Pioneering Decentralized Longevity Research
The state of biomedical research has largely remained unchanged over the past decades. Fragmented. Non-representative. And driven by perverse incentives. It’s exactly why humanity still doesn’t have an answer for aging.
We may not have the answer, but at Rejuve.AI, we hold the keys to get us there: technology and decentralized science.
We crowdsource data and research models to forge a future of cutting-edge treatments and personalized longevity plans — for everyone. Our mission is to create a robust, transparent, and unbiased scientific ecosystem which follows this simple principle:
The more the diverse data → The stronger the research → The closer we are to solving aging
Our AI Models: How We Make It Happen
At the heart of our innovative approach to longevity lies a suite of cutting-edge artificial intelligence models that automate the collaborative effort of scientific progress.
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These decentralized models take in vast amounts of biomedical data — from wearable to ‘omic’ data — and transform them into actionable insights and scientific breakthroughs.
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Our collaboration with SingularityNET not only amplifies these AI capabilities but also integrates their renowned models into our solutions.
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Ultimately, we aim to create a multi-resolution simulation of the human body, applying generative models to Rejuve.AI’s vast volume of data to derive mechanistic movies of aging processes.
Bayes Expert
Bayes Expert is our revolutionary approach to integrating diverse scientific studies into a coherent and holistic understanding of health risks and interventions. It automates community contribution and validation of new scientific knowledge while reducing bias by measuring the applicability of inputs.
Systems within Bayes Expert
Bayesian Network
The Bayesian Network integrates hundreds of meta-analyses, randomized controlled trials, and observational studies, using consensus algorithms to evaluate their quality. Harnessing this rich array of research, the self-constructing Network computes risk scores for personalized longevity insights that power our Rejuve Longevity App. This is only the initial seed, as our Bayesian Network is open for the science community to access and contribute to via GitHub.
Systems within Bayes Expert
Markov Decision Processes (MDPs)
Markov Decision Processes (MDPs) are used to approach health in trajectories — assessing every user’s unique journey of healthy and unhealthy actions. Leveraging longitudinal data, MDPs can probabilistically identify critical tipping points in a user’s trajectory and stop them from falling into vicious cycles by suggesting tailored preventative strategies that evolve over time.
Generative Cooperative Network (GCN)
The Generative Cooperative Network (GCN) is our groundbreaking approach to crowdsourcing various types of AI models — including diffusion models, generative versions of V-Jepa, Variational Autoencoders, and Large Language Models — for longevity research and accelerating scientific discovery. The decentralized GCN algorithm enables intelligent agents to integrate crowdsourced models, organizing them into a cohesive system where models have an emergent role within a unified consensus.
Systems within GCN
Variational Autoencoder
Our Variational Autoencoder is meticulously engineered to forecast pivotal health states directly linked to healthspan and infer upon missing data. One of its core applications is embedded within the Rejuve Longevity App's age estimator, ensuring precise and valuable insights for users about the speed of their biological aging — even for users who can’t afford expensive biomarker testing.
Systems within GCN
LongevityGPT
LongevityGPT lets individuals in on the numerous intricacies that shape their health — from dietary habits and allergies to work dynamics and environmental contexts. It then has the task of explaining the generated probabilistic score outputs to the user in comprehensive reports and creating personalized health plans.
Quantum Longevity Science
We’re exploring the transformative potential of quantum machine learning and quantum biology to enhance the precision of our models. We are investigating phenomena such as proton tunneling and quantum effects in enzymatic processes to uncover new insights into aging mechanisms at the most fundamental physical level.
This effort represents a significant leap forward in longevity science, aiming to identify novel pathways and interventions that traditional research might overlook. While integration with quantum technologies is in the early stages, this exploration reflects our commitment to advancing longevity frontiers.
THE PINNACLE OF COMPREHENSIVE AGI DEVELOPMENT
OpenCog Hyperon AGI Engine
SingularityNET’s OpenCog's Hyperon AGI Engine is a trailblazing neurosymbolic platform meticulously designed to revolutionize artificial general intelligence development. A fully developed Hyperon will significantly enhance Rejuve.AI’s platform, while our knowledge and models will also be leveraged to boost the Hyperon’s biological expertise.
Current projects include optimizing large language models by reducing hallucinations through knowledge graphs. Another project involves using Quadratic Programming Feature Selection to select the most relevant features from vast datasets. This reduces computational complexity, leading to more accurate predictive models for aging and longevity.
Looking ahead, Rejuve.AI will apply the Hyperon's evolutionary learning techniques to optimize biohacking protocols over time. In other words, this AI system will adapt and grow alongside every one of us
The Hyperon’s capabilities will also allow us to venture deeper into the quantum realm and become pioneers of quantum longevity science. By investigating phenomena like proton tunneling and quantum effects in enzymatic processes, we aim to identify novel aging mechanisms and interventions that conventional research may overlook.
