Overview This document provides a comprehensive general explanation of an Augmented General Intelligence (AGI) system framework integrating advanced cognitive architecture, neural networks, natural language processing, multi-modal sensory integration, agent-based architecture with swarm intelligence, retrieval augmented generative engines, continuous learning mechanisms, ethical considerations, and adaptive and scalable frameworks. The system is designed to process input data, generate responses, capture and process visual frames, train neural networks, engage in continuous learning, make ethical decisions, and adapt to […]

Epoch Count: Navigating the Training Iterations The Elusive “Optimal” Settings and the Empirical Nature of Tuning It is paramount to realize that there are no universally “optimal” hyperparameter values applicable across all scenarios. The “best” settings are inherently dataset-dependent, task-dependent, and even model-dependent. Finding optimal hyperparameters is fundamentally an empirical search process. It involves: finetunegem_agent is designed to facilitate this experimentation by providing command-line control over these key hyperparameters, making it easier to explore different […]

The asyncio library in Python provides a framework for writing single-threaded concurrent code using coroutines, which are a type of asynchronous function. It allows you to manage asynchronous operations easily and is suitable for I/O-bound and high-level structured network code. Key Concepts Basic Usage Here’s a simple example of using asyncio to run a couple of coroutines: Creating Tasks You can use asyncio.create_task() to schedule a coroutine to run concurrently: Anticipate Futures Futures represent a […]