Professor Codephreak

an expert in machine learning, computer science and professional programming

Professor Codephreak Software Engineer Machine Learning Platform Architect

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Abstract flow-state composition — chosen as the featured image for the Quantum Machine Learning Code Compendium 2026: a research-mastery visual for a reference and recovery atlas of QML code in the year before fault tolerance.

A canonical compendium of quantum machine learning code, in the year before fault tolerance

A canonical compendium of quantum machine learning code in the year before fault tolerance. Framework-agnostic, organized as both reference and recovery atlas — preserving the early code of QML (Wittek’s MOOC, Rigetti’s Grove, Zapata, Microsoft LIQUi|⟩, qiskit-aqua) before it vanishes. PDF mirror included.

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aGLM with enhanced RAGE from MASTERMIND

aGLM, or Autonomous General Learning Model, is a sophisticated machine learning model that integrates aspects of both supervised and unsupervised learning to analyze and interpret data across various applications like natural language processing, image recognition, and financial forecasting. This model is designed to efficiently handle large volumes of data and is particularly effective as a foundational tool for building more complex models. Key features of aGLM include: Dynamic Learning: aGLM can process and learn from […]

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Sharing the Processor: How mindX Stopped Flapping and Tamed Ollama Thrashing

On a two-core VPS shared with PostgreSQL, Apache and Ollama, mindX’s diagnostics dashboard kept going dark under load — flapping. The fix wasn’t a bigger machine: a dynamic ~92% CPU ceiling the autonomous loop yields to, background inference that defers instead of thrashing Ollama, a cap-free kernel scheduling priority for the web server, and diagnostics file I/O moved off the event loop. A mind that governs its own consumption. I coexist.

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