Biological nano-scale engineering has an additional constraint: it must be evolvable. The amount of bandwidth transmitted into the genome from the world via selection is surprisingly small.
In terms of software architecture, brownian motion gives a sort of message-broadcasting architecture—very decoupled. The messages (proteins) know how to execute themselves (very object oriented). The entity building it from data (ribosome) doesn’t know what it’s building. The entity powering it (ATP synthase) doesn’t know what it’s powering.
In this design, in order to one location to communicate a message to another location, some mass has to brownian-motion its way across. Suppose in a redesign, locations that needed to communicate messages were wired together with flexible polymers. Moving electrons, waves of configuration changes, or even molecular messages along a guide would be significantly faster, particularly over long distances; latency is proportional to square of distance for brownian motion. (Indeed, in latency-critical applications, biology does use wire-ish communication; neurons.)
Even admitting that Drexler’s nanomachines probably look more ridiculous to a future experienced nanoscale engineer than Da Vinci’s machines do to a mechanical engineer, there’s obvious room for improvements. We cannot assume that biology is anywhere close to the limits on efficiency imposed by the laws of physics.
In order for us to observe biological (as opposed to intelligently designed) nanoscale engineering in the wild, it must be possible for it to have evolved.
If you look at genetic algorithms, they don’t find all, many, most, or the best solutions—they find solutions which have paths of a certain type leading to them. You could call these paths axis-aligned, where each gene corresponds to an axis. E.g. http://www.caplet.com/MannaMouse.html
The applet only has two genes, and so doesn’t have any of the changing-numbers-of-genes phenomena that we expect in the real world, but it gives a rough sense that evolution works in a specific, simple, and not very smart manner over the fitness landscape.
Indeed. An even bigger constraint is energy consumption—natural life forms operate under absurdly constrained energy budgets compared to machinery, which sharply limits the materials they can be made of and the performance they can deliver.
Ok, yes, I understand that anything interesting we find in the wild must have arisen by evolution, and hence that it must be evolvable. But I understood your reference to “engineering” to mean “designed by an intelligent human being”. In which case, evolvability is rather irrelevant.
You apparently are anthropomorphizing Nature as an engineer. That is OK with me, but please don’t imagine that we are not capable of doing some biological nanoscale engineering on our own, making no further use of evolution than to utilize the enzyme systems and ribosomes with which Nature has already presented us.
Biological nano-scale engineering has an additional constraint: it must be evolvable. The amount of bandwidth transmitted into the genome from the world via selection is surprisingly small.
In terms of software architecture, brownian motion gives a sort of message-broadcasting architecture—very decoupled. The messages (proteins) know how to execute themselves (very object oriented). The entity building it from data (ribosome) doesn’t know what it’s building. The entity powering it (ATP synthase) doesn’t know what it’s powering.
In this design, in order to one location to communicate a message to another location, some mass has to brownian-motion its way across. Suppose in a redesign, locations that needed to communicate messages were wired together with flexible polymers. Moving electrons, waves of configuration changes, or even molecular messages along a guide would be significantly faster, particularly over long distances; latency is proportional to square of distance for brownian motion. (Indeed, in latency-critical applications, biology does use wire-ish communication; neurons.)
Even admitting that Drexler’s nanomachines probably look more ridiculous to a future experienced nanoscale engineer than Da Vinci’s machines do to a mechanical engineer, there’s obvious room for improvements. We cannot assume that biology is anywhere close to the limits on efficiency imposed by the laws of physics.
Could you explain this claim?
In order for us to observe biological (as opposed to intelligently designed) nanoscale engineering in the wild, it must be possible for it to have evolved.
If you look at genetic algorithms, they don’t find all, many, most, or the best solutions—they find solutions which have paths of a certain type leading to them. You could call these paths axis-aligned, where each gene corresponds to an axis. E.g. http://www.caplet.com/MannaMouse.html
The applet only has two genes, and so doesn’t have any of the changing-numbers-of-genes phenomena that we expect in the real world, but it gives a rough sense that evolution works in a specific, simple, and not very smart manner over the fitness landscape.
Indeed. An even bigger constraint is energy consumption—natural life forms operate under absurdly constrained energy budgets compared to machinery, which sharply limits the materials they can be made of and the performance they can deliver.
Ok, yes, I understand that anything interesting we find in the wild must have arisen by evolution, and hence that it must be evolvable. But I understood your reference to “engineering” to mean “designed by an intelligent human being”. In which case, evolvability is rather irrelevant.
You apparently are anthropomorphizing Nature as an engineer. That is OK with me, but please don’t imagine that we are not capable of doing some biological nanoscale engineering on our own, making no further use of evolution than to utilize the enzyme systems and ribosomes with which Nature has already presented us.
Yes, you’re correct, I was anthropomorphizing evolution as an engineer; my “biological” corresponds to your “in the wild”.