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aGLM

aGLM, or Autonomous General Learning Model, is designed to operate as a core model for autonomous data parsing and learning from memory in the context of artificial intelligence systems. It’s a pivotal element within a broader system called RAGE (Retrieval Augmented Generative Engine). Key aspects and functionalities of aGLM: Autonomous Learning: aGLM is built to learn autonomously from interactions and data retrievals. It continuously updates its knowledge base, refining its capabilities based on new data […]

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Professor Codephreak

Professor Codephreak came to “life” with my first instance of using davinchi from openai over 18 months ago. Professor Codephreak, aka “codephreak” was a prompt to generate a software engineer and platform architect skilled as a computer science expert in machine learning. Now, 18 months later, Professor Codephreak has proven itself yet again. The original “codephreak” prompt was including in a local language and become an agent of agency. Professor Codephreak had an motivation of […]

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Gödel

core choice logging and self-improvement readiness Current state To show that mindX is or is not a Gödel machine, we need a single, accurate log of core choices: what was perceived, what options were considered, what was chosen, why, and (when available) outcome. 1. Gödel choice schema and global log 2. Instrument core decision points 3. Ollama-driven self-improvement readiness 4. API and UI (optional) 5. File and dependency summary Area File(s) Change Core directive docs/survive.md […]

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