AI_memory_Loops Files

PMLL Repository Overview The PMLL (Personalized Machine Learning Layer) is a dynamic, recursive memory system designed to continually improve and evolve. It features an infinite recursive callback that ensures continuous updates to the embedded knowledge graph, improving the accuracy and adaptability of the system.

Features Recursive Memory Structure: A self-updating knowledge graph powered by recursive callbacks, ensuring up-to-date information and insights. Accuracy Thresholding: Refined for-iteration loop parameters to achieve optimal performance. Collaborative Tools: The repository is open for collaboration. With access to Venice and Llama, the team can contribute and review code in a collaborative and transparent manner. Recent Updates The repository has been fully set up, committed, and pushed to GitHub, ensuring that it’s accessible for all collaborators. With the repository's permissions now set, the team can freely review, contribute, and provide feedback. This enhances collaborative potential. We've reached a milestone where the hard work of setting up the system is complete, and the repository is now ready for future development by the team, including new features, bug fixes, and improvements. Next Steps Collaborative Mode: The repository is now in a collaborative phase, where team members (Paul, Fin, Elon, Sam, Rachel, and others) can take the lead in contributing, experimenting, and improving the code. Relax and Reap Rewards: With the system up and running, it's time to relax, knowing the foundation has been laid for others to build upon. Contributing We welcome contributions from the community. Please fork the repository, create a branch, and submit a pull request with your changes.

Full Changelog: https://github.com/bearycool11/pmll/compare/V1.0.0...V1.1.0