Deep Longevity, recently acquired by Regent Pacific (HK:0575), a company developing explainable artificial intelligence systems to track the rate of aging at the molecular, cellular, tissue, organ, system, physiological, and psychological levels today announced the availability of Young.AI to key media, longevity researchers, and clinical partners.
The company revealed the beta version of the integrated mobile app and web-based systems both running on the AWS cloud on September 15th. Key media, longevity researchers, and clinical partners are welcome to request early access for research purposes by emailing [email protected] . The company set the public launch date for September 29th, 2020.
Previously the advanced deep aging clocks were made available to the clinicians through a partnership with Human Longevity Inc's, Health Nucleus providing comprehensive diagnostic solutions to some of the most sophisticated clients.
The introduction of the Young.AI app and web system will enable everyone interested in learning more about their own aging to get access to some of these aging clocks and start tracking their rate of aging.
Here we are executing on the vision of Dr. Alex Zhavoronkov, the original inventor of deep aging clocks to provide the most advanced research tools in the hands of everyone on the planet without any biases towards social status, race, or gender to help optimize for much longer and healthier lives.
With the launch of the integrated app and web system, we are establishing the foundation for the longevity ecosystem designed to produce quantifiable results and help extend human life and performance."
Jamie Gibson, CEO, Regent Pacific
Since 2014 deep learning systems outperformed humans in multiple tasks including image and voice recognition and video games demonstrating spectacular ability to generalize.
Since aging processes transpire over long time periods and at multiple levels, they are very difficult to track. Even the best human doctors are unable to track these minute changes in the context of a patient's lifespan and many of the data types like tissue-specific protein expression, or even sophisticated lab tests are incomprehensible to human intelligence. Artificial intelligence trained on these data types in combination or separately tends to outperform.
The company plans to present its work on deep aging clocks at Metabesity 15-20th of October and at multiple other research and industry conferences in 2020 and beyond. The company is welcoming clinical and academic collaborators to engage in collaborative research using the Young.AI system.
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