$667.93 crowdfunded from 115 people
$1,781.52 received from matching pools
TLDR In the quest to democratize access to the burgeoning field of regenerative finance (ReFi), Myseelia proudly spearheads an innovative project to forge a natural language interface for the ReFi Knowledge Graph. Under leadership of Darren Zal and in strategic partnership with Monty Merlin, Myseelia is set to unlock the transformative potential of ReFi by combining tyhe language processing power of Large Language Models (LLMs) with the structured knowledge of a Knowledge Graph, setting a new standard for intelligent, accessible, and collaborative platforms in the ReFi ecosystem. The envisioned interface transcends mere information retrieval, offering a platform for dialogue that delivers personalized insights and empowers stakeholders with the knowledge for strategic action in the realm of ReFi.
Problem Statement
Our planet faces a complex web of crises: climate change, biodiversity loss, social and economic inequity, perpetuated by a lack of holistic understanding and wise collective action.
Recent advancements in AI have revolutionized the landscape of natural language processing. However, their "black-box" nature often limits their verifiability and statistical model leads to generalizations and hallucinations.
Proposed Solution
The ReFi Knowledge Graph: A living, AI-infused database designed to:
- Foster collective intelligence
- Propagate regenerative culture and insights
- Coordinate impactful ground activities
- Educate and integrate local communities globally
The ReFi Knowledge Graph is envisioned to serve as a foundational tool for holistic understanding and systemic change. By mapping out the interconnections of problems, solutions, and stakeholders in a cohesive, accessible manner, it aims to cultivate a way for informed decision-making, effective collaboration, and the fostering of collective intelligence necessary for a flourishing future. The combination of LLMs with the ReFi knowledge graph will democratize access to an evolving verifiable knowledge ecosystem.
https://arxiv.org/abs/2306.08302
Project Goals
- Educate: Serve as a comprehensive resource for learning about the ReFi ecosystem.
- Onboard: Assist individuals in finding their niche within the ReFi community.
- Facilitate Coordination: Enable bottom-up collaboration through a standardized global system interoperable with local bioregional economies.
- Innovate: Harness advanced AI to optimize the Knowledge Graph’s functionality and user experience.
Outcome of Grant
With a new AI natural language interface, the ReFi knowledge graph will become accessible to all, streamlining entry into the ReFi sector, enabling ecosystem exploration, and enhancing knowledge exchange from local to global scales.
- Database Enrichment: Ongoing enhancement of the ReFi knowledge graph database and ontology.
- Natural Language Interface: Development of a natural language question-answering system to facilitate user interaction with the database.
Budget Allocation
- 50% for the development of the technological aspects, including implementation of AI-driven tools (chatbot, recommendations engine), semantic search capabilities, and general knowledge graph database management and enhancement.
- 50% for the continuous building of ReFi DAO’s ReFi Knowledge Graph database, data collection, and ontology design & evolution.
Conclusion
With this funding, we aim to solidify this ReFi knowledge network as core infrastructure for regenerative finance and culture.
Augmenting the ReFi Knowledge Graph with AI History
-
applied to the OpenCivics Genesis Round 11 months ago which was rejected
-
accepted into Web3 Open Source Software 11 months ago. 89 people contributed $201 to the project, and $192 of match funding was provided.
-
applied to the Web3 Social 11 months ago which was rejected
-
accepted into Metacrisis 1 year ago. 13 people contributed $354 to the project, and $469 of match funding was provided.
-
accepted into Climate Solutions 1 year ago. 13 people contributed $49 to the project, and $1,121 of match funding was provided.