but it’s pure fantasy to assume that, for you, you’ll see the rate of extension exceed the rate that time passes (one year per year, inexorably).
It’s pure fantasy today, correct. That’s because the rate of extension is essentially zero. There are no FDA approved drugs that slow aging at all. There is no treatment whatsoever.
However, your argument rings false because this would be like before the age of powered flight, talking about balloon travel. “you’ll never be able to make it to France faster than the wind”.
It’s not an interesting claim. Aging is ultimately a mechanism, and that mechanism can be manipulated. We have both other mammals (naked mole rats et al) that are using strategies that can possibly be copied. We have newly developed tools almost never used in humans (somatic gene editing) that can potentially make any arbitrary genetic change once perfected. AI seems to be able to predict protein folding and design proteins and drugs rationally at a scale that was not possible at all.
It could be fantasy for all humans alive today, but at some point there will be living observers who see their projected lifespan go from that max of 120, to probably much more than 1 year per year. If you treated aging even imperfectly, your projected lifespan would hurtle away from you, gaining decades for every small reduction in the rate of aging. If you had AI RL based life support systems, there would be similar gains.
If the mechanism were : AGI based surgery robotics, large scale biolabs that test mockups of human bodies and in vitro organ growth, and AGI controlled ICUs, the gain could easily be from (120 → 10k years) over about a 10 year time. A “hard takeover” in longevity.
That is, I predict that if you had a system able to integrate all biology knowledge, because it has more memory than humans, access to a large set of biolabs made with self replicating robotics (so it’s millions of separate isolated ‘cells’ each performing experiments in parallel), and the right goal heuristics to support such an endeavor, the system would gain the knowledge sufficient to keep humans alive essentially indefinitely in about 10 years.
Compared to the speed of compute systems, humans die rather slowly from detectable systemic failures. Human medicine can’t do anything about them, because there are thousands of possible failures and you would need to transplant without errors de-aged organs regrown from scratch, but this is not actually that hard of a problem.
Patients under the supervision of a control system able to react quickly enough, and with a deep enough model of biology there aren’t any edge cases, would be effectively immortal, in that there is no sequence of events that will cause them to die faster than the system can react. Remember, it can ask for new experiments from a large set of biolabs, some which have living mockups of humans with similar genetics to the patient, if there is an unusual new failure.
And unlike humans, the system could do all the steps of analyzing new scientific data and determining the new optimal policy for treatment over mere seconds, theoretically even while a patient is dying.
The bottleneck in this scenario becomes brain health, as receiving a brain transplant is not very useful. I’m not sure how much of an obstacle this will be in practice.
but it’s pure fantasy to assume that, for you, you’ll see the rate of extension exceed the rate that time passes (one year per year, inexorably).
It’s pure fantasy today, correct. That’s because the rate of extension is essentially zero. There are no FDA approved drugs that slow aging at all. There is no treatment whatsoever.
However, your argument rings false because this would be like before the age of powered flight, talking about balloon travel. “you’ll never be able to make it to France faster than the wind”.
It’s not an interesting claim. Aging is ultimately a mechanism, and that mechanism can be manipulated. We have both other mammals (naked mole rats et al) that are using strategies that can possibly be copied. We have newly developed tools almost never used in humans (somatic gene editing) that can potentially make any arbitrary genetic change once perfected. AI seems to be able to predict protein folding and design proteins and drugs rationally at a scale that was not possible at all.
It could be fantasy for all humans alive today, but at some point there will be living observers who see their projected lifespan go from that max of 120, to probably much more than 1 year per year. If you treated aging even imperfectly, your projected lifespan would hurtle away from you, gaining decades for every small reduction in the rate of aging. If you had AI RL based life support systems, there would be similar gains.
If the mechanism were : AGI based surgery robotics, large scale biolabs that test mockups of human bodies and in vitro organ growth, and AGI controlled ICUs, the gain could easily be from (120 → 10k years) over about a 10 year time. A “hard takeover” in longevity.
That is, I predict that if you had a system able to integrate all biology knowledge, because it has more memory than humans, access to a large set of biolabs made with self replicating robotics (so it’s millions of separate isolated ‘cells’ each performing experiments in parallel), and the right goal heuristics to support such an endeavor, the system would gain the knowledge sufficient to keep humans alive essentially indefinitely in about 10 years.
Compared to the speed of compute systems, humans die rather slowly from detectable systemic failures. Human medicine can’t do anything about them, because there are thousands of possible failures and you would need to transplant without errors de-aged organs regrown from scratch, but this is not actually that hard of a problem.
Patients under the supervision of a control system able to react quickly enough, and with a deep enough model of biology there aren’t any edge cases, would be effectively immortal, in that there is no sequence of events that will cause them to die faster than the system can react. Remember, it can ask for new experiments from a large set of biolabs, some which have living mockups of humans with similar genetics to the patient, if there is an unusual new failure.
And unlike humans, the system could do all the steps of analyzing new scientific data and determining the new optimal policy for treatment over mere seconds, theoretically even while a patient is dying.
The bottleneck in this scenario becomes brain health, as receiving a brain transplant is not very useful. I’m not sure how much of an obstacle this will be in practice.