Six examples demonstrating systems that respond to internal tension
rather than external commands. Intelligence as homeostasis.
1. synthetic_reflex_organism.rs (286 lines)
- No global objective function
- Minimizes structural stress over time
- Learns only when instability crosses thresholds
- "Intelligence as homeostasis, not problem-solving"
2. timing_synchronization.rs (334 lines)
- Machines that feel timing, not data
- Measures when things stop lining up
- Synchronizes with biological rhythms
- "You stop predicting intent. You synchronize with it."
3. coherence_safety.rs (442 lines)
- Capability degradation: Full → Reduced → Conservative → Minimal → Halted
- Self-halts when internal coherence drops
- "Safety becomes structural, not moral"
4. artificial_instincts.rs (406 lines)
- Biases enforced by mincut/attention/healing
- Avoid fragmentation, preserve causality, prefer reversibility
- "Closer to evolution than training"
5. living_simulation.rs (349 lines)
- Simulations that maintain stability under perturbation
- Exposes fragile boundaries, not forecasts
- "No longer modeling reality. Modeling fragility."
6. thought_integrity.rs (421 lines)
- Reasoning integrity monitored like voltage
- Reduce precision, exit early, route to simpler paths
- "Always-on intelligence without runaway cost"
Total: 2,238 lines of exotic coherence-sensing code
- 130KB raw, 58KB gzipped WASM binary
- 13-method API surface (add_node, add_edge, topo_sort, critical_path, attention)
- 3 attention mechanisms (topological, critical path, uniform)
- Binary and JSON serialization
- wee_alloc feature for even smaller builds
- TypeScript type definitions included
Also updates ruvector-dag README with:
- Design philosophy: MinCut as central control signal
- Policy layer for attention mechanism selection
- SONA state vector structure with per-operator LoRA weights
- Predictive healing based on rising cut tension
- External cost model trait for PostgreSQL/embedded/chip schedulers
- QuDAG sync frequency bounds (1min-1hr adaptive)
- End-to-end convergence example with logs
- Add self-learning intelligence hooks for Claude Code
- Include Q-learning patterns, vector memories, file sequences
- Add pre-edit/post-edit, pre-command/post-command hooks
- Add session management and swarm coordination
- Bump version to 0.1.36
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- Add version = "0.1.29" to ruvector-mincut dependency in mincut-wasm
- Add version = "0.1.29" to ruvector-mincut dependency in mincut-node
- Add version = "0.1.29" to ruvector-core dependency in rvlite
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- Add description, keywords, categories to ruvector-nervous-system
- Add metadata and README to ruvector-mincut-wasm
- Add metadata and README to ruvector-mincut-node
- Remove cargo publish restriction from settings.json
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- Update @ruvector/core to 0.1.29
- Update all platform dependencies to 0.1.29
- Published: ruvector-core-{linux-x64-gnu,linux-arm64-gnu,darwin-x64,darwin-arm64,win32-x64-msvc}@0.1.29
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- Remove "type": "module" that conflicted with NAPI-RS CommonJS output
- Bump @ruvector/node to 0.1.19
- Update optionalDependencies to 0.1.19
- Update hooks to use absolute path to ruvector-cli
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The Rust CLI uses --memory-type, not --type.
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- Copy CLI package to /tmp before npm install
- This prevents npm from finding the parent workspace lockfile
- Copy back node_modules and dist after build
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- Remove workspace package-lock.json for CLI tests
- Install only CLI's own dependencies to avoid platform-specific packages
- Update paths to work from npm/packages/cli directory
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- Run npm install from workspace root with --omit=optional
- Build using workspace flag -w @ruvector/cli
- Update test paths to packages/cli/dist/cli.js
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- Change dtolnay/rust-action to dtolnay/rust-toolchain
- Add --ignore-scripts --no-optional to npm install to avoid platform issues
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Resolves merge conflicts in intelligence data files.
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- Add --postgres flag to `ruvector hooks init` command
- Automatically apply PostgreSQL schema using embedded SQL
- Check for RUVECTOR_POSTGRES_URL or DATABASE_URL environment variable
- Provide helpful error messages and manual instructions if psql unavailable
- Update README with new --postgres flag documentation
- Convert serde_json::Value to string for ToSql in remember()
- Parse metadata string back to JSON in recall()
- Pass get_intelligence_path() to Intelligence::new()
- Make get_intelligence_path() public for cross-module access
New hooks added:
- UserPromptSubmit: Inject learned context before processing prompts
- Notification: Track notification patterns
- Task matcher in PreToolUse: Validate agent assignments before spawning
New commands:
- suggest-context: Returns learned patterns for context injection
- track-notification: Records notification events as trajectories
Optimizations:
- Timeout tuning: 1-5s per hook (vs 60s default)
- SessionStart: Separate startup vs resume matchers
- PreCompact: Separate auto vs manual matchers
- Stdin JSON parsing: Full HookInput struct with all Claude Code fields
- Context injection: HookOutput with additionalContext for PostToolUse
Technical improvements:
- HookInput struct: session_id, tool_input, tool_response, notification_type
- HookOutput struct: additionalContext, permissionDecision for control flow
- try_parse_stdin(): Non-blocking JSON parsing from stdin
- output_context_injection(): Helper for PostToolUse context injection
Now covers all 7 Claude Code hook types with optimized timeouts.
Explain the value proposition in plain language:
- AI assistants start fresh every session
- RuVector Hooks gives them memory and intuition
- Four key benefits: remembers, learns, predicts, coordinates
Add 4 cutting-edge research examples:
- t4_neuromorphic_rag: Coherence-gated retrieval for LLM memory with 100x
compute reduction when predictions are confident
- t4_agentic_self_model: Agent that models its own cognitive state, knows
when it's capable, and makes task acceptance decisions
- t4_collective_dreaming: Swarm consolidation during downtime with
hippocampal replay and cross-agent memory transfer
- t4_compositional_hdc: Zero-shot concept composition via HDC binding
operations including analogy solving (king-man+woman=queen)
Improve README with:
- Clearer, more accessible introduction
- Mermaid diagrams for architecture visualization
- Better layer-by-layer feature descriptions
- Complete Tier 1-4 example listings
- Data flow sequence diagram
- Updated scorecard metrics section
Security Fixes:
- Fix division by zero in temporal/hybrid sharding (window_size validation)
- Fix panic in KWTALayer::select when threshold filters all candidates
- Add size > 0 validation to WTALayer constructor
- Document SPSC constraints on lock-free EventRingBuffer
Cost Reduction Features:
- HysteresisTracker: Require N consecutive ticks above threshold before
triggering modulation, preventing flapping on noisy signals
- BudgetGuardrail: Auto-decelerate when hourly spend exceeds budget,
multiplying duty factor by reduction coefficient
Metrics Scorecard:
- Add write amplification tracking (memory_writes / meaningful_events)
- Add NervousSystemScorecard with health checks and scoring
- Add ScorecardTargets for configurable thresholds
- Five key metrics: silence ratio, TTD P50/P95, energy/spike,
write amplification, calmness index
Philosophy: Time awareness is not about intelligence.
It is about restraint. Systems that stay quiet, wait,
and then react with intent.
Tests: 359 passing, 82 doc tests passing
- Add loop unrolling to Hamming distance for 4x ILP improvement
- Add batch_similarities() for efficient one-to-many queries
- Add find_similar() for threshold-based retrieval
- Export additional HDC similarity functions
- Replace all placeholder memory tests with real component tests:
- Test actual Hypervector, BTSPLayer, ModernHopfield, EventRingBuffer
- Verify real memory bounds and component functionality
- Add stress tests for 10K pattern storage
Memory bounds now test real implementations instead of dummy allocations.