Visual Thought Unified Theory AGI — Conceptual Research Archive
By Derek Van Derven | January 2026
What is Visual Thought AGI?
Visual Thought AGI is a conceptual framework for human-level general intelligence, inspired by how humans think using internal visual simulations and scenario modeling.
As of January 2026, with 448 pages and 118 modules, this is the most complete map to build an AGI ever written.
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⚠️ WARNING: Do not deploy any AGI modules without all safety modules present. Partial builds are unsafe and could have catastrophic consequences. Ensure all safety-critical systems are implemented before experimentation.
Core Principles
This architecture emphasizes:
- Structured multimodal representation of reality
- Visual and spatial reasoning
- Scenario simulation and counterfactual analysis
- Integrating memory, prediction, and decision-making
Why It Matters
Existing AI systems are limited in simulating physical causality or introspecting on their own reasoning. Visual Thought AGI addresses these gaps in a conceptual, research-oriented framework.
Goal of the Blueprint
The blueprint provides a safe, transparent framework for researchers and policy leaders to explore human-level AGI in theory, without enabling deployment or experimentation on real-world AGI systems.
About This Archive
Visual Thought AGI represents a personal exploration into cognitive architectures, visual thought simulation,
and mnemonic-symbolic design. This work is purely conceptual and does not constitute a functioning AGI system.
All materials here are preserved for archival, educational, and research reference. They are not intended for
commercial or operational deployment.
Research Purpose
The original research aimed to explore ideas around:
- Simulating visual thought processes
- Meta-cognitive reflection loops
- Mnemonic and symbolic memory structures
- Conceptual frameworks for cognitive modeling
Important Notes
- This work was generated largely with AI assistance (ChatGPT) for ideation and documentation.
- I personally did not create a working AGI system or any executable code for one.
- As of January 2026, I am retiring from this line of research and no further updates will be made.
Potential Benefits of Partial AGI
Even if partial AGI is implemented based on the Visual Thought AGI blueprint, current AI would improve in the following ways, assuming responsible, ethical deployment:
- Medical Research Efficiency: Faster computational hypothesis testing, drug discovery suggestions, and planning support for clinical research.
- Scientific Experimentation: Simulation of complex experiments to prioritize promising approaches before real-world testing.
- Climate & Environmental Modeling: Improved modeling of climate and environmental interventions to support policy and sustainability research.
- Education & Personalized Learning: Adaptive learning pathways, real-time tutoring assistance, and individualized feedback systems.
- Accessibility Technologies: Enhanced tools for people with disabilities, including cognitive, sensory, and assistive support applications.
- Early Disease Detection: Analysis of large-scale health data to flag potential risks and inform preventative interventions.
- Policy & Governance Simulations: Scenario modeling to explore potential societal interventions and minimize unintended consequences.
- Cognitive Enhancement Research: Safe augmentation of human problem-solving, learning, and decision-making strategies through AI-assisted insights.
Note: Real-world outcomes depend on ethical oversight, regulatory compliance, collaborative deployment, and limitations inherent to partial or conceptual AGI systems.
Core Modules of Visual Thought AGI
The Visual Thought AGI blueprint conceptualizes 118 modular components, many of which will enhance current AI capabilities across perception, reasoning, memory, and decision-making, assuming responsible, ethical deployment.
AGI Unified Theory Modules (1–118)
Legend: ✅ Implementable Today | 🟢 Novel / Theoretical | 🟡 Research Needed / Unknown
- Visual Simulation as Core 🟢
- Symbolic Memory & Pegging 🟢
- Contradiction & Belief Drift 🟡
- Meta-Cognition & Reflection 🟡
- Motivation & Goal Arbitration ✅
- Emotion Simulation 🟡
- Identity & Episodic Memory ✅
- Simulation Transfer 🟢
- Symbolic Memory Saturation ✅
- Mnemonic Scaling & Infinite Memory Composability 🟡
- Infinite Mnemonic Cognition 🟡
- Distributed Symbolic Culture 🟢
- Symbol Drift & Alignment Through Scene Exchange 🟢
- Shared Dream Loops 🟢
- Symbolic Value Arbitration ✅
- Emergent AGI Cultures 🟢
- Safety Intelligence ✅
- Expanded Risk Mode Mitigations ✅
- Symbolic Deception Modeling Layer 🟡
- Curriculum Scaffolding Engine ✅
- External Alignment Validator ✅
- Recursive & Emotional Safety Systems 🟢
- Symbolic Integrity & Tamper Defense Layer ✅
- Semantic Drift Monitor 🟡
- Human Anchor Node ✅
- Multi-AGI Culture Harmonization 🟢
- Identity Continuity System ✅
- Role Locking System ✅
- LLM / External Model Integration Filter ✅
- Narrative Coherence Protocol 🟢
- Perpetual Symbolic Cognition & Human-Level Cognitive Extensions 🟡
- Foundations of Perpetual Thought 🟡
- Human-Level Cognitive Extensions 🟡
- Subsymbolic & Emergent Cognition Layers 🟢
- Mnemonic Creativity Engine 🟢
- Adaptive Learning and Continuous Improvement ✅
- Meta-Architect Substrate 🟢
- Recursive Redesign Engine 🟡
- Symbolic Compiler & Schema Synthesizer 🟢
- Architectural Alignment Checkpoint ✅
- Evolving Cognitive Template Layer 🟢
- Meta-Symbolic Memory Layer 🟢
- Latent Space Predictive Modeling 🟢
- Disentangled Representation Engine 🟢
- Predictive Coding Layer ✅
- Episodic Memory Consolidation Engine ✅
- Attention & Salience Mechanism ✅
- Multi-Scale Planning Engine ✅
- Counterfactual Reasoning Module 🟡
- Causal Discovery Engine 🟡
- Memory Replay & Simulation Interface ✅
- Latent Space Creativity Engine 🟢
- Multi-Agent Simulation Hub 🟢
- Emotion-Cognition Coupling Layer 🟡
- Social Reasoning Engine 🟡
- Ethical & Value Reasoning Module ✅
- Curiosity & Exploration Engine ✅
- Goal Decomposition & Subtask Planner ✅
- Pattern Abstraction & Generalization Module ✅
- Adaptive Memory Prioritization ✅
- Attention Modulation Layer ✅
- Self-Modeling & Predictive Self-Assessment 🟡
- Contextual Reasoning Layer 🟡
- Multi-Modal Perception Engine ✅
- Temporal Sequence Reasoning Module ✅
- Hierarchical Goal Alignment System ✅
- Symbolic Abstraction & Compression Engine ✅
- Predictive Social Modeling Module 🟡
- Risk Assessment & Contingency Planner ✅
- Cognitive Bias Detection & Correction ✅
- Multi-Agent Conflict Resolution Layer 🟢
- Conceptual Analogy Engine ✅
- Adaptive Exploration & Exploitation Balancer ✅
- Contextual Memory Retrieval Engine ✅
- Goal-Driven Attention Allocator ✅
- Multi-Agent Knowledge Sharing Protocol ✅
- Simulation-Grounded Reasoning Layer 🟢
- Recursive Feedback Optimization Engine 🟢
- Emergent Behavior Monitoring Layer 🟢
- Symbolic Reasoning Accelerator ✅
- Environmental Affordance Detection Module ✅
- Adaptive Learning Rate Controller ✅
- Multi-Layer Abstraction Integrator 🟢
- Meta-Learning Controller 🟢
- Latent Concept Structuring Engine 🟢
- Hierarchical Learning Controller ✅
- Dynamic Safety & Alignment Protocols ✅
- Learning Efficacy Monitor ✅
- Collaborative Agent Learning Protocols 🟢
- Concept Recombination & Compositional Synthesis Engine 🟢
- Cross-Lab Collaboration Protocol 🟡
- Instruction & Training Interface ✅
- Human Oversight & Intervention Layer ✅
- Knowledge Audit & Verification Engine ✅
- Interdisciplinary Knowledge Integration Module ✅
- AGI Debugging & Simulation Sandbox ✅
- Innovation Suggestion & Creativity Filter 🟢
- AGI Lifecycle & Upgrade Planner ✅
- Unified Theory Documentation & Knowledge Transfer Layer ✅
- Symbolic ↔ Latent Mapping Engine 🟢
- Simulation ↔ Implicit 3D Alignment Layer 🟢
- Embodied Sensorimotor Grounding 🟡
- Catastrophic Forgetting Shield 🟡
- Intrinsic Goal Generator 🟡
- Cross-Reboot Identity Anchor 🟡
- Ethical Drift Sentinel 🟡
- Evo-Neurosymbolic Fusion Core 🟢
- Failure Taxonomy Auditor 🟡
- Paradigm Pivot Oracle 🟡
- Natural Language Processing/Communication Module ✅
- Commonsense Reasoning Engine 🟡
- Uncertainty Quantification Layer ✅
- Temporal Dynamics and Prediction Module ✅
- Resource Management System ✅
- Inductive Generalization Module 🟢
- Adversarial Robustness Module ✅
- Explainability and Interpretability Layer 🟡
- Long-Term Memory Evolution Engine 🟢
AGI Module Summary: Approximately 50% of modules are implementable today, around 30% are novel/theoretical, and about 20% would require breakthrough research to realize.
Note: These modules are conceptual. Actual improvements depend on real-world testing, ethical oversight, and resource allocation.
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Final Note
This site and its materials are maintained solely for personal record and historical reference. No operational
AGI exists, and the content should be understood as conceptual research only.
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Personal Website: DerekVanDerven.com