The main point is that if we survive or leave automation in place, can extend the lifespan of the biosphere by perhaps a billion years or more. Ecocentric ethics places value on the Earth’s biosphere, so it should approve of this. But this thread is about the physics involved.
Why is the biosphere in trouble? The main reason is that the sun is getting brighter. As hydrogen is fused into helium, it ends up as a dense helium core with higher pressure and temperature. That increases the rate of hydrogen fusion.
Eventually helium fusion begins and the sun becomes a red giant, but this is much further into the future (and harder to deal with, since it makes the sun swell up and quite possibly absorb the Earth). academic.oup.com/mnras/article/…
Earth maintains a somewhat constant temperature due to various feedbacks. One is that carbon dioxide is removed when it is warm and wet by weathering of rocks, which cools things down a bit. When it is cold and dry CO2 builds up.
(The biosphere cycles carbon at a far higher rate, but mostly between air, biomass and ocean. This geological feedback is likely how the snowball Earth episodes ended.)
Add more solar energy, and the equilibrium shifts towards less CO2. Eventually there is not enough for plant photosynthesis. At that point the biosphere starts vanishing more and more. As CO2 approaches zero, the temperature regulation is also lost and things start heating up.
Eventually there may be a runaway greenhouse as extra water vapor accelerates the heating, or a hothouse scenario where water is lost to space due to UV light splitting off hydrogen in the stratosphere. But no biosphere. arxiv.org/abs/1201.1593
When should we expect this? Modern biosphere/geosphere models tend to suggest at least 800 Myr left and 1.2 Gyr as a plausible median. Pure climate models tend to suggest that the temperature limit to the biosphere is at least 1 Gyr away.
OK, can we fix this? The most obvious thing is to try is to release CO2 from rocks artificially by heating up quartz with limestone to make wollastonite. This fixes the feedback, but will not handle the higher solar influx eventually.
More radically: move Earth outward. This is somewhat hard, but physically doable.
Another is astroengineering sun to keep luminosity stable. Removing mass from the sun using megascale engineering can also extend its lifespan. Changing core pressure or enhancing mixing may also be used. Makes geoengineering and planet moving look easy. link.springer.com/book/10.1007/9…
It is likely much easier to build a solar shade: place foil between Earth and the sun to reduce the insolation at the same rate as it is increasing. There are a fair number of papers exploring this option for current geoengineering journals.sagepub.com/doi/10.1243/09… link.springer.com/chapter/10.100…
Objects at the Earth-Sun L1 point remain in place (with some steering, otherwise they wander off in about a month), so it seems obvious that this is the spot to place the shade.
However, the light pressure on a thin shade makes the actual spot slightly different. This light pressure may also be useful for the steering, by using movable “light rudders” that adjust things. sciencedirect.com/science/articl…
An Earth-sized total shade would mass about 2 billion tonnes, or about 31 years of current annual aluminum production. The required growth rate is modest. For the next billion years, about one 100×100-m section would need to be added per year, weighing 15 kg.
There will also be refills needed when parts break because they get hit by meteors. One can imagine a regulation system that adds shade elements whenever observed Earth temperatures go up, reducing the addition when they go down. It does not have to be very smart.
Can we build a solar shade factory? It does not have to be vast given the above requirements. One can imagine a solar powered factory on an asteroid or the moon where robots scoop up raw materials and launch solar sails that join the shade. researchgate.net/publication/36…
Things will go wrong over a billion years. That is why one should have a few backups. Interestingly, even a slow growth of reserve factories can virtually guarantee that they last as long as the Earth-moon system does. fhi.ox.ac.uk/reports/2012-1…
How long can this system work? My simulations suggest it might work until the serious red giant stage in 7.4 Gyr. The shade will become larger and denser. While Earth retains its temperature light is increasingly going to be a red. But life is likely to evolve to deal with it.
The point of our paper is not so much to prescribe what must be done (these schemes will look as silly as Comte de Buffon's 18th C suggestion of adding more livestock to heat the planet) as show that there are ways we can help the biosphere survive long-term.
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The more I learn writing prompts for AI-generated art, the more I note that it is a language based on clichés.
This is not a criticism! Clichés, tropes, standard imagery are easy references to high-dimensional vectors in concept space. "evil stepmother", "greg rutkowski", "baroque" and "central perspective" link to very complex things, and we can invoke them easily and conventionally.
Each cliché helps locate a direction in the space of possible images, intersecting the manifold of reasonable images in some place. It is an additive language rather than constraining like normal grammar.
If this result holds up generally, merging networks trained on different parts of data looks feasible. Huge implications - privacy through federated learning, parallelization of learning, merging of em shards!
The basic idea is simple: you can permute hidden layer neurons, so there are actually far fewer internal models than it looks. Training gets to one, with linear mode connectivity. Can hence interpolate differently trained networks if one is careful.
If each layer has N neurons and weights can have K values there are N! permutations and K^(N^2) weight matrices. ln K^(N^2)/N! = N^2 ln K - N ln N + N + O(ln N). So wide networks have room for more possible models, but SGD consistently only seems to find one basin of attraction.
Is there any good study of the average lifespans of villages, towns and cities? My impression is that they do not disappear very often, despite there being a fair number of examples of ghost towns (that are often lightly inhabited). en.wikipedia.org/wiki/List_of_g…
This is linked to my bigger interest in what determines the lifespans of social structures and projects. Generally, constant risk over time seems to be the generic case for states, empires, species and companies; increasing risk only in software and individual organisms.
I suspect there may be a category that is just so resilient/regenerative/has economies of scale that the survival curve asymptotes or gets heavy tail: universities, religious institutions, and especially cities seem to be here.
Nice thread about why democratizing AI makes more sense the weaker the AI is. But this only looks at "offensive" capabilities: clearly AI can also protect.
The real issue might not even be the offense-defense balance, but whether defense is reliable enough. A world where bad actors occasionally have great wins may be worse than one where they can often gain small. Some credit fraud ok, not everybody's accounts drained.
Democratisation of defensive AI may be a great good, due to diverse defences. Joint defence may scale well in some domains, but we should not expect same scaling for hacking, fraud, war or philosophy.
The first consideration of how to move the planet was made by Archimedes boast: "Give me a place to stand and with a lever I will move the whole world." physics.stackexchange.com/questions/4831…
Christoph Grienberger in 1603 proposed gearing powered by a treadmill, allowing it to be raised veeeerrryyy slowly. He got the rough number of gears right by modern reckoning. bbc.com/future/article…
#FridayPhysicsFun – Coolest fact I learned this week: under some conditions light-emitting diodes can be more than 100% efficient, and act as refrigerators.
Normally energy conversion introduces losses: there is a production of entropy turning high-quality energy (e.g. mechanical motion, electricity) into disordered low-quality (e.g. heat), and turning low-quality into high-quality is less efficient.
This is why normally any device promising more than 100% efficiency is fake. Thermodynamics does not allow it.