docs: update handover with volition module (layer 7) completion Volition closes the qualia loop: sense → feel → reflect → decide. 8/8 tests passing, all signals integrated (free energy, ghost intensity, NARS confidence, rung accessibility, council modulation). https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh#123
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…d SIMD bundle fan-in MUL snapshot drives execution mode selection (Sprint/Stream/Burst/Chunk/Idle). DispatchPlan distributes FireflyFrames across N lane executors (round-robin). BundleCollector implements VSA majority-vote fan-in with columnar popcount. Architecture maps to Ballista Scheduler→Executor model with local lanes (remote executors via Arrow Flight deferred to scaling phase). https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
Ideas for next session: code-as-feeling pipeline, causal opcodes (SEE/DO/IMAGINE), inner council as VSA bundle, false flow → burst → epiphany loop, thought viscosity mapping to scheduler modes, and the threshold function that bridges Python phenomenology to Rust bitpacked fingerprints. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
Maps pure_bitpacked_vsa.py (Pearson 0.9913 Hamming↔cosine), resonance_qualia_dto.py (10KD binary ↔ 1024D float bridge), meaning_cam.py (48 canonical axes), and vsa_xor_quorum.py (ECC parity) to their ladybug-rs counterparts. Includes 4-step wiring plan: atom table → code scanning → resonance search → causal reasoning. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
…des, and epiphany detector - meaning_axes.rs: 48 canonical bipolar axes from dragonfly-vsa's meaning_cam.py, encode/decode to 16K-bit fingerprints, viscosity detection (8 types mapping to scheduler modes), CodeFeeling text analyzer for code-as-feeling pipeline - council.rs: Three-archetype inner council (Guardian/Catalyst/Balanced) with XOR-bind perspective shifting and majority-vote consensus. EpiphanyDetector monitors burst-mode resonance for unexpected discoveries (surprise > 1.5x baseline) - executor.rs: Pearl's three causal rungs as CPU opcodes — SEE (Hamming overlap ratio as NARS truth), DO (XOR-unbind confounder), IMAGINE (fork + measure causal impact as normalized Hamming distance) - qualia/mod.rs: wire new modules with re-exports https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
… without collapse Three-layer resonance architecture using Xyz (1+3)×8192 geometry: - resonance.rs: HdrResonance computes stacked popcount across 3 perspective containers (X/Y/Z) without collapsing to a single bundle. The 3D resonance profile preserves disagreement structure between archetypes. - AwarenessField: processes 8K vectors sequentially, keeping each resonance triple as the panoramic awareness. The 3×N matrix IS the awareness state. - TriangleCouncil: maps Guardian→X, Catalyst→Y, Balanced→Z in Xyz geometry. Consensus computed lazily on read (majority vote), never stored. Minority signals preserved for future epiphany detection. - FocusMask + AwarenessLens: from bighorn agi-thinking's DominoBaton.mask and SituationMap (focus/aperture/depth/lighting). The mask modulates the awareness field — perspective weights × depth sharpening × aperture cutoff. The masked field IS resonance-based thinking: the system thinks through whichever lens the mask amplifies. - Epiphany integration: split signals (one perspective high, others low) are boosted in the epiphany detector. High variance = disagreement = where future discoveries live. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
…ective, collapse gate Maps Martin Buber's relational ontology to Xyz (1+3)×8192 geometry: - X = content ⊕ ROLE_SUBJECT (I), Y = content ⊕ ROLE_PREDICATE (Thou), Z = content ⊕ ROLE_OBJECT (It), trace = X ⊕ Y ⊕ Z GestaltFrame: role binding with fixed quasi-orthogonal role atoms, frame/unframe (XOR self-inverse), holographic trace recovery. CrossPerspective: "look from the other tree" via role-swapping: - Original (I→It through Thou), Reversed (It→I), Rotated (Thou→It) - Each swap produces a different HdrResonance profile CollapseGate from sigma (variance of the I/Thou/It triangle): - Flow (sigma<0.08): aligned, can collapse - Fanout (0.08-0.18): ruminating - RungElevate (>0.18): high disagreement Quadrant selection from resonance axes (from gestalt_dto.py): - Q1: I acts on It, Q2: I experiences It - Q3: I acts with Thou, Q4: I experiences Thou look_from_other_tree(): perspective delta between two DN tree positions, applied to framed content, resonance computed from the other vantage. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
…iston free energy Tree walk that feels each branch: at every fork, compute the superposition of all siblings as the felt choice landscape (8,192 bits per level). The accumulated path context encodes what was NOT chosen at every fork. AweTriple stores 3 concepts as unresolved Xyz superposition with holographic trace (X ⊕ Y ⊕ Z) as inline edge marker for O(1) relationship lookup. Free energy (Friston surprise) computed as prediction error between spine and chosen child at each branch. felt_wander follows resonance instead of address — free will as resonance-guided navigation. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
Add reflection.rs: NARS introspection via felt walk + free energy semiring. The system can now walk its own belief tree, classify each node's state (Revise/Confirm/Explore/Stable) by comparing surprise with NARS confidence, update truth values in-place, and hydrate novel nodes from sibling context via reversible Markov chains (HydrationChain). Core additions: - read_truth/write_truth: NARS bridge to Container 0 W4-W7 - ReflectionOutcome 2x2 classification (surprise x confidence) - HydrationChain: reversible bind/unbind through sibling contexts - FreeEnergySemiring: implements DnSemiring for graph-wide surprise - reflect_walk, hydrate_explorers, reflect_and_hydrate entry points - 13 tests passing Extend ARCHITECTURE.md with 17 new sections covering the container substrate, DN tree, adjacency, SpineCache borrow/mut pattern, leaf insert, belichtungsmesser, delta encoding, NARS, rung system, lingering ghosts, semiring traversal, qualia module stack, cross-hydration, holographic markers, free energy/volition, and BlasGraph lineage. Existing CAM/scent-index documentation preserved. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
Complete handover covering the 7-layer qualia module stack, key architectural insights (SpineCache borrow/mut, ghost field vectors, Friston free energy, reversible Markov chains, rung elevation), and next steps (volition module, dream consolidation, MUL bridge). https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
…ee energy + ghost resonance + council Layer 7 of the qualia stack: the system choosing its own next action. Combines four signals into a ranked priority queue of volitional acts: - Free energy (surprise): urgency — how much does reality disagree? - Ghost intensity (sibling bundle resonance): felt context - NARS confidence: uncertainty signal (1 - confidence) - Rung accessibility: depth gate based on current cognitive level Council modulation: Guardian dampens surprise (0.6), Catalyst amplifies (1.5), Balanced neutral (1.0). Consensus = median of three scores. Public API: compute_agenda, volitional_cycle, focused_volition, volitional_gradient 8/8 tests passing. https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
Volition closes the qualia loop: sense → feel → reflect → decide. 8/8 tests passing, all signals integrated (free energy, ghost intensity, NARS confidence, rung accessibility, council modulation). https://claude.ai/code/session_01KJ2r3qXezGBXK8HutztJdh
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