Scalable MeTTa Knowledge Graphs

A powerful novel approach from a pioneering team

It is beneficial to have the data in the natural format for OpenCog Hyperon instead of some other structure. I would bet this as the solution that has the highest optionality going forward and thus being the most solid foundation to expand and build on top of.

On the other hand, the proposal is much less about immediate follow-ups and applications. Of course, it meets the RFP’s requirements that enable practical integrations and utilization by other entities.

It is clear that the technical complexity of the system as a whole is high but there could not be much more qualified team working on it. I was pretty impressed by Adam’s presentations already in the AGI 2021 conference and happily entrust this project to his management.

Feasibility & desirability are given top priority

Adam Vandervorst and Anneline Daggelinckx have fully disclosed their identities and are expected by me to be fully capable and have enough intelligence to successfully implement this complex proposal. The full presentation of technical elements in 5 milestones speaks for itself. I most appreciate the feasibility and desire of the two talented members.

knowledge graph of the future

The proposal is well-structured and comprehensive, addressing critical aspects of developing a robust knowledge graph platform using Hyperon and MeTTa. The team’s expertise aligns well with the project requirements, ensuring a high likelihood of successful implementation. The deliverables for each milestone are clear and achievable within the specified budgets, providing a solid roadmap for enhancing the SingularityNET ecosystem's data management capabilities.
hoping that Github which looks interesting can be build upon 

Knowledge Graphs for All Solutions

Desirability
The project to use Hyperon's MORK backend for hosting knowledge graphs is highly desirable within the SingularityNET ecosystem. It offers a unified solution for storing and managing large knowledge bases, supporting both SPARQL and MeTTa queries, which are crucial for advanced data manipulation and retrieval. The rich online MeTTa editor enhances user experience by providing a comprehensive interface for interacting with knowledge graphs. This project aligns well with the ecosystem's goals, promoting interoperability and efficient data management.

Usefulness
The usefulness of this project is significant, as it facilitates the integration of Hyperon's metagraphs into SingularityNET, enabling seamless data transformation and communication between services. By embedding knowledge graphs in Atom Space and using MeTTa for data transformations, the project enhances the functionality and scalability of the ecosystem. The ability to convert various data formats to graphs, edit knowledge graphs through an intuitive interface, and program custom APIs ensures that developers and companies can leverage this platform for diverse applications. This project ultimately supports more efficient and effective data management and utilization.

Feasibility
The feasibility of the project is supported by the strong expertise and experience of the Qoba.ai team, which includes AI researchers, mathematicians, UI specialists, and full-stack developers. The team's prior work with MeTTa and Hyperon, along with successful collaborations on related projects, indicates a solid foundation for implementing the proposed solution. While technical challenges exist, such as ensuring security and scalability, the project's reliance on existing robust frameworks and tools like Hyperon and MeTTa mitigates many potential risks. The project's detailed plan for data augmentation, training, and deployment further enhances its feasibility.

Viability
The viability of the project is promising, given its potential to become a cornerstone of the SingularityNET ecosystem. By offering a performant and scalable knowledge graph platform, the project addresses a critical need within the ecosystem and promotes the broader adoption of AI and knowledge graph technologies. The integration with existing infrastructure and the focus on providing a user-friendly experience support long-term sustainability and growth. However, the project will need to ensure continuous funding, effective marketing, and user adoption to achieve its full potential.

Summary
This Hyperon-based solution is all about providing a robust solution for managing and querying large knowledge bases within the SingularityNET ecosystem. Its feasibility is backed by the skilled Qoba.ai team and their experience with the core technologies involved. The project's viability is strong, with the potential to significantly enhance the ecosystem's capabilities and user experience. Ensuring continuous support and adoption will be key to its success. Overall, this project promises to be a valuable addition to the SingularityNET platform, promoting efficient data management and interoperability.

Efficient knowledge graphs directly in Hyperon

Regarding desirability and usefulness: The strength of this proposal in comparison to all others in this category is that it uses (and extends!) OpenCog Hyperon as a knowledge graph engine, rather than relying on external solutions such as semantic web technologies or Neo4j. This  paves the way for future projects to also use Hyperon for scalable knowledge representation and querying. The value of this proposal therefore goes beyond the mere RFP requirements. It contributes to the OpenCog ecosystem in a foundational way that will help in the adoption of Hyperon as flexible knowledge graph store and MeTTa as an advanced query language.

Regarding feasibility and viability: Adam and his team are capable and experienced researchers and developers, as demonstrated by their prior successful work on Hyperon implementations, MeTTa language design and creation of MeTTa examples, which can be tracked both on GitHub and in SNET discussion groups. The project milestones seem well designed and I have full trust in their ability to deliver them as specified.

Bla bla bla

I was expecting a bit more from the presentation. What I heard was bla-bla-bla, I'm a former singularity employee, this is why I know best.

This ruined the whole proposal for me, but overal planning is good

Adam Vandervorst

Jun 3, 2024 | 8:46 PM

Project Owner

Hi! I understand that you have concerns about the spotlight presentation. My coverage of our proposal was abstract and did not go into technical depth or paint the full context. Please engage in the discussion section if we can shed light on parts you especially missed. 

Scalable MeTTa Knowledge Graphs

Adam is a former employee of SingularityNET, I believe he has the qualifications and skills to complete this proposal. They have teams that demonstrate high levels of trust.
The total budget for this Pool is 120,000 USD, but the budget of this proposal is also 120,000 USD. I think the proposal's budget is a bit high. I need to make it clear that this is not against the rules, it's just my personal opinion.

Adam Vandervorst

Jun 3, 2024 | 8:25 PM

Project Owner

Hi Tu Nguyen, thank you for your trust in our team's ability to deliver. We believe the RFP's budget is well-placed in this part of the ecosystem, and we strive to deliver a correspondingly complete and robust solution. Note that the RFP has a separate pool, and only one project is being awarded. Moreover, we believe that our "dogfooding" approach of fulfilling the RFP's goals by leveraging and expanding SNET's own MeTTa/Hyperon-based tech stack is unique in its ability to provide compounding value across the ecosystem. 

This can enable comprehensive version control

I find it interesting that this project is keen on utilizing Hyperon's capabilities. In doing this, the project aims to enhance the efficiency and accessibility of knowledge graphs core to SingularityNET, facilitating seamless integration with existing platforms and file formats, supporting diverse query methods, and enabling comprehensive version control and documentation within a unified representation.

Additionally,within the SNET AI Marketplace, Scalable MeTTa Knowledge Graphs offer a robust infrastructure for hosting and querying knowledge relevant to AI applications. This infrastructure supports the diverse needs of AI developers and researchers and also fosters collaboration. 

Adam Vandervorst

Jun 3, 2024 | 8:20 PM

Project Owner

Hi Clement, I can speak for our whole team when I say that we are excited about the comprehensive version control this proposal provides. Version control and access control are critical to a collaborative platform, and by re-using Hyperon's unified representation and data "re-exporting" transformation capabilities, it will be a breeze to use.

the Hyperon backend for hosting knowledge graphs

This proposal outlines using the Hyperon backend with MeTTa for hosting knowledge graphs in the SingularityNET ecosystem. Here's a breakdown of its strengths and weaknesses:

Feasibility:

• High: The proposal leverages existing SingularityNET technology (Hyperon, MeTTa) with a focus on integration and user experience.
  • Strengths: Builds on established technologies and focuses on scalability and user-friendliness.
  • Weaknesses: Limited details on potential challenges in integrating Hyperon with existing knowledge graph infrastructure.

Viability:

• Moderate: Success depends on the adoption by developers and the overall growth of the SingularityNET ecosystem.
  • Strengths: The proposal offers a potentially valuable platform for managing and accessing knowledge graphs within SingularityNET.
  • Weaknesses: The proposal lacks details on the target user base and the competitive landscape for knowledge graph solutions.

Desirability:

• Moderate: For developers seeking a user-friendly platform for knowledge graph management within SingularityNET, this could be desirable.
  • Strengths: The proposal offers a familiar environment (Hyperon, MeTTa) for interacting with knowledge graphs.
  • Weaknesses: The proposal needs to clearly demonstrate the advantages of this approach compared to existing SingularityNET tools for knowledge graph management.

Usefulness:

• Moderate-High: The project has the potential to improve the usability and accessibility of knowledge graphs within SingularityNET, but its impact depends on user adoption and integration with existing workflows.
  • Strengths: The proposal offers a scalable and user-friendly platform for storing, editing, and querying knowledge graphs.
  • Weaknesses: The proposal lacks details on how the platform will integrate with existing AI services and workflows within SingularityNET.

Overall, this Hyperon Knowledge Graph Platform has a promising approach, but focus on:

• Integration Challenges: Providing a clearer picture of potential challenges and solutions for integrating Hyperon with existing knowledge graph infrastructure in SingularityNET.
• Target User Base: Defining the specific user groups (developers, researchers) who would benefit most from this platform.
• Competitive Advantage: Clearly articulating the unique value proposition of this platform compared to existing tools for knowledge graph management within SingularityNET.
• Integration with AI Services: Explaining how the platform will integrate with other AI services and functionalities within the SingularityNET ecosystem.

By addressing these considerations, this Hyperon Knowledge Graph Platform can increase its chances of success and become a valuable tool for developers working with knowledge graphs in SingularityNET.

Here are some strengths of this project:

• Leverages existing SingularityNET technology (Hyperon, MeTTa) for a familiar development environment.
• Focuses on user-friendliness and scalability for managing and accessing knowledge graphs.
• Offers a rich online MeTTa editor for manipulating complex data and automating tasks.

Adam Vandervorst

Jun 3, 2024 | 8:46 PM

Project Owner

With our proposal, we can take the DeepFunding comments as they come in, cross-correlate them with other responses from a particular user, and integrate AI detectors like https://www.scribbr.com/ai-detector/ and https://gptzero.me/. This solution can flag users like Joseph Gastoni who spam AI-generated responses on the platform, as well as provide more nuanced insights into the community.