mindXtrain is the first one-command Qwen3 fine-tuner natively optimized for AMD MI300X. It is the AMD-shaped half of the PYTHAI/DELTAVERSE stack: a single Python package that takes a YAML recipe and produces a trained, evaluated, FP8-quantized, served, and on-chain-anchored model — all on a single MI300X, all driven by a 60-second on-device autotune that pins kernel and collective choices before training starts. This post is the canonical landing page for the project. If you are […]

understandin the ezAGI framework requires a fundamental comprehension of reasoning with SocraticReasoning.py disclaimer: ezAGI fundamental Augmented Generative Intelligence may or not be be fun. use at own risk. breaking changes version 1 To fully audit the behavior of how the premise field is populated in the SocraticReasoning class, we will: SocraticReasoning.py Audit Initialization and setup of SocraticReasoning class Adding Premises Programmatically Adding Premises Interactively Now, let’s look at the interactive part of the interact method: […]

Building a rational Autonomous General Learning Model with Retrieval Augmented Generative Engine to create a dynamic learning loop with machine.dreaming for machine.learning as a self-healing architecture. MASTERMIND uses the Autonomous General Learning Model (aGLM) enhanced by the Retrieval Augmented Generative Engine (RAGE) to create a sophisticated AI system capable of intelligent decision-making and dynamic adaptation to real-time data. This combination leverages the strengths of both components to ensure that responses are not only based on […]