TimurSadekov

And we have a practical solution — we create a global unbiased decentralized CyberPravda platform for disputes, for analyzing the reliability of information and assessing the reputation of its authors, where people are accountable with personal reputation for their knowledge and arguments.

We have found a way to mathematically determine the veracity of Internet information and have developed a fundamentally new algorithm that does not require the use of cryptographic certificates of states and corporations, voting tokens that can bribe any user, or artificial intelligence algorithms that are not able to understand the exact meaning of what a person said. The algorithm does not require external administration, review by experts or special content curators. We have neither semantics nor linguistics — all these approaches have not justified themselves. We have found a unique and very unusual combination of mathematics, psychology and game theory and have developed a purely mathematical international multilingual correlation algorithm that uses graph theory and 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. The algorithm allows betting on different versions of events with automatic determination of the winner and allows to create a holistic structural and motivational frame in which users and news agencies can earn money by publishing reliable information, and a high reputation rating becomes a fundamentally new social elevator.

CyberPravda mathematically evaluates the balance of arguments used by different authors to confirm or refute various contradictory facts to assess their credibility, in terms of consensus in large international and socially diverse groups. From these facts, the authors construct their personal descriptions of the picture of events, for the veracity of which they are held responsible by their personal reputations. An unbiased and objective purely mathematical correlation algorithm based on graph theory checks these narratives for mutual correspondence and coherence according to the principle of "all with all" and finds the most reliable sequences of facts that describe different versions of events. Different versions compete with each other in terms of the value of the flow of meaning, and the most reliable versions become arguments in the chain of events for facts of higher or lower level, which loops the chain of mutual interaction of arguments and counterarguments and creates a global hypergraph of knowledge, in which the greatest flow of meaning flows through stable chains of consistent scientific knowledge that best meet the principle of falsifiability and Popper's criterion. A critical path in the sequence of the most credible facts forms an automatically generated multi-lingual article for each of the existing versions of events, which is dynamically rearranged according to new incoming evidences and the desired credibility levels set by readers in their personal settings ranging from zero to 100%. As a result, users have access to multiple Wikipedia-like articles describing competing versions of events, ranked by objectivity according to their desired level of credibility.

One of the world's leading experts on information security systems, Professor Ross Anderson of Cambridge University, in his article https://arxiv.org/abs/2305.17493v2 is already considering a scenario where most of the Internet will be a neural network-generated hallucination. But neither you, nor me, nor any expert or anyone at all will be able to distinguish between fake and real. As a result, neural networks will degenerate in the process of learning from their own hallucinations of the Internet, and humans will degenerate in the process of applying the degenerated neural networks. This process he called "neural network collapse". It can only be countered by a collective neural network of all the minds of humanity. For mutual validation and self-improvement of LLM and humans, we need the ability to match the knowledge of artificial intelligence with collective intelligence. This is what can get us out of the personal reality tunnels and personal information bubbles in which we are getting deeper and deeper stuck individually.

This network of real human knowledge provides a way to introduce new, clean, human-generated datasets into LLM training in a validity-conscious manner, and makes it possible to avoid model collapse and reduce unwanted errors in creating new and better generations of generative models. And we have a practical solution to avoid the collapse of large language models — we create a global unbiased decentralized CyberPravda (dot) com platform for disputes, for analyzing the reliability of information and assessing the reputation of its authors, where people are accountable with personal reputation for their knowledge and arguments.

Neural networks will degenerate in the process of learning from their own hallucinations, and humans will degenerate in the process of applying the degenerated neural networks. This process is called "neural network collapse". https://arxiv.org/abs/2305.17493v2 It can only be countered by a collective neural network of all the minds of humanity. For mutual validation and self-improvement of LLM and humans, we need the ability to match the knowledge of artificial intelligence with collective intelligence. Only the CyberPravda project is the practical solution to avoid the collapse of large language models.

The decentralized social network Mastodon did not have an unbiased algorithm for analyzing the reliability of information and assessing the reputation of its authors. This shortcoming is now being addressed by a new method - we create a CyberPravda (dot) com platform for disputes with unbiased mathematical algorithm for assessing the reliability of statements, where people are accountable with personal reputation for their knowledge and arguments.

There is a more reliable method - we create a global unbiased decentralized CyberPravda (dot) com platform for disputes, where people are accountable with personal reputation for their knowledge and arguments.

The last chance to get reliable information that hasn't been tainted by the bullshit of LLM hallucinations is CyberPravda (dot) com project. The window of opportunity is closing fast.