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Will rejuvenation technology arrive early enough for you?
Download my free longevity briefing: Who Is Likely to Benefit from Longevity Escape Velocity â and why biological age matters
đ https://daniel-kafer.kit.com/495e7b5d41
You can also access this file and all my free AI tools in my free Skool community:
đ https://www.skool.com/the-strategic-edge-1049/about?ref=72a80d2abf964f3a8bf5889ea5e80407
This is an evidence-based estimation, not a promise or prediction.
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Aging kills roughly 110,000 people every day.
In this conversation, I sit down with Aubrey de Grey, one of the most influential and controversial figures in longevity science, to discuss the war on aging â and whether meaningful rejuvenation is likely to arrive in time to matter for people alive today.
00:00 â Why aging is the worldâs biggest killer
03:05 â What the âwar on agingâ actually means
07:10 â Why most people misunderstand aging
14:35 â Why timelines for longevity differ so much
20:15 â What longevity escape velocity really requires
22:35 â Repair vs slowing aging: the core idea
32:00 â What animal experiments tell us (and donât)
34:45 â â110,000 deaths a dayâ explained
41:20 â What could accelerate or delay progress
52:10 â Who might realistically benefit
We explore:
 ⹠Why aging is the leading cause of death worldwide
 ⹠The idea of Longevity Escape Velocity and what it actually means
 ⹠Repair-based approaches to aging, rather than slowing decline
 ⹠Why timelines differ so dramatically between experts
 ⹠The role of AI, biotechnology, and translational bottlenecks
 ⹠Why biological age, not chronological age, will determine who benefits
This is not a conversation about immortality.
It is a conversation about damage, repair, timelines, and uncertainty.
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About the PDF (reinforces click without hype)
The linked briefing expands on one central question raised in this discussion:
If effective rejuvenation therapies arrive in the coming decades, who is most likely to benefit â and why?
The report:
 ⹠Compares major expert timelines (including Aubrey de Grey, Ray Kurzweil, and others)
 ⹠Explains why biological age matters more than birth year
 ⹠Uses probability ranges, not promises
 ⹠Is intended as a thinking tool, not a forecast