State of the AI industry — the OpenAI Podcast Ep. 12

章节 1：2026 年展望——代理（Agents）与缩小能力差距

📝 本节摘要：

本节作为访谈的开篇，Vinod Khosla 提出了关于 AI 发展阶段的核心论点：2025 年是“氛围编码”（vibe coding）的成熟期，而 2026 年将是“代理”（Agents）和多智能体系统产生实质性影响的一年。讨论涵盖了从企业级应用（如自动化 ERP 系统）到消费者端（如复杂的旅行规划）的转变。Sarah Friar 进一步指出，当前的挑战在于“缩小能力差距”——即虽然用户已拥有强大的工具（好比法拉利），但尚在学习如何驾驭它，主要任务是将 AI 从单纯的问答机器人转化为能够执行具体任务的“任务工作者”。

[原文] [Andrew Mayne]: Hello, I'm Andrew Mayne, and this is the OpenAI Podcast. Today, our guests are Sarah Friar, CFO of OpenAI, and legendary investor Vinod Khosla of Khosla Ventures. In this discussion, we're going to talk about the state of the AI ecosystem, whether or not we're in a bubble, and how startups and investors can succeed as AI progresses.

[译文] [Andrew Mayne]: 大家好，我是 Andrew Mayne，这里是 OpenAI 播客。今天的嘉宾是 OpenAI 的首席财务官 Sarah Friar，以及 Khosla Ventures 的传奇投资人 Vinod Khosla。在本次讨论中，我们将探讨 AI 生态系统的现状，我们是否处于泡沫之中，以及随着 AI 的进步，初创企业和投资者如何取得成功。

[原文] [Vinod Khosla]: Unlike something like Netflix, where they're running so many hours in the day, I think of it much more like infrastructure, like electricity. Demand is limited, not by anything other than availability of compute today.

[译文] [Vinod Khosla]: 不像 Netflix 那样，人们一天只能看那么几个小时，我认为它（AI）更像是基础设施，就像电力一样。今天的需求仅受限于算力的可用性，而不受其他任何限制。

[原文] [Vinod Khosla]: I think the conversation we need to have is, what will people do? 2025 was about agents and vibe coding. Now it's 2026. What's the story of 2026? I think we matured in vibe coding in 2025. I don't think we've matured in agents.

[译文] [Vinod Khosla]: 我认为我们需要进行的对话是，人们将会做什么？2025 年是关于代理（agents）和氛围编码（vibe coding）的一年。现在是 2026 年。2026 年的故事是什么？我认为我们在 2025 年已经在氛围编码上成熟了。但我不认为我们在代理方面已经成熟。

[原文] [Vinod Khosla]: So agents, especially multi-agent systems, will mature to the point of having real visible impact. Whether you're an enterprise and you have multi-agent systems doing full tasks, like running an ERP system for you, doing all the reconciliation every day, accruals every day, tracking contracts every day.

[译文] [Vinod Khosla]: 因此，代理，特别是多智能体系统（multi-agent systems），将成熟到产生真实可见影响的程度。无论你是企业，拥有多智能体系统执行完整的任务，比如为你运行 ERP 系统（企业资源计划系统），每天进行所有的对账，每天处理应计项目，每天追踪合同。

[原文] [Vinod Khosla]: I think that on the enterprise side. But today, on the consumer side, you know, it's still a hassle to plan a trip. That's a multi-agentic thing that looks across a lot of different things from your food preferences to the restaurant reservation to airline schedules to your personal calendar. Those will start to mature, I think, a year from now. So I'm pretty excited about that.

[译文] [Vinod Khosla]: 我认为这是在企业方面。但在今天，在消费者方面，你知道，规划一次旅行仍然是个麻烦事。那是一个多智能体的事情，需要跨越很多不同的事物，从你的饮食偏好到餐厅预订，到航班时刻表，再到你的个人日历。我认为一年后这些将开始成熟。所以我对此非常兴奋。

[原文] [Vinod Khosla]: I think models in robotics and real world models that go well beyond robotics, like general intuition, will all start to happen in the next year. So I think those are areas to look for.

[译文] [Vinod Khosla]: 我认为机器人领域的模型，以及远超机器人范畴的现实世界模型，比如通用直觉，都将在明年开始出现。所以我认为这些是值得关注的领域。

[原文] [Vinod Khosla]: There's usual functions like memory in LLMs, continual learning in LLMs, reduction of the impact of hallucinations. Those are all areas I could go on. There's half a dozen areas in which AI doesn't do as well today that will start to be addressed.

[译文] [Vinod Khosla]: 还有一些常规功能，比如大语言模型（LLMs）中的记忆功能，大语言模型中的持续学习，以及减少幻觉（hallucinations）的影响。这些领域我还可以继续列举。大概有半打领域是 AI 目前做得还不够好，但将开始得到解决的。

[原文] [Sarah Friar]: Yeah. And I think at its baseline, what Vinod is saying is 26 is the beginning of closing this capability gap. So what we know is we've handed people massive intelligence, right? We've handed them the keys to the Ferrari, but they are only learning how to take it out on the road for the first time.

[译文] [Sarah Friar]: 是的。我认为从根本上说，Vinod 的意思是 2026 年是开始缩小这种能力差距的一年。我们所知道的是，我们已经把巨大的智能交给了人们，对吧？我们把法拉利的钥匙交给了他们，但他们才刚刚开始学习如何把它开上路。

[原文] [Sarah Friar]: We need to give consumers more and more easy ways to go from ChatGPT is just a chat bot call and response. Most people use it today just to ask questions. But how do we take it towards being a true task worker that books that trip for them or helps them get a second opinion on what they just heard from their doctor or enables them to create a menu for their diabetic child, right?

[译文] [Sarah Friar]: 我们需要给消费者提供越来越多简单的方法，让 ChatGPT 从仅仅是一个一问一答的聊天机器人转变过来。今天大多数人只是用它来问问题。但我们如何让它成为一个真正的任务工作者，为他们预订那次旅行，或者帮助他们对刚从医生那里听到的话获取第二意见，或者让他们能为患糖尿病的孩子创建一份菜单，对吧？

[原文] [Sarah Friar]: How do we help them really move from simple questions into actual outcomes that make my life better? And then on the enterprise side, it's that same continuum. How do we close the capability gap?

[译文] [Sarah Friar]: 我们如何帮助他们真正从简单的问题转向能够让生活变得更好的实际成果？然后在企业方面，这也是同一个连续体。我们如何缩小能力差距？

[原文] [Sarah Friar]: One of the things we know from our state of the enterprise AI and the enterprise report that our chief economist put out at the end of last year is on the frontier versus just even the median corporation. The average number of messages or the median is about 6x, which will tell you that 6x the usage from a company that's already on the frontier.

[译文] [Sarah Friar]: 我们从去年年底首席经济学家发布的《企业 AI 现状》报告中了解到的一件事是，关于前沿企业与中位数企业的对比。消息数量的平均值或中位数大约是 6 倍，这告诉你，一家已经在前沿的公司其使用量是（普通公司的）6 倍。

[原文] [Sarah Friar]: And we know that frontier isn't even pushed to its max. So for us, it's this focus of how do we help consumers move along that continuum to true agentic task working?

[译文] [Sarah Friar]: 而我们知道，即使是前沿也还没有被推到极限。所以对我们来说，重点在于我们如何帮助消费者沿着这个连续体移动，迈向真正的代理式任务工作？

[原文] [Sarah Friar]: And then for enterprises, how do we create a much more sophisticated, vertically specialized outcome for enterprises that allows them to go from maybe a very simple ChatGPT implementation the whole way to something that's transforming the most important part of their business.

[译文] [Sarah Friar]: 然后对于企业，我们如何为企业创造更复杂、垂直专业化的成果，让他们能够从可能非常简单的 ChatGPT 部署，一路发展到能够改变其业务最重要部分的某种东西。

[原文] [Sarah Friar]: For a healthcare provider, it might be their drug discovery process. For a hospital, it might be the time to admit a patient to get that patient back into the community. For a really large retailer, it might be just larger basket sizes, higher conversion rates, and much happier customers. So it's the basics of closing that capability gap.

[译文] [Sarah Friar]: 对于医疗保健提供商来说，这可能是他们的药物研发过程。对于医院来说，这可能是从接收病人到让病人回到社区的时间。对于一家超大型零售商来说，可能仅仅是更大的购物篮规模（客单量）、更高的转化率和更满意的客户。所以这就是缩小能力差距的基础。

[原文] [Vinod Khosla]: So I might add one other perspective. We've talked about the number of areas in which the technology will advance and capability will advance. I would venture to guess today, of the people using AI, whether it's personal or enterprise, some single digit percentage are even using 30% of the capability of the AI.

[译文] [Vinod Khosla]: 我想再补充一个视角。我们谈到了技术将进步和能力将提升的许多领域。我敢猜测，今天在使用 AI 的人中，无论是个人还是企业，只有个位数的百分比甚至用到了 AI 能力的 30%。

[原文] [Vinod Khosla]: So this percentage of people who are using 30% or 50%, let alone 80% of the AI's capabilities, will keep increasing. I think that's a 10-year journey before people learn to use AI.

[译文] [Vinod Khosla]: 因此，使用 30% 或 50%（更不用说 80%）AI 能力的人群比例将会持续增加。我认为在人们学会使用 AI 之前，这是一段为期 10 年的旅程。

请告诉我是否需要继续输出第二章节？