Ten years

过去十年， OpenAI 实现的成就超过了我曾经敢于想象的；我们当初要做的是一件疯狂、不太可能、前所未有的事。尽管起步极其不确定、几乎不被看好，靠着持续的努力，我们现在看起来有机会实现自己的使命。

十年前的今天我们向世界公布了这项工作，不过真正正式启动略晚几周，在 2016 年 1 月初。就社会变迁的节奏而言，十年也许不算太久，但对我们看到的可能性空间来说，却已经天翻地覆。日常生活看似变化不大，但当年我们 15 个极客围坐讨论如何推进时所面对的前景，和现在相比已经大不相同。

回看早期的照片，首先映入眼帘的是大家看起来多么年轻；然后更打动我的是那种近乎不合比例的乐观与快乐。那段时期既疯狂又充满趣味：虽然外界对我们误解颇多，但我们有着深刻的信念——这件事非常重要，值得在成功概率很小的情况下投入大量努力；我们有才华横溢的人才和明确的聚焦方向。

我们一点一滴地理解了发生了什么，经历了几次胜利（以及许多失败）。当时很难具体判断该做什么，但我们建立起了一种极有利于发现的文化。深度学习显然是重要技术，但如果不把它投入真实环境进行运营和积累经验，就不够完整。我在这里就不一一叙述当时做过的事（希望有人日后能写成史册），但我们始终有一种精神：不断攻克眼前的下一个障碍——研究能把我们带到何处、怎样筹资买更大的算力、或是其他任何问题。我们在以务实方式让人工智能更安全、更鲁棒的技术上做了先导工作，这种基因一直延续至今。

2017 年我们取得了几项奠基性成果：在 Dota 1v1 中将强化学习推向新的规模；发现了一个表明语言模型学到语义而不仅仅是句法的 unsupervised sentiment neuron ；以及通过 reinforcement learning from human preferences 展示了将 AI 初步对齐到人类价值观的可行路径。那时创新还远未结束，但我们意识到需要用大规模计算把这些成果做大做强。

我们继续改进技术，并在三年前推出了 ChatGPT 。世界为之侧目；当我们推出 GPT‑4 时，关注更是骤增，AGI 不再是一个荒诞的设想。过去三年异常紧张、充满压力与沉重责任；这项技术以史无前例的规模和速度融入世界，要求我们立即练就一种新的执行能力。从无到有、在这段时间内把公司做大并不容易，我们每周要做成百上千个决策。我为团队做对的很多决策感到自豪，做错的那些大多应由我承担。

我们不得不做出新的决策类型。例如，在思考如何让人工智能最大限度地造福世界时，我们提出并实施了“迭代部署”的策略：把技术的早期版本放到现实中，让人们形成直觉，促成社会与技术的共同演化。那时这一做法颇具争议，但我认为这是我们做过的最佳决策之一，并且已成为行业标准。

十年后的今天， OpenAI 拥有的人工智能在我们最困难的智力竞赛中，能胜过大多数最聪明的人。世界已经用这项技术做出非凡事情，我们预计在未来一年还会看到更多非凡成就。同时，全球也在相当程度上缓解潜在负面影响，我们需要继续为此努力。

我对我们的研究和产品路线图以及实现使命的可见路径从未如此乐观。再过十年，我相信我们几乎可以肯定会造出超智能。未来会让人感到奇怪：在某些方面，日常生活和我们最关心的事情可能变化不大，我们可能仍然更多地关注其他人在做什么，而不是机器在做什么；但在另一些方面，2035 年的人们将能做出一些现在很难想象的事情。

我感谢那些信任我们并用我们的产品做伟大事情的人和公司。没有他们，我们只不过是实验室里的技术；许多用户和客户在技术尚早的时候就对我们抱有极高且或许不合比例的信念，没有他们我们的工作无法达到今天的水平。

我们的使命是确保 AGI 惠及全人类。前方还有大量工作要做，但我为团队的轨迹感到自豪。今天人们用这项技术已经见到巨大益处，接下来的几年我们知道还会有更多成果出现。

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 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 wrested 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.

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