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形势感知:未来十年不是技术故事,而是国家级动员预告

这篇导言最值得重视的判断不是“AGI 快来了”,而是作者明确主张:AI 正在从模型竞赛升级为电力、资本、军工与国家安全主导的总动员,但他对 AGI/超级智能时间表的外推明显过猛。
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2026-05-02 原文链接 ↗
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核心观点

  • AGI是工程必然而非科学偶然:算力与算法效率每年各提升0.5个数量级(OOM),叠加Agent形态的“去枷锁”,2027年AI能力必将从“高中生”跃迁至AGI。
  • 智能爆炸将抹平人类反应窗口:AGI一旦达成,数亿个智能体将接管AI研发,把人类需要10年的算法迭代压缩至1年内,直接催生超级智能。
  • 万亿算力集群倒逼国家机器下场:AI竞赛的终局不在商业市场,而在国家安全密室(SCIF),美国政府必将在2027-2028年接管AGI项目以应对地缘政治存亡。
  • 前沿实验室的安全漏洞是致命软肋:当前顶级AI公司重能力轻安全,根本无力抵御国家级黑客对模型权重和核心代码的窃取。

跟我们的关联

  • 对 Neta 意味着什么、下一步怎么用:大模型出海与全球化业务必须将“地缘政治断崖”纳入增长模型;下一步应立即制定“降级可用”的备用方案,剥离对单一受控API的致命依赖。
  • 对 ATou 意味着什么、下一步怎么用:做AI产品不能死磕“预测下一个词”的当前智障表现,而要基于“权限解锁”做规划;下一步应将研发重心转移到为模型搭建脚手架(记忆、工具调用、反思机制)的Agent架构上。
  • 对 Uota 意味着什么、下一步怎么用:在范式转移期,团队认知天花板决定生死;下一步在招聘和战略决策时,必须剔除用线性思维贬低AI的人,押注敢于按“2027年AGI”倒推业务流的趋势信仰者。

讨论引子

1. 如果AI的实际经济效益(ROI)无法覆盖万亿级算力与电力的资本支出,这场基于指数外推的“产业总动员”会在哪一年因资金链断裂而崩盘? 2. 当AGI竞赛被简化为“自由世界 vs 威权强权”的二元对立时,高度依赖全球化(如ASML、台积电)的半导体供应链能否支撑这种“曼哈顿计划式”的封闭研发? 3. 赋予AI“去枷锁”的Agent执行权确实能带来能力跃迁,但这种权限下放与作者呼吁的“极端安全控制”是否存在不可调和的底层矛盾?

Leopold Aschenbrenner,2024 年 6 月

在旧金山,你能最先看见未来。 过去一年里,城中谈资已经从 100 亿美元算力集群,变成 1000 亿美元集群,再变成万亿美元集群。每隔六个月,董事会计划里就会再多一个零。幕后的争夺异常激烈。人们在抢下这个十年剩余时间里一切还能拿到的电力合同,抢下一切还能采购到的电压变压器。美国大企业正在做准备,要把数万亿美元砸进一场久违的美国产业力量总动员。到这个十年结束时,美国的发电量将增长数十个百分点。从宾夕法尼亚的页岩地带到内华达的太阳能农场,数亿块 GPU 将一齐轰鸣。

AGI 竞赛已经开始。我们正在制造会思考、会推理的机器。到 2025/26 年,这些机器会超过许多大学毕业生。到这个十年结束时,它们会比你我都更聪明。我们将拥有真正意义上的超级智能。与此同时,半个世纪未见的国家安全力量将被释放出来。再过不久,这个项目就会启动。如果幸运,我们面对的是与中共的全面竞赛。如果不幸运,就是全面战争。

现在人人都在谈 AI,但几乎没人真正意识到即将发生什么。英伟达分析师仍然觉得 2024 年也许已经接近顶点。主流评论者还困在那种故意视而不见的说法里,说它不过是在预测下一个词。他们看到的只有炒作和一切照旧,顶多承认这会是另一场互联网级别的技术变化。

但用不了多久,世界就会醒来。只是此刻,也许只有几百个人,大多在旧金山和那些 AI 实验室里,真正拥有 形势感知。命运以某种奇特的方式,把我也放进了这群人里。几年前,这些人还被当成疯子。但他们相信趋势线,因此准确预判了过去几年 AI 的进展。至于他们对未来几年的判断是否也正确,还有待观察。但这些人非常聪明,是我见过最聪明的一群人,而正是他们在构建这项技术。也许他们最终只会成为历史中的一条古怪注脚。也许他们会像西拉德、奥本海默和特勒那样被写进历史。如果他们看到的未来哪怕接近正确,我们都将迎来一段疯狂旅程。

让我告诉你,我们看到了什么。


目录

每一篇文章都可以单独阅读,不过我强烈建议把整组系列连起来读。完整系列的 pdf 版本,点这里

导言 [本页]

历史正在旧金山实时发生。

一、从 GPT-4 到 AGI:细数数量级 到 2027 年实现 AGI,可能性高得惊人。从 GPT-2 到 GPT-4,我们在 4 年内从大约学龄前儿童水平走到了大约聪明高中生水平。顺着算力趋势线来看,每年大约提升 ~0.5 个数量级,也就是 OOM;算法效率每年大约提升 ~0.5 个 OOM;再加上去枷锁式的提升,也就是从聊天机器人到智能体,我们应该预期,到 2027 年还会再来一次从学龄前儿童到高中生这么大的质变跃迁。

二、从 AGI 到超级智能:智能爆炸

AI 的进步不会停在人类水平。数亿个 AGI 可以自动化 AI 研究,把十年的算法进展,也就是 5 个以上 OOM,压缩到不超过 1 年内完成。我们会很快从人类水平跨到_远远_超越人类的 AI 系统。超级智能带来的力量与危险,都会极其惊人。

三、挑战

三之一、奔向万亿美元集群 一场极不寻常的技术与资本加速已经启动。随着 AI 收入快速增长,到这个十年结束前,数万亿美元会流向 GPU、数据中心和电力基础设施建设。这场产业总动员会异常激烈,其中包括让美国发电量增长数十个百分点。

三之二、锁紧实验室:AGI 的安全 这个国家最领先的 AI 实验室,把安全当成事后才想起的东西。眼下,它们几乎是在把 AGI 的关键秘密双手奉送给中共。要把 AGI 的秘密和模型权重保护起来,挡住国家级行为体的威胁,将是一项艰巨工程,而我们现在远没有走在正确轨道上。

三之三、超级对齐

如何可靠控制那些比我们聪明得多的 AI 系统,至今仍是一个尚未解决的技术问题。而且虽然它是可解的,在快速的智能爆炸过程中,一切仍然很容易脱轨。如何处理这一切,会让人时刻紧绷。失败很可能就是灾难性的。

三之四、自由世界必须取胜 超级智能将带来决定性的经济和军事优势。中国并没有出局。在这场通往 AGI 的竞赛里,自由世界本身的生存都将受到威胁。我们还能维持对威权强权的领先地位吗。我们又能否在这个过程中避免自我毁灭。

四、这个项目 随着通往 AGI 的竞赛不断升级,国家安全机器将会介入。美国政府会从沉睡中醒来,到 27/28 年,我们会看到某种形式的政府 AGI 项目。没有哪家创业公司能独自处理超级智能。终局将在某个 SCIF 里上演。

五、最后的话

如果我们是对的呢。

本系列下一篇:

一、从 GPT-4 到 AGI:细数数量级


虽然我曾在 OpenAI 工作,但这里所有内容都基于公开可得的信息、我自己的想法、领域常识,或旧金山的小道消息。

感谢 Collin Burns、Avital Balwit、Carl Shulman、Jan Leike、Ilya Sutskever、Holden Karnofsky、Sholto Douglas、James Bradbury、Dwarkesh Patel,以及许多其他人,感谢他们带来的关键讨论。感谢许多朋友对早期草稿提出反馈。感谢 Joe Ronan 帮助制作图形,也感谢 Nick Whitaker 在发布上的帮助。

献给 Ilya Sutskever。

Leopold Aschenbrenner, June 2024

Leopold Aschenbrenner,2024 年 6 月

You can see the future first in San Francisco. Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.

在旧金山,你能最先看见未来。 过去一年里,城中谈资已经从 100 亿美元算力集群,变成 1000 亿美元集群,再变成万亿美元集群。每隔六个月,董事会计划里就会再多一个零。幕后的争夺异常激烈。人们在抢下这个十年剩余时间里一切还能拿到的电力合同,抢下一切还能采购到的电压变压器。美国大企业正在做准备,要把数万亿美元砸进一场久违的美国产业力量总动员。到这个十年结束时,美国的发电量将增长数十个百分点。从宾夕法尼亚的页岩地带到内华达的太阳能农场,数亿块 GPU 将一齐轰鸣。

The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace many college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be unleashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.

AGI 竞赛已经开始。我们正在制造会思考、会推理的机器。到 2025/26 年,这些机器会超过许多大学毕业生。到这个十年结束时,它们会比你我都更聪明。我们将拥有真正意义上的超级智能。与此同时,半个世纪未见的国家安全力量将被释放出来。再过不久,这个项目就会启动。如果幸运,我们面对的是与中共的全面竞赛。如果不幸运,就是全面战争。

Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the willful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.

现在人人都在谈 AI,但几乎没人真正意识到即将发生什么。英伟达分析师仍然觉得 2024 年也许已经接近顶点。主流评论者还困在那种故意视而不见的说法里,说它不过是在预测下一个词。他们看到的只有炒作和一切照旧,顶多承认这会是另一场互联网级别的技术变化。

Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.

但用不了多久,世界就会醒来。只是此刻,也许只有几百个人,大多在旧金山和那些 AI 实验室里,真正拥有 形势感知。命运以某种奇特的方式,把我也放进了这群人里。几年前,这些人还被当成疯子。但他们相信趋势线,因此准确预判了过去几年 AI 的进展。至于他们对未来几年的判断是否也正确,还有待观察。但这些人非常聪明,是我见过最聪明的一群人,而正是他们在构建这项技术。也许他们最终只会成为历史中的一条古怪注脚。也许他们会像西拉德、奥本海默和特勒那样被写进历史。如果他们看到的未来哪怕接近正确,我们都将迎来一段疯狂旅程。

Let me tell you what we see.

让我告诉你,我们看到了什么。



Table of Contents

目录

Each essay is meant to stand on its own, though I’d strongly encourage reading the series as a whole. For a pdf version of the full essay series, click here.

每一篇文章都可以单独阅读,不过我强烈建议把整组系列连起来读。完整系列的 pdf 版本,点这里

Introduction [this page]

导言 [本页]

History is live in San Francisco.

历史正在旧金山实时发生。

I. From GPT-4 to AGI: Counting the OOMsAGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and “unhobbling” gains (from chatbot to agent), we should expect another preschooler-to-high-schooler-sized qualitative jump by 2027.

一、从 GPT-4 到 AGI:细数数量级 到 2027 年实现 AGI,可能性高得惊人。从 GPT-2 到 GPT-4,我们在 4 年内从大约学龄前儿童水平走到了大约聪明高中生水平。顺着算力趋势线来看,每年大约提升 ~0.5 个数量级,也就是 OOM;算法效率每年大约提升 ~0.5 个 OOM;再加上去枷锁式的提升,也就是从聊天机器人到智能体,我们应该预期,到 2027 年还会再来一次从学龄前儿童到高中生这么大的质变跃迁。

AI progress won’t stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into ≤1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power—and the peril—of superintelligence would be dramatic.

AI 的进步不会停在人类水平。数亿个 AGI 可以自动化 AI 研究,把十年的算法进展,也就是 5 个以上 OOM,压缩到不超过 1 年内完成。我们会很快从人类水平跨到_远远_超越人类的 AI 系统。超级智能带来的力量与危险,都会极其惊人。

III. The Challenges

三、挑战

IIIa. Racing to the Trillion-Dollar ClusterThe most extraordinary techno-capital acceleration has been set in motion. As AI revenue grows rapidly, many trillions of dollars will go into GPU, datacenter, and power buildout before the end of the decade. The industrial mobilization, including growing US electricity production by 10s of percent, will be intense.

三之一、奔向万亿美元集群 一场极不寻常的技术与资本加速已经启动。随着 AI 收入快速增长,到这个十年结束前,数万亿美元会流向 GPU、数据中心和电力基础设施建设。这场产业总动员会异常激烈,其中包括让美国发电量增长数十个百分点。

IIIb.Lock Down the Labs: Security for AGIThe nation’s leading AI labs treat security as an afterthought. Currently, they’re basically handing the key secrets for AGI to the CCP on a silver platter. Securing the AGI secrets and weights against the state-actor threat will be an immense effort, and we’re not on track.

三之二、锁紧实验室:AGI 的安全 这个国家最领先的 AI 实验室,把安全当成事后才想起的东西。眼下,它们几乎是在把 AGI 的关键秘密双手奉送给中共。要把 AGI 的秘密和模型权重保护起来,挡住国家级行为体的威胁,将是一项艰巨工程,而我们现在远没有走在正确轨道上。

三之三、超级对齐

Reliably controlling AI systems much smarter than we are is an unsolved technical problem. And while it is a solvable problem, things could easily go off the rails during a rapid intelligence explosion. Managing this will be extremely tense; failure could easily be catastrophic.

如何可靠控制那些比我们聪明得多的 AI 系统,至今仍是一个尚未解决的技术问题。而且虽然它是可解的,在快速的智能爆炸过程中,一切仍然很容易脱轨。如何处理这一切,会让人时刻紧绷。失败很可能就是灾难性的。

IIId.The Free World Must PrevailSuperintelligence will give a decisive economic and military advantage. China isn’t at all out of the game yet. In the race to AGI, the free world’s very survival will be at stake. Can we maintain our preeminence over the authoritarian powers? And will we manage to avoid self-destruction along the way?

三之四、自由世界必须取胜 超级智能将带来决定性的经济和军事优势。中国并没有出局。在这场通往 AGI 的竞赛里,自由世界本身的生存都将受到威胁。我们还能维持对威权强权的领先地位吗。我们又能否在这个过程中避免自我毁灭。

IV. The ProjectAs the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we’ll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.

四、这个项目 随着通往 AGI 的竞赛不断升级,国家安全机器将会介入。美国政府会从沉睡中醒来,到 27/28 年,我们会看到某种形式的政府 AGI 项目。没有哪家创业公司能独自处理超级智能。终局将在某个 SCIF 里上演。

What if we’re right?

如果我们是对的呢。

Next post in series:

本系列下一篇:



While I used to work at OpenAI, all of this is based on publicly-available information, my own ideas, general field-knowledge, or SF-gossip.

虽然我曾在 OpenAI 工作,但这里所有内容都基于公开可得的信息、我自己的想法、领域常识,或旧金山的小道消息。

Thank you to Collin Burns, Avital Balwit, Carl Shulman, Jan Leike, Ilya Sutskever, Holden Karnofsky, Sholto Douglas, James Bradbury, Dwarkesh Patel, and many others for formative discussions. Thank you to many friends for feedback on earlier drafts.Thank you to Joe Ronan for help with graphics, and Nick Whitaker for publishing help.

感谢 Collin Burns、Avital Balwit、Carl Shulman、Jan Leike、Ilya Sutskever、Holden Karnofsky、Sholto Douglas、James Bradbury、Dwarkesh Patel,以及许多其他人,感谢他们带来的关键讨论。感谢许多朋友对早期草稿提出反馈。感谢 Joe Ronan 帮助制作图形,也感谢 Nick Whitaker 在发布上的帮助。

Dedicated to Ilya Sutskever.

献给 Ilya Sutskever。

Leopold Aschenbrenner, June 2024

You can see the future first in San Francisco. Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.

The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace many college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be unleashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.

Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the willful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.

Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.

Let me tell you what we see.


Table of Contents

Each essay is meant to stand on its own, though I’d strongly encourage reading the series as a whole. For a pdf version of the full essay series, click here.

Introduction [this page]

History is live in San Francisco.

I. From GPT-4 to AGI: Counting the OOMsAGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and “unhobbling” gains (from chatbot to agent), we should expect another preschooler-to-high-schooler-sized qualitative jump by 2027.

II. From AGI to Superintelligence: the Intelligence Explosion

AI progress won’t stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into ≤1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power—and the peril—of superintelligence would be dramatic.

III. The Challenges

IIIa. Racing to the Trillion-Dollar ClusterThe most extraordinary techno-capital acceleration has been set in motion. As AI revenue grows rapidly, many trillions of dollars will go into GPU, datacenter, and power buildout before the end of the decade. The industrial mobilization, including growing US electricity production by 10s of percent, will be intense.

IIIb.Lock Down the Labs: Security for AGIThe nation’s leading AI labs treat security as an afterthought. Currently, they’re basically handing the key secrets for AGI to the CCP on a silver platter. Securing the AGI secrets and weights against the state-actor threat will be an immense effort, and we’re not on track.

IIIc. Superalignment

Reliably controlling AI systems much smarter than we are is an unsolved technical problem. And while it is a solvable problem, things could easily go off the rails during a rapid intelligence explosion. Managing this will be extremely tense; failure could easily be catastrophic.

IIId.The Free World Must PrevailSuperintelligence will give a decisive economic and military advantage. China isn’t at all out of the game yet. In the race to AGI, the free world’s very survival will be at stake. Can we maintain our preeminence over the authoritarian powers? And will we manage to avoid self-destruction along the way?

IV. The ProjectAs the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we’ll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.

V. Parting Thoughts

What if we’re right?

Next post in series:

I. From GPT-4 to AGI: Counting the OOMs


While I used to work at OpenAI, all of this is based on publicly-available information, my own ideas, general field-knowledge, or SF-gossip.

Thank you to Collin Burns, Avital Balwit, Carl Shulman, Jan Leike, Ilya Sutskever, Holden Karnofsky, Sholto Douglas, James Bradbury, Dwarkesh Patel, and many others for formative discussions. Thank you to many friends for feedback on earlier drafts.Thank you to Joe Ronan for help with graphics, and Nick Whitaker for publishing help.

Dedicated to Ilya Sutskever.

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