So, regarding the reversible cryopreservation.
First, we need to prove that reversible human cryopreservation doesn't violate any physical, chemical, engineering, or biological limitations.
To do this, we'll put together a proposed procedure plan and draw a computational graph based on it.
The graph should answer just one question: "Is it possible?" with three answers: YES, NO, I DON'T KNOW.
And we'll calculate in 2 versions: if the graph is optimistic:
"IF I'M LUCKY, IS IT POSSIBLE?"
And if the graph is pessimistic:
"EVEN IF I'M UNLUCKY, IS IT POSSIBLE?"
Optimism is cheaper to calculate than pessimism, but if even optimism fails, then calculating pessimism is pointless.
I already have a plan and partially a graph. Considering that it will contain 10^3 - 10^6 points, the AI will do everything.
To protect against AI laziness, each formula must have a reference, a citation from it, and a hash as proof of its validity. The graph's connectivity and quality is calculated by the validator. The runnet gives back the result.
Ideally, reference values should be concentrated as much as possible in the graph's inputs. Meanwhile in the graph's inner layers, the reference values can serve as a reference (but it's important to indicate the conditions that occurred). If the calculation diverges from the reference values, that's great - it means we've stitched something together somewhere in physics, chemistry, or biology and can unstitch it.
Any "no" kills the graph version, and the procedure needs to be improved.
A side effect of the graph is that I'll know under what conditions the answer is "YES." But I'll likely lack the numbers for the minimum synapse integrity, the minimum water content in cells, and the acceptable cytoskeletal injury.