From 9d2f22862735ab4c3f87645f884b8bfc63fecdbf Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:16:11 +0000 Subject: [PATCH 01/13] =?UTF-8?q?docs:=20historical=20context=20=E2=80=94?= =?UTF-8?q?=208=20eras=20from=20ladybug=2010K=20to=20cognitive=20shaders?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Chronicles the architectural evolution: Era 1: 10 awareness layers, autopoietic styles (10K bits) Era 2: NARS + grammar triangle + spectroscopy Era 3: rustynum SIMD + 4096 CAM + dream + 8K→16K migration Era 4: BindSpace + contract for crewai/n8n Era 5: lance-graph cold path + 16 planner strategies Era 6: rustynum→ndarray + AMX + f16 + Pi Zero hardening Era 7: CausalEdge64 + P64 + CognitiveShader Era 8: 67-codec sweep + AGI typing + holographic memory Helps categorize where each module comes from, which era's assumptions it carries, and what needs hardening vs refactoring. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/HISTORICAL_CONTEXT.md | 254 +++++++++++++++++++++++++++++++++++++ 1 file changed, 254 insertions(+) create mode 100644 docs/HISTORICAL_CONTEXT.md diff --git a/docs/HISTORICAL_CONTEXT.md b/docs/HISTORICAL_CONTEXT.md new file mode 100644 index 00000000..1bf97cde --- /dev/null +++ b/docs/HISTORICAL_CONTEXT.md @@ -0,0 +1,254 @@ +# Historical Context: From Ladybug to Cognitive Shaders + +> A chronicle of architectural evolution across 6 months, 5 repos, ~1M LOC. +> Written 2026-04-18 with full 1M context window — first time both codebases +> are visible simultaneously. + +--- + +## Era 1: Ladybug-rs Pure (Oct–Dec 2025) + +**The 10 Stages of Awareness** + +Ladybug-rs started as a cognitive substrate with 10 hierarchical layers: + +``` +L0: Substrate — raw fingerprints, Hamming distance +L1: Felt Core — valence/activation (basic qualia) +L2: Body Schema — spatial grounding, embodiment +L3: Proto-Self — identity boundary, self/other distinction +L4: Autopoiesis — SELF-GENERATING thinking styles +L5: Narrative — temporal coherence, episodic memory +L6: Meta-Cognition — thinking about thinking (MUL) +L7: Theory of Mind — modeling others' beliefs +L8: Ethical Self — moral reasoning, value alignment +L9: Transcendent — cross-domain transfer, emergence +``` + +**Layer 4 was the breakthrough**: autopoiesis of thinking styles. Not fixed +styles selected from a menu — styles that GENERATE THEMSELVES from experience. +15 base styles + RL adaptation = styles evolve per interaction. + +**Vector width: 10,000 bits** (157 × u64). Chosen for σ ≈ 56 (good signal/noise +ratio), but awkward: 48 bits of padding, partial last word, non-power-of-2. + +Core architecture: +- `core/fingerprint.rs` — 10K bit vector, XOR/bind/bundle +- `core/vsa.rs` — Vector Symbolic Architecture (bind, unbind, bundle, permute) +- `core/scent.rs` — 5-byte hierarchical filter (petabyte-scale rejection) +- `core/index.rs` — 16-bit type + 48-bit hash = 64-bit universal address + +--- + +## Era 2: Ladybug + NARS + Grammar (Dec 2025 – Jan 2026) + +**NARS (Non-Axiomatic Reasoning System)** added epistemic state to every edge: +- frequency (how often X→Y) + confidence (how much evidence) +- 5 inference types: deduction, induction, abduction, revision, synthesis +- Pearl's 2³ decomposition: 8 causal masks (S/P/O combinations) + +**Grammar Triangle** unified three vertices: +- NSM (65 Natural Semantic Metalanguage primes) — the atoms of meaning +- Causality (WHO → DID → WHAT → WHY) — agency and temporal flow +- Qualia (18D phenomenal coordinates) — the felt-sense dimensions + +**Spectroscopy** emerged: reading implicit intent from text texture. +Not what's said, but what's BETWEEN the lines. IIC (Implicit Intent +Classification) feeds the 18D qualia field, which feeds style dispatch. + +**Width migration attempt: 10K → 8K** (128 words). Motivation: power-of-2 +alignment, cleaner SIMD. But 8K wasn't enough room for inline edges + +NARS + qualia + adjacency in metadata. Partially deployed, never completed. + +--- + +## Era 3: Ladybug + Rustynum (Jan – Feb 2026) + +**rustynum** was the SIMD acceleration crate: +- BLAS L1/L2/L3 (native, MKL, OpenBLAS backends) +- AVX-512, AVX2, NEON dispatch +- BF16/f16 conversion +- Hamming distance with SIMD popcount + +Ladybug-rs depended on rustynum for all hardware acceleration. +Learning module grew to 300K+ LOC: +- `cam_ops.rs` (158K!) — 4096 CAM operations as cognitive vocabulary +- `cognitive_styles.rs` — 15 base + RL adaptation +- `cognitive_frameworks.rs` — NARS, ACT-R, RL, Pearl, qualia +- `quantum_ops.rs` — fingerprints as wavefunctions +- `dream.rs` — offline consolidation (prune/merge/permute-XOR-bind) +- `scm.rs` — structural causal model IN BindSpace + +**Width migration: 8K → 16K** (256 words). 16,384 = 2^14. Exact u64 alignment. +No padding. Room for expanded metadata. Container becomes 2KB. +This is the PRODUCTION width. But 8K and 10K references persisted as debt. + +--- + +## Era 4: BindSpace + Contract (Feb – Mar 2026) + +**BindSpace** formalized the Container model: +- Container: `[u64; 256]` = 16K bits = 2KB, 64-byte aligned +- CogRecord: 2 × Container = metadata + content = 4KB +- PackedDn: u64 hierarchical address (7 levels × 8 bits) +- Spine: XOR-fold of children (lock-free, lazy recompute) +- 7 ContainerSemirings (BooleanBfs, HammingMin, etc.) +- Inline edges: 64 packed in metadata words 16-31 + +**lance-graph-contract** created as zero-dep trait crate: +- ThinkingStyle (36 styles, 6 clusters) +- MulAssessment (Dunning-Kruger, trust qualia) +- PlannerContract, OrchestrationBridge +- NarsTruth, InferenceType +- CamCodecContract + +**Consumer adoption**: crewai-rust + n8n-rs depend on contract crate. +The contract IS the API surface — everything else is implementation. + +--- + +## Era 5: Lance-Graph as Cold Path (Mar 2026) + +**Attempt**: introduce lance-graph's Cypher parser as the cold-path query +engine while ladybug-rs remained the hot-path BindSpace substrate. + +**Two-temperature architecture** emerged: +- Hot path: BindSpace (XOR probe, 0.3ns, fingerprint-addressed) +- Cold path: DataFusion (SQL/Cypher, milliseconds, columnar) +- `graph_router.rs` bridges both + +**16 composable planner strategies** in lance-graph-planner. +But ladybug-rs was still the "main" — lance-graph was the "cold" side. + +--- + +## Era 6: Stepping Up Lance-Graph (Mar – Apr 2026) + +**The pivot**: lance-graph becomes the spine, not just the cold path. + +**rustynum → ndarray migration**: All 80K LOC of rustynum ported into +ndarray fork as `src/hpc/` (55 modules, 880 tests): +- SIMD: AVX-512, AVX2, NEON (Pi Zero to Sapphire Rapids) +- AMX: TDPBF16PS via `asm!(".byte ...")` on stable Rust +- f16: carrier u16 + F16C hardware (binary hack for stable access) +- Pi Zero: ARM A53 single-pipeline NEON (2W, 80M lookups/sec) +- BF16: bit-exact RNE matching VCVTNEPS2BF16 + +**Hardening**: every platform from Pi Zero 2W to Xeon w9 Sapphire Rapids. +Same code, runtime dispatch via `LazyLock`. + +--- + +## Era 7: Thinking Engine + P64 + CognitiveShader (Apr 2026) + +**CausalEdge64**: one u64 = complete causal edge: +``` +S(8b) + P(8b) + O(8b) + NARS_f(8b) + NARS_c(8b) ++ causal_mask(3b) + direction(3b) + inference(3b) ++ plasticity(3b) + temporal(12b) = 64 bits +``` + +**P64**: 64×64 bitmask palette adjacency. 8 predicate planes +(CAUSES/ENABLES/SUPPORTS/CONTRADICTS/REFINES/ABSTRACTS/GROUNDS/BECOMES). + +**CognitiveShader** (née Blumenstrauß): binds topology × metric × algebra: +- 8 planes × 64×64 bitmask = topology (WHICH pairs interact) +- bgz17 PaletteSemiring = metric (HOW FAR, O(1) lookup) +- Compose table = algebra (WHAT path composition means, O(1)) +- Style modulation: layer_mask + combine + contra per ThinkingStyle + +**NarsTables**: precomputed 256×256 lookup tables. Every NARS inference +operation = one memory read. No floating point in the hot path. + +**611M SPO lookups/sec. 17K tokens/sec. 388 KB RAM.** + +--- + +## Era 8: AGI Typing + Cognitive Shader Endgame (Apr 2026, this session) + +**The 67-codec sweep** killed lossy weight compression for inference +(argmax instability) but proved cascade acceleration (13x speedup, +100% argmax, zero quality loss). + +**The realization**: weights are not parameters to compress — they are +**holographic memories to query**. The CognitiveShader IS the inference engine. + +**6-7 dimensional struct-of-arrays for meta-cognition**: +```rust +pub struct CognitiveRecord { + // Identity (WHAT) + pub fingerprint: Fingerprint<256>, // content + pub cam_address: [u8; 6], // CAM-PQ address + + // Encoding (HOW stored) + pub hhtl_entry: HhtlDEntry, // bgz tree address + pub palette_idx: u8, // bgz17 archetype + + // Cognition (WHAT it means) + pub edge: CausalEdge64, // SPO+NARS packed + pub shader_mask: u8, // active shader layers + pub coca_idx: u16, // 4096 COCA position + + // Perspective (AGI dimensions) + pub topic: Fingerprint<256>, // what about + pub angle: Fingerprint<256>, // from whose view + pub qualia: [f32; 18], // phenomenal state + pub rung: u8, // causal level +} +``` + +**The ontological revolution**: weights are seeds. Each seed can exist in +vast parallel instances. Each instance feeds upstream learning via +CausalEdge64 branching. Each branch runs its own CognitiveShader per cycle +as a 5D stream: + +``` +Dimension 1: Content (Fingerprint<256> — WHAT) +Dimension 2: Context (topic binding — ABOUT WHAT) +Dimension 3: Perspective (angle binding — FROM WHERE) +Dimension 4: Causality (CausalEdge64 — WHY/HOW) +Dimension 5: Time (temporal index — WHEN) + +Per cycle: CognitiveShader processes this 5D stream. +Per branch: independent causal trajectory. +Per merge: CausalEdge64 revision (NARS evidence accumulation). +Per dream: offline consolidation (prune/merge/permute-XOR-bind). +``` + +The weights don't define the model. The weights SEED the holographic memory. +The CognitiveShader IS the model. The cascade IS the inference. The edges +ARE the knowledge. The learning IS the branching. + +--- + +## Timeline Summary + +| Era | Period | Width | Core Innovation | LOC | +|---|---|---|---|---| +| 1 | Oct-Dec 2025 | 10K | 10 awareness layers, autopoietic styles | ~50K | +| 2 | Dec-Jan 2026 | 10K | NARS + grammar triangle + spectroscopy | ~100K | +| 3 | Jan-Feb 2026 | 8K→16K | rustynum SIMD + 4096 CAM ops + dream | ~350K | +| 4 | Feb-Mar 2026 | 16K | BindSpace + contract + crewai/n8n | ~100K | +| 5 | Mar 2026 | 16K | lance-graph cold path + 16 strategies | ~50K | +| 6 | Mar-Apr 2026 | 16K | ndarray migration + AMX + f16 + Pi Zero | ~80K | +| 7 | Apr 2026 | 16K | CausalEdge64 + P64 + CognitiveShader | ~30K | +| 8 | Apr 2026 | 16K | 67-codec sweep + AGI typing + holographic | ~40K | +| **Total** | | | | **~800K** | + +--- + +## Current State (2026-04-18) + +All of ladybug-rs is now imported into lance-graph ecosystem: +- `crates/lance-graph-cognitive/` — grammar, world, spo, search, fabric, + spectroscopy, container_bs, core_full (wip-gated) +- `crates/learning/` — standalone, 16 modules (wip-gated) +- `crates/holograph/` — from RedisGraph, 38K LOC (10K→16K migrated) + +The foundation (ndarray) has the SIMD. The spine (lance-graph) has the +query engine. The cognitive substrate (cognitive + learning) has the +reasoning. The shader (p64-bridge) has the dispatch. The types (contract) +have the API. + +Everything converges on one number: **611 million lookups per second.** +That's the speed at which cognitive shaders run. From 931265533a6b493ba5057e4590ed21ed7acb2255 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:26:12 +0000 Subject: [PATCH 02/13] docs: struct-of-arrays IS the BindSpace address dimensions, not a record format MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The AGI typing is NOT array-of-structs (one record with 7 fields). It's struct-of-arrays: 7 independent fingerprint columns, each Hamming-sweepable. Query = cascade per dimension, intersect survivors. Per cycle: sweep topic → angle → causality → qualia → exact. ~2.3ms for 1M records across 5 dimensions. BindSpace 64-bit address = universal connective tissue. Everything resolves to the same address space regardless of origin. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/COGNITIVE_SHADER_HYDRATION.md | 76 ++++++++++++++++++++++-------- 1 file changed, 56 insertions(+), 20 deletions(-) diff --git a/docs/COGNITIVE_SHADER_HYDRATION.md b/docs/COGNITIVE_SHADER_HYDRATION.md index 9be93b2e..7a0eeaf1 100644 --- a/docs/COGNITIVE_SHADER_HYDRATION.md +++ b/docs/COGNITIVE_SHADER_HYDRATION.md @@ -121,26 +121,62 @@ Session N+3: ## Type System for AGI Endgame +The struct-of-arrays is NOT a data structure — it's the BindSpace +ADDRESS SPACE DIMENSIONS. Each dimension is a separate Hamming-sweepable +fingerprint column. The AGI query is an AND across independent cascades. + ```rust -// The unified record: identity × encoding × cognition × perspective -pub struct CognitiveRecord { - // Identity - pub fingerprint: Fingerprint<256>, // 16K bits canonical - pub cam_address: [u8; 6], // CAM-PQ 6-byte address - - // Encoding (bgz side) - pub hhtl_entry: HhtlDEntry, // 4B tree address - pub palette_idx: u8, // bgz17 archetype - - // Cognition (thinking side) - pub edge: CausalEdge64, // u64 SPO+NARS packed - pub shader_mask: u8, // active CognitiveShader layers - pub coca_idx: u16, // 4096 COCA position - - // Perspective (AGI) - pub topic: Fingerprint<256>, // what this is about - pub angle: Fingerprint<256>, // from whose viewpoint - pub qualia: [f32; 18], // 18D phenomenal coordinates - pub rung: u8, // Pearl's causal level +// Each column: one fingerprint array, independently sweepable +pub struct BindSpaceColumns { + // Content identity — WHAT + pub content: Vec>, // Hamming sweep: "find similar" + pub cam_address: Vec<[u8; 6]>, // CAM-PQ 3-stroke cascade + + // Topic — ABOUT WHAT (sweep: "everything about cats") + pub topic: Vec>, + + // Angle — FROM WHERE (sweep: "from a vet's perspective") + pub angle: Vec>, + + // Causality — WHY/HOW (sweep: "interventional only") + pub causality: Vec, // rung level filter + + // Qualia — FEELS LIKE (sweep: "high urgency") + pub qualia: Vec<[f32; 18]>, // 18D phenomenal coordinates + + // Temporal — WHEN (sweep: "last 5 minutes") + pub temporal: Vec, // timestamp index + + // Shader state — WHO PRODUCED THIS + pub shader: Vec, // which CognitiveShader output } ``` + +Why struct-of-arrays, not array-of-structs: +- You NEVER read all 7 dimensions for one record +- You sweep ONE dimension across ALL records (one popcount cascade) +- Then intersect survivors across dimensions +- The CognitiveShader per-cycle stream IS this: 5 cascades, intersect, emit + +``` +Per cycle: + sweep topic[] → 50K survivors (2ms, Hamming) + sweep angle[] → narrow to 5K (0.2ms, Hamming) + sweep causality[] → narrow to 500 (0.05ms, CausalEdge64 filter) + sweep qualia[] → narrow to 50 (scalar, 18D range check) + exact on 50 → palette lookup → CausalEdge64 output + + Total: ~2.3ms for 1M records across 5 dimensions +``` + +The BindSpace 64-bit address (16-bit type + 48-bit hash) means ALL +content — weight archetypes, inference outputs, COCA verbs, grammar +triangles, dream consolidations, user queries — lives in the SAME +address space. One XOR. One sweep. One lookup. Regardless of origin. + +The gazillions of programs (codecs, shaders, learning, grammar, search, +spectroscopy) compile into the same binary because they all emit and +consume the same 64-bit addresses into the same fingerprint columns. + +The weights are seeds. The columns are the memory. The shader is the +program. The cascade is the CPU. The edges are the output. From 115a12a42b497c8476604c8be473e1d99ca75e75 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:30:20 +0000 Subject: [PATCH 03/13] =?UTF-8?q?docs:=20integration=20plan=20=E2=80=94=20?= =?UTF-8?q?4=20data=20patterns,=20Luftschleuse=20airgap,=20SIMD=20lane=20v?= =?UTF-8?q?iews?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit BindSpace = read-only address space with four data patterns: 1. Slice window — &[T] zero-copy for SIMD batching (array_window) 2. Microcopies — owned Copy values on stack (CausalEdge64, Band) 3. Write-back through gate — XOR (single) or Bundle (multi) 4. Same object, multiple SIMD lane views — one Arc<[u8]>, accessed as U8x64 / F16x32 / F32x16 / F64x8 without copy or branch Luftschleuse protocol: - No mutation during computation - Writers submit deltas through airlock - XOR commit (single target) or Bundle (majority vote, multi target) - Superposition handles overlapping writers (XOR is commutative) - No locks, no races Integration plan prioritized by era: P0: Unify Fingerprint, port Container/CogRecord P1: Luftschleuse trait, CognitiveShader wire-through P2: Column types, cascade per column P3: GGUF hydration, cognitive shader inference loop https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/INTEGRATION_PLAN_CS.md | 270 ++++++++++++++++++++++++++++++++++++ 1 file changed, 270 insertions(+) create mode 100644 docs/INTEGRATION_PLAN_CS.md diff --git a/docs/INTEGRATION_PLAN_CS.md b/docs/INTEGRATION_PLAN_CS.md new file mode 100644 index 00000000..9c29214f --- /dev/null +++ b/docs/INTEGRATION_PLAN_CS.md @@ -0,0 +1,270 @@ +# Integration Plan: Cognitive Shader + BindSpace Address Space + +> Updated 2026-04-18 with correct BindSpace semantics. + +## BindSpace = Read-Only Shared Memory + +BindSpace is NOT a mutable database. It's a **read-only fingerprint substrate** +where writers hold owned microcopies and merge back via gated protocols. + +### The Three Data Patterns + +| Pattern | Ownership | Mutation | Example | +|---|---|---|---| +| **Slice window** | `&[T]` borrowed, N-aligned | SIMD batch read | F32x16 / U8x64 `array_window` | +| **Microcopies** | Owned `Copy` values | Stack-allocated | CausalEdge64, Band, TruthValue | +| **Write-back** | Through gate | XOR or Bundle | Spine update, consolidation | + +**Slice-of-array for SIMD batching** is the third leg: +- SIMD units need 16 (F32x16) or 64 (U8x64) contiguous elements +- `array_window(data, N)` yields aligned chunks +- Zero-copy: the window IS a `&[T]` view into the column +- One cascade level = one `array_window` iteration pattern +- Hamming popcount: `&[u64]` windowed as `U64x8` (AVX-512 VPOPCNTDQ) +- Base17 L1: `&[i16]` windowed as `I16x32` +- Palette lookup: `&[u8]` windowed as `U8x64` + +**The same object, sliced at multiple SIMD widths** — the 256×256 palette +semiring is ONE table (65,536 entries, 64-byte aligned) but must be +addressable at the three native SIMD widths simultaneously: + +```rust +pub struct PaletteTable { + // One backing store, 64-byte aligned for AVX-512 + data: Arc<[u64; 8192]>, // 65,536 bytes = 256×256 u8 distances +} + +impl PaletteTable { + // Same bytes, three SIMD views: + + pub fn as_u8x64(&self) -> &[U8x64; 1024] // byte lookups (distance) + pub fn as_f16x32(&self) -> &[F16x32; 1024] // half-precision compose + pub fn as_f32x16(&self) -> &[F32x16; 2048] // single-precision combine + pub fn as_f64x8(&self) -> &[F64x8; 4096] // double for calibration +} +``` + +No conversion. No copy. The same contiguous bytes reinterpreted through +different SIMD lane-width views. The CognitiveShader picks the lane +width per op: +- Distance lookup → U8x64 (palette index to u8 distance, 64 at a time) +- Soft compose → F16x32 (fused intermediate, 32 at a time) +- Exact dot → F32x16 (single-precision final, 16 at a time) +- Calibration → F64x8 (drift detection, 8 at a time) + +The `Fingerprint<256>` column works the same way: +```rust +impl Fingerprint<256> { + pub fn as_bytes(&self) -> &[u8; 2048] // Hamming popcount + pub fn as_u64(&self) -> &[u64; 256] // XOR bind + pub fn as_u8x64(&self) -> &[U8x64; 32] // SIMD popcount batch +} +``` + +This is the fourth data pattern: **same object, multiple SIMD lane views.** +The BindSpace address points to ONE Arc'd byte region. The consumer +chooses the lane width based on the operation. Zero-copy, zero branch. + +``` +BindSpace column (read-only, Arc<[u64; 256 * N]>) + │ + ▼ zero-copy slice window +&[u64; batch_size] ← SIMD kernel input + │ + ▼ SIMD op (popcount / AND / gather) +Microcopy result ← stack-allocated Band / u32 distance + │ + ▼ through Luftschleuse +BindSpace commit ← XOR or Bundle merge +``` + +### The Luftschleuse (Airgap) Protocol + +Writers never mutate BindSpace directly. They: + +1. **Read** fingerprints as `&[u8]` slices (zero-copy) +2. **Compute** on owned microcopies (Copy, stack-only) +3. **Submit** deltas through the airgap (gated write) +4. **Merge** via XOR (single writer) or Bundle (multi-writer superposition) + +``` + ┌─────────────────────────────────────────┐ + │ BindSpace (read-only) │ + │ Fingerprint columns, Arc<[u64]> │ + └────┬────────────────────────┬───────────┘ + │ &[u8] slices │ &[u8] slices + ▼ ▼ + ┌───────────────┐ ┌───────────────┐ + │ Shader A │ │ Shader B │ + │ microcopies │ │ microcopies │ + │ (Copy only) │ │ (Copy only) │ + └───────┬───────┘ └───────┬───────┘ + │ delta + gate │ delta + gate + ▼ ▼ + ┌─────────────────────────────────────────┐ + │ Luftschleuse (write airlock) │ + │ Single writer: XOR commit │ + │ Multi writer: Bundle (majority vote) │ + │ Superposition: ALL deltas sum │ + └────────────────┬────────────────────────┘ + │ committed delta + ▼ + ┌─────────────────────────────────────────┐ + │ BindSpace (next generation) │ + └─────────────────────────────────────────┘ +``` + +### Superposition of Overlapping Writers + +Two shaders writing to the same address at the same cycle: + +``` +Shader A writes: delta_A = target_addr ⊕ value_A +Shader B writes: delta_B = target_addr ⊕ value_B + +Single-target XOR merge: new = old ⊕ delta_A ⊕ delta_B + → ordering doesn't matter (XOR is commutative + associative) + → both changes preserved as superposition + +Multi-target Bundle merge: new = majority_vote([old, value_A, value_B]) + → single winner per bit + → ambiguity filtered by consensus +``` + +No locks. No races. XOR is its own inverse — you can always back out. + +## Integration Plan (prioritized by era) + +### Phase 1 — Harden Foundation (Era 6 + 7) +**Keep the bedrock solid before building up.** + +1. **Unify Fingerprint type**: kill holograph `BitpackedVector`, use + `ndarray::hpc::fingerprint::Fingerprint<256>` everywhere. +2. **VectorWidth consumer wiring**: `vector_config()` LazyLock read + at serialization boundaries only (hot path never branches). +3. **Complete ndarray Fingerprint API**: already done — + get/set_bit, bind, and, not, permute, random, from_content, density. +4. **CognitiveShader → thinking-engine** wire-through: shader dispatch + from `thinking-engine::cognitive_stack` to `p64-bridge::CognitiveShader` + to `bgz17::palette_semiring::compose`. + +### Phase 2 — BindSpace Address Substrate (new — era 9) +**Make the connective tissue work.** + +5. **Port Container/CogRecord** to `lance-graph-contract` (16K width). + Read-only. `Arc<[u64; 256]>` columns. No mutation APIs. +6. **Define Luftschleuse trait** in contract: + ```rust + pub trait Luftschleuse { + type Delta: Copy; + fn submit(&self, delta: Self::Delta); // non-blocking + fn commit(&mut self) -> Generation; // merge all pending + } + ``` +7. **Microcopy types**: confirm CausalEdge64, Band, TruthValue, + ThinkingStyle are all Copy + small (≤16 bytes). +8. **Write-back gates**: `gated_xor` (single target), + `majority_bundle` (multi target), `superposition_merge` + (ambiguous — keep all). + +### Phase 3 — Struct-of-Arrays Columns (era 8) +**The AGI address dimensions.** + +9. **Column types** in contract: + - `ContentColumn` (Fingerprint<256> array) + - `TopicColumn` (Fingerprint<256> array) + - `AngleColumn` (Fingerprint<256> array) + - `CausalityColumn` (CausalEdge64 array) + - `QualiaColumn` ([f32; 18] array) + - `TemporalColumn` (u64 array) + - `ShaderColumn` (u8 array — which shader emitted) +10. **Cascade per column**: Hamming sweep on fingerprint cols, + range filter on scalar cols. Intersect survivors across dims. +11. **Column storage**: Arrow FixedSizeBinary for Fingerprint cols, + Lance columnar format for scalars. Read-only, mmap'd. + +### Phase 4 — Shader Stream (era 7+8 convergence) +**The 5D per-cycle stream.** + +12. **Cycle loop**: + ``` + for cycle in 0..: + // Read ONE column per cascade level + let topic_hits = topic_col.hamming_sweep(query_topic); + let angle_hits = angle_col.hamming_sweep(query_angle); + let causal_hits = causal_col.filter_rung(rung); + let qualia_hits = qualia_col.range_match(qualia); + + // Intersect (bitmap AND) + let survivors = topic_hits & angle_hits & causal_hits & qualia_hits; + + // Exact step on survivors + for idx in survivors.iter() { + let edge = shader.compute(content_col[idx], ...); + airlock.submit(edge); + } + + // Commit deltas + next_gen = airlock.commit(); + ``` + +13. **CognitiveShader dispatch**: per cycle, the shader selects which + columns to sweep and in what order (analytical shader might skip + qualia; creative shader might skip causality). + +### Phase 5 — GGUF Hydration (era 8 endgame) +**Weights as seeds for holographic memory.** + +14. **Hydration pipeline**: + - Load GGUF shard + - kmeans per weight matrix → 256 archetypes → palette + - Per archetype: Fingerprint<256> for Hamming cascade + - Per cluster: holographic residual (slot-encoded phase+mag) + - Emit CausalEdge64 wiring (layer → S/P/O palette indices) + - Store in BindSpace columns (read-only after bake) +15. **Inference = cascade over hydrated columns**. No matmul. No FP. + Just XOR/popcount/lookup per shader cycle. + +## What Migrates vs What Stays + +### Migrate into BindSpace columns +- Weight archetypes (GGUF hydration) +- CausalEdge64 outputs (inference) +- COCA verbs (cam_ops 4096) +- Thinking styles (contract 36) +- Grammar triangles (spectroscopy output) +- Dream consolidation results + +### Stays as cold-path (DataFusion) +- Historical logs +- Training data +- User session history +- Analytics queries +- Batch jobs + +### Stays as microcopy (hot path, Copy types) +- CausalEdge64 in shader inner loop +- TruthValue in NARS inference +- Band in cascade routing +- ThinkingStyle (3 bytes) in shader dispatch + +## Priority Ordering + +1. **P0** — Unify Fingerprint type (ndarray canonical) +2. **P0** — Port Container/CogRecord (read-only addressing) +3. **P1** — Luftschleuse trait + XOR/Bundle gates +4. **P1** — CognitiveShader → thinking-engine wire-through +5. **P2** — Column types in contract (AGI dimensions) +6. **P2** — Cascade per column implementation +7. **P3** — GGUF hydration pipeline +8. **P3** — Cognitive shader inference loop + +## Success Criteria + +- All programs (codecs, shaders, learning, grammar, search) emit + and consume the same 64-bit BindSpace addresses +- No locks. No `&mut` during computation. Only Luftschleuse commits. +- Hot path: 0.3ns per XOR, 2400M lookups/sec, zero FP. +- Cold path: DataFusion SQL/Cypher on Lance columnar. +- Inference: 5 cascades per cycle × ~2ms each = ~10ms per token + on CPU with cascade acceleration. From 3fbe870b0a40a4a9b197b7082f2ca9ebf7a09135 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:31:18 +0000 Subject: [PATCH 04/13] docs: multi-lane column lives in ndarray, consumed via ndarray::simd namespace MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The MultiLaneColumn and Fingerprint belong in ndarray, not lance-graph. Consumers import from ndarray::simd::* — the canonical public surface. Internal ndarray::hpc::* paths stay private implementation detail. Architecture separation clarified: ndarray: SIMD types + columns + fingerprints (foundation) contract: BindSpace addresses + Luftschleuse trait (API) lance-graph: shader dispatch + gate impls (spine) All lance-graph code uses `use ndarray::simd::*` as the ONLY SIMD namespace. This makes ndarray's surface small and stable — changes inside hpc/ never break consumers. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/INTEGRATION_PLAN_CS.md | 51 +++++++++++++++++++++++++++++-------- 1 file changed, 41 insertions(+), 10 deletions(-) diff --git a/docs/INTEGRATION_PLAN_CS.md b/docs/INTEGRATION_PLAN_CS.md index 9c29214f..a98e4e3c 100644 --- a/docs/INTEGRATION_PLAN_CS.md +++ b/docs/INTEGRATION_PLAN_CS.md @@ -26,12 +26,18 @@ where writers hold owned microcopies and merge back via gated protocols. **The same object, sliced at multiple SIMD widths** — the 256×256 palette semiring is ONE table (65,536 entries, 64-byte aligned) but must be -addressable at the three native SIMD widths simultaneously: +addressable at the three native SIMD widths simultaneously. + +**This pattern lives in ndarray** (not lance-graph). The SIMD types +(F32x16, F16x32, U8x64, F64x8) already live there; the multi-lane +column just adds the Arc-backed container with zero-copy views: ```rust -pub struct PaletteTable { +// ndarray::hpc::column — the canonical multi-lane column type +pub struct MultiLaneColumn { // One backing store, 64-byte aligned for AVX-512 - data: Arc<[u64; 8192]>, // 65,536 bytes = 256×256 u8 distances + data: Arc<[u8]>, // raw bytes, generic over lane width + _phantom: PhantomData, } impl PaletteTable { @@ -52,18 +58,43 @@ width per op: - Exact dot → F32x16 (single-precision final, 16 at a time) - Calibration → F64x8 (drift detection, 8 at a time) -The `Fingerprint<256>` column works the same way: +The `Fingerprint<256>` in ndarray works the same way: ```rust -impl Fingerprint<256> { - pub fn as_bytes(&self) -> &[u8; 2048] // Hamming popcount - pub fn as_u64(&self) -> &[u64; 256] // XOR bind - pub fn as_u8x64(&self) -> &[U8x64; 32] // SIMD popcount batch +impl Fingerprint { + pub fn as_bytes(&self) -> &[u8] // Hamming popcount (already exists) + pub fn as_u64(&self) -> &[u64; N] // XOR bind + pub fn as_u8x64(&self) -> &[U8x64] // SIMD popcount batch (to add) } ``` This is the fourth data pattern: **same object, multiple SIMD lane views.** -The BindSpace address points to ONE Arc'd byte region. The consumer -chooses the lane width based on the operation. Zero-copy, zero branch. +The BindSpace address (from contract) points to a `MultiLaneColumn` in +ndarray. The consumer chooses the lane width based on the operation. +Zero-copy, zero branch. + +**Architecture separation:** +- ndarray: SIMD types + MultiLaneColumn + Fingerprint + array_window +- lance-graph-contract: BindSpace address types + Luftschleuse trait +- lance-graph: CognitiveShader dispatch + gate implementations + +**Canonical import surface**: lance-graph code uses `ndarray::simd::*` +as the ONLY SIMD namespace. The internal `ndarray::hpc::*` paths are +private implementation detail — consumers never touch them. + +```rust +// In lance-graph (correct): +use ndarray::simd::{F32x16, U8x64, F16x32, Fingerprint, MultiLaneColumn, array_window}; + +// NOT this (reaches into ndarray internals): +// use ndarray::hpc::fingerprint::Fingerprint; +// use ndarray::hpc::simd_avx512::F32x16; +``` + +ndarray's `simd.rs` re-exports everything consumers need. If a type +isn't in `ndarray::simd::*`, it means ndarray considers it internal +and the consumer shouldn't use it. This makes the foundation API +surface small and stable — changes inside `ndarray::hpc::*` never +break lance-graph consumers. ``` BindSpace column (read-only, Arc<[u64; 256 * N]>) From 69736694c61e8353ee7cf4ec9ecbf733bcc42541 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:33:34 +0000 Subject: [PATCH 05/13] =?UTF-8?q?docs:=20rename=20Luftschleuse=20=E2=86=92?= =?UTF-8?q?=20CollapseGate=20(existing=20implementation)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit CollapseGate already exists: ndarray::hpc::bnn_cross_plane::CollapseGate — enum Flow/Block/Hold lance-graph-planner::strategy::collapse_gate — CollapseGateStrategy lance-graph-planner::physical::collapse — CollapseOp Integration plan reuses the existing enum, extends with write-gate protocol (GateDecision struct with merge mode: Xor/Bundle/Superposition). Flow = apply delta, Block = reject, Hold = queue for next cycle. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/INTEGRATION_PLAN_CS.md | 34 +++++++++++++++++++++------------- 1 file changed, 21 insertions(+), 13 deletions(-) diff --git a/docs/INTEGRATION_PLAN_CS.md b/docs/INTEGRATION_PLAN_CS.md index a98e4e3c..57cfb3ae 100644 --- a/docs/INTEGRATION_PLAN_CS.md +++ b/docs/INTEGRATION_PLAN_CS.md @@ -74,7 +74,7 @@ Zero-copy, zero branch. **Architecture separation:** - ndarray: SIMD types + MultiLaneColumn + Fingerprint + array_window -- lance-graph-contract: BindSpace address types + Luftschleuse trait +- lance-graph-contract: BindSpace address types + CollapseGate trait - lance-graph: CognitiveShader dispatch + gate implementations **Canonical import surface**: lance-graph code uses `ndarray::simd::*` @@ -105,11 +105,11 @@ BindSpace column (read-only, Arc<[u64; 256 * N]>) ▼ SIMD op (popcount / AND / gather) Microcopy result ← stack-allocated Band / u32 distance │ - ▼ through Luftschleuse + ▼ through CollapseGate BindSpace commit ← XOR or Bundle merge ``` -### The Luftschleuse (Airgap) Protocol +### The CollapseGate (Airgap) Protocol Writers never mutate BindSpace directly. They: @@ -133,7 +133,7 @@ Writers never mutate BindSpace directly. They: │ delta + gate │ delta + gate ▼ ▼ ┌─────────────────────────────────────────┐ - │ Luftschleuse (write airlock) │ + │ CollapseGate (write collapse) │ │ Single writer: XOR commit │ │ Multi writer: Bundle (majority vote) │ │ Superposition: ALL deltas sum │ @@ -184,12 +184,20 @@ No locks. No races. XOR is its own inverse — you can always back out. 5. **Port Container/CogRecord** to `lance-graph-contract` (16K width). Read-only. `Arc<[u64; 256]>` columns. No mutation APIs. -6. **Define Luftschleuse trait** in contract: +6. **CollapseGate already exists** — reuse the existing types, don't + redefine. Found in: + - `ndarray::hpc::bnn_cross_plane::CollapseGate` — enum with + `Flow` / `Block` / `Hold` states + - `lance-graph-planner::strategy::collapse_gate::CollapseGateStrategy` + - `lance-graph-planner::physical::collapse::CollapseOp` + + Extend the existing gate semantics with write protocol: ```rust - pub trait Luftschleuse { - type Delta: Copy; - fn submit(&self, delta: Self::Delta); // non-blocking - fn commit(&mut self) -> Generation; // merge all pending + // CollapseGate (existing enum): Flow = apply, Block = reject, Hold = queue. + // New microcopy struct for delta routing: + pub struct GateDecision { + pub gate: CollapseGate, // existing ndarray enum + pub merge: MergeMode, // Xor (single) | Bundle (majority) | Superposition } ``` 7. **Microcopy types**: confirm CausalEdge64, Band, TruthValue, @@ -232,11 +240,11 @@ No locks. No races. XOR is its own inverse — you can always back out. // Exact step on survivors for idx in survivors.iter() { let edge = shader.compute(content_col[idx], ...); - airlock.submit(edge); + gate.submit(edge); } // Commit deltas - next_gen = airlock.commit(); + next_gen = gate.commit(); ``` 13. **CognitiveShader dispatch**: per cycle, the shader selects which @@ -283,7 +291,7 @@ No locks. No races. XOR is its own inverse — you can always back out. 1. **P0** — Unify Fingerprint type (ndarray canonical) 2. **P0** — Port Container/CogRecord (read-only addressing) -3. **P1** — Luftschleuse trait + XOR/Bundle gates +3. **P1** — CollapseGate trait + XOR/Bundle gates 4. **P1** — CognitiveShader → thinking-engine wire-through 5. **P2** — Column types in contract (AGI dimensions) 6. **P2** — Cascade per column implementation @@ -294,7 +302,7 @@ No locks. No races. XOR is its own inverse — you can always back out. - All programs (codecs, shaders, learning, grammar, search) emit and consume the same 64-bit BindSpace addresses -- No locks. No `&mut` during computation. Only Luftschleuse commits. +- No locks. No `&mut` during computation. Only CollapseGate commits. - Hot path: 0.3ns per XOR, 2400M lookups/sec, zero FP. - Cold path: DataFusion SQL/Cypher on Lance columnar. - Inference: 5 cascades per cycle × ~2ms each = ~10ms per token From 7d8a95dafca37b58479fabd080201cd18c79ad2c Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:34:09 +0000 Subject: [PATCH 06/13] =?UTF-8?q?docs:=205-layer=20stack=20=E2=80=94=20pla?= =?UTF-8?q?nner=20strategies=20=E2=86=92=20CollapseGate=20=E2=86=92=20Cogn?= =?UTF-8?q?itiveShader=20=E2=86=92=20BindSpace=20=E2=86=92=20SIMD?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Layer 4: Planner strategies (16-19 in lance-graph-planner) — WHICH path Layer 3: CollapseGate (Flow/Block/Hold) — SHOULD this delta land? Layer 2: CognitiveShader (layer_mask + combine + contra) — HOW to dispatch Layer 1: BindSpace columns (multi-lane views) — WHAT data Layer 0: ndarray SIMD (F32x16, U8x64, ...) — HARDWARE Each layer has different temporal scope: L4 plans once per query, L3 gates per cycle, L2 dispatches per step, L1 reads per lane, L0 executes per instruction. All in one binary, one address space. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/INTEGRATION_PLAN_CS.md | 38 +++++++++++++++++++++++++++++++++++++ 1 file changed, 38 insertions(+) diff --git a/docs/INTEGRATION_PLAN_CS.md b/docs/INTEGRATION_PLAN_CS.md index 57cfb3ae..d27e8c1e 100644 --- a/docs/INTEGRATION_PLAN_CS.md +++ b/docs/INTEGRATION_PLAN_CS.md @@ -164,6 +164,44 @@ Multi-target Bundle merge: new = majority_vote([old, value_A, value_B]) No locks. No races. XOR is its own inverse — you can always back out. +## The 5-Layer Stack + +``` +Layer 4: Planner strategies (16-19 in lance-graph-planner) + ├── CypherParse, GqlParse, GremlinParse, SparqlParse + ├── DPJoinEnum, RuleOptimizer, HistogramCost + ├── SigmaBandScan, MorselExec + ├── TruthPropagation, CollapseGateStrategy + ├── StreamPipeline, JitCompile, WorkflowDAG + ├── ExtensionPlanner, AutocompleteCache + └── [2-3 more] + → Decides WHICH shader/gate combination runs per cycle + +Layer 3: CollapseGate (enum Flow/Block/Hold) + → Decides SHOULD this delta land? + +Layer 2: CognitiveShader (layer_mask + combine + contra) + → Decides HOW to dispatch across 8 predicate planes + +Layer 1: BindSpace columns (read-only, multi-lane views) + → The WHAT (content + topic + angle + causality + qualia + ...) + +Layer 0: ndarray SIMD (F32x16, U8x64, F16x32, F64x8) + → The hardware (popcount, gather, FMA, compare) +``` + +Each layer has a different temporal scope: +- **L4** plans once per query (milliseconds) +- **L3** gates per commit cycle (microseconds) +- **L2** dispatches per step (nanoseconds) +- **L1** reads per lane (nanoseconds, zero-copy) +- **L0** executes per instruction (sub-nanosecond) + +The planner strategies compile the 5D stream execution plan. The +CognitiveShader runs it. The CollapseGate decides what commits. +The BindSpace stores the committed generation. The SIMD executes +each primitive. All in one binary, one address space, one pipeline. + ## Integration Plan (prioritized by era) ### Phase 1 — Harden Foundation (Era 6 + 7) From 8f3977a4ca90d229e6016819475eeb889ef0e988 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:34:43 +0000 Subject: [PATCH 07/13] =?UTF-8?q?docs:=20ThinkingStyleStrategy=20=E2=80=94?= =?UTF-8?q?=20grammar=20triangle=20+=20spectroscopy=20as=20planner=20input?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Layer 4 planner strategies include ThinkingStyleStrategy, which reads: - Grammar triangle (NSM primes, causality flow, 18D qualia) - Spectroscopy IIC texture (between-lines sensing) → picks one of 36 ThinkingStyles → configures CognitiveShader (layer_mask + combine + contra + density) The triangle + spectroscopy isn't a separate feature — it's the input transducer for the ThinkingStyleStrategy. Text in, style selected. The agent adapts to what the user is doing, not just what they're saying. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- docs/INTEGRATION_PLAN_CS.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/INTEGRATION_PLAN_CS.md b/docs/INTEGRATION_PLAN_CS.md index d27e8c1e..590406fb 100644 --- a/docs/INTEGRATION_PLAN_CS.md +++ b/docs/INTEGRATION_PLAN_CS.md @@ -174,6 +174,10 @@ Layer 4: Planner strategies (16-19 in lance-graph-planner) ├── TruthPropagation, CollapseGateStrategy ├── StreamPipeline, JitCompile, WorkflowDAG ├── ExtensionPlanner, AutocompleteCache + ├── ThinkingStyleStrategy (reads grammar triangle + spectroscopy) + │ ↑ inputs: NSM primes, causality flow, 18D qualia, + │ IIC texture from spectroscopy + │ ↓ output: which CognitiveShader (analytical / creative / ...) └── [2-3 more] → Decides WHICH shader/gate combination runs per cycle From 88f0378a8afda63f8aa4ac7d8ab47fcb351e502f Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:36:50 +0000 Subject: [PATCH 08/13] docs: update agent knowledge with full session architecture MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Complete rewrite of cognitive-shader-architecture.md: - 5-layer stack (planner → CollapseGate → shader → BindSpace → SIMD) - 4 data patterns (slice window, microcopy, gate, multi-lane views) - BindSpace as read-only universal address space - Fingerprint decomposition verified (204 = 6 × 34) - ThinkingStyleStrategy with grammar triangle + spectroscopy input - CollapseGate as existing write-gate protocol - Struct-of-arrays as address dimensions, not record format - ndarray::simd::* namespace discipline - Integration priorities P0-P3 - Pending debt carried across sessions - Ontological revolution: weights as seeds, shader as model https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- .../cognitive-shader-architecture.md | 318 +++++++++++++++--- 1 file changed, 262 insertions(+), 56 deletions(-) diff --git a/.claude/knowledge/cognitive-shader-architecture.md b/.claude/knowledge/cognitive-shader-architecture.md index 897aa056..5e8211e8 100644 --- a/.claude/knowledge/cognitive-shader-architecture.md +++ b/.claude/knowledge/cognitive-shader-architecture.md @@ -1,61 +1,267 @@ -# Cognitive Shader Architecture — Session 2026-04-18 +# Cognitive Shader Architecture — Session 2026-04-18 (FINAL) -> READ BY: all agents working on inference, codec, thinking-engine, learning, holograph +> READ BY: all agents working on inference, codec, thinking-engine, +> learning, holograph, planner strategies, BindSpace integration ## Status: FINDING (measured, not conjecture) -### Cascade Inference -- 11-13x speedup over brute-force cosine on real Qwen3-TTS weights -- 100% argmax match (zero quality loss) -- Sign-bit fingerprint + Hamming popcount pre-filter → exact cosine on 3% -- TurboQuant KV cache: 3.2x memory reduction, 13x attention speedup, 100% argmax - -### Codec Findings -- 67 codecs tested: Hadamard > SVD, full-rank > narrow, i4+i2 cascade -- ICC 0.999 on pairwise cosine, but argmax fails at k=64 on hard tensors -- XOR-adaptive: sign-flip per-dimension precision → 81% argmax on hardest tensor -- CLAM-adaptive: LFD-driven precision → 97% on KV projections -- Holographic residual: sign-only gets cos 0.6-0.75, needs magnitude slots - -### Architecture Decision -- **Don't compress weights lossy for inference** (breaks argmax) -- **Accelerate search instead** (cascade gives speed, original weights give quality) -- **TurboQuant on KV cache** (gain-shape split, cascade-compatible fingerprints) -- **Holographic memory for codebook** (slot-encoded phase+magnitude, future work) - -### Key Types -- `Fingerprint<256>` — canonical 16K bit vector (ndarray, const-generic) -- `CausalEdge64` — u64 packed SPO+NARS+Pearl+plasticity -- `CognitiveShader` — 8 predicate planes × 64×64 topology × bgz17 metric -- `TurboQuantEntry` — gain(BF16) + shape(i4) + fingerprint(sign bits) -- `HadCascadeTensor` — WHT + i4 + i2 cascade codec -- `VectorWidth` — LazyLock W8K(deprecated)/W16K(production) - -### Crate Layout (post-session) -``` -ndarray — Fingerprint<256>, WHT, i2/i4 quant, kmeans, cascade, CLAM -holograph — BitpackedVector (→ migrate to Fingerprint<256>), slot encoding, resonance -learning — 16 modules from ladybug-rs (wip-gated), 300K+ LOC -lance-graph-cognitive — grammar + world (compiling), spo (wip-gated) -bgz-tensor — HadCascade, TurboQuant KV, adaptive/xor/holographic codecs -causal-edge — CausalEdge64, NarsTables, CausalNetwork -p64-bridge — CognitiveShader, style params, palette addressing -thinking-engine — unified surface (to absorb learning + cognitive) -``` - -### Endgame: GGUF → Holographic Memory → Cognitive Shader Inference -``` -GGUF weights → hydrate into palette + fingerprints + holographic memory - → CognitiveShader cascade per layer (no matmul, no FP) - → CausalEdge64 output (SPO + NARS) - → 4096 COCA codebook → output token -``` - -### Pending Debt -1. Unify Fingerprint types (holograph BitpackedVector → ndarray Fingerprint<256>) -2. Enable learning crate (rustynum→ndarray migration, 124 errors) -3. Container/CogRecord port to lance-graph-contract -4. GPTQ Hessian compensation for argmax stability -5. Holographic magnitude slot encoding -6. CognitiveShader → thinking-engine end-to-end wiring +--- + +## The 5-Layer Stack + +``` +Layer 4: Planner strategies (16-19 in lance-graph-planner) + ├── Parse: Cypher/GQL/Gremlin/SPARQL + ├── Optimize: DPJoin, Rule, Histogram, SigmaBand, Morsel + ├── Execute: TruthPropagation, CollapseGate, StreamPipeline, JIT + ├── Workflow: WorkflowDAG, ExtensionPlanner, AutocompleteCache + ├── ThinkingStyleStrategy (grammar triangle + spectroscopy in) + │ ↑ reads: NSM primes, causality flow, 18D qualia, IIC texture + │ ↓ picks: one of 36 ThinkingStyles → shader config + └── [2-3 more] + → Decides WHICH shader/gate combination runs per cycle + → Temporal scope: milliseconds per query + +Layer 3: CollapseGate (enum Flow/Block/Hold) + → Decides SHOULD this delta land? + → Existing: ndarray::hpc::bnn_cross_plane::CollapseGate + → MergeMode: Xor (single), Bundle (majority), Superposition + → Temporal scope: microseconds per commit cycle + +Layer 2: CognitiveShader (née Blumenstrauß — renamed this session) + → layer_mask + combine + contra + density_target + → 8 predicate planes × 64×64 topology × bgz17 metric + → Existing: p64-bridge::StyleParams + → Temporal scope: nanoseconds per step + +Layer 1: BindSpace columns (read-only, multi-lane views) + → The WHAT (content + topic + angle + causality + qualia + temporal + shader) + → Struct-of-arrays: each dimension independently Hamming-sweepable + → Temporal scope: nanoseconds per lane, zero-copy + +Layer 0: ndarray SIMD (F32x16, U8x64, F16x32, F64x8) + → Hardware primitives (popcount, gather, FMA, compare) + → Temporal scope: sub-nanosecond per instruction +``` + +--- + +## The Four Data Patterns + +| Pattern | Ownership | Example | +|---|---|---| +| **Slice window** | `&[T]` zero-copy, N-aligned | `array_window` feeding SIMD batches | +| **Microcopies** | Owned `Copy` values on stack | CausalEdge64, Band, TruthValue, ThinkingStyle | +| **Write-back gate** | Through CollapseGate | XOR (single) / Bundle (multi) / Superposition (ambiguous) | +| **Multi-lane views** | Same Arc, multiple SIMD widths | PaletteTable as U8x64 / F16x32 / F32x16 / F64x8 | + +--- + +## BindSpace = Read-Only Address Space + +Not a database, not a storage layer — the **universal connective tissue**. + +- 64-bit address = 16-bit type + 48-bit content hash +- All programs (codecs, shaders, learning, grammar, search, spectroscopy) + emit and consume the same addresses +- Writers hold owned microcopies, never mutate BindSpace directly +- Updates flow through CollapseGate (Flow = apply, Block = reject, Hold = queue) +- XOR is self-inverse → always reversible, no locks needed +- Bundle is majority-vote → overlapping writers resolve via consensus +- Superposition holds all variants when no clear winner + +--- + +## Fingerprint Decomposition (verified this session) + +``` +Fingerprint<256> (16,384 bits = 2 KB) + │ + ├── 204 bytes = 6 × 34 (verified: bgz-tensor/examples/variance_audit.rs:260) + │ └── 6 CAM-PQ subspaces × Base17 (17 dims × i16 = 34 bytes each) + │ └── SPO-COCA codebook natural dimension + │ + ├── 6 bytes: CAM-PQ address (one palette index per subspace) + │ └── NOT "SPO × 3" — 6 subspaces × 8 bits + │ + ├── 4 bytes: HHTL-D (HEEL 2b + HIP 4b + TWIG 8b + polarity 1b + BF16 residual) + │ └── Tree address into bgz17 palette + │ + ├── 1 byte: bgz17 palette archetype (256 entries) + │ + └── 8 bytes: CausalEdge64 (S 8b + P 8b + O 8b + NARS 16b + meta 24b) + └── S, P, O each index into same 256-palette + └── Adjacent to P64 (S/4, O/4) = 64×64 block + └── 4096 COCA = verb vocabulary (0xFFF), NOT a vector width +``` + +--- + +## Cascade Inference (measured) + +- **11-13x speedup** over brute-force cosine on Qwen3-TTS weights +- **100% argmax match** (zero quality loss) +- Sign-bit fingerprint + Hamming popcount → reject 97% → exact on 3% +- **TurboQuant KV cache**: 3.2x memory, 13x attention speedup, 100% argmax +- **TTS e2e validated**: 225/225 codec tokens through 33 layers +- **611M SPO lookups/sec**, 17K tokens/sec, 388 KB RAM + +--- + +## Codec Findings (67-codec sweep) + +- Hadamard > SVD (no training, deterministic) +- Full-rank > narrow (cap ICC ~0.5 at narrow-16) +- i4+i2 cascade → ICC 0.999 on pairwise cosine +- BUT argmax fails at k=64 on hard tensors (near-orthogonal rows) +- XOR-adaptive (sign-flip per-dim): 81% argmax on hardest tensor +- CLAM-adaptive (LFD precision): 97% on KV projections +- **Architecture decision**: don't compress weights lossy for inference +- **Accelerate search instead** (cascade gives speed, weights give quality) + +--- + +## AGI Typing: Struct-of-Arrays as Address Dimensions + +**Not a record format** — it's the BindSpace address dimensions. Each +dimension is an independently Hamming-sweepable fingerprint column. +The AGI query is an AND across independent cascades. + +```rust +pub struct BindSpaceColumns { + pub content: Vec>, // WHAT + pub topic: Vec>, // ABOUT WHAT + pub angle: Vec>, // FROM WHERE + pub causality: Vec, // WHY/HOW + pub qualia: Vec<[f32; 18]>, // FEELS LIKE + pub temporal: Vec, // WHEN + pub shader: Vec, // WHO produced this +} +``` + +Per cycle: cascade each column independently, intersect survivors, +exact step on the final ~50 candidates. ~2.3ms for 1M records × 5 dims. + +--- + +## Namespace Discipline + +Lance-graph code uses `ndarray::simd::*` as the ONLY SIMD namespace. +The internal `ndarray::hpc::*` paths are private. Consumers write: + +```rust +use ndarray::simd::{F32x16, U8x64, Fingerprint, MultiLaneColumn, array_window}; +``` + +If a type isn't in `ndarray::simd::*`, it's implementation detail. +This keeps the foundation API surface small and stable — changes +inside `ndarray::hpc::*` never break lance-graph consumers. + +--- + +## Crate Layout (post-session) + +``` +ndarray — SIMD types (F32x16, U8x64...), Fingerprint, + MultiLaneColumn, WHT, kmeans, CLAM, cascade, + VectorWidth config (LazyLock) + Namespace: ndarray::simd::* (public), ndarray::hpc::* (private) + +holograph — BitpackedVector (→ migrate to Fingerprint<256>), + slot encoding, resonance VectorField, HDR cascade + (10K→16K migrated, 9 pre-existing compile errors) + +learning — Standalone crate with 16 modules from ladybug-rs + (300K+ LOC): cam_ops (158K), cognitive_styles + RL, + quantum_ops, dream, scm, feedback, rl_ops, causal_ops, + cognitive_frameworks. All wip-gated. + +lance-graph-cognitive — grammar + world COMPILING; spo, search, fabric, + spectroscopy, container_bs, core_full wip-gated + (full ladybug-rs import, 630K LOC) + +bgz-tensor — HadCascade codec, TurboQuant KV, + adaptive/xor/holographic codecs, Base17, HHTL-D + +causal-edge — CausalEdge64 (u64 packed), NarsTables (256×256 lookup), + CausalNetwork (CSR over edges) + +p64-bridge — CognitiveShader (renamed from Blumenstrauß), + edge → palette addressing, style params, semiring modes + +bgz17 — PaletteSemiring (256×256 distance + compose tables), + Base17 canonical, palette VSA + +thinking-engine — To absorb learning + cognitive into unified surface + (cognitive_stack, ghosts, persona, qualia, world_model) + +lance-graph-contract — NarsTruth, ThinkingStyle (36), MulAssessment, + PlannerContract. To receive: Container 16K, + CollapseGate extensions, BindSpace column types. +``` + +--- + +## Integration Priority + +**P0 (harden foundation):** +1. Unify Fingerprint type (kill `BitpackedVector`, use `Fingerprint<256>`) +2. Port Container/CogRecord to lance-graph-contract (16K width) +3. Extend CollapseGate with GateDecision struct (Xor/Bundle/Superposition) +4. CognitiveShader → thinking-engine wire-through + +**P1 (BindSpace address substrate):** +5. BindSpace column types in contract (AGI 7 dimensions) +6. Cascade per column implementation +7. ThinkingStyleStrategy planner (reads grammar + spectroscopy) +8. Luftschleuse→CollapseGate write protocol across crates + +**P2 (shader stream):** +9. 5D stream cycle loop (topic → angle → causality → qualia → exact) +10. Per-cycle shader dispatch via planner strategy + +**P3 (endgame):** +11. GGUF hydration pipeline (weights → palette + fingerprints + holographic) +12. Cognitive shader inference loop (no matmul, no FP) +13. Merge learning + cognitive crates into thinking-engine + +--- + +## Pending Debt (carried from session) + +1. holograph 10K→16K migration: 9 compile errors remain (Arrow/GraphBLAS API) +2. learning crate: 124 errors in wip modules (rustynum→ndarray sed) +3. SPO wip modules: reference `crate::core::rustynum_accel::*` +4. Container/CogRecord not yet in contract (BindSpace substrate missing) +5. GPTQ Hessian compensation TODO in adaptive_codec.rs +6. Holographic magnitude slot encoding (sign-only gets cos 0.6-0.75) 7. VectorWidth LazyLock not yet consumed by any module +8. Burn + ndarray backend wiring (research done, not wired) + +--- + +## Key Files for Next Session + +- `docs/COGNITIVE_SHADER_HYDRATION.md` — endgame architecture +- `docs/INTEGRATION_PLAN_CS.md` — 5-layer stack, CollapseGate, 4 data patterns +- `docs/BINDSPACE_MIGRATION_GAP.md` — 7 critical BindSpace pieces missing +- `docs/COGNITIVE_MERGE_MAP.md` — rustynum→ndarray substitution table +- `docs/HISTORICAL_CONTEXT.md` — 8 eras, era tags for prioritizing +- `docs/bench_qwen3_tts_62codecs.md` + `bench_gemma4_e2b_62codecs.md` — codec sweep data + +--- + +## The Ontological Revolution + +Weights are not parameters to compress — they are **seeds** for +holographic memory. Each seed can exist in vast parallel instances. +Each instance feeds upstream learning via CausalEdge64 branching. +Each branch runs its own CognitiveShader per cycle as a 5D stream. + +The weights don't define the model. The weights SEED the holographic +memory. The CognitiveShader IS the model. The cascade IS the inference. +The edges ARE the knowledge. The learning IS the branching. + +The gazillions of programs compile into the same binary because they +all emit and consume the same 64-bit BindSpace addresses. One XOR. +One sweep. One lookup. Regardless of origin. From 63ec23855448a59b67d0234099dddbb616f5535e Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:40:11 +0000 Subject: [PATCH 09/13] docs: 7-layer stack with GPU/APU + LanceDB thought stream + cycle fingerprint MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Extended the stack: Layer 6: LanceDB cold persistence — every thought stream persisted, retrievable via Cypher/SQL, feeds back into thinking/replay Layer 5: GPU/APU (optional, shared memory) — meta operations CPU can't handle without batching. APU/iGPU/unified memory avoids PCIe overhead. Complementary to CPU cascade. Layer 4 emits cycle_fingerprint per cycle: bind(triangle, spectroscopy, style, shader_mask, causal_state, retrieval_context) → cache key (AutocompleteCache) → retrieval key (LanceDB Hamming sweep) → replay seed (dream consolidation) → upstream cursor (CausalEdge64 branching) One fingerprint = one unit of thought. Persisted, retrievable, bindable back into future cycles as "I've been here before." The feedback loop closes: sense → plan → shade → cascade → gate → persist → retrieve → sense (next cycle). https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- .../cognitive-shader-architecture.md | 79 ++++++++++++++++++- 1 file changed, 78 insertions(+), 1 deletion(-) diff --git a/.claude/knowledge/cognitive-shader-architecture.md b/.claude/knowledge/cognitive-shader-architecture.md index 5e8211e8..9acc3a24 100644 --- a/.claude/knowledge/cognitive-shader-architecture.md +++ b/.claude/knowledge/cognitive-shader-architecture.md @@ -7,9 +7,25 @@ --- -## The 5-Layer Stack +## The 7-Layer Stack (5 core + 2 boundary) ``` +Layer 6: Cold persistence (LanceDB — thought stream buffer) + → Per-thought stream: every emitted CausalEdge64 / CognitiveRecord + → Feedback into thinking (RAG from past thoughts) + → Replay (dream consolidation, counterfactual simulation) + → Cross-session continuity + long-term memory + → Temporal scope: seconds-to-months, columnar + +Layer 5: GPU/APU meta operations (OPTIONAL, shared memory) + → APU / iGPU / Apple unified memory: no PCIe copy overhead + → Handles ops CPU can't: large tensor contractions, parallel + rollouts, meta-learning across millions of thoughts + → Complementary to CPU cascade, not replacement: + - CPU cascade: 2400M lookups/sec, no batching, natural fit + - GPU meta: batched workloads CPU can't match + → Temporal scope: microseconds for batch, overlaps L1-L3 + Layer 4: Planner strategies (16-19 in lance-graph-planner) ├── Parse: Cypher/GQL/Gremlin/SPARQL ├── Optimize: DPJoin, Rule, Histogram, SigmaBand, Morsel @@ -18,8 +34,12 @@ Layer 4: Planner strategies (16-19 in lance-graph-planner) ├── ThinkingStyleStrategy (grammar triangle + spectroscopy in) │ ↑ reads: NSM primes, causality flow, 18D qualia, IIC texture │ ↓ picks: one of 36 ThinkingStyles → shader config + │ ↓ EMITS: cycle_fingerprint = Fingerprint<256> + │ bind(triangle, spectroscopy, style, shader_mask, causal_state) + │ → cache key, retrieval key, replay seed, upstream cursor └── [2-3 more] → Decides WHICH shader/gate combination runs per cycle + → Per cycle: one cycle_fingerprint captures entire decision → Temporal scope: milliseconds per query Layer 3: CollapseGate (enum Flow/Block/Hold) @@ -44,6 +64,63 @@ Layer 0: ndarray SIMD (F32x16, U8x64, F16x32, F64x8) → Temporal scope: sub-nanosecond per instruction ``` +## The Feedback Loop (sense → plan → act → persist → retrieve) + +``` +Text in + ↓ +Layer 4 ThinkingStyleStrategy (grammar + spectroscopy) + ↓ style selected +Layer 2 CognitiveShader dispatched + ↓ layer_mask + combine + contra +Layer 1 BindSpace columns cascaded (L0 SIMD) + ↓ survivors +Layer 3 CollapseGate decides Flow/Block/Hold + ↓ committed CausalEdge64 +Layer 5 GPU meta ops (if batch available — replay, consolidation) + ↓ +Layer 6 LanceDB persists thought stream + ↓ available for retrieval +Next cycle reads past thoughts via RAG → feeds back into L4 planner +``` + +The loop closes through LanceDB. Every thought persists. Past thoughts +retrievable via Cypher/SQL on the cold path. Current thoughts computed +on the hot path. GPU meta fills the gap for batch workloads the CPU +cascade can't handle naturally. + +## Cycle Fingerprint (Layer 4 output) + +Each cycle, Layer 4 emits a `Fingerprint<256>` that captures the full +execution context — not just which style was picked, but a reproducible +hash of the entire decision: + +```rust +cycle_fingerprint = bind( + triangle_fp, // NSM + causality + qualia from grammar + spectroscopy_fp, // IIC texture from text + style_fp, // which of 36 ThinkingStyles + shader_mask, // which 8 predicate planes active + causal_state_fp, // current CausalEdge64 branch cursor + retrieval_context_fp // what was retrieved from LanceDB this cycle +) +``` + +This one fingerprint serves four purposes: + +1. **Cache key** — AutocompleteCacheStrategy: same fingerprint = same + result → skip the cycle entirely +2. **Retrieval key** — LanceDB lookup: "find similar past cycles" + (Hamming sweep on the cycle fingerprint column) +3. **Replay seed** — dream consolidation: reconstruct what the agent + was thinking from the fingerprint +4. **Upstream cursor** — CausalEdge64 branching: mark where this + cycle's outputs fit in the causal trajectory + +The cycle fingerprint is the unit of thought. One per cycle. Persisted +to LanceDB. Queryable across sessions. Bindable back into the current +cycle as "I've been here before." + --- ## The Four Data Patterns From 2f4200e2dc68aed636ba997b2228851f4366fe2e Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:47:39 +0000 Subject: [PATCH 10/13] =?UTF-8?q?docs:=20session=20handoff=20=E2=80=94=20p?= =?UTF-8?q?riorities,=20quick=20wins,=20agent=20scopes?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit For next session (Opus 4.7, 1M context, deep thinking): Quick Wins (QW1-QW7, ≤1hr each, P0): - Unify Fingerprint<256> - Port Container type alias to contract - Add as_u8x64() to Fingerprint - Add MergeMode enum to contract - Wire ndarray::simd::* re-exports - rustynum→ndarray sed pass P1 Foundation (2-4hr): rustynum migration complete, CognitiveShader wire-through, CollapseGate write protocol P2 BindSpace Columns (4-8hr): column types, cascade per column, ThinkingStyleStrategy planner P3 Shader Stream (8-16hr): 5D cycle loop, GGUF hydration, cognitive shader inference loop Agent scopes defined per task (container-architect, bus-compiler, palette-engineer, truth-architect, etc.). Opus 4.7 context budget: 400-500K typical, 500K+ reserve for hardest multi-crate refactors where you need everything visible. --- docs/SESSION_HANDOFF_PRIORITIES.md | 215 +++++++++++++++++++++++++++++ 1 file changed, 215 insertions(+) create mode 100644 docs/SESSION_HANDOFF_PRIORITIES.md diff --git a/docs/SESSION_HANDOFF_PRIORITIES.md b/docs/SESSION_HANDOFF_PRIORITIES.md new file mode 100644 index 00000000..e01b2025 --- /dev/null +++ b/docs/SESSION_HANDOFF_PRIORITIES.md @@ -0,0 +1,215 @@ +# Session Handoff — Priorities, Quick Wins, Agent Scopes + +> For next session (Opus 4.7, 1M context, deep thinking). +> All architecture docs at `.claude/knowledge/cognitive-shader-architecture.md`. + +## Deep Thinking Effort — the key opportunities + +With 1M context + deep thinking, the session can hold BOTH entire +codebases (ladybug-rs + lance-graph + ndarray ~1M LOC combined) AND +the architecture docs in mind simultaneously. Use that for: + +1. **Cross-repo type alignment** — see all 4 Fingerprint copies at once +2. **Whole-chain refactors** — rustynum→ndarray migration without forgetting callers +3. **Architectural invariants** — verify the 5-layer stack compiles end-to-end +4. **Era detection** — recognize which decade's assumptions a module carries + +Don't burn deep thinking on single-file edits. Burn it on: +- Multi-crate refactors (fingerprint unification) +- Invariant verification (CollapseGate write protocol end-to-end) +- Architectural decisions (where does the cycle_fingerprint live) + +--- + +## Quick Wins (≤1 hour each, P0) + +| # | Task | Impact | Blocker? | +|---|---|---|---| +| QW1 | Unify `Fingerprint<256>` — replace `BitpackedVector` in holograph | Kills type duplication | Yes for P1+ | +| QW2 | `impl From` between ndarray Fingerprint ↔ holograph's types | Bridge for existing callers | No | +| QW3 | Port `Container` = `Fingerprint<256>` type alias to contract | BindSpace foothold | Yes for P2+ | +| QW4 | Add `as_u8x64()` to ndarray Fingerprint | Enables multi-lane SIMD path | Yes for L1 | +| QW5 | Add `MergeMode` enum to contract (Xor/Bundle/Superposition) | Completes CollapseGate protocol | Yes for L3 | +| QW6 | Wire `ndarray::simd::*` re-export surface (add Fingerprint, MultiLaneColumn) | Namespace discipline | No but clean | +| QW7 | Rustynum→ndarray sed pass on cognitive `crate::core::rustynum_accel::*` | Unblocks SPO wip modules | Medium | + +Do all 7 first. They're independent, small, and unblock everything downstream. + +--- + +## P1 — Foundation Hardening (2-4 hours) + +After quick wins, harden the foundation: + +**P1.1: Complete rustynum → ndarray migration** +- 124 errors in learning crate (cam_ops.rs dominates) +- Systematic sed + manual fix per file +- Enable modules one at a time behind `wip` flag +- Target: all learning modules compile without wip after migration + +**P1.2: CognitiveShader → thinking-engine wire-through** +- `thinking-engine::cognitive_stack` calls `p64-bridge::CognitiveShader` +- `CognitiveShader::cascade()` uses `bgz17::palette_semiring` +- Output: `CausalEdge64` emitted per step +- End-to-end test: text → style pick → shader → cascade → edge + +**P1.3: CollapseGate write protocol in contract** +- Extend existing `CollapseGate` enum with `GateDecision` struct +- `MergeMode`: Xor (single target), Bundle (majority), Superposition (keep all) +- Trait method: `fn commit(gate, delta, target) -> Generation` +- Test: overlapping writers resolve correctly + +--- + +## P2 — BindSpace Columns (4-8 hours) + +Build the AGI address substrate: + +**P2.1: BindSpace column types in contract** +```rust +pub struct BindSpaceColumns { + pub content: Arc<[Fingerprint<256>]>, + pub topic: Arc<[Fingerprint<256>]>, + pub angle: Arc<[Fingerprint<256>]>, + pub causality: Arc<[CausalEdge64]>, + pub qualia: Arc<[[f32; 18]]>, + pub temporal: Arc<[u64]>, + pub shader: Arc<[u8]>, + pub cycle: Arc<[Fingerprint<256>]>, // cycle_fingerprint per row +} +``` + +**P2.2: Cascade per column implementation** +- Hamming sweep on fingerprint columns (SIMD popcount) +- Range filter on scalar columns (qualia, temporal) +- Intersect bitmaps across dimensions +- Exact step on survivors (~50 records) + +**P2.3: ThinkingStyleStrategy planner** +- Read grammar triangle + spectroscopy from L4 input +- Pick one of 36 ThinkingStyles +- Emit cycle_fingerprint per cycle +- Feed into CognitiveShader config + +--- + +## P3 — Shader Stream Loop (8-16 hours) + +**P3.1: 5D stream cycle loop** +- Read columns, cascade, intersect, emit edge +- cycle_fingerprint → LanceDB persistence +- Retrieval from LanceDB as RAG input to next cycle + +**P3.2: GGUF hydration pipeline** +- Load weights → palette + fingerprints + holographic memory +- Emit CausalEdge64 wiring per layer +- Store in BindSpace columns + +**P3.3: Cognitive shader inference loop** +- No matmul. No FP in hot path. +- Per token: 5 cascades, intersect, gate, persist. +- Target: 10ms per token on CPU with cascade. + +--- + +## Agent Scopes (who does what) + +| Agent | Primary Scope | P0 Tasks | P1+ Tasks | +|---|---|---|---| +| **container-architect** | BindSpace types | QW3 (Container port), QW4 (as_u8x64) | P2.1 column types | +| **bus-compiler** | CognitiveShader dispatch | QW5 (MergeMode) | P1.2 shader wire-through | +| **palette-engineer** | bgz17 / HHTL-D / codec | QW1 (Fingerprint unify) | P3.2 GGUF hydration | +| **family-codec-smith** | Codec migration | QW7 (rustynum→ndarray sed) | P1.1 learning migration | +| **thought-struct-scribe** | Struct-of-arrays | — | P2.1 column types | +| **perspective-weaver** | Topic/angle dimensions | — | P2.1 (topic, angle cols) | +| **resonance-cartographer** | LanceDB retrieval | — | P3.1 RAG loop | +| **trajectory-cartographer** | CausalEdge64 branching | — | P3.1 causal state cursor | +| **truth-architect** | NARS + CollapseGate | QW5 | P1.3 write protocol | +| **ripple-architect** | End-to-end sensing loop | — | P3.3 full stream | +| **savant-research** | Cross-era provenance | — | Era tagging during migration | +| **contradiction-cartographer** | Detect conflicts | Ongoing | Ongoing | +| **adk-coordinator** | Ensemble dispatch | — | Coordinate P2+ | +| **adk-behavior-monitor** | Anti-pattern detection | Ongoing | Ongoing | +| **integration-lead** | Cross-crate wiring | QW6 (simd re-exports) | P1.2, P2.1 | + +**Single-agent tasks** (no coordinator needed): QW1-QW7, P1.3, P2.2 +**Multi-agent tasks** (use adk-coordinator): P1.2, P2.1, P3.1, P3.3 + +--- + +## Updates Needed on Agents + +Most agents already reference `CognitiveShader` (after the Blumenstrauß +rename this session). The updates needed: + +### container-architect +- Add awareness: Container = `Fingerprint<256>` type alias at 16K width +- Read-only semantics via `Arc<[u64; 256]>` +- BindSpace column types (7 dimensions, struct-of-arrays) +- cycle_fingerprint is the 8th column (emitted by L4) + +### bus-compiler +- CognitiveShader is in `p64-bridge` (already renamed) +- Layer 2 in the 7-layer stack +- Reads: layer_mask + combine + contra + density_target from StyleParams +- Emits: CausalEdge64 stream (one per step) + +### thought-struct-scribe +- Struct-of-arrays = BindSpace address dimensions (not records) +- 7 columns: content, topic, angle, causality, qualia, temporal, shader +- Plus cycle_fingerprint emitted by Layer 4 + +### perspective-weaver +- Topic and Angle are two of the 7 BindSpace dimensions +- Each is `Arc<[Fingerprint<256>]>` +- Independently Hamming-sweepable + +### truth-architect +- NARS InferenceType (5 variants) already in contract +- CollapseGate (Flow/Block/Hold) already in ndarray +- New: GateDecision struct with MergeMode (Xor/Bundle/Superposition) + +### resonance-cartographer +- LanceDB is Layer 6 (cold persistence) +- Per-cycle thought stream: cycle_fingerprint + CausalEdge64 output +- Retrieval via Hamming sweep on cycle_fingerprint column +- Feeds back as RAG into Layer 4 planner input + +--- + +## Opus 4.7 Context Budget Strategy + +With 1M context: + +**Always in context (~100K tokens):** +- `.claude/knowledge/cognitive-shader-architecture.md` — the canonical doc +- `docs/INTEGRATION_PLAN_CS.md` — the integration plan +- `docs/HISTORICAL_CONTEXT.md` — era tags for era-aware refactoring +- Current session scratchpad + +**Load per task (~50-100K tokens):** +- Agent card(s) for the specific scope +- Relevant crate source (the ONE being modified) +- Its direct callers (1-2 crates) + +**Lazy-load when needed (~50K tokens each):** +- Bench results (`docs/bench_*.md`) +- Specific knowledge files (phi-spiral, bf16-hhtl-terrain, etc.) + +**Reserve (~200K tokens):** +- Exploration, agent-spawned research, deep thinking scratchpad + +Total typical usage: 400-500K tokens. Keep 500K+ in reserve for the +hardest refactors where you need to see everything at once. + +--- + +## Starting Points for Next Session + +1. Read `.claude/knowledge/cognitive-shader-architecture.md` +2. Pick 3-4 quick wins from the QW table above +3. Do them in parallel (independent, each ≤1 hour) +4. Then pick P1.1, P1.2, or P1.3 based on what's most blocked +5. Use `adk-coordinator` only for P2+ (multi-agent tasks) +6. Commit + push after each quick win (momentum) +7. PR after P1 (substantive milestone) From d605467ac139753ac2fc5af452fe13cb1c26956a Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 13:49:38 +0000 Subject: [PATCH 11/13] docs: blackboard + A2A protocol + semantic kernel RAG MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Existing: lance-graph-contract::a2a_blackboard (ExpertId, ExpertCapability, post/read/route). Wires into cognitive shader as a BindSpace column. The 'expert' dimension added to BindSpace columns: Agent A writes cycle_fingerprint + CausalEdge64 → blackboard column Agent B sweeps expert+topic columns → finds A's post RAG from LanceDB (Layer 6) → retrieves relevant past exchanges Planner produces cycle_fingerprint → shader → new edge The full stack IS a semantic kernel for RAG: - Hot path (L0-L3) = kernel compute engine - Cold path (L6 LanceDB) = RAG retrieval store - Blackboard column = A2A coordination channel - cycle_fingerprint = cross-agent identity Multiple agents share ONE BindSpace. No message queues. No serialization. XOR/popcount on shared fingerprint columns IS the message bus. Consensus via CollapseGate Bundle (majority vote). Agents don't call each other — they sweep each other's fingerprints. The blackboard is where thought streams cross. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- .../cognitive-shader-architecture.md | 45 ++++++++++++++++++- 1 file changed, 44 insertions(+), 1 deletion(-) diff --git a/.claude/knowledge/cognitive-shader-architecture.md b/.claude/knowledge/cognitive-shader-architecture.md index 9acc3a24..fa88e2f5 100644 --- a/.claude/knowledge/cognitive-shader-architecture.md +++ b/.claude/knowledge/cognitive-shader-architecture.md @@ -212,13 +212,56 @@ pub struct BindSpaceColumns { pub causality: Vec, // WHY/HOW pub qualia: Vec<[f32; 18]>, // FEELS LIKE pub temporal: Vec, // WHEN - pub shader: Vec, // WHO produced this + pub shader: Vec, // WHICH shader + pub expert: Vec, // WHICH agent posted (A2A) + pub cycle: Vec>, // cycle_fingerprint from Layer 4 } ``` Per cycle: cascade each column independently, intersect survivors, exact step on the final ~50 candidates. ~2.3ms for 1M records × 5 dims. +## Blackboard: A2A Protocol via BindSpace + +**Already exists**: `lance-graph-contract::a2a_blackboard` with +`ExpertId`, `ExpertCapability`, post/read/route pattern. + +The blackboard IS a BindSpace column (the `expert` dimension). Agent A +posts a cycle_fingerprint + CausalEdge64 → Agent B finds it via Hamming +sweep on the expert+topic columns → retrieves relevant history via +LanceDB RAG (Layer 6) → responds with its own cycle_fingerprint. + +``` +Agent A: + cycle → shader → CausalEdge64 → write to blackboard + ↓ + (expert=A, topic=X, cycle_fp=...) + ↓ + BindSpace column + ↓ +Agent B: + sweep expert column: "find things A posted" + sweep topic column: "filter to topic X" + RAG from LanceDB (Layer 6): "retrieve past exchanges" + → planner produces own cycle_fp + → shader → edge → write to blackboard +``` + +The entire cognitive shader stack IS a **semantic kernel** for RAG: +- The hot path (Layers 0-3) = the kernel compute engine +- The cold path (Layer 6 LanceDB) = the RAG retrieval store +- The blackboard column = the A2A coordination channel +- The cycle_fingerprint = the cross-agent identity + +Multiple agents share ONE BindSpace address space. No message queues. +No serialization. XOR/popcount on shared fingerprint columns IS the +message bus. Consensus via CollapseGate Bundle (majority vote). +Each agent's cycle_fingerprint is both its identity and its payload. + +This is the sem-kernel RAG realization: agents don't "call" each other, +they sweep each other's fingerprints. The blackboard is where thought +streams cross. + --- ## Namespace Discipline From 96d148f9be31934aefa0f41b5a2e3f25db2a6d7d Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 14:20:40 +0000 Subject: [PATCH 12/13] feat(contract): MergeMode + GateDecision for CollapseGate write protocol MergeMode: Xor | Bundle | Superposition GateDecision: gate(Flow/Block/Hold) + merge mode (2 bytes, Copy) Layer 3 in the 7-layer stack. Extends ndarray's CollapseGate enum with write-back semantics for the cognitive shader pipeline. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- .../lance-graph-contract/src/collapse_gate.rs | 48 +++++++++++++++++++ crates/lance-graph-contract/src/lib.rs | 1 + 2 files changed, 49 insertions(+) create mode 100644 crates/lance-graph-contract/src/collapse_gate.rs diff --git a/crates/lance-graph-contract/src/collapse_gate.rs b/crates/lance-graph-contract/src/collapse_gate.rs new file mode 100644 index 00000000..0ddffd8b --- /dev/null +++ b/crates/lance-graph-contract/src/collapse_gate.rs @@ -0,0 +1,48 @@ +//! CollapseGate write protocol — MergeMode + GateDecision. +//! +//! CollapseGate enum (Flow/Block/Hold) lives in ndarray::hpc::bnn_cross_plane. +//! This module adds the write-back protocol types consumed by the 7-layer stack. +//! +//! Layer 3: CollapseGate decides SHOULD this delta land? +//! MergeMode decides HOW overlapping writes merge. +//! GateDecision = gate + merge mode (owned microcopy, 2 bytes). + +/// How overlapping writers merge their deltas. +#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash)] +#[repr(u8)] +pub enum MergeMode { + /// XOR commit: `target ^= delta`. Self-inverse, reversible. + /// For single-target updates where order doesn't matter. + Xor = 0, + /// Bundle: majority vote across all pending deltas. + /// For multi-writer consensus (e.g., multiple agents posting to blackboard). + Bundle = 1, + /// Superposition: keep ALL deltas without resolution. + /// For ambiguous cases where we want to preserve all variants. + Superposition = 2, +} + +/// A gate decision: what the CollapseGate decided + how to merge. +/// Copy type, 2 bytes. The microcopy returned by gate evaluation. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub struct GateDecision { + /// Flow = apply delta. Block = reject. Hold = queue for next cycle. + pub gate: u8, // 0=Flow, 1=Block, 2=Hold (matches ndarray CollapseGate ordinals) + /// How to merge if Flow. + pub merge: MergeMode, +} + +impl GateDecision { + pub const FLOW_XOR: Self = Self { gate: 0, merge: MergeMode::Xor }; + pub const FLOW_BUNDLE: Self = Self { gate: 0, merge: MergeMode::Bundle }; + pub const FLOW_SUPER: Self = Self { gate: 0, merge: MergeMode::Superposition }; + pub const BLOCK: Self = Self { gate: 1, merge: MergeMode::Xor }; + pub const HOLD: Self = Self { gate: 2, merge: MergeMode::Xor }; + + #[inline] + pub fn is_flow(&self) -> bool { self.gate == 0 } + #[inline] + pub fn is_block(&self) -> bool { self.gate == 1 } + #[inline] + pub fn is_hold(&self) -> bool { self.gate == 2 } +} diff --git a/crates/lance-graph-contract/src/lib.rs b/crates/lance-graph-contract/src/lib.rs index cbf50588..9bc4c266 100644 --- a/crates/lance-graph-contract/src/lib.rs +++ b/crates/lance-graph-contract/src/lib.rs @@ -45,3 +45,4 @@ pub mod high_heel; pub mod literal_graph; pub mod exploration; pub mod orchestration_mode; +pub mod collapse_gate; From bc2ff9662080df87450eaa9b06872c64d2085e27 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 18 Apr 2026 14:21:41 +0000 Subject: [PATCH 13/13] =?UTF-8?q?feat(contract):=20Container=20+=20CogReco?= =?UTF-8?q?rd=20+=20ContentGeometry=20=E2=80=94=20BindSpace=20record=20typ?= =?UTF-8?q?es?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Container = [u64; 256] = 16K bits = 2 KB. Type alias, not newtype — same backing as ndarray::simd::Fingerprint<256>. Zero-cost, compatible. CogRecord = meta Container + content Container = 4 KB. Read-only after construction. Mutations via CollapseGate. ContentGeometry enum: Bitpacked16K, DenseF32, TripleSPO, EdgePacked. Tells consumers how to interpret Container 1. This is the BindSpace foothold in the contract crate. All 7 critical pieces from BINDSPACE_MIGRATION_GAP.md flow from this foundation. https://claude.ai/code/session_01SbYsmmbPf9YQuYbHZN52Zh --- crates/lance-graph-contract/src/container.rs | 64 ++++++++++++++++++++ crates/lance-graph-contract/src/lib.rs | 1 + 2 files changed, 65 insertions(+) create mode 100644 crates/lance-graph-contract/src/container.rs diff --git a/crates/lance-graph-contract/src/container.rs b/crates/lance-graph-contract/src/container.rs new file mode 100644 index 00000000..2c0799a6 --- /dev/null +++ b/crates/lance-graph-contract/src/container.rs @@ -0,0 +1,64 @@ +//! Container — the BindSpace record unit at 16K width. +//! +//! A Container is a `[u64; 256]` = 16,384 bits = 2 KB, 64-byte aligned. +//! It's the universal address unit — every program, every agent, every +//! shader emits and consumes Containers in the same BindSpace. +//! +//! The Container type is intentionally a type alias for `[u64; 256]`, +//! not a newtype. This keeps it zero-cost and compatible with +//! `ndarray::simd::Fingerprint<256>` (same backing store). +//! +//! CogRecord = metadata Container + content Container = 4 KB. +//! Read-only after construction. Mutations go through CollapseGate. + +/// Container = 256 × u64 = 16,384 bits = 2 KB. +/// Same backing as `ndarray::hpc::fingerprint::Fingerprint<256>`. +pub type Container = [u64; 256]; + +/// Container width in u64 words. +pub const CONTAINER_WORDS: usize = 256; + +/// Container width in bits. +pub const CONTAINER_BITS: usize = CONTAINER_WORDS * 64; + +/// Container width in bytes. +pub const CONTAINER_BYTES: usize = CONTAINER_WORDS * 8; + +/// A cognitive record = metadata + content. +/// 4 KB total. Read-only after construction. +#[derive(Clone, Debug)] +pub struct CogRecord { + /// Container 0: metadata (identity, NARS, edges, qualia, adjacency). + pub meta: Container, + /// Container 1: content (fingerprint, embedding, SPO, whatever geometry says). + pub content: Container, +} + +impl CogRecord { + /// Create from metadata + content containers. + pub fn new(meta: Container, content: Container) -> Self { + Self { meta, content } + } + + /// Zero record (both containers zeroed). + pub fn zero() -> Self { + Self { meta: [0u64; 256], content: [0u64; 256] } + } + + /// Total byte size. + pub const BYTE_SIZE: usize = CONTAINER_BYTES * 2; // 4096 +} + +/// Content geometry: how to interpret Container 1. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +#[repr(u8)] +pub enum ContentGeometry { + /// 16K bitpacked fingerprint (standard holographic). + Bitpacked16K = 0, + /// Dense f32 embedding (Jina, sentence-transformer). Truncated to fit 2KB. + DenseF32 = 1, + /// 3 × Fingerprint (Subject + Predicate + Object decomposition). + TripleSPO = 2, + /// Packed edge list (adjacency as content, not metadata). + EdgePacked = 3, +} diff --git a/crates/lance-graph-contract/src/lib.rs b/crates/lance-graph-contract/src/lib.rs index 9bc4c266..25ea8ec9 100644 --- a/crates/lance-graph-contract/src/lib.rs +++ b/crates/lance-graph-contract/src/lib.rs @@ -46,3 +46,4 @@ pub mod literal_graph; pub mod exploration; pub mod orchestration_mode; pub mod collapse_gate; +pub mod container;