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We just completed a major architectural upgrade to MEGAMIND and deployed it live at https://thataiguy.org/talk.html
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This system does not rely on token prediction alone. It performs dynamical reasoning using phase-coupled dynamics and energy minimization, then applies an Evidence Sufficiency Score (ESS) gate before answering.
Core mechanics:
Energy descent is enforced via Armijo line search on the true post-projection state:
xₜ₊₁ = xₜ − η ∇H(xₜ)
Accepted steps must decrease the Hamiltonian:
H = − Σ Jᵢⱼ cos(θᵢ − θⱼ)
This guarantees monotonic energy descent or fallback.
On top of that, we implemented an epistemic gate:
ESS = σ(α(s_max − τ₁) + β(s̄ − τ₂) + γ(cov − τ₃) − δ(contra − τ₄))
ESS alone was not sufficient. High similarity saturation (s_max ≈ 1.0) sometimes produced confident answers even when phase coherence Φ was low.
We corrected this by introducing an adjusted score:
ESS* = ESS × (a + (1−a)·coh₊) × (b + (1−b)·Φ)
where coherence is normalized from [−1,1] to [0,1].
Final decisions now require both evidence sufficiency and dynamical convergence:
Confident → ESS* ≥ 0.70
Hedged → 0.40 ≤ ESS* < 0.70
Abstain → ESS* < 0.40
We also added:
Saturation protection for s_max artifacts
Deterministic seeded retrieval
Bounded-state projection
Early stop on gradient norm and descent rate
Warm-start cache with norm safety clamp
Deployment status:
Port 9999 (full mode)
11.2M neurons
107k knowledge chunks loaded
ESS + Φ + Energy displayed per response
UI updated to call /think directly (no chat proxy)
The result is a reasoning system that:
Refuses to hallucinate when evidence is missing
Falls back safely if descent invariants fail
Differentiates confident vs hedged vs abstain
Exposes internal coherence metrics in real time
You can test it live at:
https://thataiguy.org/talk.html
This work moves beyond pattern completion toward constrained dynamical reasoning with explicit epistemic control.
.
This system does not rely on token prediction alone. It performs dynamical reasoning using phase-coupled dynamics and energy minimization, then applies an Evidence Sufficiency Score (ESS) gate before answering.
Core mechanics:
Energy descent is enforced via Armijo line search on the true post-projection state:
xₜ₊₁ = xₜ − η ∇H(xₜ)
Accepted steps must decrease the Hamiltonian:
H = − Σ Jᵢⱼ cos(θᵢ − θⱼ)
This guarantees monotonic energy descent or fallback.
On top of that, we implemented an epistemic gate:
ESS = σ(α(s_max − τ₁) + β(s̄ − τ₂) + γ(cov − τ₃) − δ(contra − τ₄))
ESS alone was not sufficient. High similarity saturation (s_max ≈ 1.0) sometimes produced confident answers even when phase coherence Φ was low.
We corrected this by introducing an adjusted score:
ESS* = ESS × (a + (1−a)·coh₊) × (b + (1−b)·Φ)
where coherence is normalized from [−1,1] to [0,1].
Final decisions now require both evidence sufficiency and dynamical convergence:
Confident → ESS* ≥ 0.70
Hedged → 0.40 ≤ ESS* < 0.70
Abstain → ESS* < 0.40
We also added:
Saturation protection for s_max artifacts
Deterministic seeded retrieval
Bounded-state projection
Early stop on gradient norm and descent rate
Warm-start cache with norm safety clamp
Deployment status:
Port 9999 (full mode)
11.2M neurons
107k knowledge chunks loaded
ESS + Φ + Energy displayed per response
UI updated to call /think directly (no chat proxy)
The result is a reasoning system that:
Refuses to hallucinate when evidence is missing
Falls back safely if descent invariants fail
Differentiates confident vs hedged vs abstain
Exposes internal coherence metrics in real time
You can test it live at:
https://thataiguy.org/talk.html
This work moves beyond pattern completion toward constrained dynamical reasoning with explicit epistemic control.
