--- author: All-In Podcast date: '2026-06-02' guest: '' layout: post.njk source: https://www.youtube.com/watch?v=TjrShuj_Zsg speaker: All-In Podcast tags: - ai-infrastructure - compute-scarcity - capital-allocation - multimodality - ai-strategy title: OpenAI CFO Sarah Friar谈IPO、AI竞争、新设备与千亿级算力投资 summary: OpenAI首席财务官Sarah Friar就公司IPO前景、与Anthropic等竞争对手的战略差异、AI算力稀缺性及其在教育、医疗等领域的应用潜力，以及未来AI广告平台的发展进行了深入探讨。她强调了AI作为基础设施层的战略定位，并揭示了OpenAI在多CSP和多芯片策略上的布局，以应对对算力指数级增长的需求，并确保AGI的普惠性。Friar还透露了OpenAI正在开发一款全新的消费级AI设备，预计在今年底或明年初发布，将带来更自然、无缝的AI交互体验。 insight: '' draft: true series: '' category: ai-ml area: tech-engineering project: [] people: - Sarah Friar - Sam Altman - Greg Brockman companies_orgs: - OpenAI - Anthropic - SpaceX - Sidio Ramco - Google - Yahoo - Lyft - Uber - SEC - Thermopisher - Travelers - Microsoft - Nvidia - Oracle - Coreweave - GCP - AWS - AMD - Cerebrris - Broadcom - SoftBank Energy - Meta products_models: - ChatGPT - Sora - Codeex - GPT-4 - GPT-4o - ChatGPT Plus - iPhone - Rubin - Fineman - Gemini media_books: - Wall Street Journal status: evergreen --- ### IPO与AI融资新时代 **主持人**: OpenAI的首席财务官**Sarah Friar**。我们得马上进入正题了。你刚刚完成了我所认为史上最成功的融资轮。
Original English **Host**: Open AAI's CFO, **Sarah Frier**. We got to get right to it. You have just completed what I regard as the most successful fundraising round in history.
**Sarah Friar**: 我们实际上将募集超过**1200亿美元**。我们认为**AI**是迄今为止我们所见过的最大时代。我们才刚刚开始理解它对全球生产力意味着什么，以及随之而来的，希望能为每个人带来更多的富裕和更好的生活。运气就是准备遇到机会，但你必须抓住它。
Original English **Sarah Friar**: We're going to raise actually north of **$120 billion**. We think **AI** is the biggest era that we've seen to date. We're just starting to understand what it's going to mean for global productivity and with that, you know, hopefully more affluence, better lives for everyone. Luck is whatever the preparation meets opportunity, but you got to grab it.
**采访者A**: 长期的听众，第一次打电话。很高兴能和大家一起玩。你好。
Original English **Interviewer A**: Longtime listener, first time caller. Quite exciting to get to hang out with all the bros here. Hello.
**采访者B**: 我们不确定该如何开始，但我认为最好的方式是让我们的URSTW cryptosar…
Original English **Interviewer B**: We weren't sure how to start this off, but I thought the best thing was to allow our URSTW cryptosar to maybe...
**Sarah Friar**: ...保留评论。我今天看到一篇文章，我想可能是在《**华尔街日报**》上，说人们认为**AI公司**更早上市具有优势。所以现在我们知道**SpaceX**正在推进**IPO**，问题是**OpenAI**和**Anthropic**什么时候会上市？我很好奇，你对此怎么看？你认为这有一点竞争吗？或者，你还没有就此做出决定？最后，**IPO**，我一直对团队说，它是一个里程碑，而不是终点。不要把你的公司运营得好像那是一个终点。它只是另一种筹集资金的方式。我们刚刚，你听我在预告片里说了，在三月份筹集了**1220亿美元**，那是为了给自己最大的灵活性。我认为我作为**CFO**的工作是为这家公司，甚至是我们所处的这个时代，创造选择性。
Original English **Sarah Friar**: ...save comments. I saw an article today, I think it might have been in the **Wall Street Journal**, that the perception is that there's an advantage to **IPOing** earlier if you're an **AI company**. So now we know **SpaceX** is going and then the question is when's when are **OpenAI** and **Anthropic** going to go? And I'm curious, how do you think about that? Do you think there is a little bit of a race on or you know, you haven't made a decision about that yet? Like in the end, an **IPO**, I say this to the team all the time, it's a milestone. It is not a destination. Do not run your company as if that's some sort of destination. It's just another way to fund raise. We just did, you heard me on on the the s the sizzle reel, raise **122 billion dollars** in March, and that was to give ourselves maximum flexibility. I feel like my job as a **CFO** is create optionality for this not just this company but just this era that we're living in.
**David**: 那么Sarah，那次筹款，直到**SpaceX IPO**之前，是史上最大的私营企业筹款吗？
Original English **David**: So Sarah was that that point in fundraising is that the biggest private republic up until the **SpaceX IPO**?
**Sarah Friar**: 是的。
Original English **Sarah Friar**: It is.
**David**: 是的，按数量级计算是。我认为迄今为止最大的**IPO**是**Sidio Ramco**，大约**300亿美元**。所以，实际上令人难以置信的是，你可能会有三个**IPO**，其规模甚至会超过2000-2001年。那个时期市场也发生了很多事情，但市场已经增长了，顺便说一下，市场上还在发生另一件事，那就是如果你看看**股票回购**、**并购**等等，实际上有很多资本不断返还给股东和现金，所以有很多资金闲置。但本着**David**你的问题精神，我认为最终你会得到衡量，对吗？最终市场是一个称重机，而不是一个受欢迎度机器。没有人记得**Google**或**Yahoo**、**Lyft**或**Uber**谁先上市。我说这些不是因为我想争第一或第二，我只是觉得，你知道，媒体喜欢一点戏剧性，但最终，我们要建立大型、可持续、持久的公司，而**筹款**将是实现这一点的关键组成部分。
Original English **David**: It is by orders of magnitude. I think the largest **IPO** to date was the **Sidio Ramco** which was about **$30 billion**. So it is actually incredible that you're going to have potentially three **IPOs** at a scale that will be bigger even than 2001 2000 that that time frame there was a lot that went on in the market too but the market has grown and by the way the other thing going on in the market is like if you look at **buybacks** **M&A** and so on it's actually a lot of capital keeps being returned back to shareholders and cash so there is a lot of money sitting on the sidelines but in the spirit of like the question David, I think in the end you want to you'll be measured, right? It's the in the end the market is a weighing machine, not a popularity machine. No one remembers who went first, **Google** or **Yahoo**, **Lyft** or **Uber**. And I say that not because whether I want to be first or second, but I just think it, you know, the the press loves a bit of drama, but in the end, we're going to have to build big, sustainable, durable companies, and **fundraising** will be a key component of doing exactly that.
### OpenAI与Anthropic的战略差异 **Jason**: Sarah，突发新闻。
Original English **Jason**: Sarah, breaking news.
**Sarah Friar**: 哦，天哪，这么多人冲着我来。嗨，**Jason**。不，同时平衡四位采访者确实很困难。
Original English **Sarah Friar**: Oh my god, so many people coming at me. Hi, Jason. No, it is it is it is hard balancing four interviewers at the same time.
**Jason**: 没关系，这是我的世界，顺便说一下。所以我对此很满意。**Jason**，
Original English **Jason**: It's okay. This is my world, by the way. So, I'm good with this. Jason,
**采访者C**: **Anthropic**刚刚秘密提交了他们的**S1文件**。那么，这是否意味着你们在提交方面排名第三？
Original English **Interviewer C**: **Anthropic** just uh confidentially filed their **S1**. So, does that mean you're third place in terms of the filing?
**Sarah Friar**: 这并不意味着什么，因为你现在必须经历**SEC**的考验，谁知道对任何人来说需要多长时间。
Original English **Sarah Friar**: It does not mean anything yet because you have to run now the gauntlet of the **SEC** and who knows how long that takes for anyone.
**采访者D**: 是的。那么，他们继续前进有好处吗？我认为解开与**Anthropic**的竞争是大家都在关心的问题。所以，我想你不能谈太多关于**IPO**的事情。所以我就转到**Anthropic**以前远远落后，但现在他们真的，我想业内每个人都会同意，他们在开发者和公司方面已经超越了**OpenAI**，看起来营收也是。那么，**OpenAI**在拥有如此巨大领先优势的情况下，这又是怎么发生的呢？**Anthropic**是如何超越你们的？
Original English **Interviewer D**: Yeah. Is it is there though a benefit to them going forward? And I think unpacking the rivalry with **Anthropic** is on everybody's minds. So just I guess you can't talk too much about **IPOs**. So I'll just pivot to **Anthropic** was far behind and now they've really um I think everybody would agree in the industry now blown past **OpenAI** in terms of **developers** and **corporations** and it seems **revenue**. So did how did that happen at **OpenAI** when you had such a tremendous lead? How did **Anthropic** blow past you guys?
**Sarah Friar**: 那么，我们来谈谈策略。我们的策略是不同的，对吗？所以我们正在构建**AI层**，即基础设施，拥有一个单一的基础非常重要，然后通过许多接口进入世界。所以**ChatGPT**是其中一个面向消费者的接口。每周有超过**9亿人**使用**ChatGPT**，它已经成为了一个名词和动词。这是大多数人第一次体验**AI**的方式。一个有趣的事实是，我们的**经济研究团队**刚刚给我看，现在增长最快的大洲是**非洲**。考虑到它的基础较小，这可能并不完全令人惊讶。增长最快的语言是**阿塞拜疆语**和**哈萨克语**，这谈论它的发展方向是相当不可思议的。所以，有多个接口，**ChatGPT**当然有，还有**Codeex**，周末刚刚突破**500万用户**，我们为此感到非常自豪，它在一月份几乎是零用户。**500万用户**使用**Codeex**，它也帮助我准备了这个小专题。当然还有**Frontier**，我们的企业产品，以及所有其他我们能够接触到各种规模企业的方式。这是一个非常不同的策略。我们认为，因为它基于一个模型提供服务，所以这会带来一种复合优势。更多的用户，更多的数据，更多的个性化聊天能力作为前端。随着模型变得更大，效率会更高。这应该会降低向世界提供**token**的总体成本。这应该会复合为更高的毛利率，最终有更多的方式来支付算力，而获得算力是当前一个非常大的竞争优势。所以，我们都必须跑自己的比赛，但我们也必须认识到我们是生态系统的一部分，也需要集体地带动人们。
Original English **Sarah Friar**: So let's talk a little bit about a strategy. Our strategy is different, right? So we are building the **AI layer**, the **infrastructure** and it's really important that there's a single foundation but then with many interfaces out into the world. So **Chat GPT** is one to the consumer. Over **900 million people** use **Chat GPT** weekly and it's become the noun and the verb. It's how most people experience um **AI** for the first time. Kind of fun fact, our **economic research team** just showed me um the fastest growing continents now are **Africa**. Probably not totally surprising since it started a small base. fastest growing languages are um **Azerbjani** and um what Kazakhstani what is it's **Kazak** um which it's kind of incredible to talk about where it's going so multiple interfaces **chatgpt** of course there's um **codeex** um just hit **5 million** over the weekend we're really proud of that coming from almost zero in January **5 million users** go **codeex** um help me prepare for this little special up here too um there's of course **Frontier** our **enterprise offering** ing and everything every other way that we can get out there to reach businesses of all sizes. That is a very different strategy. We think that because it's served up on one model, there's a **compounding element of advantage** that comes from that. More users, more data, more ability to personalize chats as a front door. As we as models get bigger, there's more efficiency. That should lower the overall cost to give you a **token** in the world. That should compound to higher **gross margins**, ultimately more ways to pay for **compute**, and then access to **compute** is one of the really big competitive advantages at the moment. So, you know, we have to all run our own races, but we all have to recognize we're part of an ecosystem that also needs to bring people along collectively.
**主持人**: 你们是否分散了太多项目？人们在谈论这款新设备**Sora**，然后可能对企业关注不够。如果说去年犯了一个错误，那是不是就是这个错误？这是一个公平的评估吗？
Original English **Host**: Did you spread a little bit too then too many projects? People were talking about this new gadget, **Sora**, and and then maybe not enough focus on enterprise. Is that a fair assessment of if there was a mistake in the last year that was it?
**Sarah Friar**: 不，我认为世界喜欢走向二元对立，比如“你是**消费者公司**Sarah？”“你是**企业公司**？”现实是，我们两者兼而有之。我们不是非此即彼。现在我们的收入已经相当平衡，大约**50/50**。我们非常专注于企业。我花了很多时间，我的意思是，就在上周，我可以告诉你，我去了波士顿拜访**Thermopisher**。我和纽约的一群银行家在一起。周五我与**Travelers**通了电话。今天早上我与一家科技公司通了电话。无论是哪个垂直领域。人们现在真的都在关注**AI**。我们的新营收主管**Denise Dresser**自去年12月上任。她是一个自然的力量。所以我认为**企业**总的来说确实是火力全开。但我们不想抛弃消费者。请记住，**OpenAI**的使命是**造福全人类的AGI**，而不是造福那些能支付费用的人，也不是造福那些在企业中生活的人，而是非常广泛的。这就是为什么我们提供如此多的免费服务，因为我们希望人们尝到甜头。一旦他们尝到**智能**的甜头，他们向上攀升的承诺曲线是不可思议的。我们的免费用户每天大约进行**7次对话**，即**7个问题**。我们的第一个付费层用户大约是这个的两倍，**15次**。我们的真正的付费层，即**20美元的Plus会员**。希望你们都在使用，或更高级别，大约是免费用户的**3倍**，专业版大约是**11倍**。所以请记住，当你拿到翻盖手机时，你会想，“是的，我不知道它有什么用，打几个电话。”现在同一部手机，想想它为你做了所有的事情。这就是我们现在在**智能**方面所走的道路。抱歉。
Original English **Sarah Friar**: No, I I think that the world loves to go to binaryisms like are you a consumer company Sarah? Are you an enterprise company? The reality is we're very much both. We're not one or the other. Right now our revenue is getting pretty balanced about **50/50**. We are incredibly focused on the enterprise. Like I spend so much of my time with I mean just even in the last week I could tell you I've been to see **Thermopisher** in Boston. I was with a bunch of banks in New York. I was on the phone with **travelers** on Friday. I spent this morning on the phone with a tech company. It doesn't matter the vertical. People are really moving on **AI** right now. Our new head of revenue, **Denise Dresser**, in seats since December. She is a force of nature. And so I think the enterprise broadly speaking is really firing on all cylinders. But we don't want to leave the consumer behind. Remember our mission at **OpenAI** is **AGI** for the benefit of humanity, not for the benefit of humanity who can pay or for the benefit of humanity who live in an enterprise, but very broadbased. Um, it's why we offer so much free because we want people to get a taste. Once they get a taste of **intelligence**, the ability to come up a commitment curve is incredible. Our free users do about **seven turns**, **seven questions** a day. Our first paid tier do double that about **15**. Our our real paid tier the **plus 20 bucks**. Hopefully you're all on it or higher about **3x** and pro about um **11x** over a free user. So remember when you got your flip phone and you're like yeah I don't know what it does make some calls. Now that same phone think of all the things it does for you. That's the path we're on with **intelligence** right now. Sorry.
### AI算力稀缺性与投资 **主持人**: 你说了一些非常有影响力的话。我想大约18个月前，对我们行业中的很多人来说，你提出了一个非常简单的经济权衡，那就是**千兆瓦**转化为现金。我想你说过，**1千兆瓦**大致相当于**OpenAI**每年**100亿美元**的收入。所以第一个常见的数字是**1千兆瓦**等于你每年**100亿美元**的收入。但这不仅仅是你，因为你可能可以推断到**Anthropic**和其他公司，比如**Gemini**。
Original English **Host**: You said something very influential. I think it was about 18 months ago for a lot of us in the industry where you framed a very simple economic trade-off which was **gigawatts** to cash and I think you said one **gigawatt** is roughly equivalent to about **$10 billion** a year of revenue to open **AAI**. So common number one was this one **gigawatt** equals**10 billion** a year of revenue for you. But it's not just you because you can probably extrapolate that to **anthropic** and other folks **Gemini**
**Sarah Friar**: 但那时你确实走在了最前沿，获得了**电力**和**数据中心**，以及拥有**电力供应的土地**。这看起来有点疯狂，但现在看来，算力存在巨大的供应赤字。你能详细解释一下所有这些，并解释一下我们所处的现状，以及具体的经济学，以及它是否发生了变化？
Original English **Sarah Friar**: but then you were really at the forefront of getting access to **power** and **data centers** and **powered land**. It seemed a little crazy but now it looks like hold on there's a huge deficit of supply. Can you just unpack all of that and explain...
**Sarah Friar**: ...无论是从我们所处的范围，还是那些具体的经济学，以及它是否发生了变化。首先，是的，**算力**目前是一个非常稀缺的资源。我的意思是，我们在业务中看到的是，我们现在正面临着**需求**的垂直增长，而且没有足够的**token**可用。所以我非常感谢能与**Greg**和**Sam**一起工作。我认为我们对此非常有先见之明，去年我们肯定受到了很多批评，质疑我们为什么要出去购买所有这些算力，我想感谢上帝我们这样做了，因为到2026年，我们仍然没有足够的算力。**算力**的连续体中，到处都是瓶颈，而且我认为它们将继续来回移动。我的意思是，你们都在谈论这个，并且和任何人一样清楚，无论是首先的**能源**，还是**土地**、**电力**，我们都要获得监管环境，以便我们能够快速建设。当你进入**机架**和**芯片**本身时，我们显然有足够的，在那个**供应链**中，内存峰值正在发生，获得优秀人才，我们的教育系统是否有足够的人才？我现在真的很担心这个问题，我是**斯坦福大学**的受托人，你知道，我看到我们需要继续关注**教育**和**科学**。然后是**信任**，我的意思是，我实际上把它作为**供应链**的一部分。**Sam**现在在**密歇根州塞林**，他将在大约两个小时内剪彩，所以你们会得到一个预览，但他们告诉我可以在房间里说出来，那将是，你知道，在一个**1千兆瓦**的**数据中心**动工，这是我们或**Oracle**复合体的一部分。在**信任**方面非常重要，我们不要抛弃社区。我花了七年的时间在**Next Door**工作，做着成为本地人意味着什么这种艰苦的工作，你不能自上而下地告诉人们他们需要什么，因为他们会告诉你“谢谢，但不用了，我会告诉你我需要什么”。所以在一个像那样的**数据中心**里，实际上花了很多时间在社区里说第一，我们不会提高你的**电费**。我们将支付我们的基础设施和电力。不会由纳税人来支付。第二，我们将带来就业机会，**2500个工会工作**，像**电工**、**HVAC**等好工作。我们将支付我们的税款，仅仅那个**数据中心**就将向**密歇根州**缴纳**10亿美元的税款**。最重要的是，我们将投资**4500万美元**用于**Codeex积分**的教育，做你们这个周末谈论的所有事情，就像任何一个没有准备好就进入新工作的人一样。我的青少年们正在使用**Codeex**。就像我永远不会雇佣一个不会使用**Excel**的财务人员一样。我几乎肯定不会雇佣一个今天不会使用**Codeex**这样的工具的财务人员。所以，你知道，所以当我考虑投资时，我们必须在需求之前进行投资。这意味着我们既需要找到所有的**算力**和所有部件，然后支付它。所以这又回到了你的**IPO**的资本问题。然后另一方面，在经济学方面，你看，经济学确实在不断变好。它们在多个方面都在变好。我认为我们在实际向客户展示真正的价值方面做得更好。我想你超越了那种**成本加成**的定价，进入了更接近所创造价值的定价。现在，**token**的稀缺性有所帮助，因为它正在造成一点**压缩**。你能谈谈这一点，就像不提具体名称，现在**电力**的可用性以及每个人对**电力**的需求所存在的局面吗？是的。
Original English **Sarah Friar**: ...both the spectrum of where we are and then those specific economics and if that's changed. So first of all, yes, **compute** is a very scarce resource at the moment. I mean, what we see in our business, we're going up that kind of vertical wall of demand right now and there's just not enough **tokens** available. So we I'm very grateful that I got to work alongside **Greg** and **Sam**. I think we're very precient on this and last year we were definitely taking some you know arrows in the back about why are they out there buying all this **compute** and I think thank god we did because in 26 we still won't have enough **compute**. Um where are we on the **compute continuum** there's kind of choke points everywhere and and I think they will continue to move back and forth. I mean you all talk about this and know this as well as anyone um here whether it's **energy** first and foremost um **land power** we get regulatory um environment such that we can build quickly um when you get into the **racks** and **chips** themselves clearly do we have enough um in that **supply chain memory spike** is is on at the moment access to great talent um do we have enough people coming through our **education system** I really worry about this right now I'm a trustee at **Stanford** and you know I see just that you know we need to keep the focus on **education** and **science** um and then **trust** I mean I actually put that as part of the **supply chain** um **Sam** right now is in **Selen Michigan** he's going to be cutting the ribbon in about two hours so you are getting a sneak preview but they told me it was okay to say it in the room um that will be you know sticking shovels in the ground on a **1 gigawatt data center** which is part of our or **Oracle** complex really important there on the **trust** side that we don't leave communities behind. I spent seven years of my life working at **Next Door** doing the hard work of what it means to be local and you cannot tell people from top down what they need because they will tell you thank you but no thank you. I will tell you what I need. And so in a **data center** like that actually spending a lot of time in the community saying number one, we're not going to raise your **electricity bills**. We're going to pay for our **infrastructure** and our **power**. It will not be the **rateayer** that has to pay. Number two, we're going to bring **jobs**, **2500 union jobs**, good jobs like **electricians**, **HVAC**, and so on. We are going to pay our taxes, a **billion dollars** in taxes just for that **data center** into **Michigan**. And on top of that, we're going to invest **$45 million** going into **education** for **codeex credits** to do what you all talked about this weekend is like anyone who's not like coming in filled to their new job. I have teenagers using **Codeex**. It would be like I would never hire a finance person didn't know how to use **Excel**. And I pretty much probably wouldn't hire a finance person today that doesn't know how to use a tool like **Codeex**. Um so that you know so when I think about **investment** we're having to invest ahead of demand. That means we need to both be able to find all of the **compute** and all the pieces and then pay for it. So that goes back to your **capital question** on **IPO**. And then on the other side on the economics, look, the economics do continue to get better. They're getting better on multiple fronts. I think we are doing a better job of actually showing true value to our customers. And I think you get beyond kind of a **cost plus type pricing** into something that feels more akin to the **value being created**. Now, **scarcity of tokens** helps because it's causing a bit of a **compression**. Can you talk about that in just like without specific names where you know the landscape exists today in terms of all the power that's available and all the demand that exists across everybody. Yep.
**主持人**: 考虑到当前**数据中心**的可用性、**token**的可用性以及每个人可用的基础设施，未来一年将会发生什么？因为，你知道，我上周讲了这个故事，但我会用**Anthropic**作为例子，令人沮丧的事情之一是，在某个时候，它就会说“上午10:30，好的，**Jimoth**，下午2:30见。”
Original English **Host**: What's going to happen over the next year just at the current course and speed of what is available of the **data centers** that's available of the **tokens** that's available of the **infrastructure** that's available for everybody because you know I told this story last week but you know I'll use **anthropic** and one of the frustrating things is at some point it just says you know 10:30 it's like all right Jimoth see you at 2:30.
**Sarah Friar**: 是的。
Original English **Sarah Friar**: Yeah.
**主持人**: 那不是一个可行的体验。
Original English **Host**: And that's not a viable experience.
**Sarah Friar**: 对。嗯...
Original English **Sarah Friar**: Right. Um...
**主持人**: 而且公平地说，对于**ChatGPT**，我从来没有遇到过这种情况。
Original English **Host**: And in fairness to **chat GPT** actually I've never had that with...
**Sarah Friar**: 是的。我们在**token**方面非常慷慨，而且再次强调，我们是故意这样做的，我们试图推动**普及**，让人们理解，因为如果你使用的是免费层，你实际上没有得到最新的模型，但我们试图把它交到你手中，让你感受一下。顺便说一下，如果你是个孩子，在做作业，我想起我小时候，**大英百科全书**出现在北爱尔兰一个小小社区的家门口，在**骚乱**之中。就像乌云散去一样，所以我们想确保人们能有那种感觉。顺便说一下，但现在2026年的情况是，如果你想购买更多的**算力**，祝你好运，告诉我哪里能找到，因为我不知道。我的意思是，你知道...
Original English **Sarah Friar**: Yeah. We we're quite generous with our **tokens** and again on purpose we're trying to drive **access** so people understand because if you're on that free tier not actually getting the latest model but we're trying to put it in your hands so you get a sense for it by the way because you know if you're a kid um doing homework like I think about when I grew up and the **encyclopedia bratannicas** showed up at the front door in **Northern Ireland** in a tiny little community in the middle of the troubles. It was like the clouds parted and so we want to make sure that people get that feeling by the way but the landscape right now in 26 if you want to buy more **compute** good luck to you like tell me cuz I don't know where else to find it. I mean as you know...
**主持人**: 我本来想说，讽刺的是**Elon**最终是唯一一个拥有太多算力的人，但你很擅长把那些卖掉。嗯，2027年，坦率地说，它也相当有限。现在谈到**算力**，有几件事正在发生变化。**训练**大部分仍然发生在美国，出于美国政府的原因，确保**国家资产**实际上发生在美国本土。对于**推理**，我们希望它是全球性的。我认为特别是在**Agentic**世界中，你希望有更多的实时性。即使对于像**Sora**和**视频**这样的事情，顺便说一下，是的，我们有，你知道，我们不得不做出一个非常艰难的选择，因为我们没有足够的**算力**，我们说了很多...
Original English **Host**: well I was going to say **Elon** ironically ended up being the one person that had too much **compute** in a way but good job on like figuring out how to sell that off. Um in 27 it's pretty limited as well frankly. Now there's a couple of things shifting around when we talk about **compute**. There's **training** that mostly still all happens here in the **United States** for **USG** reasons for making sure that a national asset and effect is happening on **US soil**. For **inference**, we want that to be global. And I think particularly in an **agentic world**, you want much more kind of **real time**. Even for things like **Sora** and **video**, which by the way, yeah, we have, you know, we had to make a really tough choice because we didn't have enough **compute** and we said a lot...
**Sarah Friar**: ...现在。是的，视频确实需要，但视频还没有结束。特别是在你开始思考**AI**将把我们带向**多模态**的未来时。所以请记住，我们都被上一代技术教导用拇指交流。这是一种疾病。你走在路上，每个人都低头看。他们不再抬头。青少年晚上坐在我的沙发上，用拇指互相交流。我就会说，“你在和谁说话？”我儿子就会说，“他。”我就会说，“好的，说话。”**多模态**已经到来。嗯，希望我想你们这个周末都讨论了。你在和你的工具交谈。我每天都和**Codeex**交谈。所以这正在迅速变化，但这需要更多的实时算力，因为如果我说话，那将是一种奇怪的体验。
Original English **Sarah Friar**: ...right now. Yeah, video does, but video is not over. Like in particular, when you start to think about where **AI** is taking us into more **multimodality**. So remember, we've all been taught by the last generation of technology to talk with our thumbs. It's a disease. You walk around, everyone's looking down. They don't look up anymore. Teenagers sit on my sofa at night and talk to each other with their thumbs. I'm like, who are you talking to? And my son will be like him. I'm like, okay, talk. **Multimodality** is here. Um hopefully I think you all talked about it this weekend. You're talking to your tool. I talk to **codeex** every day. And so that is changing rapidly, but that is going to need much more kind of **real time compute** because it's an odd experience if I was talking to...
### OpenAI的神秘消费级AI设备 **主持人**: **Johnny**，我这些耳塞。那么也许告诉我们一些关于那个问题的事情，如果你现在已经承认了。
Original English **Host**: **Johnny** I of this puck these earpieces. So maybe tell us a little bit about that problem if you've admitted it now.
**Sarah Friar**: 如果我告诉你那是个耳塞，**Johnny**会来偷我的青少年儿子。我可能会把它给他。把它们给...
Original English **Sarah Friar**: If I if I tell you it's an earpiece, **Johnny** will come and steal my teenage son. I might give it to him. give them to...
**主持人**: 但你确实相信应该有一些...
Original English **Host**: but you do believe that there should be some...
**Sarah Friar**: 我们正在转向一种**消费级AI设备**，我不能告诉你它是什么，但在今年年底前，我们会公布它，明年初。我见过它，我试过它，我现在是一个手势说话者，我坐在我的范式上。
Original English **Sarah Friar**: we're changing into a **consumer substrate** that I cannot tell you what it is but by the end of this year we will unveil it early next year I have seen it I've tried it I am a hand talker right now I'm sitting on my paradigm...
**主持人**: ...当你使用它时，感觉就像第一次拿到**iPhone**一样吗？
Original English **Host**: ...shift when when yeah when you used it was it like having an **iPhone** for the first time...
**Sarah Friar**: **Johnny**和团队非常擅长将**人性**带入设备。我真的不知道如何很好地解释，但当你看到它时，你会感受到它。
Original English **Sarah Friar**: it's very what **Johnny** and team are really good at is bringing **humanity** to devices. And I don't really know how to explain that well, but when you see it, you feel it.
**主持人**: 它感觉很自然。
Original English **Host**: It feels natural in some way.
**Sarah Friar**: 它感觉非常自然，但它感觉非常可爱。
Original English **Sarah Friar**: It feels very natural, but it feels very lovable.
**主持人**: 真的吗？
Original English **Host**: Really.
**Sarah Friar**: 我真的无法解释那种情感，因为...
Original English **Sarah Friar**: And I can't really explain what that emotion is cuz...
**主持人**: 在某种程度上很亲密。
Original English **Host**: intimate in some way in terms of...
**Sarah Friar**: **技术**，而不是拿出你的手机，它是无缝的，这是我从玩过它的人那里听到的。
Original English **Sarah Friar**: **technology**, not taking your phone out and it's it's seamless is what I've heard from people that played with it.
**Sarah Friar**: **技术**可以是机械化的，但我们都知道**出色的设计**能让一切消逝，对吗？嗯，那时候，你知道，简单就是困难。
Original English **Sarah Friar**: **Technology** is very um can be very mechanistic, but we all know great **design** just makes everything fade away, right? what um at the time you know the simple is hard.
**主持人**: 是的。
Original English **Host**: Yeah.
**Sarah Friar**: 但我想这是一个非常...这个故事只是回到之前的问题。所以，戴上...
Original English **Sarah Friar**: But I I think this is a very this story just going back to the earlier question. So putting on...
### 资本分配模型与客户价值 **主持人**: ...**CFO的帽子**，帮助我们理解你使用的**资本分配模型**，因为在过去十年、二十年中，很多业务都获得了超额回报，它们找到了一些独特的方式，以比其他任何公司更高的**投资回报率（ROC）**部署资本。然后你会把所有的资本投入到那个**高ROC**的领域。
Original English **Host**: ...the **CFO hat**, help us understand the **capital allocation model** that you use cuz a lot of businesses over the last decade, two decades that have kind of been these outsized returners have found some unique way to deploy capital at a higher **ROC** than anyone else. and then you end up plowing all your capital into that higher **ROC bucket**.
**主持人**: 对你们来说那是什么？你如何看待这种**投资组合方法**，即拥有更多这种高回报的机会，并且是否有某种引擎能让它随着时间的推移变得更好？
Original English **Host**: What is that for you guys? And how do you think about that le that **portfolio approach** to having more of these kind of big returner shots and is there an engine where that gets better over time?
**Sarah Friar**: 必须有，因为最终在这个时代创造的**持久高价值公司**，我认为它们不会是神奇的。它们会像以前时代的伟大公司一样。它们会创造**客户价值**。从客户开始，真正帮助客户做一些不同、更好、带来更多收入、更高效率的事情，对吗？**Thermopisher**希望能够更快地完成**病人筛查**，这样他们就能更快地获得**FDA批准**。这真的很重要。如果你患有一种**癌症**，只剩下几周生命，那么在**四周内**和**两周内**取得突破的差异，可能真的是生与死。他们还有，我可能会引用错误，但大约有**3万到3.8万人**在实地销售那些令人惊叹的产品，如果你走进全国任何一个实验室，你会看到**Thermopisher**的标志贴满了所有设备。那些人希望工作更高效。现在，**Codeex**在**OpenAI**内部最快的采用实际上是在我们的**市场推广团队（GTM）**。我们的开发者在那里，但如果你看看逐月增长的速度，那全都在**GTM**。所以他们希望他们的**GTM团队**能有更高的**生产力**，当然，他们还在**财务**等领域做一些让我非常兴奋的事情。所以，首先是**客户价值**，然后你需要达到**高毛利率**。那么如何达到**高毛利率**呢？你正在关注**收入成本**。主要的投入是**算力**。关于**算力**的好消息是，成本上存在巨大的**通缩曲线**。从**ChatGPT 4**到**GPT-4o**，成本的折旧率达到了**97%**。这简直是一个惊人的曲线。实际上，我是指从**GPT-4**到**GPT-4o**，在短短两年内就达到了**97%**。
Original English **Sarah Friar**: There has to be because in the end the **durable highvalue companies** created in this era, I don't think they're not going to be magical. They're going to look like the great companies of prior eras. They're going to create **customer value**. starts with a customer um and really helps the customer do something different, better, more revenue, more efficiency, right? **Thermmaisher** wants to be able to get um **patient screening** done faster so they get **FDA approval** faster. That's really important. Like if you have a form of **cancer** where you have weeks to live, the difference between a breakthrough in **four weeks** and **two weeks** can literally be **life or death**. They also have, I'm going to misquote this, but something like **30,000 38,000 people** in the field selling those amazing like if you walk into any lab in the country, you'll just see **thermopisher** plastered all over every device. Those people want to be more efficient going to work. Like the the fastest takeoff of **codecs** within **OpenAI** right now is actually in our **go to market team**. Our **devs** are there, but like if you look at the pace of growth kind of month over month, it's all in **GTM**. So they want more **productivity** out of their **GTM team** and of course um they're doing things in areas like **finance** which I get really excited about. So **customer value** first from that now you need to get to great **gross margin**. So how do you get to great **gross margin**? You're looking at like the **cost of revenue**. The main input is **compute**. The good news on **compute** is that there is a massive **deflationary curve** on cost right from **chat GBT 4** uh five to **54** I think the **deprecation of cost** was something like **97%**. It's like kind of an amazing curve. Actually, I'm slightly from **four** to **54**, it was **97%**. But that happened in like two years.
**主持人**: 这有点令人震惊，对吗？
Original English **Host**: That's kind of wowing, right?
**Sarah Friar**: 嗯，即使是我们刚刚发布的最新模型**GPT-4o**，我们现在也在努力将其成本降低回馈给客户。所以，我们实际上把**GPT-4o**的价格提高了两倍。但如果你看看客户的成本，他们可能仍然能获得**20%到30%**的**token成本**降低，因为每个**token**的效率更高了。所以在这个范围内还有很多工作要做，而做出**资本分配决策**的一部分是必须...
Original English **Sarah Friar**: Um, even our newest model, if you look at **55** that we just released, we're trying to now translate that back to the customer. So, we actually raise prices on **552x**. But if you look at what the cost of the customer is, they're probably still getting a break of about **20 to 30% cost reduction per token** because just much more efficient per token. So there's a lot to do in that envelope and and part of making an alloc a **capital allocation decision** is having to...
**Sarah Friar**: ...如果你根据今天的成本状况做出决策，你实际上可能会错误定价结果。所以你必须在成本状况上稍微倾斜。然后当我们考虑建设时，是的，你必须真正专注于**算力**，我今天关注的**算力**是我可以为**28年**及以后购买的。例如，**塞林**的那个**密歇根数据中心**，我认为我们可能要到**27年底**或**28年初**才能从中获得**算力**。所以这就是你开始下赌注的地方。事实上，我现在感到最缺乏**算力**的地方是开始展望**30年、31年、32年**。所以你必须创建一个**商业模式**。嗯，好消息是每年过去，我们对建设的信心就越多。我们看到它大大超出了预期，所以这给了我们越来越多的信心，市场也越来越接近我们。
Original English **Sarah Friar**: ...if you make it on today's cost profile, you actually might mispric the outcome. So you have to lean in a little on the **cost profile**. And then as we think about like the builds, yeah, you are having to make like really my focus today on **compute** is what's the **compute** I can buy for **28** onwards. Like that **Michigan data center** in **Seline**, I don't think we will be getting **compute** out of it until probably **end of 27**, early **28**. So that's where you're starting to make your bets. And in fact, where I feel most short of **compute** right now is starting to look at **30, 31, 32**. So you're having to create a **business model**. Um now the good news is each year goes by we get more confidence in the build. We're seeing it massively outperform and so that's giving us more and more confidence and the market is coming towards us much more.
### 算力需求预测与多维策略 **主持人**: 好的。那么你们如何预测未来多年的**算力需求**，同时考虑到所有正在发生的**架构和模型进步**，即**单位电力**的价值或效用正在上升，并帮助我们理解你们如何估计这一点，考虑到有很多**技术开发**正在进行，其**方差**很高。
Original English **Host**: All right. So how are you making the **compute need forecast** multiple years out accounting for all of the **architectural** and **model advancements** that are happening where call it value or utility per unit of power is going up and help us understand how you kind of estimate that given that there's a lot of **technology development** going on that has a high kind of **variance** to it.
**Sarah Friar**: 是的。是的。所以我们必须在**算力**本身上做出多个假设。所以我们现在假设**算力**实际上在每**千兆瓦**上变得更贵，因为**电力**变得更贵，**内存**变得更贵等等。然而，由于**芯片**方面的折旧，我们在另一方面获得的**智能**足以弥补这一点。所以就出售给客户的每单位而言，它实际上应该会便宜很多。
Original English **Sarah Friar**: Yeah. Yeah. So we we do have to make multiple um assumptions both on the **compute** itself. So we assume right now that **compute** actually on a per **gigawatt** is getting more expensive because **power** is getting more expensive, **memory** is getting more expensive and so on. However, the the **intelligence** that we get on the other side out because of the **deprecation** on the **chip side** is is more than making up for that. So in in terms of a per unit sold to a customer, it should actually get a lot less expensive for...
**主持人**: ...没有**模型改进**。那只是...
Original English **Host**: ...no **model improvement** in that. That's just...
**Sarah Friar**: 完全正确，那只是**芯片**本身。我们不会试图过高估计**模型**方面，因为有时像**GPT-4o**在效率方面是一个非常好的模型，但如果你看看像**GPT-4**这样的前一个模型，它是一个非常大的**预训练模型**。它非常昂贵。它实际上很难提供服务。有时我们想做那个非常大的**预训练时刻**，然后我们进行多次**模型迭代**，以便在成本方面降低。我的意思是，在短期内，比如2026年和2027年，我显然会建立一个自下而上的模型。所以我知道我的产品是什么。我对定价有一个概念。你知道**P乘以Q**。我认为我有多少“哇”的时刻？我可以看到这条线的形状。其中有多少人会订阅？**广告**的到来也仍然与每周活跃用户数量、每日活跃用户数量、消息数量等等有关。所以你可以在2026年和2027年做得相当好的**模型**工作。尽管如此，这条线的形状总是给我们带来惊喜，超出了我们的预期。当你进入更远的年份时，你实际上更多地关注你购买的**算力**，几乎只是反向算法，也就是说，这个数量的**算力**应该大致等同于这个数量的**收入**。我不能确定它将全部来自哪里。就像一年前，我为投资者建立了一个模型，展示了**Agentic收入**。故事是，我们将拥有这个东西。我们将进入**Agentic时代**。我们将把它交给一个用**自然语言**开发的开发者。他们将能够构建，我们认为他们每月可能支付高达**2000美元**，这事后看来有点可笑，但没有人相信。他们会说，我甚至不知道她在说什么。这不可能发生。**每月2000美元**，还记得人们对**ChatGPT Pro**每月**200美元**而抓狂吗？哦，天哪，没有人会为那个付费。
Original English **Sarah Friar**: exactly that's just the **chip** itself. We don't try to overestimate on the **model** side because sometimes like **55** is an incredibly good model on the **efficiency side**, but if you look at something like **54**, the prior **model**, it was a really large **pre-trained model**. It was very expensive. It was actually hard to serve. And sometimes we want to do that really big **pre-train moment** and then we take multiple **model turns** to be able to kind of drive down on the cost side. I mean in the in the near term like in **26** and **27** I clearly build a **model** that's **bottoms up**. So I know what my products are. I have a sense of what the pricing will be. Um you know **P time**, you know, consumer **P*Q**. How many Wows do I think I have? I can see what the shape of the line is. How many of them will subscribe **advertising** coming in is also still related to how many weekly activives, how many dailies, how many messages and so on. So you can you can do actually a pretty good **model** job in **26** and **27**. That said, the shape of the line keeps taking us by surprise to the upside. When you get into the outer years, you're actually looking more at the **compute** you've bought and almost just doing an algorithm the other way that's saying this amount of **compute** should equate somewhat to this amount of **revenue**. I don't know for certain exactly where it will all come from. Like a year ago, I built a **model** for investors that showed **agentic revenue**. And the story was, we're going to have this thing. We're going to be in the **agent era**. We're going to hand it to a developer with **natural language**. They're going to be able to build and we think they will pay upwards of maybe **$2,000** a month for it, which is kind of laughable in hindsight, but nobody believed. Um, they were like, I don't even know what she's talking about. There's no way that will happen. And **$2,000** a month, remember when people were losing their minds over **Chat GBT Pro** being at **$200**? Oh my god, no one will ever pay for that.
**主持人**: 是的。
Original English **Host**: Yeah.
**主持人**: 那么为什么是**1220亿美元**呢？这能让你撑到2031年、2032年吗？你如何计算**资本需求**呢？
Original English **Host**: So why **122 billion**? Does it take you to **2031, 2032**? Like how do you get the calculus on the **capital needs** as you do that modeling?
**主持人**: 你甚至可以更具体一点。我看到的估计是，要建立**1千兆瓦的AI算力**，需要大约**500亿美元**的资本支出，包括土地、电力、芯片，所有加起来大约**500亿美元**。当你创建一个新的**数据中心**时，你是否需要预付所有这些资金？你承担了多少？你能获得多少**债务**？**1000亿美元**的融资只能让你获得**2千兆瓦**还是**5千兆瓦**？它能让你获得什么？
Original English **Host**: You maybe even more specific. So the estimates I've seen is that to stand up **1 gigawatt of AI compute** costs about **$50 billion** in **cap land**, **PowerShell chips**, everything all in around **50 billion**. Do you have to front all of that money when you create a new **data center** or how much of it do you do? How much of it can you get debt for? Does a **100red billion** raise only get you **two gigawatts** or does it get you five? Like what does it get you?
**Sarah Friar**: 这是一个很好的问题。所以如果你看看我们的**算力策略**，世界变化的速度真是疯狂。所以就在两年前，我们实际上只有一家**云服务提供商（CSP）**，我们与**微软Azure**合作，我们只使用一种**芯片**，**英伟达**，我们只有一款产品，**ChatGPT**，一个价位，每月**20美元**。所以我经常用**魔方**来比喻。所以我们当时就像底部的**一个魔方**。今天，如果你看看我们的策略，首先是转向**多CSP**，因为**CSP**对我们来说，实际上是将**资本支出（capex）**转化为**运营支出（opex）**，所以你随着收入的增长而支付，就像你实际利用**数据中心**一样。所以实际上，我们有点依赖他们建设和拥有**资本支出**和**融资**的能力。所以今天，我们位于所有**CSP**之上，**Oracle**，**Coreweave**，**微软GCP**，**AWS**以及许多小型**新玩家**。在**芯片**方面。我们还实施了一个**多芯片计划**，因为我们想确保你始终处于前沿。我认为如果你只依赖一种**芯片**，就必然会有一个时刻你无法处于前沿，因为会发生一些**跳跃式发展**。所以今天，**英伟达**仍然是我们的绝对优先合作伙伴。他们拥有**Frontier芯片**。我们下一次大规模的**训练**将在秋季使用**Ver Rubin**进行。我们对此非常兴奋。现在我们正在规划即将到来的**Fineman系列**。但我们现在也有**AMD**提供的**芯片**。**Cerebrris**已经在线了。它是一款令人难以置信的**低延迟芯片**。例如，对于需要**实时编码**的开发者来说非常棒。还有我们正在与**Broadcom**合作开发的**自己的芯片**。除此之外，我们还有其他多样化的方式。所以现在，想想那个**魔方**。它已经变得更加**多维度**了。它允许我们有效地利用**投资级CSP**，以便能够快速发展，并将其推回到更多的**运营支出**，而不是**资本支出**。现在，我们正在开始转向一种更像**定制建造**的环境。我们宣布正在与**软银能源**在德克萨斯州建设一个**数据中心**。这只是超越**CSP**的开端。这需要更多的**资本支出**。最后，我认为随着世界的发展，请记住我们仅仅在两年内就完成了所有这些。我喜欢用**魔方**来比喻的原因是，再次，请**ChatGPT**来解释，但我认为**魔方**大约有**一万亿亿**种不同的形态。所以它给了我们很多**选择性**。所以请记住我之前说的，我的工作是最大化**选择性**，而在我还没有成为一个**投资级实体**，可以获得更低成本的**债务融资**的时刻，能够与合作伙伴合作做到这一点非常重要。
Original English **Sarah Friar**: It's it's a great question. So if you look at our **compute strategy** um and it's crazy how fast the world has changed. So just two years ago we were literally one we had one **CSP** we worked with **Microsoft Azure** um we we sat on one **chip Nvidia** we had one product **chat GBT** one price point **$20** a month so I often use a **Rubik's cube** as kind of my metaphor so we were like one cube in the bottom today if you look at our **strategy** it's been to go first of all multi multiple **CSPs** because what **CSPs** do for us in effect is they shift **capex** into **opex** so you pay as you get the revenue so as you're actually utilizing the **data centers**. So in effect we are writing somewhat on their ability to build and have **capex** and um **financing**. So today we sit on top of every **CSP Oracle** um **coreweave** um **Microsoft GCP AWS** and a bunch of small **neocalars** on the **chip side**. We've also um gone for a program of being **multi-chip** um because we want to make sure you're always on the frontier. I think if you're only on one **chip**, there's just inherently a moment where you can't be on the frontier because there's some **leaprogging** that happens. So today, **Nvidia** remains our absolute priority partner. They have the **Frontier chip**. Our next big **trading run** in the fall will be done on **Ver Rubin**. We're really excited about that. And now we're plotting kind of the **Fineman series** that's coming. But we also now have **chips** in the pipeline from **AMD**. Um **Cerebrris** is already online. It's been an incredible **low latency chip**. Great for **devs**, for example, that want **real-time coding**. And there's our **own chip** that we're working on with **Broadcom**. And then beyond that, there's other ways we've diversified. So now, think about that **Rubik cube**. It's become much more **multi-dimensional**. And it allows us to effectively utilize **investment grade CSPs** in order to be able to go fast and push it back to be more **opex**, not **capex**. Now, we are starting to shift gears into more of a **built to suit type environment**. We announced a **data center** we're building with **SoftBank Energy** um down in **Texas**. That's the beginning of something that's beyond a **CSP**. There's a little bit more **capex** required there. And then finally, I think as the world progresses, remember we've done all that just in **two years**. The reason I like a **Rubik's cube** is again, please **chat GBT** this, but I think a **Rubik's cube** has something like a **quintilion** different um forms it can come up with. And so it just gives us a lot of **optionality**. So remember what I said, my job is maximum **optionality** and in a moment where I'm not yet an **investment grade type of entity** where I can go get lowerc cost **debt financing**, being able to work with partners to do that is really important.
### AI生态系统融合与广告策略 **主持人**: 那么你认为在五年后，整个堆栈会融合在一起吗？我指的是什么？在传统或历史市场中，**英伟达**只销售**芯片**，但他们只做这些。然后，你知道，**微软**只运营**云**。他们只做这些。然后你会有一个**消费应用**。你也只做这些。但现在我们看到每个人都在做所有事情。你知道，你们有自己的**芯片**。你们有自己制造的**模型**。你们可能会或可能不会最终决定需要成为某种**新云**。如果你看看**英伟达**，他们有令人难以置信的**芯片**，但他们也有自己的**开源模型**。他们正越来越多地成为一个**承购方**。**Google**首先是一家**云公司**，但他们也有**芯片**。现在他们有**模型**。所以一切都在融合。如果这种情况继续发生，这会使**竞争格局**变得更简单还是更容易？
Original English **Host**: So do you think that in **5 years** from now the stack is just merged together? What do I mean? In traditional or historical markets, you'd have **Nvidia** sell the **chips**, but that's all they do. And then you'd have, you know, **Microsoft** just run a **cloud**. That's all they would do. And then you would have a **consumer app**. That's all you would do. But now we see everybody doing everything. You know, you guys have **silicon** that you're spinning. You have **models** that you make. You may or may not eventually decide that you need to be some form of a **NeoCloud** yourself. If you look at **Nvidia**, they have incredible **silicon**, but they also have their own **open source models**. They're increasingly becoming an **offtaker**. **Google** is a **cloud company** first, but they also have a **chip**. Now they have **models**. So it's all merging. is if that continues to happen, does that make the **competitive landscape** simpler or easier?
**Sarah Friar**: 我的意思是，我认为每个人都在努力确保他们所处的位置是离客户最近的那一层，通常你会从生态系统中获得最大一部分利润，对吗？没有人愿意发现自己被排除在外。绝对是这样。所以这就是为什么今天当我思考我们的定位时，又回到了我最初说过的，为什么我们想成为**AI智能层**，因为一年前人们还在谈论**LLM的商品化**。嗯，坦率地说，情况恰恰相反，因为当你开始构建一个**Agentic层**时，我们都开始使用“**harness**”这个词，但**harness**带来了**上下文**和**记忆**，对吗？我在我的**Codeex**里有一个巨大的**记忆文件**，它知道我是谁，它知道我是**OpenAI的CFO**，它知道我喜欢如何写作，我喜欢如何表达，它知道我感兴趣什么，它实际上也知道我是一个有青少年孩子的妈妈。我的意思是，它携带着所有这些**记忆**，这使得**模型**对我来说更加强大。现在想想看，当这种**记忆**和**上下文**被带入一个实际的企业环境中时会发生什么。所以现在不仅仅是关于驻留在那里**数据**，但我总是想到那种直觉，就像我以前在**华尔街**工作时一样，对吗？世界上所有的**数据**都告诉你一家股票在**财报电话会议**后应该怎么走。但请给我一秒钟。然后你打电话给你的交易员，交易员会说，“是的，股票不会上涨，**Sarah**。”我就会说，“你在说什么？所有数字都显示它做了这个，它做了那个。”他说，“是的，我知道，但我也知道这个基金面临压力，他们需要卖出他们的股票，这将在下周扼杀这只股票。”对吗？那就是**企业**的**直觉**。就像我总是想到的最好的例子，因为我来自**金融界**，但在生活的各个领域都有这种**直觉**。这就是我认为**模型**现在与你公司的**记忆**、**上下文**和**直觉**紧密相连的地方。这就是让**CEO**和**高管**们真正兴奋的地方，因为他们会觉得，“好的，我现在真的看到了这如何能为我的收入线、我的营收线增加价值，而且你知道，我也可以把它看作是一个**效率提升**。”所以回到你问的，我认为人们想要确保的是，他们尽可能地接近那种价值。
Original English **Sarah Friar**: I mean, I think where everyone is trying to make sure they reside is the layer that is closest to the customer where usually you take the the largest portion of the profits of the ecosystem, right? No one wants to find themselves away. Absolutely. And so that's why today when I think about our position and comes back to where I started why we want to be that **AI intelligence layer** is because a year ago people talked about the **commoditization of the LLMs**. Um and frankly it's gone the opposite because as you start building an **agentic layer** and we've all started to use this word **harness** but the **harness** is what brings the **context** the **memory** right it I I have in my **codeex** I have a whole ginormous **memory file** where it knows that I'm me it knows I'm the **CFO of openai** it knows how I like to write things how I like to say things it knows what I'm interested in it actually also knows that I'm a mom teenagers I mean it just carries all this **memory** and that makes the **model** more powerful for me. Now think about what happens when that **memory** in that **context** is brought into an actual **enterprise environment**. So now it's not just even about the **data** that resides there, but I always think about the the **intuition** of like back when I worked on **Wall Street**, right? There was all the **data** in the world that told you what a stock should do post an **earnings call**. But give me one second. Then you called your trader and the trader be like, "Yeah, stock's not going up, Sarah." And I'm like, "What are you talking about? Like all the numbers say it did this, it did this, it did this." He's like, "Yeah, I know, but I know this fund is under pressure and they need to sell down their book and that is going to kill the stock for the next week." Right? That is the **intuition** of an **enterprise**. Like it's the best example I always think of because I came out of a **financing world**, but there's this **intuition** in every walk of life. And that's where I think the **models** are now getting very connected to the **memory** and **context** and **intuition** of your company. And that's what gets **CEOs** and **seuite** really excited because they're like okay now I really see how this is going to add value to drive my **revenue line** my **top line** but also you know I can think about as an **efficiency play** as well. And so back to what you're asking, I think what people want to make sure is they stay as close to that value as possible.
**主持人**: ...并且足够灵活，以便在你需要时进行调整。
Original English **Host**: ...and be flexible enough to pivot as you have to rap.
**Sarah Friar**: 是的。
Original English **Sarah Friar**: Yeah.
**主持人**: 但是...
Original English **Host**: But...
**Sarah Friar**: 对不起，**Jason**。
Original English **Sarah Friar**: sorry Jason,
**Jason**: 完全没关系。嗯，非常棒，你提供了很多细节。最后一个细节问题。快问快答。我们一生中三家最伟大的消费企业。**iPhone**，**Meta广告网络**和**Google的广告网络**。这三家中有两家是基于广告的，甚至**苹果**也有少量的广告。
Original English **Jason**: it's quite all right. Um it's been wonderful and and you've been so great with the details. One final detail question. Rapid fire. Three great greatest consumer businesses of our lifetime. **iPhone**, **Meta Advertising Network**, and **Google's advertising network**. Two of those three are **ad based** and and even **Apple** has a sprinkling of ads.
**Jason**: 我没怎么听你谈论**广告**。人们告诉我他们在免费版本的实验中看到了一些广告。你对**广告版本**的承诺是什么？你们在**超级碗**期间被**Anthropic**稍微嘲笑了？哦，你们将会有**广告**。但**广告**是让全世界免费使用的解决方案吗？
Original English **Jason**: Haven't heard you talk about **ads** much. People tell me they're seeing some **ads** in the experiment in the free version. What is your commitment to the **ad version**? You guys got a little uh trolled by **Anthropic** during the **Super Bowl**? Oh, you're going to have **ads**. But is **ads** the solution to making this free for the world?
**Sarah Friar**: 是的。所以，首先在**广告**方面，你知道，我们希望坚持我们的原则。我们希望确保你总是得到基于**模型**的最佳结果，而不是由赞助商提供。所以这一点必须保持真实。我认为第二点是，我们总是会为那些不想看到**广告**的人提供一个免费层，或者抱歉，一个**无广告层**。但话虽如此，如果你听了**Fiji**说得很好的一句话，如果你知道**Google**和**Meta**生了一个孩子，那将是**ChatGPT**，因为你拥有**Google搜索**的优势，顺便说一下，我们知道我们至少拥有**11%的搜索市场**。实际上更多，因为当你进行一次**Google搜索**时，页面刷新算作一次，而在**ChatGPT**中，当你进行一整个对话，你可能会问50个问题，那也只算作一次。所以实际上，我们拥有更高的份额，非常高的意图。这对广告商来说是好事，因为我实际上是在告诉你我在做什么，对吗？我想要非常酷的鞋子坐在舞台上。我正在告诉你我想去买什么。在**Meta**的案例中，他们使用“像你这样的人”这种意图。所以他们拥有**人口统计数据**。我们拥有更多，因为我们拥有**记忆**，对吗？我刚刚告诉你它知道我是谁。所以想象一下将**记忆**和**上下文**与**意图**结合起来。你将拥有一个非常强大的**广告平台**，这将使你能够向广大世界提供大规模的访问权限，因为现在你可以为此付费。我想回到你问**Freeberg**的一个问题，如果你看看现在的**每个token的收入**。如果我只为了今天而优化，我会把每个**token**都给**API**。
Original English **Sarah Friar**: Yeah. So, first of all, on the **ad front**, you know, we we want to stick by our **principles**. We want to make sure that you know you're always getting the best result based on the **model**, not by something that was **sponsored**. So that has to hold true. And I think the second thing is that we'll always provide a free a tier, sorry, an **ad free tier** for people that just don't want **ads**. But with that said, if you took if you took **Fiji** says this really well, if you know **Google** and **Meta** had a baby, it would be **chat GPT** because what you have in **Google search** and by the way we know we have at least **11% of the search market**. It's a lot more because actually when you do a **Google search** and the page refreshes that counts as one in **chat GBT** when you do a whole conversation where you might ask **50 questions** that also only counts as one. So in reality, we have a much higher portion, very high **intent**. That is great for **advertisers** because I'm effectively telling you what I'm doing, right? I want really cool shoes to sit on the stage. I'm telling you what I want to go by. In **Meta's case**, right, they use this like people like you sort of **intent**. So they have the **demographic**. We have more than that because we have **memory**, right? I just told you it knows who I am. So imagine putting **memory** and **context** next to **intent**. You should have a very potent **ad platform** which gives you an ability to offer up massive **access** to the world writ large because now you can pay for it. And I think back to a question you asked **Freeberg** like if you look at um the **revenue per token** right now. If I was optimizing only for today, I would give every **token** to the **API**.
**主持人**: 对吗？
Original English **Host**: right?
**Sarah Friar**: 每个**token**给**API**的收入，比给**消费者**的收入高一个数量级。然而，我告诉过你，我们正在玩自己的游戏。我们有一个策略，我们相信存在一个**AI基础设施层**，就像**电力**这样的公共事业，在未来的某个状态下，你将能够为广大世界、消费者、小型企业、大型企业、政府提供服务。这就是我们的策略。
Original English **Sarah Friar**: Every **token** to the **API** order of magnitude more than to the consumer. However, I told you we're playing our own game. We have a **strategy** where we believe there's an **AI infrastructure layer**, a **utility** like **electricity**, and in a future state, you'll want to be able to serve the world at large, consumers, small businesses, large enterprises, governments. That's our **strategy**.
**主持人**: 各位女士先生，OpenAI的CFO，**Sarah Friar**。干得好。太棒了。
Original English **Host**: Ladies and gentlemen, the CFO of **Open AI**, **Sarah Frier**. Well done. Fabulous.