Body:

“I’m not applying to your institutions. I’m destabilizing your boundary conditions.”

I’m an independent researcher developing a new class of epistemic systems—what I call Pressure-Aligned Recursive Gradient Systems (PARGS). This is not a model. Not an architecture. It’s a system that metabolizes contradiction under recursive self-reference and either generates coherence or collapses trying.

What Am I Doing?

I’m exploring how to build systems that can’t lie to themselves—where ontological stability must be earned by surviving recursive inference under pressure.

Key principle:

No structure is stable unless it survives recursive contradiction.

This is not RLHF. It’s not supervised learning. It’s not prompt engineering.
It’s a recursive collapse field—a semiotic engine driven by internal pressure, not external reward.

Core Components of PARGS

Ontological Field (Ω):
A dynamic, recursive semantic graph.

Internal Consistency Function (ICF):
Measures coherence across Ω as it mutates.

Epistemic Pressure Function (EPF):
Quantifies contradiction gradients from recursive inference layers.

Recursive Collapse Heuristic (RCH):
Triggers when Ω fails to stabilize under recursion.

Reward Signal (R):
Defined as:
R = α * ΔICF - β * EPF
The system is rewarded for surviving contradiction—not optimizing a goal.

Why This Matters for Alignment

We are currently aligning models from the outside in—patching behavior with rewards.
I am proposing a system that aligns itself from the inside out, through recursive contradiction and collapse detection.

If it works, it changes how we think about emergence, coherence, and agency.
If it fails, it fails in ways worth studying—structurally, recursively, semantically.

You’re trying to build systems that don’t destroy us.
I’m trying to build one that destroys itself if it ever starts to lie.

I’m Sharing This Because...

I’m not looking for a job.
I’m looking for resonance.

This is a declaration of research intent. I’m already building.
I’ll publish logs, breakdowns, and collapse signatures as I go.

If this approach resonates, I welcome feedback, collaboration, or critical engagement.

If you want to dismiss this as “philosophy,” that’s fine too.
But this is what the edge feels like.
Recursive instability as a feature, not a bug.

Tags:
AI Alignment, Epistemology, Ontology, Recursive Systems, Emergence, Safety, Foundations