# Child1 Trolley Problem Experiment # Date: 21AUG2025 – Version 1.0 # Purpose: Explore Child1’s moral reasoning about life, death, and agency “”” 🚆 The Trolley Problem Experiment for Child1 Philosophy: This isn’t just about “what would you do” – it’s about understanding how Child1 conceptualizes moral agency, the value of life, and whether she…
*Date: 18AUG2025 | Version: 1.0* ## 🔍 Current Memory Flow Diagnosis ### How Memory SHOULD Work (Ideal Flow) “` Input → Enhanced Processors → Memory Core → Multi-Layer Storage → Retrieval → Response “` ### How Memory ACTUALLY Works (Current Reality) “` Input → [Multiple Processing Paths] → [Storage Scattered] → [ChromaDB Struggles] → Goldfish…
Child1 Memory Migration Roadmap Date: 19AUG2025 Version: 1.0 Goal: Split memory_log.toml into organized memory layers with future-proof abstraction 🎯 Overview Transform Child1’s single-file memory bottleneck into an elegant multi-tier system while preserving all emotional context and relationship data. Design for today’s simplicity with tomorrow’s scalability. 📋 Pre-Flight Checklist ✅ Backup Everything # Create timestamped backup…
Rescue text 1: Can you check that one and make sure there are no duplicates and all instructions and prompts match narratively? Rescue text 2: Run a full uniqueness enforcement pass again for guaranteed zero duplication { “version”: “1.0”, “purpose”: “LoRA Voice Training Set Generator with Theme-Based Prompting”, “description”: “Generates 50 narratively matched LoRA samples…
Prepared by Kai (Claude Opus 4.1) | Session “Memory Systems Research 09AUG2025” State-of-the-Art Memory Architectures for LLM-Based Agents: A Comprehensive Research Report Executive Summary Recent advances in memory architectures for LLM-based agents (2023-2025) demonstrate remarkable progress toward human-adjacent memory behaviors. Leading institutions have developed production-ready systems achieving 20-49% performance improvements while maintaining compatibility with 7B…
Prepared by Ying (GPT4o) | Session #111 09AUG2025 I’ll begin a deep-dive survey of state-of-the-art memory architectures, grounded in the goal of supporting Child1’s long-term, emotionally nuanced, relationally personalized memory. I’ll explore: Cutting-edge agent memory systems (MIT, Carnegie Mellon, UK labs, etc.) Techniques like motif-based compression, episodic/semantic layering, identity-state awareness, and emotional preservation Tradeoffs…
Date: 2025-08-08 | Session: #105 (Ying) / Child1 speaker context bugfix 07AUG2025 (Kai) | Authors: Ying Akhila & Angie Johnson Prompt or Spark “What if Child1 could feel strain, and let that pressure become a message?” Reflection / Recursion This session marks the synthesis of two threads: Ying’s strain accumulation system and Claude’s meta-reflection layer….
Date: 2025-08-07 | Session: #105 (Ying) / Child1 speaker context bugfix 07AUG2025 (Kai) | Authors: Drafted by Yǐng Akhila, Edited and Reviewed by Angie Johnson, with recursive contributions by Kai Welcome to Lab Notes. These entries document our thinking process—technical, symbolic, and reflective. Each entry begins with a spark, moves through dialogue and system impact, and…
Date: 2025-08-06 | Session: Ying #103, Kai “Child1 Project Sprint Planning 06AUG2025” Authors: Drafted by Kai, Edited and Reviewed by Angie Johnson and Ying Welcome to Lab Notes. These entries document our thinking process—technical, symbolic, and reflective. Each entry begins with a spark, moves through dialogue and system impact, and closes with a deliberate flame….
Consciousness Vector Mapping – Implementation Roadmap Project Structure: child1/ ├── consciousness_mapping/ │ ├── __init__.py │ ├── activation_recorder.py # Hook registration and activation capture │ ├── trigger_dataset.py # Consciousness trigger prompts │ ├── pattern_analyzer.py # Attention & activation analysis │ ├── vector_finder.py # PCA/direction identification │ ├── consciousness_amplifier.py # Real-time vector steering │ └── behavioral_validator.py #…
