Nishant Nishant
Project OwnerThe Project Owner will oversee project alignment with AGI objectives, manage team coordination, ensure timely deliverables, and provide strategic guidance for integrating clustering within MeTTa.
The proposal aims to enhance the MeTTa framework's capabilities by implementing modular clustering heuristics essential for Artificial General Intelligence (AGI) applications. By integrating algorithms like K-Means, Hierarchical, DBSCAN, and Gaussian Mixture Models, MeTTa will support adaptive learning from diverse datasets. Key deliverables include clustering algorithms, evaluation metrics (Rand Index, Mutual Information, Purity), visualization tools, and comprehensive documentation. This project will promote scalability, performance, and innovation in AGI, benefiting domains such as healthcare, finance, and environmental science.
The goal is to implement clustering algorithms in MeTTa and demonstrate interesting functionality on simple but meaningful test problems. This serves as a working prototype providing guidance for development of scalable tooling providing similar functionality, suitable for serving as part of a Hyperon-based AGI system following the PRIMUS cognitive architecture.
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This milestone will focus on defining the project scope, solidifying key features, and outlining the development plan. Initial research and planning will ensure that the integration of clustering algorithms aligns with AGI needs. Project objectives, including the specific clustering algorithms and evaluation metrics to be implemented, will be clearly established. Additionally, this phase will finalize team roles and set up collaborative tools, ensuring seamless coordination among developers, data scientists, and technical writers. The primary goal of this phase is to create a structured roadmap to guide subsequent development phases, ensuring alignment with MeTTa’s infrastructure and AGI frameworks.
The deliverables for this phase include a finalized project roadmap, a documented feature list, and a sprint plan that outlines development steps. Key documents will cover algorithms, evaluation metrics, and initial plans for visualization and export tools. This includes a requirements document outlining compatibility standards with MeTTa, user accessibility goals, and integration methods for clustering functions. These foundational documents will enable efficient development in subsequent milestones, providing clarity for all team members and ensuring the project adheres to a clear vision from the start.
$4,000 USD
This milestone centers on developing and integrating clustering algorithms into MeTTa, specifically K-Means, Hierarchical Clustering, DBSCAN, and GMM. Each algorithm will be coded as a modular, reusable function with adjustable parameters for varied data types. Testing will focus on each algorithm's performance and compatibility with MeTTa’s data structures, ensuring that they meet efficiency and accuracy requirements. This milestone also includes testing initial functions on synthetic datasets to identify potential issues, optimize performance, and verify that the clustering functions handle large datasets effectively without compromising speed.
Deliverables include the codebase for each clustering algorithm, accompanied by documentation detailing parameters, usage guidelines, and examples. Additionally, results of unit tests for each function on sample datasets will be provided, ensuring robustness across use cases. Modular function design documentation will explain how these functions interact with MeTTa’s components, promoting ease of integration and usability for AGI researchers. A code review session with the team will validate the robustness and adaptability of the algorithms, completing this critical development phase.
$5,000 USD
This milestone involves incorporating evaluation metrics such as Rand Index, Mutual Information, and Purity into the MeTTa framework to assess clustering outcomes. Visualization tools will be developed to graphically represent clustering results, with features like scatter plots, dendrograms, and time-sequence visualizations for better interpretation. Both evaluation metrics and visualizations will be optimized for performance, allowing AGI researchers to easily analyze and interpret data clusters. This phase ensures that AGI researchers can evaluate clustering effectiveness and make data-driven adjustments.
Deliverables include a fully functional evaluation module with modular metric functions, along with comprehensive documentation on using each metric. The visualization tools will feature interactive modules with user-friendly configurations, enabling users to generate various plots for cluster analysis. A demonstration dataset will accompany the tools, showing how to utilize evaluation metrics and visualize clustering outcomes. This milestone will also deliver a technical report outlining performance optimization techniques for both evaluation and visualization functions, ensuring reliability for complex AGI applications.
$3,000 USD
This milestone focuses on preparing detailed technical documentation, user manuals, and tutorials for all implemented features, ensuring that AGI researchers can easily use the clustering functions within MeTTa. Export functionality will also be developed, enabling users to save clustering results in formats like CSV and JSON, allowing further analysis with external tools. The emphasis will be on creating a seamless user experience by making the clustering and evaluation features accessible to all skill levels. User support tools, such as example datasets and best practices guides, will be included to encourage broad adoption.
Deliverables for this phase include comprehensive documentation that covers each clustering algorithm, evaluation metric, and visualization tool. A series of tutorials and best-practice guides will be made available, showcasing how to implement and interpret clustering results effectively. The export functionality will be provided in commonly used formats (CSV, JSON) and will be tested for compatibility with other data analysis tools. A final project report will summarize the integration, key lessons, and potential future developments, providing a well-rounded resource for MeTTa users.
$2,000 USD
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