CyberPravda – Knowledge Graph & Rating of Veracity

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Timur Sadekov
Project Owner

CyberPravda – Knowledge Graph & Rating of Veracity

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Overview

LLMs can degenerate by learning from their own hallucinations on the Internet and humans will degenerate by applying the degenerated LLMs. This process is called "neural network collapse". For mutual validation and self-improvement of LLM and humans, we need the ability to match the knowledge of artificial intelligence with collective intelligence. And for all of this, we need a reliability rating of human knowledge. We have found a fundamentally new way to determine the veracity of information that does not depend on admins, biased experts, special content curators, oracles, authority certificates of states and corporations, clickbait likes/dislikes or voting tokens that can bribe any user.

RFP Guidelines

Advanced knowledge graph tooling for AGI systems

Proposal Submission (12 days left)
  • Type SingularityNET RFP
  • Total RFP Funding $350,000 USD
  • Proposals 3
  • Awarded Projects n/a
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SingularityNET
Apr. 16, 2025

This RFP seeks the development of advanced tools and techniques for interfacing with, refining, and evaluating knowledge graphs that support reasoning in AGI systems. Projects may target any part of the graph lifecycle — from extraction to refinement to benchmarking — and should optionally support symbolic reasoning within the OpenCog Hyperon framework, including compatibility with the MeTTa language and MORK knowledge graph. Bids are expected to range from $10,000 - $200,000.

Proposal Description

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  • Total Milestones

    1

  • Total Budget

    $200,000 USD

  • Last Updated

    30 Apr 2025

Milestone 1 - Creation of a minimum viable product (MVP)

Description

Prototype refinement for demonstration of a minimum viable product (MVP) polishing algorithms involving users starting first monetization preparing for the transition to blockchain. 1. Algorithm of veracity of information and reputation of its autors (ready) 2. Readers' interface (ready) 3. Authors' interface (60% ready) 4. Smart contract for disputes about different versions of events (ready) and for corporate orders for verification of the veracity of information (50% ready) 5. LLM trained to find basic facts and arguments in any websites or publications (80% ready)

Deliverables

We will launch an app with fundamentally new algorithm that mathematically determines the veracity of information without AI hallucinations, cryptographic certificates of states and corporations or voting tokens that can bribe any user. The algorithm does not require external administration review by experts or special content curators. It has neither semantics nor linguistics — all these approaches have not justified themselves. It has a unique and very unusual combination of mathematics psychology and game theory. We have developed a purely mathematical international multilingual correlation algorithm that allows us to get a deeper scientometric assessment of the accuracy and reliability of information sources compared to the PageRank algorithm or the Hirsch index. At a very fundamental level it revolutionizes existing information technologies making a turn from information verification to the world's first algorithm for analyzing its compliance with Popper's falsifiability criterion which is the foundation of the scientific method. The algorithm will be completely transparent and visible to all users of the system. Everyone will know the rules of the game and will be able to check them at any time. All this makes possible to assign each message in the system a credibility rating and authors — a reputation rating. Knowledge graph will support integration with MeTTa.

Budget

$200,000 USD

Success Criterion

Target audience 100 000 MAU. 20 corporate clients place orders for analysis and verification of information veracity on average 5 times a month with an average check of $500. Half of the order amount is automatically paid to the authors of the most reliable information, who scored the highest reputation rating in the system, and a commission of 50% of the order amount generates $25K/month in revenue, and the project becomes self-sustaining preparing for the full transition to blockchain. We made mathematical modeling that shows that after creating a million information blocks, the leading scientific hypothesis consistently wins the credibility rating over competing versions of ignorames, bots and trolls. And reputation ratings of academical minority are much higher than ratings of countless ignorames, bots, and trolls and that gap only widens as the total number of publications grows. Mathematical model — https://youtu.be/r3MCpSDLSEo

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