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trojblue
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✅ New Article on Hugging Face: Teaching AI to Think Like a System — Not a Toolkit Title: 🏗️ Understanding Structured Cognitive Architecture: A Unified Framework for AI Reasoning Systems 🔗 Read it here: https://huggingface.co/blog/kanaria007/understanding-structured-cognitive-architecture Summary: After exploring how AI can select reasoning modes or learn from failure, this new article zooms out: *How do all these capabilities form a single mind, not just a menu of functions?* The **Structured Cognitive Architecture** defines a unified framework where protocols interact coherently — forming a self-organizing, reflective, and ethically grounded reasoning system. This architecture enables agents to: • Integrate memory, ethics, reasoning, and identity across layers • Select and execute reasoning jumps with traceable structure • Coordinate failure recovery and adaptive learning • Maintain cross-session identity and self-editing capability It’s not modular stacking. It’s **structured systemhood** — cognition with intentional protocol interaction. Key Features: • Three-layer design (Foundational, Extended, Learning) • Semantic rule-layer to avoid protocol interference • Integrated flow: problem → jump → feedback → pattern update • Built-in ethics, rollback, and trace integrity The framework integrates protocols like: • `jump-generator`, `failure-trace-log`, `memory-loop`, `identity-construct` • Extended modules: `chronia`, `structure-cross`, `evaluation-planning`, and more 🧠 Protocol Dataset: https://huggingface.co/datasets/kanaria007/agi-structural-intelligence-protocols Useful for: • Researchers designing unified AGI architectures • Developers building reflective protocol-based agents • Anyone curious how AI can think as a *system* This isn’t modularity. It’s **meta-coherence by design**.
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trojblue/million-song-subset
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trojblue/danbooru2025-metadata
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trojblue/rvc-kanade-dataset
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