#27 - Bryan Johnson - Science-backed Ways to Living FOREVER? 'Don’t Die'

The Innovation Civilization Podcast - Podcast autorstwa Waheed Nabeel

We welcome Bryan Johnson, multi-millionaire visionary entrepreneur and founder of "Don't Die." Known as the most measured man in human history, Bryan is pushing the boundaries of human longevity by meticulously tracking his body's biomarkers in pursuit of an extended health span, not just lifespan. His 'Blueprint' protocols can be found here.Bryan's journey from revolutionizing digital payments with Braintree Venmo, which he sold to PayPal for $800 million, to dedicating over $100 million of his fortune to extend human life reveals a deep commitment to humanity's future. Through his initiative Blueprint, Bryan is developing an algorithm that takes better care of our bodies than we can do ourselves, aiming for a world where "Don't Die" becomes a societal mantra.In this episode, Bryan discusses his philosophy behind "Don't Die" and how it could reshape politics, economics, ethics, and more. He explores the potential of AI to revolutionize decision-making and extend human capabilities beyond our current limitations. Bryan also put forward the challenges of aligning AI with human longevity and the ethical dilemmas that arise when pursuing extended life spans.The conversation spans topics such as the future of artificial intelligence, the exploration of human consciousness, and the need for societal shifts toward sustainable living. Bryan talks about the potential of technology to transform our understanding of life and offers a visionary perspective on what humanity might look like in the 25th century.We also cover how Bryan’s work could redefine what it means to be human, the importance of mastering the basics of health, and the potential for algorithms to outperform human decision-making in every aspect of life.All the topics that we covered in the episode:-Health and Longevity: Bryan's quest to extend life through science and technology.-AI and Human Potential: Artificial intelligence's role in shaping humanity's future.-Societal Transformation: How "Don't Die" could redefine our approach to politics, ethics, and economics.-Consciousness and Technology: Exploring the next frontier of human experience.-Ethical Challenges: The dilemmas of aligning AI with human longevity.Join us for a forward-thinking discussion as we explore the intersection of technology, longevity, and the future of civilization with one of the leading minds in the field.Follow our host, Waheed Rahman (@iwaheedo), for more updates on tech, civilizational growth, progress studies, and emerging markets.   Subscribe to our newsletter to get these directly into your inbox.Here are the timestamps for the episode. On some podcast players, you should be able to click the timestamp for the episode:   (00:00) - Intro(02:56) - Bryan's background and the origins of "Don't Die" (04:56) - Limitations of LLMs and their reliance on historical data for generating responses(07:57) - Living with a future-oriented mindset and connecting the dots retrospectively(09:41) - Trust in science through the use of biomarkers and objective data as a source of truth(11:15) - The philosophical motivations behind pursuing rejuvenation science and the desire to live forever despite not fearing death(14:37) - Why might humanity's progress in decision-making and societal improvements not continue at the same rate despite past achievements?(17:51) - Reflecting on the idea that 'Don't die' is the greatest virtue, contrasting it with the ethical teachings of philosophers like Socrates, Confucius, and Plato(19:47) - How does the paradigm shift of 'don't die' impact all actions and social structures and confront the influence of AI-driven recommendation systems on personal behavior?(21:54) - The contrast between inherent human nature, whether inherently good or bad and the internal conflict between different versions of ourselves, like 'evening Brian' and 'morning Brian?(25:36) - Discussing whether the goal of the Blueprint is to achieve a consistently performing self across different ti

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