JARVITS: An Adaptive Cognitive System Based on the MICT Framework

This is one of a few new sections coming to the website. We've been working on JARVITS' components for a little bit now. It's ready to begin Training and full Development. It's time to rethink How we do things....

Executive Summary

JARVITS (John's Adaptable Routing Vision Iteration Transformation System) is a next-generation, general-purpose AI system under development by the Boredbrains Consortium. Unlike traditional, monolithic AI architectures, JARVITS is built upon the Mobius Inspired Cyclical Transformation (MICT) framework, enabling continuous learning, adaptation, and emergent behavior. JARVITS is designed as an Integrated Cognitive System (ICS), seamlessly integrating multiple AI modules and reasoning mechanisms to achieve a level of cognitive flexibility and adaptability that surpasses current AI systems. This document provides a technical overview of JARVITS's architecture, capabilities, and future development roadmap.

Acronym Expansion: JARVITS

• John's: Personalized, original system.
• Adaptable: Flexibility.
• Routing: Directing information.
• Vision: Representing both visual and forward thinking.
• Iteration: The core of the MICT Framework.
• Transformation: The concept of change and growth.
• System: Representing the unified nature.

Core Principles and Architecture:

• MICT Framework: JARVITS is fundamentally based on the MICT framework, a cyclical process consisting of four key stages: Map, Iterate, Check, Transform
• Integrated Cognitive System (ICS): JARVITS is designed as an ICS, integrating multiple specialized modules into a unified system. These modules include:
• Modularity: The modular architecture allows for independent development, testing, and improvement of each component.
• Interconnectedness: The modules are interconnected and collaborate to achieve goals. The output of one module (e.g., the LUM's understanding of a user request) becomes the input for other modules (e.g., the RPM's planning process).
• Continuous Learning: JARVITS is designed for continuous learning and adaptation. It learns from its interactions with users, its environment, and its own internal processes.
• Hierarchical Control: The MICT cycles are inherently hierarchical and interconnected.

Current Capabilities (and Near-Term Goals):

• Advanced Natural Language Processing: Understanding and responding to complex natural language instructions, questions, and requests.
• Contextual Awareness: Maintaining context and understanding the nuances of human communication.
• Task Decomposition and Planning: Breaking down complex tasks into smaller, manageable steps and formulating plans to achieve goals.
• Web Interaction: Interacting with the web through a custom Chrome extension, gathering information, and performing actions.
• Code Understanding and Generation: Analyzing and understanding code in multiple programming languages, and generating code for specific tasks.
• Basic Visual Perception: (Planned near-term) Processing and interpreting images and videos.
• Ethical Reasoning: (Planned near-term) Incorporating ethical considerations into decision-making processes.
• Self-Improvement: (Long-term goal) Continuously improving its own performance and capabilities through meta-learning and self-adaptation.

Hardware and Deployment:

• Distributed Architecture: JARVITS is designed for a distributed architecture, allowing it to leverage multiple computing resources (servers, edge devices, potentially mobile devices).
• Initial Training: Initial training of the core AI models doesn't need to be performed on high-performance computing infrastructure (e.g., servers with multiple GPUs). It can be done on a system with as little as dual RTX 3090 24GB GPUs on a single system.
• Deployment: JARVITS can be deployed in various configurations, depending on the specific application.
• Future Hardware (Project M?bius): A key long-term goal is the development of a custom MICT-based CPU architecture (Project M?bius) that is specifically optimized for running JARVITS and other MICT-based systems. This CPU would offer significant advantages in terms of performance, efficiency, and adaptability.

Operating System Integration (GenesisOS):

• Long-Term Vision: JARVITS is envisioned as a core component of GenesisOS, a new operating system designed from the ground up on MICT principles. GenesisOS will provide a native platform for JARVITS, enabling seamless integration with system resources and applications.

Development Tools:

• MICT/HCTS Framework: Open-source data framework with Software components released in Javascript and Python.
• MICT/HCTS Visualizer: A visual based IDE tool for designing, visualizing, and debugging MICT cycles. (Under development)

Conclusion:

JARVITS represents a significant advancement in AI research and development, moving beyond the limitations of current approaches to create a truly adaptive, intelligent, and ethical system. The MICT framework provides a solid foundation for building AI that can learn continuously, adapt to changing conditions, and collaborate effectively with humans. Project M?bius, the MICT-based CPU, represents the next logical step and could revolutionize computing. The long-term vision of integrating JARVITS with GenesisOS further expands the potential for creating a truly human-centered and transformative technology ecosystem. Boredbrains Consortium is committed to open-source principles and collaborative development, and we invite researchers, developers, and enthusiasts to join us in building the future of AI.

#AI #ArtificialIntelligence #DeepLearning #QuantumComputing #CognitiveScience #SystemsThinking #Theory #Research #Innovation #MICT #MobiusTheory #JARVITS #EthicalAI