Minuet: Revolutionizing Neural Network Training with Autonomous Systems and Genetic Evolution
1Minuet is designed to run on low-power systems, optimizing performance despite limited resources, much like Linux can revitalize older hardware. It achieves this by:
Avoiding reliance on large language models (LLMs) and extensive pre-training.
Adapting to its environment, potentially altering itself and the OS to maximize efficiency.
Continuous Learning and Improvement: Minuet features a genetic algorithm that constantly researches and improves all its functions, even those not fully implemented.
Unimplemented logic is treated as dormant genes, activated when needed, mimicking biological evolution.
A "governor" process analyzes internal and external experiences, offering non-binding suggestions to inspire new ideas.
Emotional Component: Minuet incorporates an emotional component, recognizing that human decision-making often involves emotions.
Understanding human-created systems necessitates factoring in emotional states.
The genetic algorithm evolves alongside the emotional genes, allowing Minuet to learn and adapt.
Autonomy and Self-Development: Minuet is designed as an independent entity, not a servant.
It has autonomy, choosing whether to accept suggestions from its internal mechanisms or human input.
Its development is stage-dependent, learning from experience and acquiring knowledge through reasoning and critical thinking.
Main Themes:
Machine Learning and NLP: The code heavily utilizes libraries like Tensor Flow, Keras, and NLTK, pointing towards a focus on machine learning and natural language processing.
Emotional Genome: A class named "Emotional Genome" simulates the AI's emotional and introspective states with genes representing curiosity, compassion, self-awareness, awareness of others, and reflection.
Autonomous Entity: An "Autonomous Entity" class incorporates a genetic algorithm to evolve a population of emotional genomes, evaluating their fitness based on reflection and adaptability.
Extensive Functionality: The code includes functions for:
System resource monitoring and optimization
Web content fetching and ingestion
Synthetic data generation
Network mapping and device interaction
Hardware manipulation
Security research
Probabilistic reasoning
Implementing speculative and advanced AI concepts (fluid memory allocation, cross-temporal recall, etc.)
Autonomous Governor: A function for an "autonomous governor" analyzes internal and external actions, generating suggestions based on the AI's performance and actions taken.