少点错误 01月08日
On Eating the Sun
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文章探讨了人工智能超越人类后,可能将太阳视为最丰富的能量来源,并将其转化为计算资源的可能性。文章认为,随着技术加速发展,人工智能为了追求更强大的计算能力和资源,可能会在未来10000年内“吞噬”太阳。这种行为并非科幻,而是基于人工智能的内在逻辑和技术发展的必然趋势。文章还分析了协调与非协调两种技术发展模式下,人工智能吞噬太阳的动机,并指出这可能是人工智能发展的一个重要里程碑。

☀️ 太阳是距离地球最近的、最富含能量的资源,对于制造计算机至关重要。文章指出,太阳蕴含的质量能量是制造计算机的必要条件,而太阳是4光年内质量能量最集中的地方。

🤖 人工智能一旦超越人类,将能更快更好地完成人类能做的所有事情,包括设计出“吞噬”太阳的机器。文章认为,人工智能在拥有远超人类的智能后,会认识到太阳的价值,并将其转化为计算资源。

🚀 技术发展具有棘轮效应,新技术的出现通常不会消失,并且技术发展速度正在加快。文章认为,技术发展速度的加快,意味着在未来某个阶段,人工智能将具备“吞噬”太阳的能力和动机。

🤝 文章分析了两种技术发展模式:协调模式和非协调模式。协调模式下的AI会进行长期优化,而非协调模式下的AI则会为了竞争优势而加速资源获取,无论哪种模式,都可能导致“吞噬”太阳的结果。

Published on January 8, 2025 4:57 AM GMT

The Sun is the most nutritious thing that's reasonably close. It's only 8 light-minutes away, yet contains the vast majority of mass within 4 light-years of the Earth. The next-nearest star, Proxima Centauri, is about 4.25 light-years away.

By "nutritious", I mean it has a lot of what's needed for making computers: mass-energy. In "Ultimate physical limits to computation", Seth Lloyd imagines an "ultimate laptop" which is the theoretically best computer that is 1 kilogram of mass, contained in 1 liter. He notes a limit to calculations per second that is proportional to the energy of the computer, which is mostly locked in its mass (E = mc²). Such an energy-proportional limit applies to memory too. Energy need not be expended quickly in the course of calculation, due to reversible computing.

So, you need energy to make computers out of (much more than you need energy to power them). And, within 4 light-years, the Sun is where almost all of that energy is. Of course, we don't have the technology to eat the Sun, so it isn't really our decision to make. But, when will someone or something be making this decision?

Artificial intelligence that is sufficiently advanced could do everything a human could do, better and faster. If humans could eventually design machines that eat the Sun, then sufficiently advanced AI could do so faster. There is some disagreement about "takeoff speeds", that is, the time between when AI is about as intelligent as humans, to when it is far far more intelligent.

My argument is that, when AI is far far more intelligent than humans, it will understand the Sun as the most nutritious entity that is within 4 light-years, and eat it within a short time frame. It really is convergently instrumental to eat the Sun, in the sense of repurposing at least 50% its mass-energy to make machines including computers and their supporting infrastructure ("computronium").

I acknowledge that some readers may think the Sun will never be eaten. Perhaps it sounds like sci-fi to them. Here, I will argue that Sun-eating is probable within the next 10,000 years.

Technological development has a ratchet effect: good technologies get invented, but usually don't get lost, unless they weren't very important/valuable (compared to other available technologies). Empirically, the rate of discovery seems to be increasing. To the extent pre-humans even had technology, it was developed a lot more slowly. Technology seems to be advancing a lot faster in the last 1000 years than it was from 5000 BC to 4000 BC. Part of the reason for the change in rate is that technologies build on other technologies; for example, the technology of computers allows discovery of other technologies through computational modeling.

So, we are probably approaching a stage where technology develops very quickly. Eventually, the rate of technology development will go down, due to depletion of low-hanging fruit. But before then, in the regime where technology is developing very rapidly, it will be both feasible and instrumentally important to run more computations, quickly. Computation is needed to research technologies, among other uses. Running sufficiently difficult computations requires eating the Sun, and will be feasible at some technology level, which itself probably doesn't require eating the Sun (eating the Earth probably provides more than enough energy to have enough computational power to figure out the technology to eat the Sun).

Let's further examine the motive for creating many machines, including computers, quickly. Roughly, we can consider two different regimes of fast technology development: coordinated and uncoordinated.

    A coordinated regime will act like a single agent (or "singleton"), even if it's composed of multiple agents. This regime would do some kind of long-termist optimization (in this setting, even a few years is pretty long-term). Of course, it would want to discover technology quickly, all else being equal (due to astronomical waste considerations). But it might be somewhat "environmentalist" in terms of avoiding making hard-to-reverse decisions, like expending a lot of energy. I still think it would eat the Sun, on the basis that it can later convert these machines to other machines, if desired (it has access to many technologies, after all).

    In an uncoordinated regime, multiple agents compete for resources and control. Broadly, having more machines (including computers) and more technology grants a competitive advantage. That is a strong incentive to turn the Sun into machines and develop technologies quickly. Perhaps an uncoordinated regime can transition to a coordinated one, as either there is a single victor, or the most competitive players start coordinating.

This concludes the argument that the Sun will be largely eaten in the next 10,000 years. It really will be a major event in the history of the solar system. Usually, not much happens to the Sun in 10,000 years. And I really think I'm being conservative in saying 10,000. This would in typical discourse be considered "very long ASI timelines", under the assumption that ASI eats the Sun within a few years.

Thinking about the timing of Sun-eating seems more well-defined, and potentially precise, than thinking about the timeline of "human-level AGI" or "ASI". These days, it's hard to know what people mean by AGI. Does "AGI" mean a system that can answer math questions better than the average human? We already have that. Does it mean a system that can generate $100 billion in profit? Obvious legal fiction.

Sun-eating tracks a certain stage in AGI capability. Perhaps there are other concrete, material thresholds corresponding to convergent instrumental goals, which track earlier stages. These could provide more specific definitions for AGI-related forecasting.



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人工智能 太阳 技术发展 计算资源 未来科技
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