Sam AltmanModify

我们正从用户对Sora的使用方式中快速学习，并积极采纳用户、版权方及其他相关群体的反馈。当然，在发布前我们已进行了大量讨论，但如今产品已上线，我们不仅能停留在理论层面。

我们即将推出两项调整（未来还会有更多）。

首先，我们将为版权方提供更精细的角色生成控制权，类似于肖像权的选择加入模式，但会附加更多调控选项。

许多版权方向我们表达了他们对这种新型"互动式同人创作"的热情，认为这种互动形式将为他们创造巨大价值，但他们希望能具体规定角色如何使用（包括完全禁止）。我们预计不同版权方会尝试截然不同的策略，并找到最适合自己的方式。但我们将对所有人采用统一标准，由版权方自行决定如何参与（当然我们的目标是让这种模式足够吸引人，促使多数人愿意加入）。可能会有个别不应通过的生成内容漏网，完善我们的系统需要多次迭代。

特别要提及的是，日本创作者们的惊人产出令我们印象深刻——用户与日本内容之间的深厚联结实在令人惊叹！

其次，我们必须为视频生成找到可持续的盈利模式。目前每位用户生成的视频量远超预期，且大量视频的受众群体非常小众。我们计划尝试与允许用户生成其角色的版权方共享部分收益。具体模式需要经过试验调整，但我们打算尽快启动。我们希望这种新型互动形式的价值能超越收益分成，当然两者都具备价值才是理想状态。

请做好我们会高频更新的准备；这让我想起ChatGPT的早期阶段。我们会做出一些正确决策，也会有些失误，但我们将迅速收集反馈并纠正错误。我们计划先在Sora上试验不同方案，然后将成熟经验应用到所有产品中。

We have been learning quickly from how people are using Sora and taking feedback from users, rightsholders, and other interested groups. We of course spent a lot of time discussing this before launch, but now that we have a product out we can do more than just theorize.

We are going to make two changes soon (and many more to come).

First, we will give rightsholders more granular control over generation of characters, similar to the opt-in model for likeness but with additional controls.

We are hearing from a lot of rightsholders who are very excited for this new kind of "interactive fan fiction" and think this new kind of engagement will accrue a lot of value to them, but want the ability to specify how their characters can be used (including not at all). We assume different people will try very different approaches and will figure out what works for them. But we want to apply the same standard towards everyone, and let rightsholders decide how to proceed (our aim of course is to make it so compelling that many people want to). There may be some edge cases of generations that get through that shouldn't, and getting our stack to work well will take some iteration. 

In particular, we'd like to acknowledge the remarkable creative output of Japan--we are struck by how deep the connection between users and Japanese content is!

Second, we are going to have to somehow make money for video generation. People are generating much more than we expected per user, and a lot of videos are being generated for very small audiences. We are going to try sharing some of this revenue with rightsholders who want their characters generated by users. The exact model will take some trial and error to figure out, but we plan to start very soon. Our hope is that the new kind of engagement is even more valuable than the revenue share, but of course we we want both to be valuable.

Please expect a very high rate of change from us; it reminds me of the early days of ChatGPT. We will make some good decisions and some missteps, but we will take feedback and try to fix the missteps very quickly. We plan to do our iteration on different approaches in Sora, but then apply it consistently across our products.

# Sora：一款创意视频应用的全新启航

我们即将推出名为**Sora**的新应用。它融合了新一代模型**Sora 2**与创新产品功能，让视频创作、分享和观看变得前所未有的简单。对我们许多人而言，这仿佛是"创意界的ChatGPT时刻"——充满新鲜趣味。从灵感到成果的极速转化，以及由此衍生的新型社交互动，都令人振奋。创意领域可能即将迎来"寒武纪大爆发"，艺术与娱乐的质量也将飞跃提升。

## 核心亮点
- **开放创意场域**：早期测试中，Sora展现的创作自由度令人惊艳
- **角色一致性技术**：团队精心打造的"客串功能"可让你和朋友自然融入视频，成为测试中最受欢迎的连接方式
- **社交新维度**：创造了一种出人意料的沉浸式互动体验

## 责任与挑战
我们清醒认识到：
- 此类服务可能引发成瘾问题
- 存在被用于网络霸凌的风险
- 需警惕AI视频生成的滥用导致用户陷入算法优化的低质内容漩涡

团队已采取多重防护措施：
- 防止深度伪造滥用
- 屏蔽不良/非法内容
- 定期评估用户心理影响
- 持续探索更完善的解决方案

## 产品原则
1. **长期用户价值优先**  
   - 核心指标：用户回顾6个月使用经历时，应感觉生活因Sora变得更美好
   - 否则将进行重大调整（必要时终止服务）

2. **用户主导内容消费**  
   - 支持按需求定制内容（放松/激励/特定兴趣）
   - 未来支持自然语言精准控制
   - 青少年模式含非个性化推送/私信关闭等功能

3. **创作普惠化**  
   - 降低创作门槛，激发人人参与的成就感
   - 坚信创造是人类天性，关乎根本幸福

4. **助力长期目标实现**  
   - 深度理解用户真实需求（社交/健康/事业等）
   - 提供对应内容支持
   - 尊重用户自主选择权（包括"愤怒刷屏"等行为）

我们期待Sora能放大科技带来的美好，同时谨慎规避潜在风险。这款产品将随着用户反馈持续进化。

我们即将推出一款名为Sora的新应用。它融合了全新模型Sora 2的技术优势，是一款能轻松创作、分享与观看视频的创新产品。

对我们许多人而言，这仿佛是"创意领域的ChatGPT时刻"，充满新鲜趣味。从灵感到成果的极速转化，以及由此衍生的新型社交互动模式，都令人振奋。

创意领域可能即将迎来寒武纪式大爆发，艺术与娱乐的品质将随之飞跃。即便在Sora的早期测试阶段，其开放包容的创作环境已让众多参与者惊叹不已。

特别值得一提的是角色一致性功能——团队倾注心血开发的"客串特效"，让我们在测试中乐此不疲。这种将自身与好友融入视频的新颖方式，已成为许多人眼中极具吸引力的社交纽带。

我们亦心怀敬畏。社交媒体对世界的影响向来利弊参半。我们深知此类服务的潜在成瘾性，也预见到其可能被滥用于网络霸凌的多种情形。

不难想象AI视频生成的极端场景：人类沉溺于算法优化的信息泥潭。团队精心设计产品机制以避免此类陷阱，并已提出多项可行性方案。产品初期我们将尝试不同路径。

除现有防护措施（包括防止深度伪造滥用肖像、屏蔽不良非法内容、定期评估用户心理影响等）外，我们确信若Sora大获成功，仍需持续完善。以下是指导产品发展的核心原则：

*以长期用户满意度为核心。多数用户在回溯半年使用体验时，应感受到Sora提升了生活品质。若非如此，我们将大刀阔斧改革（若无法改善则会终止服务）。

*赋予用户内容控制权。你可以明确告知Sora需求——想观看舒缓还是振奋的视频？特定兴趣内容？或限定使用时长？随着技术进步，最终你将能用自然语言细致定制。（青少年家长控制功能包含关闭个性化推荐及私信等选项）

*创作体验优先。我们致力于让每个人都能轻松享受创作乐趣；相信人类天生具有创造力，而创造正是幸福之源。

*助力用户实现长期目标。我们愿洞悉用户真实诉求并助其达成。无论是增进友情、健身塑形还是创业逐梦，Sora都将提供对应支持。即便你只想沉浸式刷屏宣泄情绪，我们同样予以尊重（虽然希望用户认为时间花得值，但我们不会家长式定义何为"值得"）。

We are launching a new app called Sora. This is a combination of a new model called Sora 2, and a new product that makes it easy to create, share, and view videos.

This feels to many of us like the “ChatGPT for creativity” moment, and it feels fun and new. There is something great about making it really easy and fast to go from idea to result, and the new social dynamics that emerge.

Creativity could be about to go through a Cambrian explosion, and along with it, the quality of art and entertainment can drastically increase. Even in the very early days of playing with Sora, it’s been striking to many of us how open the playing field suddenly feels.

In particular, the ability to put yourself and your friends into a video—the team worked very hard on character consistency—with the cameo feature is something we have really enjoyed during testing, and is to many of us a surprisingly compelling new way to connect.

We also feel some trepidation. Social media has had some good effects on the world, but it’s also had some bad ones. We are aware of how addictive a service like this could become, and we can imagine many ways it could be used for bullying.

It is easy to imagine the degenerate case of AI video generation that ends up with us all being sucked into an RL-optimized slop feed. The team has put great care and thought into trying to figure out how to make a delightful product that doesn’t fall into that trap, and has come up with a number of promising ideas. We will experiment in the early days of the product with different approaches.

In addition to the mitigations we have already put in place (which include things like mitigations to prevent someone from misusing someone’s likeness in deepfakes, safeguards for disturbing or illegal content, periodic checks on how Sora is impacting users’ mood and wellbeing, and more) we are sure we will discover new things we need to do if Sora becomes very successful. To help guide us towards more of the good and less of the bad, here are some principles we have for this product:

*Optimize for long-term user satisfaction. The majority of users, looking back on the past 6 months, should feel that their life is better for using Sora that it would have been if they hadn’t. If that’s not the case, we will make significant changes (and if we can’t fix it, we would discontinue offering the service).  

*Encourage users to control their feed. You should be able to tell Sora what you want—do you want to see videos that will make you more relaxed, or more energized? Or only videos that fit a specific interest? Or only for a certain about of time? Eventually as our technology progresses, you will be should to the tell Sora what you want in detail in natural language. (However, parental controls for teens include the ability to opt out of a personalized feed, and other things like turning off DMs.)

*Prioritize creation. We want to make it easy and rewarding for everyone to participate in the creation process; we believe people are natural-born creators, and creating is important to our satisfaction.

*Help users achieve their long-term goals. We want to understand a user’s true goals, and help them achieve them. If you want to be more connected to your friends, we will try to help you with that. If you want to get fit, we can show you fitness content that will motivate you. If you want to start a business, we want to help teach you the skills you need. And if you truly just want to doom scroll and be angry, then ok, we’ll help you with that (although we want users to spend time using the app if they think it’s time well spent, we don’t want to be paternalistic about what that means to them).

人工智能服务的使用增长令人震惊，我们预计未来这一趋势将更加惊人。随着AI变得更智能，获取AI技术将成为经济的核心驱动力，甚至可能最终被视为一项基本人权。几乎所有人都希望AI能为自己提供更多服务。

为了满足全球需求——既需要运行这些模型的推理算力，也需要持续改进模型的训练算力——我们正在为大幅扩展AI基础设施的宏伟计划奠定基础。如果AI按我们预期的轨迹发展，将可能实现惊人突破：或许10吉瓦的算力能让AI找到治愈癌症的方法，或是为地球上的每个学生提供个性化辅导。若受限于算力，我们将被迫做出优先级选择；但没人愿意面临这种取舍，所以我们必须行动起来。

我们的愿景很简单：打造一个每周能生产1吉瓦AI新基础设施的"工厂"。实现这一目标极具挑战性，需要多年时间，并在芯片、能源、建筑、机器人等全产业链实现创新。但我们已全力投入，并坚信其可行性。这将是史上最酷且最重要的基础设施项目。

我们尤其期待在美国建设大量设施。当前其他国家在芯片工厂和新能源生产等领域的建设速度远超美国，我们希望能扭转这一局面。未来几个月，我们将公布具体计划和合作伙伴；今年晚些时候将探讨融资方案——鉴于增加算力直接关乎收入增长，我们已构思了一些创新思路。

AI服务的使用增长令人惊叹；我们预计未来这一趋势将更加惊人。

随着AI日益智能化，获取AI技术将成为经济发展的核心驱动力，或许最终会被视为一项基本人权。几乎每个人都希望有更多AI为自己服务。

为了满足全球需求——既要运行这些模型的推理计算，又要通过训练计算持续优化它们——我们正在奠定基础，以大幅扩展建设AI基础设施的宏伟计划。

如果AI沿着我们预期的轨迹发展，将可能实现非凡成就。或许10吉瓦的计算能力能让AI找到治愈癌症的方法，或是为地球上每个学生提供个性化辅导。若受限于计算资源，我们将被迫做出优先级选择；没人愿意面临这种抉择，所以让我们行动起来共同建设。

我们的愿景很简单：打造一个每周能生产1吉瓦级AI基础设施的超级工厂。实现这一目标将极具挑战性，需要多年时间达成里程碑，并在从芯片到能源、从建筑到机器人技术的全产业链实现创新。但我们已为此付出巨大努力，并坚信其可行性。在我们看来，这将是史上最酷且最重要的基础设施项目。我们尤其期待在美国本土大量建设这类设施；当前其他国家在芯片工厂和新能源生产等领域的建设速度远超我们，我们希望能助力扭转这一局面。

接下来几个月，我们将陆续公布部分计划及合作方信息。今年晚些时候，我们会探讨融资方案；鉴于提升计算能力直接关乎收入增长，我们有些令人耳目一新的创新思路。

Growth in the use of AI services has been astonishing; we expect it to be even more astonishing going forward.

As AI gets smarter, access to AI will be a fundamental driver of the economy, and maybe eventually something we consider a fundamental human right. Almost everyone will want more AI working on their behalf.

To be able to deliver what the world needs—for inference compute to run these models, and for training compute to keep making them better and better—we are putting the groundwork in place to be able to significantly expand our ambitions for building out AI infrastructure.

If AI stays on the trajectory that we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer. Or with 10 gigawatts of compute, AI can figure out how to provide customized tutoring to every student on earth. If we are limited by compute, we’ll have to choose which one to prioritize; no one wants to make that choice, so let’s go build.

Our vision is simple: we want to create a factory that can produce a gigawatt of new AI infrastructure every week. The execution of this will be extremely difficult; it will take us years to get to this milestone and it will require innovation at every level of the stack, from chips to power to building to robotics. But we have been hard at work on this and believe it is possible. In our opinion, it will be the coolest and most important infrastructure project ever. We are particularly excited to build a lot of this in the US; right now, other countries are building things like chips fabs and new energy production much faster than we are, and we want to help turn that tide.

Over the next couple of months, we’ll be talking about some of our plans and the partners we are working with to make this a reality. Later this year, we’ll talk about how we are financing it; given how increasing compute is the literal key to increasing revenue, we have some interesting new ideas.

近年来，AI技术突飞猛进——ChatGPT展现的惊人能力已让我们习以为常。这本就是人类进步的常态。但在那个闪烁的光标背后，隐藏着人类智慧最伟大的篇章：无数人付出了难以想象的努力，实现了多数专家认为短期内不可能完成的任务，并创建了规模化交付产品的公司，让全球受益。

虽然大多数ChatGPT用户不会深究背后的付出（这完全合理），但请容我占用一分钟，致敬两位OpenAI不可或缺的灵魂人物：**Jakub Pachocki**和**Szymon Sidor**。他们屡次以「科研+工程」的复合能力攻克难题，却未获得足够的公众赞誉。例如：
- 当学界普遍认为强化学习（RL）无法扩展时，他们坚持推进并发现其边界，最终成就了Dota项目；
- 搭建了支撑多项科学发现的基础设施；
- 领导GPT-4预训练；
- 与Ilya、Lukasz共同开创了推理突破的初始构想；
- 在新范式探索中取得重大进展。

Jakub现任OpenAI首席科学家，他曾用"**indefatigable（不知疲倦）**"形容Szymon——这个词的精准运用令我叹服。至今OpenAI尚未抛出他们无法解决的难题。这种如同昔日实验室传奇般的黄金搭档，能在多年间持续互补共进，实属罕见而珍贵。

近年来，人工智能取得了显著进步；ChatGPT能完成许多我们视为理所当然的惊人任务。这本就是技术发展的应有之义，也是人类进步的故事。但在那闪烁的光标背后，被优雅封装起来的，是我所见过最伟大的人类智慧结晶。无数人付出了难以想象的努力，在多数专家认为不可能的时间框架内实现了技术突破，并创建公司大规模交付产品，让世人受益。大多数ChatGPT用户永远不会想到幕后付出艰辛的人们，这完全正常，但请允许我占用您一分钟时间……

有两位不可或缺的人物让OpenAI成为今天的OpenAI：雅库布·帕霍茨基和希蒙·西多尔。他们屡次将研究与工程相结合，攻克了看似无解的难题。虽然公众给予的赞誉远不足够，但正是他们决定将强化学习作为基线进行扩展测试——当时普遍认为这是不可扩展的——最终成就了我们在Dota项目上的突破；他们搭建的基础设施支撑了大量科学发现，主导了GPT-4的预训练，与伊利亚和卢卡什共同催生了带来推理突破的初始构想，并在探索新范式方面取得重大进展。

雅库布是我们的首席科学家。他曾用"不知疲倦"形容希蒙，这是我听过对这个词最完美的诠释。OpenAI尚未提出过他们无法解决的难题；我听说过历史上研究实验室里那种珠联璧合的合作伙伴关系，但能亲眼见证这种默契多年来的发展，实属难得。

AI has gotten remarkably better in recent years; ChatGPT can do amazing things that we take for granted. This is as it should be, and is the story of human progress. But behind the blinking circle, nicely abstracted away, is the greatest story of human ingenuity I have ever seen. A lot of people have worked unbelievably hard to discover how to build something that most experts thought was impossible on this timeframe, and to build a company to deliver products at massive scale to let people benefit from it. Most people who use ChatGPT will never think about the people that put so much work into it, which is totally ok, but just to take a minute of your time…

There are two people I'd like to mention that OpenAI would not be OpenAI without: Jakub Pachocki and Szymon Sidor. Time and again, they combine research and engineering to solve impossible problems. They have not gotten enough public credit, but they decided to scale up RL as a baseline to see where it broke when the conventional wisdom was that it didn't scale which led to our Dota result, built much of the infrastructure that enabled a lot of our scientific discoveries, led GPT-4 pretraining, drove together with Ilya and Lukasz the initial ideas that led to the reasoning breakthrough, and have made significant progress exploring new paradigms.

Jakub is our chief scientist. He once described Szymon as “indefatigable”, which is as perfect of a use of that word as I have ever heard. OpenAI has not yet thrown a problem at them they have not been able to solve; I have heard about partnerships like there is research labs of the past where two people are able to complement each other so well, but it is very special to get to watch it unfold over the years.

# 超越奇点：AI时代的加速未来

## 已跨越临界点
人类已跨过技术奇点的门槛，数字超级智能的诞生近在咫尺。尽管当前世界尚未出现机器人满街走的科幻场景，但GPT-4等系统的突破性进展证明：**我们已创造出在多方面超越人类智能的AI工具**。这些系统能显著放大使用者的生产力，而最艰难的科学突破阶段已经过去。

## 指数级演进路线图
- **2025年**：可完成真实认知工作的AI代理将重塑编程领域  
- **2026年**：具备自主发现新知识能力的系统问世  
- **2027年**：能执行实体任务的机器人可能出现  
到2030年，单个人的生产力将出现**数量级跃升**，艺术与软件的创作门槛将大幅降低，但专家仍将保持优势——前提是善用新工具。

## 双面革命
**表层生活**：家庭、娱乐、自然体验等人类本质需求不会剧变  
**深层变革**：智力与能源（实现想法的两大基础要素）将变得极度丰富，突破长期制约人类发展的根本瓶颈。AI已使科学家效率提升2-3倍，更关键的是：**AI正加速AI研究本身**，形成递归式进步循环。

## 经济奇点临近
- 数据中心自动化将使智能成本趋近于电力成本（当前ChatGPT单次查询耗能≈0.34瓦时）  
- 机器人制造机器人的产业链一旦形成，进步速度将呈指数级跃升  
- 技术变革可能催生全新的社会契约与政策范式

## 挑战与机遇并存
**关键任务清单**：  
1. **解决对齐问题**：确保AI系统长期符合人类集体利益（避免重蹈社交媒体算法短视优化的覆辙）  
2. **分布式普及**：使超级智能廉价、广泛可用且权力不过度集中  

## 未来图景
- 2035年前可能相继突破高能物理、太空殖民、脑机接口等领域  
- 人类将保持对AI的独特优势：**与生俱来的人际关怀**（这是AI难以复制的特质）  
- 工作形态将持续演化（如同工业革命后的职业变迁），未来职业在当下看来可能如同"虚假工作"  

## 行动纲领
OpenAI定位为**超级智能研究公司**，致力于构建"世界大脑"。行业需要：  
- 在保障安全的前提下最大化技术自由度  
- 尽快启动关于AI伦理边界的社会共识讨论  
- 释放"创意者"的潜力（技术实现门槛降低后，优质想法将成为核心稀缺资源）  

> "如果2020年预测当前成就显得疯狂，那么今天对2030年的展望或许同样如此——但历史证明，我们总能适应技术的加速。"  

**最终目标**：实现"廉价到可忽略的智能"，让人类在超级智能时代平稳驶向更美好的未来。

我们已跨越事件视界，起飞正式启动。人类距离构建数字超级智能仅一步之遥，而迄今为止，其发展轨迹远比预想中更为平顺。

机器人尚未漫步街头，多数人也未整日与AI对话。疾病仍在夺走生命，太空旅行依旧艰难，宇宙中仍有无数未解之谜。

然而，我们已创造出在多方面超越人类智慧的体系，能显著放大使用者的产出效能。最艰难的科学突破——如GPT-4和o3系统的诞生——已成过往，这些硬仗赢得的认知将引领我们走得更远。

AI将以多种方式造福世界，但最重大的贡献在于加速科学进步与提升生产力带来的生活质量跃升。未来可能远比现在美好，因为科学突破始终是文明进步的核心引擎——想到我们即将拥有的可能性，实在令人振奋。

从某种宏大意义上说，ChatGPT已比历史上任何人类都更强大。数亿人每天依赖它处理日益重要的事务：微小新功能可能产生巨大积极影响，细微偏差经数亿倍放大也会造成严重负面效应。

2025年，能完成真实认知工作的智能体已然问世，编程领域永远改变。2026年或将出现能发现新颖洞见的系统，2027年可能迎来能在现实世界执行任务的机器人。

更多人将能创作软件与艺术。但世界对二者的需求永无止境，只要善用新工具，专家仍将远胜新手。到2030年，个人生产力相较2020年的跃升将形成震撼变革，无数人将从中获益。

在最本质的层面，2030年代或许不会天翻地覆：人们仍会热爱家庭、挥洒创意、享受游戏、湖畔畅游。

但在同样关键的维度，2030年代或将前所未有地颠覆认知。我们尚不知智能水平能超越人类多远，但答案即将揭晓。

2030年代，智力与能源——即创意与实现创意的能力——将变得极度丰沛。这两者长期制约着人类发展，而充足的智能与能源（辅以良治）理论上能带来一切。

我们已与惊人数字智能共存，经历短暂震撼后大多习以为常。转瞬间，AI从生成优美段落到创作完整小说，从诊断疾病到研发疗法，从编写小程序到创立新公司——奇点降临的轨迹总是如此：奇迹先成常态，再变基础配置。

科学家们自述生产力已提升2-3倍。先进AI最深远的意义或许在于它能加速AI研究本身：新计算基质、更优算法，乃至未知突破。若能将十年研究压缩至一年甚至一月，进步速率将彻底改变。

既有工具将助我们发现新科学洞见，构建更优AI系统。虽非完全自主的代码演进，但这已是递归自我改进的雏形。

其他增强循环也在运转：经济价值创造正推动AI基础设施的复合增长。能自我复制的机器人（某种意义上也包括数据中心）已不遥远。

若首批百万仿生机器人需传统方式制造，之后它们便可自主运营整个供应链——采矿冶炼、驾驶运输、工厂运营等——进而制造更多机器人，建设芯片厂与数据中心，进步速率将截然不同。

随着数据中心生产自动化，智能成本终将趋近电力成本。（人们常好奇ChatGPT查询耗能：单次约0.34瓦时，相当于烤箱运作一秒或多或高效灯泡两分钟，耗水约0.000085加仑，近乎十五分之一茶匙。）

技术进步将持续加速，人类适应力始终在线。尽管某些职业将整体消失，但世界财富的极速增长将使我们能尝试前所未有的新政。社会契约不会瞬间重构，但数十年后回望，渐变累积终成巨变。

历史表明，我们总能找到新需求，快速吸纳新工具（工业革命后的职业变迁即为例证）。期待值与能力同步跃升，我们将为彼此创造更美好的事物。人类相较AI存在根本优势：我们天生在意他人所思所为，而非机器。

千年前的农夫会视现代工作为"虚假职业"，认为我们因丰衣足食而游戏人生。但愿未来千年后的职业同样被视作"虚假"，但对从业者而言，它们必将充满意义与满足。

奇迹诞生的速度将超乎想象。今日甚至难以构想2035年的突破：或许今年解决高能物理，明年开启太空殖民；或今年材料科学突破，明年实现高带宽脑机接口。虽多数人生活方式依旧，但必有人选择"接入"新维度。

前瞻未来令人目眩，但亲历过程或将从容。从相对论视角看，奇点是渐进过程，融合缓慢发生。我们正攀登技术进步的指数曲线——前瞻时似垂直陡壁，回望时如平坦大道。（试想2020年预言2025年接近AGI有多疯狂，对比过去五年的实际发展。）

伴随巨大机遇的是严峻挑战。我们需从技术和社会层面解决安全问题，但鉴于经济影响，广泛普及超级智能访问权同样关键。最佳路径或许是：

1. 解决对齐问题，确保AI系统长期稳定地学习并践行人类集体真实意愿（社交媒体推荐即未对齐案例：算法精于捕捉短期偏好让你持续刷屏，却利用了违背你长期利益的认知弱点）。

2. 致力于使超级智能廉价、普及且不过度集中于个体、企业或国家。社会具备韧性、创造力与快速适应力。若能凝聚集体智慧，纵有失误与挫折，我们终将快速学习调整，最大化技术收益，最小化负面影响。在社会共识的宽泛边界内赋予用户充分自由至关重要。世界越早开始探讨这些边界与集体对齐的定义越好。

我们（整个行业，不止OpenAI）正在为世界构建大脑。它将极度个性化且易用，唯一限制将是好创意。长期以来，科技创业者常嘲笑"点子王"——那些只有创意却无执行团队的人。现在看来，他们的高光时刻即将到来。

OpenAI如今有多重身份，但首先是超级智能研究公司。前路虽仍有挑战，但多数路径已然明朗，黑暗区域正快速消退。能从事这份事业，我们深感荣幸。

近乎免费的智能触手可及。此言或许惊人，但若在2020年预言今日成就，恐怕比如今对2030年的预测更显荒诞。

愿我们在超级智能时代平稳、指数级且波澜不惊地攀登高峰。

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.

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.

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 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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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. 

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.

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.)

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.

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.

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.

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”.

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.)

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. 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. 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.

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 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.

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.

May we scale smoothly, exponentially and uneventfully through superintelligence.

我们的使命是确保人工通用智能（AGI）造福全人类。  
初现AGI雏形的系统正在形成，因此理解当下至关重要。AGI虽定义模糊，但通常指能在多领域以人类水平解决复杂问题的系统。  

人类天生渴望探索与创造，代代传承的发明（电力、晶体管、计算机、互联网，直至未来的AGI）推动世界进步。尽管进程曲折，创新持续带来难以想象的繁荣与生活改善。AGI既是人类进步阶梯中的新工具，又可能标志着一个"这次不同"的时代——经济增长或将颠覆想象：治愈所有疾病、更多家庭时光、释放创造力。十年后，普通人成就或超越当今最具影响力者。  

### 关于AI经济的三点观察：  
1. **智能与资源对数相关**：训练算力、数据与推理资源投入越多，模型智能提升越可预测。  
2. **成本骤降，应用激增**：AI使用成本每12个月下降10倍（如GPT-4到GPT-4o的token成本降150倍），远超摩尔定律。  
3. **智能的 socioeconomic 价值呈超指数增长**：指数级投资增长短期内无停止迹象。  

### 未来图景：  
- **AI智能体**将如虚拟同事渗透各领域。例如，软件工程AI可完成资深工程师数日任务（需人类监督），百万量级应用将重塑知识工作。  
- AI或如晶体管般渗透经济各角落，效益广泛分配但隐性存在。  

### 社会影响：  
- 短期生活变化有限，但长期变革不可忽视。  
- **适应力与决策力**成为核心价值，AGI将放大个人影响力。  
- 影响不均衡：科研加速，商品价格暴跌（智力与能源成本下降），奢侈品与土地价格或飙升。  

### 政策与技术协同：  
- 早期产品发布旨在促进社会与技术共同进化。  
- 需平衡安全与个体赋权，警惕威权政府滥用AI。  
- 广泛分配AGI收益是关键，可能需创新方案（如全球"算力预算"）。  

2035年，每人或可调动2025年全人类的智力资源。释放未被开发的创造力，将惠及全球。  

*注：本文使用AGI术语仅为清晰表达，不改变与微软合作的定义与进程。我们期待与微软长期合作。此脚注看似多余，实为预判某些媒体的夸张解读。*  

我们的使命是确保人工通用智能（AGI）惠及全人类。

指向AGI*的系统已初现端倪，因此理解当下这一关键时刻至关重要。AGI虽定义模糊，但通常指能在多领域以人类水平解决日益复杂问题的系统。

人类天生具有理解与创造的工具制造本能，这种驱动力推动世界不断进步。每一代人都站在前人的发现之上，创造出更强大的工具——电力、晶体管、计算机、互联网，以及即将到来的AGI。

历经跌宕起伏，人类创新的稳步前行已将难以想象的繁荣与生活各领域的改善带到我们面前。

从某种角度看，AGI只是人类共同搭建的进步阶梯中又一新工具；但从另一角度看，我们很难不感叹"这次不同以往"——眼前的经济增长令人震撼，我们已能构想一个治愈所有疾病、拥有更多家庭时光、充分释放创造潜能的世界。

十年后，或许地球上的每个人都能超越当今最具影响力人物的成就。

AI发展持续迅猛，以下是关于AI经济学的三点观察：

1. AI模型的智能水平大致与其训练和运行资源消耗的对数成正比。 这些资源主要包括训练算力、数据和推理算力。事实证明，投入任意资金都能获得持续可预测的收益，这种规模定律在多个数量级上都精确成立。

2. 固定AI水平的使用成本每12个月下降约10倍，低价催生更广泛应用。 从2023年初GPT-4到2024年中GPT-4o，单token价格下降约150倍。相比摩尔定律18个月翻倍的变革力，这堪称惊人。

3. 线性增长的智能所产生的社会经济价值本质上是超指数级的。 这意味着我们没有理由认为指数级增长的投资会在近期停止。

若这三点观察持续成立，社会影响将极为深远。

我们正开始部署AI智能体，它们终将成为虚拟同事。

以软件工程智能体为例——这类我们预期特别重要的智能体。想象它能完成顶尖公司数年经验工程师数日内的多数工作，虽缺乏突破性创意、需要大量人工指导，且能力存在明显波动。

不妨将其视为真实但资历尚浅的虚拟同事。再想象拥有1000个，或100万个这样的同事。进而推及所有知识工作领域。

经济层面，AI或许会像晶体管——一项渗透经济各角落的重大科学发现。我们很少思考晶体管或其公司，但广泛享受着它带来的奇迹。

世界不会骤然改变。短期内生活依旧，2025年人们的时间分配与2024年大同小异。我们仍会恋爱成家、网络争论、徒步自然。

但未来将以不可忽视的方式降临，社会经济将经历深刻变革。人类将发现新的存在价值、互助方式和竞争形态，它们可能与当今职业大相径庭。

自主性、意志力和决断力将弥足珍贵。在瞬息万变的世界中正确决策将价值连城，韧性与适应力成为关键技能。AGI将成为人类意志的最大杠杆，让个体产生空前而非减弱的影响力。

AGI的影响将不均衡。虽然某些行业变化甚微，但科学进步可能远超今日——这一影响或许超越其他所有领域。

多数商品价格终将大幅下降（当前受限于智能与能源成本），而奢侈品及土地等有限资源的价格可能飙升。

技术路径已然清晰，但AGI的社会整合政策与共识至关重要。我们频繁推出产品的原因之一，正是为了让社会与技术协同进化。

AI将渗透经济社会各领域，万物都将智能化。相比历史做法，我们预期需要赋予人们更多技术控制权，包括更多开源，在安全与个体赋权间寻求平衡。

尽管我们绝不轻率，但某些AGI安全相关的重大决策难免引发争议。总体而言，随着AGI临近，我们认为个体赋权趋势至关重要——另一可能路径是威权政府通过AI实施大规模监控、剥夺民众自主权。

确保AGI收益广泛分配是关键。历史表明技术进步平均改善健康、经济等指标，但平等性提升非技术必然，需要创新思路。

尤其资本与劳动力的力量平衡极易失调，可能需要早期干预。我们愿尝试非常规方案，如分配"算力预算"让全球民众共享AI，但也看到持续降低智能成本的显著效果。

到2035年，每个人都应能调动相当于2025年全人类的智力资源，获得无限天才的指引。当今无数天赋因资源限制未能绽放，若改变这点，世界将因创造力爆发而共同受益。

特别感谢Josh Achiam、Boaz Barak和Aleksander Madry审阅本文草稿。

*此处使用AGI术语仅为清晰表述，无意改变或解释我们与微软合作关系的定义及流程。我们期待与微软建立长期伙伴关系。本注看似多余，但鉴于某些媒体会为点击率制造噱头，我们先行预防...

Our mission is to ensure that AGI (Artificial General Intelligence) benefits all of humanity. 

Systems that start to point to AGI* are coming into view, and so we think it’s important to understand the moment we are in. AGI is a weakly defined term, but generally speaking we mean it to be a system that can tackle increasingly complex problems, at human level, in many fields.

People are tool-builders with an inherent drive to understand and create, which leads to the world getting better for all of us. Each new generation builds upon the discoveries of the generations before to create even more capable tools—electricity, the transistor, the computer, the internet, and soon AGI.

Over time, in fits and starts, the steady march of human innovation has brought previously unimaginable levels of prosperity and improvements to almost every aspect of people’s lives.

In some sense, AGI is just another tool in this ever-taller scaffolding of human progress we are building together. In another sense, it is the beginning of something for which it’s hard not to say “this time it’s different”; the economic growth in front of us looks astonishing, and we can now imagine a world where we cure all diseases, have much more time to enjoy with our families, and can fully realize our creative potential.

In a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.

We continue to see rapid progress with AI development. Here are three observations about the economics of AI:

1. The intelligence of an AI model roughly equals the log of the resources used to train and run it. These resources are chiefly training compute, data, and inference compute. It appears that you can spend arbitrary amounts of money and get continuous and predictable gains; the scaling laws that predict this are accurate over many orders of magnitude.

2. The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use. You can see this in the token cost from GPT-4 in early 2023 to GPT-4o in mid-2024, where the price per token dropped about 150x in that time period. Moore’s law changed the world at 2x every 18 months; this is unbelievably stronger. 

3. The socioeconomic value of linearly increasing intelligence is super-exponential in nature. A consequence of this is that we see no reason for exponentially increasing investment to stop in the near future.

If these three observations continue to hold true, the impacts on society will be significant.

We are now starting to roll out AI agents, which will eventually feel like virtual co-workers.

Let’s imagine the case of a software engineering agent, which is an agent that we expect to be particularly important. Imagine that this agent will eventually be capable of doing most things a software engineer at a top company with a few years of experience could do, for tasks up to a couple of days long. It will not have the biggest new ideas, it will require lots of human supervision and direction, and it will be great at some things but surprisingly bad at others.

Still, imagine it as a real-but-relatively-junior virtual coworker. Now imagine 1,000 of them. Or 1 million of them. Now imagine such agents in every field of knowledge work.

In some ways, AI may turn out to be like the transistor economically—a big scientific discovery that scales well and that seeps into almost every corner of the economy. We don’t think much about transistors, or transistor companies, and the gains are very widely distributed. But we do expect our computers, TVs, cars, toys, and more to perform miracles.

The world will not change all at once; it never does. Life will go on mostly the same in the short run, and people in 2025 will mostly spend their time in the same way they did in 2024. We will still fall in love, create families, get in fights online, hike in nature, etc.

But the future will be coming at us in a way that is impossible to ignore, and the long-term changes to our society and economy will be huge. We will find new things to do, new ways to be useful to each other, and new ways to compete, but they may not look very much like the jobs of today. 

Agency, willfulness, and determination will likely be extremely valuable. Correctly deciding what to do and figuring out how to navigate an ever-changing world will have huge value; resilience and adaptability will be helpful skills to cultivate. AGI will be the biggest lever ever on human willfulness, and enable individual people to have more impact than ever before, not less.

We expect the impact of AGI to be uneven. Although some industries will change very little, scientific progress will likely be much faster than it is today; this impact of AGI may surpass everything else.

The price of many goods will eventually fall dramatically (right now, the cost of intelligence and the cost of energy constrain a lot of things), and the price of luxury goods and a few inherently limited resources like land may rise even more dramatically.

Technically speaking, the road in front of us looks fairly clear. But public policy and collective opinion on how we should integrate AGI into society matter a lot; one of our reasons for launching products early and often is to give society and the technology time to co-evolve.

AI will seep into all areas of the economy and society; we will expect everything to be smart. Many of us expect to need to give people more control over the technology than we have historically, including open-sourcing more, and accept that there is a balance between safety and individual empowerment that will require trade-offs.

While we never want to be reckless and there will likely be some major decisions and limitations related to AGI safety that will be unpopular, directionally, as we get closer to achieving AGI, we believe that trending more towards individual empowerment is important; the other likely path we can see is AI being used by authoritarian governments to control their population through mass surveillance and loss of autonomy.

Ensuring that the benefits of AGI are broadly distributed is critical. The historical impact of technological progress suggests that most of the metrics we care about (health outcomes, economic prosperity, etc.) get better on average and over the long-term, but increasing equality does not seem technologically determined and getting this right may require new ideas.

In particular, it does seem like the balance of power between capital and labor could easily get messed up, and this may require early intervention. We are open to strange-sounding ideas like giving some “compute budget” to enable everyone on Earth to use a lot of AI, but we can also see a lot of ways where just relentlessly driving the cost of intelligence as low as possible has the desired effect.

Anyone in 2035 should be able to marshall the intellectual capacity equivalent to everyone in 2025; everyone should have access to unlimited genius to direct however they can imagine. There is a great deal of talent right now without the resources to fully express itself, and if we change that, the resulting creative output of the world will lead to tremendous benefits for us all.

Thanks especially to Josh Achiam, Boaz Barak and Aleksander Madry for reviewing drafts of this.

*By using the term AGI here, we aim to communicate clearly, and we do not intend to alter or interpret the definitions and processes that define our relationship with Microsoft. We fully expect to be partnered with Microsoft for the long term. This footnote seems silly, but on the other hand we know some journalists will try to get clicks by writing something silly so here we are pre-empting the silliness…