Clarus FAQ: The Stability Framework Explained
A public‑safe overview of Clarus, K, C64, and the principles behind stability‑based compute.
Clarus is a meta‑structural framework for evaluating long‑horizon stability in decision‑making systems. It measures how trajectories behave under perturbation and whether their structure reconverges or collapses over time — revealing deep coherence that local evaluation cannot see.
K is the core stability signal: a finite‑horizon measure of drift, reconvergence, recovery margins, basin entry, and long‑range coherence. It generalises classical stability concepts without relying on Lyapunov forms, and its computation pathway remains proprietary.
C64 is the conceptual coherence engine underlying Clarus — a stability‑based computational regime distinct from digital switching and statistical deep learning. Clarus is domain‑agnostic, complementary to deep learning, and foundational for safety, creativity, and long‑horizon reasoning.
This FAQ provides the public‑safe conceptual layer: what Clarus is, what problems it solves, how K behaves, what can be shared, and why stability‑based compute represents a third computational regime.
Index
Index
1. What is Clarus?
A meta‑structural framework for long‑horizon stability and trajectory coherence.
2. What problem does it solve?
Recovering globally stable trajectories that local evaluation prunes or misses.
3. What is K (kappa)?
A continuous stability signal measuring drift, reconvergence, recovery margins, basin entry, and long‑horizon coherence.
4. Is K a Lyapunov exponent?
No — it generalises finite‑horizon stability for non‑linear, high‑dimensional decision spaces.
5. How is K computed?
Public description only: “K measures contraction or expansion of perturbations across a trajectory.”
All protocols and algorithms remain proprietary.
6. What is the C64 coherence engine?
The abstract computational regime underlying Clarus — continuous settling, equilibrium convergence, stability evaluation.
7. Is C64 a real processor?
Not yet — fabricable in principle, but no schematics or micro‑dynamics are disclosed.
8. How does Clarus relate to AlphaGo’s Move 37?
Move 37 as a high‑K trajectory: locally irregular, globally coherent.
9. Is Clarus domain‑specific?
No — stability is meta‑structural. Clarus applies across strategic games, biology, modelling, planning, and reasoning.
10. Does Clarus replace deep learning?
No — it complements it. Deep learning provides representation; Clarus provides stability.
11. How does Clarus affect model safety?
K exposes hidden failure basins, drift‑prone regions, and instability invisible to local metrics.
12. Does Clarus reveal creativity?
Yes — creativity emerges from reconvergent structures that appear irregular locally.
13. Is Clarus an algorithm?
No — it is a framework. Multiple computational pathways can implement it.
14. What can be shared publicly?
Concepts, definitions, intuition, high‑level math.
Not shareable: protocols, algorithms, basin logic, C64 micro‑dynamics.
15. What is the future trajectory?
The emergence of a third computational regime: stability‑based compute.
16. What does this mean for labs like DeepMind?
A formal account of superhuman moves, a stability framework, new metrics, and a bridge toward equilibrium‑based hardware.