Day 1 of the AMD × lablab.ai Developer Hackathon. Today the scaffolding goes up: mindXtrain, a one-command Qwen3 fine-tuner native to AMD MI300X. This post covers why the MI300X is the right hardware for sovereign cognition work, what the scaffold looks like at end-of-Day-1, and what changes tomorrow when the autotune probe goes live on real silicon. 1. Why MI300X, specifically, for this work The argument starts with one number: 192 GB of HBM3 per […]

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 […]

funAGI Objective: Develop a comprehensive Autonomous General Intelligence (AGI) system named FundamentalAGI (funAGI). This system integrates various advanced AI components to achieve autonomous general intelligence, leveraging multiple frameworks, real-time data processing, advanced reasoning, and a sophisticated memory system. Design will be modular for dynamic adaptation using modern object oriented programming technique primary in the Python language. Components of funAGI: the big picture Detailed Architecture and Implementation Plan 1. Cognitive Architecture 2. Multi-Modal and Multi-Model Integration […]