The AI can kill us and then take over with better optimized biotech very easily.
Doubling time for
Plants (IE:solar powered wet nanotech) > single digit days
Algae in ideal conditions 1.5 days
E. Coli 20 minutes
There are piles of yummy carbohydrates lying around (Trees, plants, houses)
The AI can go full Tyranid
The AI can re-use existing cellular machinery. No need to rebuild the photosynthesis or protein building machinery, full digestion and rebuilding at the amino acid level is wasteful.
Sub 2 minute doubling times are plausible for a system whose rate limiting step is mechanically infecting plants with a fast acting subversive virus. Spreading flying things are self replicators that steal energy+cellular machinery from plants during infection (IE:mosquito like). Onset time could be a few hours till construction of shoggoth like things. Full biosphere assimilation could be limited by flight speed.
Nature can’t do these things since they require substantial non-incremental design changes. Mosquitoes won’t simultaneously get plant adapted needles + biological machinery to sort incoming proteins and cellular contents + continuous grow/split reproduction that would allow a small starting population to eat a forest in a day. Nature can’t design the virus to do post infection shoggoth construction either.
The only thing that even re-uses existing cellular machinery is viruses and that’s because they operate on much faster evolutionary time scales than their victims. Evolution takes so long that winning strategies to eat or subvert existing populations of organisms are self-limiting. The first thing to sort of work wipes out the population and then something else not vulnerable fills the niche.
Design is much more powerful than evolution since individually useless parts can be developed to create a much more effective whole. Evolution can’t flip the retina or reroute the recurrent laryngeal nerve even though those would be easy changes a human engineer could make.
Endgame biotech (IE: can design new proteins/DNA/organisms) is very powerful.
But that doesn’t mean dry nanotech is useless.
even if production is expensive it may be worth building some things that way anyways.
computers
structural components
Biology is largely stuck with ~0.15 Gpa materials (collagen, cellulose, chitin)
oriented UHMWPE should be wet synthesizeable (6 Gpa tensile strength)
graphene/diamondoid may be worth it in some places to hit 30 Gpa (EG:for things that fly or go to space)
dry nanotech won’t be vulnerable to parasites that can infect a biological system.
even if the AI has to deal with single day doubling times that’s still enough to cover the planet in a month.
but with the right design parasites really shouldn’t be a problem.
“Design is much more powerful than evolution since individually useless parts can be developed to create a much more effective whole. Evolution can’t flip the retina or reroute the recurrent laryngeal nerve even though those would be easy changes a human engineer could make.”
But directed evolution of a polymeric macromolecule (E.g. repurposing an existing enzyme to process a new substrate) is so much easier practically speaking than designing and making a bespoke macromolecule to do the same job. Synthesis and testing of many evolutionary candidates is quick and easy, so many design/make/test cycles can be run quickly. This is what is happening at the forefront of the artificial enzyme field.
Yes, designing proteins or RNAzymes or whatever is hard. Immense solution space and difficult physics. Trial and error or physically implemented genetic algorithms work well and may be optimal. (EG:provide fitness incentive to bacteria that succeed (EG:can you metabolize lactose?))
Major flaw in evolution:
nature does not assign credit for instrumental value
assume an enzymatic pathway is needed to perform N steps
all steps must be performed for benefit to occur
difficulty of solving each step is “C” constant
evolution has to do O(C^N) work to solve problem
with additional small constant factor improvement for horizontal genetic transfer and cooperative solution finding (EG: bacterial symbiosis)
intelligent agent can solve for each step individually for O(C*N) (linear) work
this applies also to any combination of structural and biochemical changes.
Also, nature’s design language may not be optimal for expressing useful design changes concisely. Biological state machines are hard to change in ways that carry through neatly to the final organism. This shows in various small ways in organism design. Larger changes don’t happen even though they’re very favorable (EG:retina flip would substantially improve low light eye capabilities (it very much did in image sensors)) and less valuable changes not happening and not varying almost at all over evolutionary time implies there’s something in the way there. If nature could easily make plumbing changes, organisms wouldn’t all have similar topology (IE:not just be warped copies of something else). New part introduction and old part elimination can happen but it’s not quick or clean.
Nature has no mechanisms for making changes at higher levels of abstraction. It can change one part of the DNA string but not “all the start codons at once and the ribosome start codon recognition domain”. Each individual genetic change is an independent discovery.
Working in these domains of abstraction reduces the dimensionality of the problem immensely and other such abstractions can be used to further constrain solution space cheaply.
edit: (link)green goo is plausible
The AI can kill us and then take over with better optimized biotech very easily.
Doubling time for
Plants (IE:solar powered wet nanotech) > single digit days
Algae in ideal conditions 1.5 days
E. Coli 20 minutes
There are piles of yummy carbohydrates lying around (Trees, plants, houses)
The AI can go full Tyranid
The AI can re-use existing cellular machinery. No need to rebuild the photosynthesis or protein building machinery, full digestion and rebuilding at the amino acid level is wasteful.
Sub 2 minute doubling times are plausible for a system whose rate limiting step is mechanically infecting plants with a fast acting subversive virus. Spreading flying things are self replicators that steal energy+cellular machinery from plants during infection (IE:mosquito like). Onset time could be a few hours till construction of shoggoth like things. Full biosphere assimilation could be limited by flight speed.
Nature can’t do these things since they require substantial non-incremental design changes. Mosquitoes won’t simultaneously get plant adapted needles + biological machinery to sort incoming proteins and cellular contents + continuous grow/split reproduction that would allow a small starting population to eat a forest in a day. Nature can’t design the virus to do post infection shoggoth construction either.
The only thing that even re-uses existing cellular machinery is viruses and that’s because they operate on much faster evolutionary time scales than their victims. Evolution takes so long that winning strategies to eat or subvert existing populations of organisms are self-limiting. The first thing to sort of work wipes out the population and then something else not vulnerable fills the niche.
Design is much more powerful than evolution since individually useless parts can be developed to create a much more effective whole. Evolution can’t flip the retina or reroute the recurrent laryngeal nerve even though those would be easy changes a human engineer could make.
Endgame biotech (IE: can design new proteins/DNA/organisms) is very powerful.
But that doesn’t mean dry nanotech is useless.
even if production is expensive it may be worth building some things that way anyways.
computers
structural components
Biology is largely stuck with ~0.15 Gpa materials (collagen, cellulose, chitin)
oriented UHMWPE should be wet synthesizeable (6 Gpa tensile strength)
graphene/diamondoid may be worth it in some places to hit 30 Gpa (EG:for things that fly or go to space)
dry nanotech won’t be vulnerable to parasites that can infect a biological system.
even if the AI has to deal with single day doubling times that’s still enough to cover the planet in a month.
but with the right design parasites really shouldn’t be a problem.
biological parasite defenses are not-optimal
“Design is much more powerful than evolution since individually useless parts can be developed to create a much more effective whole. Evolution can’t flip the retina or reroute the recurrent laryngeal nerve even though those would be easy changes a human engineer could make.”
But directed evolution of a polymeric macromolecule (E.g. repurposing an existing enzyme to process a new substrate) is so much easier practically speaking than designing and making a bespoke macromolecule to do the same job. Synthesis and testing of many evolutionary candidates is quick and easy, so many design/make/test cycles can be run quickly. This is what is happening at the forefront of the artificial enzyme field.
Yes, designing proteins or RNAzymes or whatever is hard. Immense solution space and difficult physics. Trial and error or physically implemented genetic algorithms work well and may be optimal. (EG:provide fitness incentive to bacteria that succeed (EG:can you metabolize lactose?))
Major flaw in evolution:
nature does not assign credit for instrumental value
assume an enzymatic pathway is needed to perform N steps
all steps must be performed for benefit to occur
difficulty of solving each step is “C” constant
evolution has to do O(C^N) work to solve problem
with additional small constant factor improvement for horizontal genetic transfer and cooperative solution finding (EG: bacterial symbiosis)
intelligent agent can solve for each step individually for O(C*N) (linear) work
this applies also to any combination of structural and biochemical changes.
Also, nature’s design language may not be optimal for expressing useful design changes concisely. Biological state machines are hard to change in ways that carry through neatly to the final organism. This shows in various small ways in organism design. Larger changes don’t happen even though they’re very favorable (EG:retina flip would substantially improve low light eye capabilities (it very much did in image sensors)) and less valuable changes not happening and not varying almost at all over evolutionary time implies there’s something in the way there. If nature could easily make plumbing changes, organisms wouldn’t all have similar topology (IE:not just be warped copies of something else). New part introduction and old part elimination can happen but it’s not quick or clean.
Nature has no mechanisms for making changes at higher levels of abstraction. It can change one part of the DNA string but not “all the start codons at once and the ribosome start codon recognition domain”. Each individual genetic change is an independent discovery.
Working in these domains of abstraction reduces the dimensionality of the problem immensely and other such abstractions can be used to further constrain solution space cheaply.