1. Physics Framework

A derivation-first formal stack for geometry, dynamics, hierarchy, measurement, gauge structure, gravity, action, symmetry, and scale.

2. Phase Calculus

A discrete lifted-state operator calculus that tracks the full carried object before projection into continuous shadows and downstream branches.

3. Cognitive Runtime

A sparse, event-driven, zero-training runtime that learns through real-time self-structuring rather than gradient descent, backpropagation, or pretrained corpora.

This video is an introduction, not the whole burden.

The full burden lives in the papers, validation bundles, code, notebooks, logs, and formal artifacts.

Attack this:

Website

https://www.neuroca.ai/

Active VDM Repo

https://github.com/justinlietz93/Prometheus_VDM.git

Zenodo — VDM

https://zenodo.org/communities/void-dynamics-model/records?q=&l=list&p=1&s=10&sort=newest

Zenodo — Phase Calculus

https://zenodo.org/communities/vdm-phase-calculus/records?q=&l=list&p=1&s=10&sort=newest

Zenodo — Cognitive Runtime

https://zenodo.org/communities/vdm-cognitive-runtime/records?q=&l=list&p=1&s=10&sort=newest

Academia.edu

https://independent.academia.edu/justinlietz

Contact

[email protected]