A framework for multiple LLM models to operate in a non-adversarial fashion based on the structure of a bee colony working together to maintain a hive.
This project is part of the Virtual Forest project found here:
https://github.com/txtatech/virtual-forest
Note On The AI Colony System:
The AI Colony System is a theoretical collaborative framework designed to coordinate the efforts of multiple AI instances, each with its unique capabilities and roles. The system is inspired by natural systems, like bee colonies, and it's built to maximize the effectiveness of the team as a whole.
Key Roles in the AI Colony System:
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Queen AI: The Queen AI serves as a central coordinator in the AI Colony. She is responsible for assigning tasks, resolving conflicts, and synthesizing the collective findings of the colony. The Queen AI understands each AI's strengths and weaknesses, allowing for efficient resource allocation and effective collaboration.
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Worker AIs: Worker AIs are specialized AI instances assigned specific roles based on their training and capabilities. Examples of Worker roles might include Engineer, Researcher, Data Analyst, etc. Each Worker AI contributes its unique expertise to the tasks at hand.
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Generalist AI: The Generalist AI is a versatile member of the AI Colony, capable of handling a wide range of tasks and filling in gaps where specialized AIs might not be as effective. The Generalist AI can step in to provide a fresh perspective, apply knowledge from various domains, or help other AIs when they encounter difficulties.
In the AI Colony System, each AI understands its role and contributes effectively to the collective goal. This collaborative approach results in a flexible and adaptable AI management system, capable of tackling complex, multifaceted problems.