温柔的奇点

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温和的奇点 The Gentle Singularity(https://blog.samaltman.com/the-gentle-singularity)

我们已经越过了事件视界；起飞已经开始。人类即将构建数字超级智能，至少到目前为止，它远没有看起来那么奇怪。

We are past the event horizon; the takeoff has started. Humanity is close to building digital superintelligence, and at least so far it’s much less weird than it seems like it should be.

机器人还没有走上街头，我们大多数人也没有整天与 AI 交谈。人们仍然死于疾病，我们仍然无法轻易进入太空，而且我们对宇宙还有很多不了解的地方。

Robots are not yet walking the streets, nor are most of us talking to AI all day. People still die of disease, we still can’t easily go to space, and there is a lot about the universe we don’t understand.

然而，我们最近构建的系统在许多方面比人类更聪明，并且能够显著放大使用它们的人的输出。工作中最不可能的部分已经过去；让我们达到 GPT-4 和 o3 这类系统的科学洞察来之不易，但将带我们走得很远。

And yet, we have recently built systems that are smarter than people in many ways, and are able to significantly amplify the output of people using them. The least-likely part of the work is behind us; the scientific insights that got us to systems like GPT-4 and o3 were hard-won, but will take us very far.

AI 将以多种方式为世界做出贡献，但 AI 推动更快的科学进步和提高生产力所带来的生活质量提升将是巨大的；未来可以比现在好得多。科学进步是整体进步的最大驱动力；想到我们还能拥有多少，真是令人兴奋。

AI will contribute to the world in many ways, but the gains to quality of life from AI driving faster scientific progress and increased productivity will be enormous; the future can be vastly better than the present. Scientific progress is the biggest driver of overall progress; it’s hugely exciting to think about how much more we could have.

从某种意义上说，ChatGPT 已经比任何曾经存在的人类都更强大。数亿人每天依赖它处理越来越重要的任务；一个小的新能力可以产生巨大的积极影响；而一个小的对齐问题乘以数亿人则可能造成巨大的负面影响。

In some big sense, ChatGPT is already more powerful than any human who has ever lived. Hundreds of millions of people rely on it every day and for increasingly important tasks; a small new capability can create a hugely positive impact; a small misalignment multiplied by hundreds of millions of people can cause a great deal of negative impact.

2025 年已经出现了能够进行真正认知工作的智能体；编写计算机代码将不再一样。2026 年可能会看到能够发现新颖见解的系统。2027 年可能会看到能够在现实世界中执行任务的机器人。

2025 has seen the arrival of agents that can do real cognitive work; writing computer code will never be the same. 2026 will likely see the arrival of systems that can figure out novel insights. 2027 may see the arrival of robots that can do tasks in the real world.

更多的人将能够创建软件和艺术。但世界对这两者的需求更大，只要专家接受新工具，他们可能仍然比新手好得多。总的来说，一个人在 2030 年比 2020 年能完成更多事情的能力将是一个显著的变化，许多人将学会如何从中受益。

A lot more people will be able to create software, and art. But the world wants a lot more of both, and experts will probably still be much better than novices, as long as they embrace the new tools. Generally speaking, the ability for one person to get much more done in 2030 than they could in 2020 will be a striking change, and one many people will figure out how to benefit from.

在最关键的方面，2030 年代可能不会有太大不同。人们仍然会爱他们的家人，表达他们的创造力，玩游戏，在湖里游泳。

In the most important ways, the 2030s may not be wildly different. People will still love their families, express their creativity, play games, and swim in lakes.

但在仍然非常重要的方面，2030 年代很可能与以往任何时代都截然不同。我们不知道我们能超越人类智能多远，但我们即将发现。

But in still-very-important-ways, the 2030s are likely going to be wildly different from any time that has come before. We do not know how far beyond human-level intelligence we can go, but we are about to find out.

在 2030 年代，智能和能量——想法以及实现想法的能力——将变得极其丰富。这两者长期以来一直是人类进步的基本限制因素；有了丰富的智能和能量（以及良好的治理），理论上我们可以拥有其他一切。

In the 2030s, intelligence and energy—ideas, and the ability to make ideas happen—are going to become wildly abundant. These two have been the fundamental limiters on human progress for a long time; with abundant intelligence and energy (and good governance), we can theoretically have anything else.

我们已经生活在令人难以置信的数字智能中，经过最初的震惊后，我们大多数人已经相当习惯了。我们很快从惊叹 AI 能生成一段优美文字，转变为想知道它何时能生成一部优美的小说；或者从惊叹它能做出救命的医疗诊断，转变为想知道它何时能开发出治疗方法；或者从惊叹它能创建一个小型计算机程序，转变为想知道它何时能创建一家全新的公司。这就是奇点的过程：奇迹变成日常，然后变成基本要求。

Already we live with incredible digital intelligence, and after some initial shock, most of us are pretty used to it. Very quickly we go from being amazed that AI can generate a beautifully-written paragraph to wondering when it can generate a beautifully-written novel; or from being amazed that it can make live-saving medical diagnoses to wondering when it can develop the cures; or from being amazed it can create a small computer program to wondering when it can create an entire new company. This is how the singularity goes: wonders become routine, and then table stakes.

我们已经听到科学家说，他们的生产力比使用 AI 之前提高了两到三倍。高级 AI 因许多原因而有趣，但也许没有什么比我们可以用它来加速 AI 研究更重要。我们可能发现新的计算基质、更好的算法，谁知道还有什么。如果我们能在一年或一个月内完成十年的研究，那么进步的速度显然会大不相同。

We already hear from scientists that they are two or three times more productive than they were before AI. Advanced AI is interesting for many reasons, but perhaps nothing is quite as significant as the fact that we can use it to do faster AI research. We may be able to discover new computing substrates, better algorithms, and who knows what else. If we can do a decade’s worth of research in a year, or a month, then the rate of progress will obviously be quite different.

从现在开始，我们已经构建的工具将帮助我们找到进一步的科学洞察，并帮助我们创建更好的 AI 系统。当然，这与 AI 系统完全自主更新自己的代码不同，但无论如何，这是递归自我改进的幼虫版本。

From here on, the tools we have already built will help us find further scientific insights and aid us in creating better AI systems. Of course this isn’t the same thing as an AI system completely autonomously updating its own code, but nevertheless this is a larval version of recursive self-improvement.

还有其他自我强化的循环在起作用。经济价值创造启动了一个复合基础设施建设的飞轮，以运行这些越来越强大的 AI 系统。能够建造其他机器人的机器人（在某种意义上，能够建造其他数据中心的数据中心）也不远了。

There are other self-reinforcing loops at play. The economic value creation has started a flywheel of compounding infrastructure buildout to run these increasingly-powerful AI systems. And robots that can build other robots (and in some sense, datacenters that can build other datacenters) aren’t that far off.

如果我们必须用传统方式制造第一批百万个人形机器人，但随后它们可以操作整个供应链——挖掘和提炼矿物、驾驶卡车、运营工厂等——来建造更多机器人，这些机器人又可以建造更多的芯片制造设施、数据中心等，那么进步的速度显然会大不相同。

If we have to make the first million humanoid robots the old-fashioned way, but then they can operate the entire supply chain—digging and refining minerals, driving trucks, running factories, etc.—to build more robots, which can build more chip fabrication facilities, data centers, etc, then the rate of progress will obviously be quite different.

随着数据中心生产自动化，智能的成本最终应收敛到接近电力的成本。（人们常常好奇一次 ChatGPT 查询消耗多少能量；平均查询消耗约 0.34 瓦时，相当于烤箱运行一秒多一点，或高效灯泡运行几分钟。它还消耗约 0.000085 加仑水，大约十五分之一茶匙。）

As datacenter production gets automated, the cost of intelligence should eventually converge to near the cost of electricity. (People are often curious about how much energy a ChatGPT query uses; the average query uses about 0.34 watt-hours, about what an oven would use in a little over one second, or a high-efficiency lightbulb would use in a couple of minutes. It also uses about 0.000085 gallons of water; roughly one fifteenth of a teaspoon.)

技术进步的速度将继续加速，人们适应几乎任何事物的能力也将继续存在。会有非常困难的时期，比如整类工作消失，但另一方面，世界将变得如此之快如此富裕，以至于我们能够认真考虑以前从未有过的新政策想法。我们可能不会一下子采用新的社会契约，但当我们几十年后回顾时，渐进的变化将累积成巨大的成果。

The rate of technological progress will keep accelerating, and it will continue to be the case that people are capable of adapting to almost anything. There will be very hard parts like whole classes of jobs going away, but on the other hand the world will be getting so much richer so quickly that we’ll be able to seriously entertain new policy ideas we never could before. We probably won’t adopt a new social contract all at once, but when we look back in a few decades, the gradual changes will have amounted to something big.

如果历史有指导意义，我们将找到新的事情做和新的欲望，并迅速吸收新工具（工业革命后的职业变化是一个很好的近期例子）。期望会上升，但能力也会同样迅速上升，我们将得到更好的东西。我们将为彼此建造越来越美好的事物。人类相对于 AI 有一个长期重要且奇特的优势：我们天生关心他人及其所思所为，而对机器不太关心。

If history is any guide, we will figure out new things to do and new things to want, and assimilate new tools quickly (job change after the industrial revolution is a good recent example). Expectations will go up, but capabilities will go up equally quickly, and we’ll all get better stuff. We will build ever-more-wonderful things for each other. People have a long-term important and curious advantage over AI: we are hard-wired to care about other people and what they think and do, and we don’t care very much about machines.

一千年前的自给自足农民看到我们许多人做的事情会说我们做的是假工作，认为我们只是在玩游戏自娱自乐，因为我们有充足的食物和难以想象的奢侈品。我希望我们将来看一千年后的工作，会觉得它们是非常假的工作，而且我毫不怀疑它们对从事这些工作的人来说会感到极其重要和满足。

A subsistence farmer from a thousand years ago would look at what many of us do and say we have fake jobs, and think that we are just playing games to entertain ourselves since we have plenty of food and unimaginable luxuries. I hope we will look at the jobs a thousand years in the future and think they are very fake jobs, and I have no doubt they will feel incredibly important and satisfying to the people doing them.

新奇迹实现的速度将是巨大的。今天甚至很难想象到 2035 年我们会发现什么；也许我们会从一年解决高能物理，到下一年开始太空殖民；或者从一年重大材料科学突破，到下一年真正的高带宽脑机接口。许多人会选择以大致相同的方式生活，但至少有些人可能会决定“接入”。

The rate of new wonders being achieved will be immense. It’s hard to even imagine today what we will have discovered by 2035; maybe we will go from solving high-energy physics one year to beginning space colonization the next year; or from a major materials science breakthrough one year to true high-bandwidth brain-computer interfaces the next year. Many people will choose to live their lives in much the same way, but at least some people will probably decide to “plug in”.

展望未来，这听起来难以理解。但可能经历它会感觉令人印象深刻但可控。从相对论的角度看，奇点一点一点地发生，融合缓慢进行。我们正在攀登指数级技术进步的长弧；向前看总是垂直的，向后看是平坦的，但它是一条平滑的曲线。（回想一下 2020 年，如果那时告诉你到 2025 年会有接近 AGI 的东西，听起来会是什么样子，而过去 5 年实际又是怎样的。）

Looking forward, this sounds hard to wrap our heads around. But probably living through it will feel impressive but manageable. From a relativistic perspective, the singularity happens bit by bit, and the merge happens slowly. We are climbing the long arc of exponential technological progress; it always looks vertical looking forward and flat going backwards, but it’s one smooth curve. (Think back to 2020, and what it would have sounded like to have something close to AGI by 2025, versus what the last 5 years have actually been like.)

在巨大好处的同时，也有严峻的挑战需要面对。我们确实需要从技术和社会层面解决安全问题，但考虑到经济影响，广泛分配超级智能的访问权也至关重要。最好的前进道路可能是这样的：

There are serious challenges to confront along with the huge upsides. We do need to solve the safety issues, technically and societally, but then it’s critically important to widely distribute access to superintelligence given the economic implications. The best path forward might be something like:

1. 解决对齐问题，即我们能够稳健地保证 AI 系统学习并朝着我们集体真正想要的长期目标行动（社交媒体信息流是未对齐 AI 的一个例子；驱动这些的算法在让你不断滚动方面非常出色，并且清楚理解你的短期偏好，但它们通过利用你大脑中覆盖长期偏好的东西来实现这一点）。

1. Solve the alignment problem, meaning that we can robustly guarantee that we get AI systems to learn and act towards what we collectively really want over the long-term (social media feeds are an example of misaligned AI; the algorithms that power those are incredible at getting you to keep scrolling and clearly understand your short-term preferences, but they do so by exploiting something in your brain that overrides your long-term preference).

2. 然后专注于使超级智能廉价、广泛可用，并且不过度集中于任何个人、公司或国家。社会是有韧性的、有创造力的，并且适应迅速。如果我们能够利用集体的意志和智慧，那么尽管我们会犯很多错误，有些事情会真的出错，但我们会迅速学习和适应，并能够利用这项技术获得最大收益和最小损失。在广泛的社会必须决定的边界内，给用户大量自由似乎非常重要。世界越早开始讨论这些广泛边界是什么以及我们如何定义集体对齐，就越好。

2. Then focus on making superintelligence cheap, widely available, and not too concentrated with any person, company, or country. Society is resilient, creative, and adapts quickly. If we can harness the collective will and wisdom of people, then although we’ll make plenty of mistakes and some things will go really wrong, we will learn and adapt quickly and be able to use this technology to get maximum upside and minimal downside. Giving users a lot of freedom, within broad bounds society has to decide on, seems very important. The sooner the world can start a conversation about what these broad bounds are and how we define collective alignment, the better.

我们（整个行业，不仅仅是 OpenAI）正在为世界构建一个大脑。它将极其个性化且易于每个人使用；我们将受限于好的想法。长期以来，创业行业的技术人员一直嘲笑“点子王”——那些有想法但寻找团队来实现的人。现在看来，他们即将迎来他们的高光时刻。

We (the whole industry, not just OpenAI) are building a brain for the world. It will be extremely personalized and easy for everyone to use; we will be limited by good ideas. For a long time, technical people in the startup industry have made fun of “the idea guys”; people who had an idea and were looking for a team to build it. It now looks to me like they are about to have their day in the sun.

OpenAI 现在有很多身份，但首先，我们是一家超级智能研究公司。我们面前有很多工作，但我们面前的大部分道路现在已被照亮，黑暗区域正在迅速消退。我们非常感激能够做我们所做的事情。

OpenAI is a lot of things now, but before anything else, we are a superintelligence research company. We have a lot of work in front of us, but most of the path in front of us is now lit, and the dark areas are receding fast. We feel extraordinarily grateful to get to do what we do.

智能廉价到不计量的程度已经触手可及。这听起来可能疯狂，但如果我们 2020 年告诉你我们将达到今天的位置，那可能比我们现在对 2030 年的预测听起来更疯狂。

Intelligence too cheap to meter is well within grasp. This may sound crazy to say, but if we told you back in 2020 we were going to be where we are today, it probably sounded more crazy than our current predictions about 2030.

愿我们平稳、指数级且平静地通过超级智能。

May we scale smoothly, exponentially and uneventfully through superintelligence.

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