伴随 GPT5.2 的发布，Sam Altman 写了一封公开信《Ten Years》

这个公开信被放在了 OpenAI 的首页，随之而来的还有一段视频

本篇为翻译稿件，后附原文

过往十年

序：关于这十年突破、经验与通向造福全人类的 AGI 之路的一些思考

OpenAI 取得的成就，已经远超我当初敢想象的边界。我们一开始就是要做一件疯狂的、不太可能成功的、前无古人的事。从一个充满不确定性的起点出发，顶着所有理性分析都不看好的压力，凭借持续的努力，现在看起来，我们真的有机会完成我们的使命了。

十年前的今天，我们向世界宣布了这个计划，尽管正式启动要等到几周后的 2016 年 1 月初。

十年，从某种意义上说很长。但如果放在社会变革通常需要的时间尺度里，其实又很短。虽然日常生活和十年前比起来并没有那么大的不同，但我们面前的可能性空间，已经和当初 15 个技术宅围坐在一起、绞尽脑汁想着怎么往前推进时，完全不一样了。

回看早期的照片，我首先被每个人年轻的面孔震撼到。但更让我震撼的是，每个人脸上那种不合理的乐观，以及那种发自内心的快乐。那是一段疯狂而快乐的时光：虽然外界对我们充满误解，但我们有深刻的信念、有「这件事太重要了，哪怕成功概率很小也值得拼命去做」的使命感、有极其优秀的人才，还有高度聚焦的目标。

一点一点地，随着几次小胜（和更多次失败），我们逐渐建立起对正在发生之事的理解。那时候很难想清楚具体该做什么，但我们建立了一种极其适合探索发现的文化。深度学习（Deep Learning）显然是一项伟大的技术，但如果只是在实验室里闭门造车、不在真实世界中积累运营经验，总感觉哪里不对。那些年我们做过的事情太多了（希望以后有人能写一部完整的历史），但我们始终保持着一种精神：专注于眼前的下一个障碍——可能是研究能把我们带向何方，可能是怎么搞到钱买更大的计算机，或者别的什么。我们在实践中开创了让 AI 安全、可靠的技术路线，这种 DNA 一直延续到今天。

2017 年，我们取得了几项奠基性的成果：Dota 1v1 的突破，把强化学习（Reinforcement Learning）推向了新的规模高度；无监督情感神经元（Unsupervised Sentiment Neuron）的发现，让我们清楚地看到语言模型确实在学习语义，而不仅仅是语法；还有基于人类反馈的强化学习（RLHF，Reinforcement Learning from Human Preferences）成果，展示了一条让 AI 与人类价值观对齐的初步路径。到这个阶段，创新远未结束，但我们已经知道，需要用海量的算力把这些成果放大。

我们继续推进，技术越来越好。三年前，我们发布了 ChatGPT。世界开始关注我们，而当我们发布 GPT-4 后，关注变成了震动——突然之间，AGI（通用人工智能，Artificial General Intelligence）不再是一个疯狂的想法了。过去这三年极其紧张，充满压力和沉甸甸的责任。这项技术以前所未有的规模和速度融入了世界。这需要极其高难度的执行力，而我们必须马上练出这块新肌肉。在这么短的时间内从零成长为一家大型公司并不容易，我们每周都要做出上百个决策。我为团队做对的那些决策感到骄傲，而做错的那些，大多是我的责任。

我们必须做出一些全新类型的决策。比如，当我们在思考如何让 AI 最大程度地造福世界时，我们提出了「迭代部署」（Iterative Deployment）策略——把技术的早期版本投放到真实世界中，让人们建立直觉，让社会与技术共同演化。这在当时争议很大，但我认为这是我们做过的最好的决策之一，现在也已经成为行业标准。

OpenAI 走过十年，我们已经拥有一个 AI，它在我们最顶尖的人才所参与的、难度最高的智力竞赛中，表现得比大多数人都好。

全世界已经在用这项技术做出非凡的事情，而我们预计，在接下来的一年里，还会有更多非凡之事发生。与此同时，世界在应对潜在负面影响方面做得还不错，我们需要继续努力保持这个势头。

我对我们的研究路线和产品路线从未如此乐观，对通向使命的整体视野也是如此。我相信，再过十年，我们几乎肯定能造出超级智能（Superintelligence）。我预计未来会让人感到奇异：从某种意义上说，日常生活和我们最在意的那些事不会有太大变化，我相信我们仍然会比关注机器更关注其他人在做什么。但从另一个意义上说，2035 年的人们能做到的事情，我觉得我们今天根本无法轻易想象。

我感谢那些信任我们、使用我们产品去做伟大事情的人和公司。没有他们，我们只是一个实验室里的技术。我们的用户和客户，在很多情况下是用一种早期的、不合理的高度信念押注了我们。没有他们，我们的工作不可能达到今天的水平。

我们的使命是确保 AGI 造福全人类。前方还有很多工作要做，但我真的为团队带领我们走上的这条轨迹感到骄傲。人们今天已经用这项技术做出了巨大的成就，而我们知道，未来几年还有更多精彩在等着我们。

下为英文版原文

Ten years

Reflections on a decade of breakthroughs, learnings, and the path toward AGI that benefits all of humanity.

OpenAI has achieved more than I dared to dream possible; we set out to do something crazy, unlikely, and unprecedented. From a deeply uncertain start and against all reasonable odds, with continued hard work it now looks like we have a shot to succeed at our mission.

We announced our effort to the world ten years ago today, though we didn’t officially get started⁠(opens in a new window) for another few weeks, in early January of 2016.

Ten years is a very long time in some sense, but in terms of how long it usually takes the arc of society to bend, it is not very long at all. Although daily life doesn’t feel all that different than it did a decade ago, the possibility space in front of us all today feels very different than what it felt like when we were 15 nerds sitting around trying to figure out how to make progress.

When I look back at the photos from the early days, I am first struck by how young everyone looks. But then I’m struck by how unreasonably optimistic everyone looks, and how happy. It was a crazy fun time: although we were extremely misunderstood, we had a deeply held conviction, a sense that it mattered so much it was worth working very hard even with a small chance of success, very talented people, and a sharp focus.

Little by little, we built an understanding of what was going on as we had a few wins (and many losses). In those days it was difficult to figure out what specifically to work on, but we built an incredible culture for enabling discovery. Deep learning was clearly a great technology, but developing it without gaining experience operating it in the real world didn’t seem quite right. I’ll skip the stories of all the things we did (I hope someone will write a history of them someday) but we had a great spirit of always just figuring out the next obstacle in front of us: where the research could take us next, or how to get money for bigger computers, or whatever else. We pioneered technical work for making AI safe and robust in a practical way, and that DNA carries on to this day.

In 2017, we had several foundational results: our Dota 1v1 results, where we pushed reinforcement learning to new levels of scale. The unsupervised sentiment neuron, where we saw a language model undeniably learn semantics rather than just syntax. And we had our reinforcement learning from human preferences result, showing a rudimentary path to aligning an AI with human values. At this point, the innovation was far from done, but we knew we needed to scale up each of these results with massive computational power.

We pressed on and made the technology better, and we launched ChatGPT three years ago. The world took notice, and then much more when we launched GPT‑4; all of a sudden, AGI was no longer a crazy thing to consider. These last three years have been extremely intense and full of stress and heavy responsibility; this technology has gotten integrated into the world at a scale and speed that no technology ever has before. This required extremely difficult execution that we had to immediately build a new muscle for. Going from nothing to a massive company in this period of time was not easy and required that we make hundreds of decisions a week. I’m proud of how many of those the team has gotten right, and the ones we’ve gotten wrong are mostly my fault.

We have had to make new kinds of decisions; for example, as we wrestled with the question of how to make AI maximally beneficial to the world, we developed a strategy of iterative deployment, where we successfully put early versions of the technology into the world, so that people can form intuitions and society and the technology can co-evolve. This was quite controversial at the time, but I think it has been one of our best decisions ever and become the industry standard.

Ten years into OpenAI, we have an AI that can do better than most of our smartest people at our most difficult intellectual competitions.

The world has been able to use this technology to do extraordinary things, and we expect much more extraordinary things in even the next year. The world has also done a good job so far of mitigating the potential downsides, and we need to work to keep doing that.

I have never felt more optimistic about our research and product roadmaps, and overall line of sight towards our mission. In ten more years, I believe we are almost certain to build superintelligence. I expect the future to feel weird; in some sense, daily life and the things we care most about will change very little, and I’m sure we will continue to be much more focused on what other people do than we will be on what machines do. In some other sense, the people of 2035 will be capable of doing things that I just don’t think we can easily imagine right now.

I am grateful to the people and companies who put their trust in us and use our products to do great things. Without that, we would just be a technology in a lab; our users and customers have taken what is in many cases an early and unreasonably high-conviction bet on us, and our work wouldn’t have gotten to this level without them.

Our mission is to ensure that AGI benefits all of humanity. We still have a lot of work in front of us, but I’m really proud of the trajectory the team has us on. We are seeing tremendous benefits in what people are doing with the technology already today, and we know there is much more coming over the next couple of years.