Hand-crafted Bayes Net Model of Individual Aging Page 2

Figure 5. The Markov blanket of the Telomere Attrition Hallmark node in Rejuve.AI’s longevity Bayesian net currently used in the Rejuve.AI app. There are 9 other hallmarks and many other inputs. The extent to which we can be confident that the structure of the markov blanket is correct is the extent to which the meta analyses have controlled for confounding, and since the studies are of gold standard Randomized Controlled Trials, or use statistical instruments on observational data. When more data is available we will be able to learn the structure of the network through techniques such as Pearl’s inductive causation. Modeling and comprehending the human body is far too large a task for any single entity or organization. Rejuve. Using SingularityNET's open AI platform, AI is developing methods for a swarm of researchers to reach consensus on models of increasing complexity, while also exploring multiple combinations of models and datasets that make sense to combine together. Metrics of consonance, or formal measurements of how much sense models and data make when combined, allow for decentralized automated complexification. Models submitted by various researchers can be combined automatically or with researcher participation.

Decentralization brings the wisdom of the crowd to the challenge of longevity, and automated models embody the cumulative consensus of researchers. Rejuve. The community can collaborate on AI's human biology models because they are tangible and cumulative, but they are larger than reductionist randomized controlled trials and take into account more variables. Concrete models concentrate the discussion on a single object, which the hive mind can debug until agreement is reached. Working on common tangible models and seeing how their models affect other models helps researchers discover what their models imply and think more holistically and systemically than when focusing on a single variable.