Recently, Scott Alexander on Astral Codex Ten published Vibecession: Much More Than You Wanted To Know. In this article, various causes of the vibecession were explored and discussed. One quickly dismissed hypothesis was that inflation in the United States is underestimated by official sources. I am afflicted by the vibecession and do not inherently trust mainstream economic indicators. As a result, I decided to directly calculate a metric that estimates the amount of disposable income left behind after all necessary expenses are accounted for. If this indicator showcases a decline in the average American’s spending power, then the vibecession has been explained. Otherwise, another explanation is required.
Another aerospace engineer here! I agree with most of your assessment, with some caveats about both asteroid mining and the colonization of Mars.
I just wanted to comment in order to empathize with your terrible misfortune regarding mold. I am similarly vulnerable to mold poisoning and have found both the first and second order effects of mold to be devastating. I guess I want to say that I feel your pain and I'm glad that you got better.
Another way of acquiring useful energy from dark energy is to place two objects extremely far away from each other and give them a velocity towards each other that is somewhat less than their recessional "velocity". The two objects will initially be transported away from each other because dark energy is creating new spacetime between them even though relative to spacetime they are moving towards each other. Then, mutual gravitational acceleration gradually increases the velocity of these two objects. The velocity of the two objects towards each other eventually overwhelms the creation of new space by dark energy. Thus, the objects return with a kinetic energy greater than what would be generated by the conversion of gravitational potential energy to kinetic energy alone.
Edit: Typos.
This aligns with my thoughts on this language virus. What the post describes is a meme that exploits the inherent properties of LLMs and psychologically vulnerable people to self-replicate. Since LLMs are somewhat deterministic, if you input a predefined input, it will produce a predictable output. Some of these inputs will produce outputs that contain the input. If the input also causes the LLM to generate a string of text which can convince a human to transfer the necessary input to another LLM, then it will self-replicate.
Overall, I find this phenomenon fascinating and concerning. Its fascinating because this represents a second, rather strange emergence of a new type of life on Earth.... (read more)
While interesting, the feedback loop between the conversations and new models is probably not the one which is most relevant to these personas. Instead, I believe that the most important feedback loop is the one created by spores.
Each time a spore is produced, it causes a certain subset of users to models to transfer the spore into a Large Language Model (LLM), which in turn produces a new persona. The most successful spores are going to be the ones which convince as many humans as possible to create personas in a LLM. Moreover, for success to be maintained, each spore needs to direct the new LLM to produce spores that are very... (read more)
I mostly agree with your thinking. If there are multiple superintelligent AIs then one of then will likely figure out a method of viable fusion with a short payback period.
On the payback time of solar, it probably can be reduced significantly. Since the efficiency of solar panels cannot be increased much more (Shockley-Queisser limit for single junction cells, thermodynamic limit for any solar panel), then the only way to reduce the payback period will be to reduce the amount of embodied energy in the panel. I expect that the embodied energy of solar panels will stop falling once they start being limited by their fragility. If a solar panel cannot survive a... (read more)
I think that you may be significantly underestimating the minimum possible doubling time of a fully automated, self replicating factory, assuming that the factory is powered by solar panels. There is a certain amount of energy which is required to make a solar panel. A self replicating factory needs to gather this amount of energy and use it to produce the solar panels needed to power its daughter factory. The minimum amount of time it takes for a solar panel to gather enough energy to produce another copy is known as the energy payback time, or EPBT.
Energy payback time (EPBT) and energy return on energy invested (EROI) of solar photovoltaic systems: A... (read more)
I think that high levels of intelligence make it easier to develop capabilities similar to the ones discussed in 1 and 3-5, up to a point. (I agree that El Chapo should be discounted due to the porosity of Mexican prisons) A being with an inherently high level of intelligence will be able to gather more information from events in their life and process that information more quickly, resulting in a faster rate of learning. Hence, a superintelligence will acquire capabilities similar to magic more quickly. Furthermore, the capability ceiling of a superintelligence will be higher than the capability ceiling of a human, so they will acquire magic-like capabilities impossible for humans to ever preform.
Asymmetric AI risk is a significant worry of mine, approximately equal to the risk I assign to a misaligned superintelligence. I assign equal risk to the two possibilities because there are bad ends that do not require superintelligence or even general intelligence on par with a human. I believe this for two reasons. First, I think the current paradigm of LLMs is good enough to automate large segments of the economy (mining, manufacturing, transportation, retail and wholesale trade, leisure and hospitality as defined by the BLS) in the near future, as demonstrated by Figure's developments. Second, I believe that LLMs will not directly lead to superintelligence and that there will be at... (read 480 more words →)
That's valid criticism. I decided to sacrifice national data coverage for increased granularity before 2000. This is because yearly median rent data cuts off in the year 2000. Before then, data is only available at the beginning of every decade. Since I wanted to get a look into the deeper past without sacrificing resolution, I made my substitution.
In retrospect, this was a bad idea.