Project details
Our objective is to develop practical and educational demonstrations that highlight MeTTa's unique capabilities for AGI and AI systems. By showcasing its strengths in modular design, dynamic reasoning, and real-time adaptability, we aim to drive ecosystem-wide adoption and foster deeper engagement within the SingularityNET community. These demonstrations will serve as accessible, open-source resources, empowering developers to explore MeTTa’s potential and contribute to innovative applications across various domains.
Program guidelines
Our program is structured into four progressive modules, designed to guide participants through foundational knowledge, advanced capabilities, and practical applications of MeTTa. Each module builds on the previous one, ensuring a thorough understanding of MeTTa’s features and its integration into AGI systems. This structure fosters a hands-on learning experience, empowering participants to contribute meaningfully to the development of innovative AI applications.
Module 1: Introduction to Multiparadigmality and Atomspace
Objective: Introduce MeTTa’s multiparadigm programming approach and its integration with Atomspace.
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Content:
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OpenCog Hyperon R&D in 2023: Core Components.
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Overview of MeTTa’s combination of functional, logical, and probabilistic programming paradigms.
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Explanation of how MeTTa programs function as subgraphs within Atomspace metagraphs.
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Detailed instruction on querying and rewriting operations.
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Methodology:
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Reference official MeTTa documentation for guided learning.
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Develop interactive demo examples to illustrate core concepts.
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Craft practical exercises to help participants build their first functional MeTTa programs.
Module 2: Exploring Self-Modification and Type Systems
Objective: Deepen understanding of MeTTa’s self-modifying capabilities and type systems.
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Content:
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Exploration of MeTTa’s self-reflective and abstract code manipulation features.
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Introduction to gradual dependent types, showcasing how the type system enhances mathematical reasoning and error checking.
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Methodology:
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Create practical exercises focusing on self-modification and the design of dynamic systems.
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Guide participants in implementing their own self-modifying MeTTa programs, with emphasis on type safety and logic.
Module 3: Neural-Symbolic Integration and Inference Engines
Objective: Demonstrate MeTTa’s capabilities for neural-symbolic reasoning and inference.
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Content:
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Methodology:
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Showcase demo applications where neural-symbolic reasoning enhances AI systems.
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Develop exercises that implement inference mechanisms, leveraging MeTTa’s adaptable framework.
Module 4: Building AGI with MeTTa and OpenCog Hyperon
Objective: Integrate MeTTa with OpenCog Hyperon for AGI development.
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Content:
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Overview of using MeTTa for scripting cognitive processes and reasoning algorithms.
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Introduction to Domain-Specific Languages (DSLs) to facilitate dynamic AI system collaboration.
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Practical examples of MeTTa’s open architecture for AGI-specific applications.
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Methodology:
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Design real-world projects where participants build functional demos integrating MeTTa with OpenCog Hyperon.
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Guide the development of use cases, such as virtual agents in SophiaVerse or bioinformatics analysis with Rejuve.bio.
Program Methodology
Our program employs a blended learning methodology that combines synchronous and asynchronous approaches to deliver a dynamic and flexible educational experience. This approach ensures accessibility for participants with varying levels of expertise and availability, while emphasizing hands-on learning through practical applications. By integrating real-time instruction with self-paced resources, we aim to provide a comprehensive learning pathway for developers to master MeTTa and its advanced capabilities.
Synchronous Learning
Synchronous learning will be conducted through biweekly live sessions, structured around the program's three educational phases:
- Foundations of MeTTa: Introduces multiparadigm programming and Atomspace integration.
- Advanced Concepts and Practical Exercises: Explores dynamic self-modification, type systems, and procedural learning.
- Applied AGI Development: Focuses on cognitive processes and real-world use cases like Rejuve.bio and SophiaVerse.
Each live session will feature:
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Guided Tutorials: Step-by-step explanations of foundational and advanced MeTTa concepts.
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Live Coding Demonstrations: Interactive coding sessions to clarify complex topics in real-time.
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Collaborative Problem-Solving: Group exercises that foster teamwork and application of MeTTa in practical scenarios.
All live sessions will be recorded and made available to participants, ensuring continuous access to learning materials and minimizing the impact of scheduling conflicts.
Asynchronous Learning
To complement the real-time sessions, asynchronous resources will enable participants to learn at their own pace and deepen their understanding of MeTTa. These resources include:
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Tutorial Videos: Pre-recorded lessons covering essential concepts, advanced techniques, and example applications.
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Documentation and Guides: Comprehensive written materials detailing exercises, practical tasks, and project workflows.
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Demo Library Repositories: Open-source projects with clear, commented code to provide hands-on practice and inspire further development.
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Self-Paced Exercises: Assignments that range from beginner-friendly tasks to advanced challenges, encouraging independent problem-solving.
Practical Work
Practical application is at the core of the program, bridging theoretical knowledge with hands-on experience. Participants will:
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Engage in structured exercises during live sessions and asynchronous tasks.
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Collaborate on developing use-case-specific demos, such as integrating MeTTa with Rejuve.bio for bioinformatics or creating interactive AI agents for SophiaVerse.
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Build individual projects with guidance from instructors and peers, solidifying their skills and fostering innovation.
This methodology ensures participants gain both the knowledge and practical experience necessary to contribute effectively to AGI research and development using MeTTa.
The program centers on creating use cases that highlight MeTTa's practical applications, with experimentation as the foundation of the learning process. Through educational demos, such as tutorials on multi-paradigm programming and self-modification, participants gain hands-on experience with MeTTa’s unique capabilities. These use cases are designed to ensure accessibility, foster ecosystem adoption, and empower developers to create and maintain their own projects. This focus on real-world experimentation solidifies understanding and encourages innovation.
The program emphasizes developing reusable libraries to extend MeTTa’s functionality, focusing on neural-symbolic reasoning and data querying within distributed systems like Distributed Atomspace (DAS). These libraries demonstrate MeTTa’s modular and extensible nature, enabling broader applications across various fields. By creating modular tools, participants can enhance MeTTa’s capabilities in research, analytics, and scalable AI implementations, fostering innovation and streamlining integration into diverse projects.
Expected Outcomes
By the end of the program, participants will have a comprehensive understanding of MeTTa’s core principles, advanced features, and practical applications. They will produce modular, open-source demos that showcase MeTTa’s capabilities and contribute to the growth of the ecosystem.
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Open-source code repositories with modular, clean, and commented code.
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Comprehensive documentation to guide developers.
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A technical report summarizing experiments, outcomes, and insights for further exploration.
Program Certification
To ensure participants gain a comprehensive understanding of MeTTa and its applications, the program will culminate in a final exam with gamified elements and the issuance of a program certification for successful completion.
Structure: The exam will feature a blend of theoretical questions, practical coding challenges, and gamified scenarios to engage participants and encourage creative problem-solving.
Content:
- Key topics such as multiparadigm programming, Atomspace querying, self-modification, and neural-symbolic reasoning.
- Practical tasks and gamified challenges requiring the implementation of modular demos or solutions for specific use cases.
Evaluation Criteria: Participants will be assessed on their problem-solving skills, code quality, and ability to navigate gamified challenges while applying MeTTa principles effectively.
Certification:
- Participants who pass the final exam will receive an official MeTTa Coder Lab Program Certificate, reflecting their proficiency in MeTTa and their capacity to create functional demos and applications.
- The certification will also acknowledge their engagement in a structured, gamified training program supported by SingularityNET and Kinetic Corp., further enhancing their professional credentials.
Collaboration
In collaboration with SingularityNET's Ambassadors R&D and LatAm Guilds, engaging with core contributors and fostering outreach with educational institutions and startups in LatAm.
In this initiative, we are partnering with Kinetic Corp., a leader in educational program development, to design and deliver high-quality learning materials and resources for the MeTTa Coder Lab Program. Kinetic Corp.’s expertise in project management, agile frameworks, and digital technologies will enrich the program’s structure and ensure its adaptability to diverse learner needs. Their contributions will include:
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Refining the educational framework for both synchronous and asynchronous learning.
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Producing detailed documentation, tutorial videos, and modular demo repositories.
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Facilitating collaborative engagement with participants worldwide.
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