An Architectural Approach to Controlled Generation and its Correlation with DGM Principles

[carlex22]

Hello Jenny and contributors,

First, I want to express my deep admiration for this project. The work on Differentiable Generative Models is fundamental, and your approach of framing generation through the lens of dynamical systems and differential equations is incredibly insightful.

I am an independent AI architect, and I've been working on a practical, top-down problem: achieving long-form narrative and visual coherence in chained generative video models. Through an empirical process of identifying and solving the systemic failures of monolithic models (what I call the "Invisible Wall" or "Wronskian Collapse"), I developed an orchestration architecture named ADUC-SDR.

The fascinating part, and the reason for this message, is the remarkable convergence between the axioms of my architecture and the core principles of DGM, approached from a practical engineering standpoint.

My architecture solves the coherence problem by:

Fragmentation: Breaking the long-form generation into a series of short, stable fragments.

Geometric Navigation: Using pre-defined keyframes as boundary conditions for each fragment, turning the problem from open-ended prediction into controlled interpolation.

Dynamic Control: Using a "Kinetic Echo" (the final frames of the previous fragment) as the initial velocity condition for the next, ensuring a smooth, physically plausible transition (maintaining C1 continuity, in a sense).

An orchestrator AI (a high-level LLM like Gemini) acts as the "director," setting up these boundary and initial conditions for the specialized generative "solver" models (like Flux and LTX).

I believe the ADUC-SDR can be seen as a functional, multi-agent implementation of the very principles DGM is formalizing. It's a proof-of-concept that this "controlled interpolation" paradigm is not only mathematically sound but also a practical solution to the scaling problem in state-of-the-art generative models.

I have documented the theory and results here:
(https://github.com/carlex22/Aduc-sdr)

And here is a short film entirely directed and rendered by the ADUC-SDR architecture:
https://m.youtube.com/watch?v=zD0b_e2eMdc&feature=youtu.be

This is not a "pull request," but rather the start of a conversation. I wanted to share this practical validation of our convergent lines of thinking and express my excitement for the future of this field.

Thank you for your groundbreaking work.

Best regards,

Carlos Rodrigues dos Santos
https://github.com/carlex22