Inside the Trillion-Dollar AI Buildout | Dylan Patel Interview

章节 1：资本迷局——OpenAI、Oracle与Nvidia的三角交易

📝 本节摘要：

本章揭开了围绕 OpenAI、Nvidia（英伟达）与 Oracle（甲骨文）之间复杂交易的迷雾。Dylan Patel 指出，这并非外界误传的“无限金钱漏洞”，而是 OpenAI 为应对万亿级算力竞赛所设计的生存策略。由于缺乏科技巨头（如 Google、Meta）那样的巨额现金流与资产负债表，OpenAI 必须寻找盟友（如 Oracle）来预付昂贵的基础设施资本支出（Capex）。同时，Nvidia 通过回购股权等方式参与其中，确保存储芯片的高价预售。这是一场关于现金流、算力储备与未来赌注的高风险博弈。

[原文] [Host]: i was going to lay out this idea of going through the past present and future of compute as like the big big idea for our conversation but since it just happened I don't think you've heard you talk about it anywhere i'd love to start by asking about this whole OpenAI Nvidia thing which uh sounds exciting seems vague not really sure what's going on and maybe you could explain it to us as you see it and what the strategic implications are of the big announcement

[译文] [Host]: 我原本打算以梳理计算（compute）的过去、现在和未来作为我们对话的宏大主旨，但既然这件事刚刚发生，而且我还没听你在其他地方谈论过，我想先问问关于 OpenAI 和 Nvidia 的整件事情。这件事听起来很激动人心，但似乎又很模糊，我不确定到底发生了什么。也许你可以向我们解释一下你眼中的情况，以及这一重大声明的战略含义是什么。

[原文] [Dylan Patel]: all right so I think it's I think it's very very simple right you've got OpenAI paying Oracle lots of money you've got Oracle paying Nvidia lots of money you've got Nvidia paying open lots of money meme we've got we've got the infinite money glitch here

[译文] [Dylan Patel]: 好的，所以我认为这非常非常简单，对吧。你有 OpenAI 支付给 Oracle 大笔资金，你有 Oracle 支付给 Nvidia 大笔资金，你有 Nvidia 支付给 OpenAI 大笔资金。这就成了一个梗，好像我们这里有个“无限金钱漏洞”（infinite money glitch）。

[原文] [Dylan Patel]: uh no no no i that's not actually what's happening right what's really happening is open air has an insatiable demand for compute um the compute precedes the buildup of business you have to have the cluster before you can rent it out for inference right or rather run models on it for inference you have to have the cluster to train the model that's good enough that it unlocks new use cases which then can be adopted and there's an adoption curve there for any new use case so you have to have all these things like sequenced

[译文] [Dylan Patel]: 呃，不不不，实际上并不是那样。真正发生的是 OpenAI 对算力有着无法满足的需求。算力的储备先于业务的建立。你必须先拥有集群，然后才能将其租出去进行推理（inference），或者说在其上运行模型进行推理。你必须拥有集群来训练足够好的模型，从而解锁新的用例，这些用例随后才能被采用。任何新用例都有一个采用曲线，所以你必须按顺序准备好所有这些东西。

[原文] [Dylan Patel]: given this is a game of the richest people in the world or rather the biggest tech giants in the world right it's Zuck it's Google you know Larry and Sergey or Sergey is like constantly in the business now again right it's all the biggest people in the world it's Elon right there's there's very much a risk of OpenAI being too small to matter right you know which is crazy to say because they've got 800 million users but like where's the revenue where's the compute they could easily get swamped in terms of having of of how much compute they have yeah if they don't move fast enough and if they don't have the most compute or like among the most compute they will get beaten

[译文] [Dylan Patel]: 考虑到这是一场世界上最富有的人——或者说世界上最大的科技巨头——的游戏，对吧，有扎克伯格（Zuck），有 Google——你知道 Larry 和 Sergey，Sergey 现在又经常参与业务了，对吧。这全是世界上最有权势的人，还有 Elon。OpenAI 很有可能因为体量太小而无关紧要，对吧。这么说很疯狂，因为他们有 8 亿用户，但是收入在哪里？算力在哪里？如果他们行动不够快，或者如果不拥有最多——或者哪怕是名列前茅——的算力，他们很容易在算力规模上被淹没并被击败。

[原文] [Dylan Patel]: the magic of OpenAI was that they just spent way more compute on a single model run on GP3 and four and they had the foresight and the vision and the execution yeah but they made that bet and they were able to secure it and at the time it was like meh right it was a few hundred million whatever right you know that's a ton of money but like now it's sort of like well Mark Zuckerberg sees how much compute he's going to have to get even though he has this insane cash flow that he's like "Oh wait i need to go sign a deal with Apollo for you know $30 billion on this data center right in Louisiana this mega data center I'm going to build." It's like "Wait why didn't you just fund this with cash flows you have so much cash flow." It's like "Because my plans that's just the physical data center now what am I going to put in it?" Is like so much money the amount of capital that people are going to have and are dumping into this is is insane right

[译文] [Dylan Patel]: OpenAI 的魔力在于他们在 GPT-3 和 GPT-4 的单个模型运行上投入了比别人多得多的算力，而且他们有远见、愿景和执行力。是的，他们下了那个赌注并且成功了。在当时，这看起来没什么大不了的，对吧，也就几亿美元什么的。虽然那也是一大笔钱，但现在的情况是，哪怕像马克·扎克伯格这样拥有疯狂现金流的人，在看到需要多少算力时也会想：“哦，等等，我需要去和阿波罗（Apollo）签个协议，搞个 300 亿美元来建路易斯安那州的这个大型数据中心。”你会问：“等等，你为什么不直接用现金流资助这个？你有那么多现金流。”回答是：“因为我的计划里那还仅仅是物理数据中心，我还得往里面填设备呢？”这就需要更多的钱。人们拥有并正在投入其中的资本数额是疯狂的。

[原文] [Dylan Patel]: google was slow to wake up and then you know they were slow to pivot their data center operations they were slow to do everything and so there while they could have way more compute than anyone by a humongous degree they haven't been able to deploy as fast so so open is like still been on the curve of and then they have like you know how much they allocate to search and you know generative search is not really necessarily competing with open AI right it's it's the mega models so if you have this like tremendous vision of what's going to happen with AI you know that it takes a ton of compute to build them you know pretty much the amount of compute you could dedicate to these models is limitless and they will get better

[译文] [Dylan Patel]: Google 醒悟得很慢，然后你也知道，他们在调整数据中心运营方面也很慢，做所有事情都很慢。所以，尽管他们本可以拥有比任何人多得多的算力，但他们没能部署得那么快。所以 OpenAI 仍然处在（领先的）曲线上。而且 Google 还要分配资源给搜索，你知道生成式搜索并不一定是在与 OpenAI 竞争，真正的战场是巨型模型（mega models）。如果你对 AI 的未来有宏大的愿景，你就知道构建它们需要大量的算力，你也知道你可以投入到这些模型中的算力几乎是无限的，而且模型会变得更好。

[原文] [Dylan Patel]: now it's a log log scale right i.e you need 10x more compute to get to the next tier of performance you might think of it as diminishing returns but what if the next tier of performance is like you know you know a six-year-old versus a 16-year-old like child labor is like quite like effective versus a six-year-old you can't get to do much right you know and this is not exactly the way to think of AI but this is the conundrum that OpenAI is in right um they have to get more compute than anyone or at least among there they have to race with the giants these giants are trillion dollar businesses so how does OpenAI get there well it's it's partnering with Microsoft well that soured some right um it's partnering with Oracle well Oracle can can do a lot but Oracle doesn't even have a balance sheet like like Google and Microsoft and and Amazon and you know etc right

[译文] [Dylan Patel]: 现在这是一个双对数（log-log）比例，也就是说你需要 10 倍的算力才能达到下一个性能层级。你可能会认为这是收益递减，但如果下一个性能层级的差距就像是——你知道——一个 6 岁孩子和一个 16 岁少年的差距呢？比如童工虽然……相对于 6 岁孩子你干不了什么活，对吧。这不完全是思考 AI 的方式，但这就是 OpenAI 面临的难题。他们必须获得比任何人都多的算力，或者至少要在前列，他们必须与巨头赛跑。这些巨头都是万亿美元级别的企业。那么 OpenAI 如何达到目标呢？通过与微软合作，但这关系有点变味了，对吧。通过与 Oracle 合作，Oracle 能做很多，但 Oracle 甚至没有像 Google、微软和亚马逊那样的资产负债表。

[原文] [Dylan Patel]: oracle can be part of it but it's OpenAI needs allies right they need they need people to effectively spend the the capex ahead of the curve and trust that they'll be able to pay the rental income because that's what it is at the end of the day openai is committing to fiveyear deals these five-year deals cost X amount of money it's 10 to 15 billion dollars per gigawatt of data center capacity that you pay a year and then that 10 to 15 billion dollars of gig for a gigawatt of data center capacity you're paying that for five years okay that's 50 to 75 billion of of cash that goes out the door to OpenAI for one gigawatt of capacity

[译文] [Dylan Patel]: Oracle 可以成为其中的一部分，但 OpenAI 需要盟友，对吧。他们需要有人能有效地在曲线之前花费资本支出（Capex），并相信 OpenAI 能够支付租金收入，因为这归根结底就是租赁。OpenAI 正在承诺签署五年期的协议。这些五年期协议花费数额巨大。每吉瓦（gigawatt）数据中心容量每年的费用是 100 到 150 亿美元。然后这一吉瓦的数据中心容量你要付五年。好吧，这就意味着为了获得一吉瓦的容量，OpenAI 要支付 500 到 750 亿美元的现金。

[原文] [Dylan Patel]: and you talk about what Sam's saying is like hey I need I need 10 gigawatts i need more than 10 gigawatts right then you end up with this like really challenging aspect of like how do you pay for that and hey that's only the rental price if I were to actually do the capex it's or if I were to like you know because it's frontloaded right it it becomes who is the balance sheet for this that's the reason these deals are coming about and so Oracle is making a massive bet right Larry you know hey he's getting good margin off of it but he's making a massive bet that this capex that he's going to pay for OpenAI will actually be paid cuz you know he signed a $300 billion deal with OpenAI it's like where's that going to come from yeah is like you you your revenue is like 15 billion ARR this month maybe right on a run rate basis it'll get to 20 by the end of the year uh pretty pretty clearly maybe it's like 16 now but how do you pay $300 billion of revenue

[译文] [Dylan Patel]: 而你谈到 Sam（OpenAI CEO）所说的是：“嘿，我需要 10 吉瓦，我需要超过 10 吉瓦。”那么你就会面临一个非常具有挑战性的方面：你如何支付这笔钱？而且嘿，这还只是租赁价格。如果我要实际承担资本支出（Capex），或者因为它是前置投入的，这就变成了“谁来提供资产负债表”的问题。这就是这些交易产生的原因。所以 Oracle 正在下一个巨大的赌注，对吧。Larry（Oracle 创始人），嘿，他从中获得了不错的利润率，但他正在下一个巨大的赌注，赌他为 OpenAI 支付的这笔资本支出实际上能得到偿还。因为你知道，他与 OpenAI 签署了一项 3000 亿美元的协议。这就好像，这笔钱从哪儿来？你们现在的年化收入（ARR）可能也就是 150 亿美元，也许到年底能达到 200 亿，现在可能大概是 160 亿，但你如何支付 3000 亿美元的账单？

[原文] [Dylan Patel]: Nvidia's kind of got the same conundrum right it's like well Google and Amazon are doing these these deals whether it's uh to two other vendors for TPUs or for tranium whether it's anthropic or others they're trying to court openai uh they're trying to court other companies how do I get into this game right okay fine I can rely on Microsoft somewhat I can rely on Oracle somewhat but at the end of the day GPUs if I want GPUs to be king part of it is just like my chip is the best but part of it is also who's going to pay the capex upfront

[译文] [Dylan Patel]: Nvidia 也有同样的难题，对吧。就像是，Google 和亚马逊正在做这些交易，无论是为了 TPU 还是 Trainium 芯片与其他供应商合作，无论对象是 Anthropic 还是其他人。他们在试图拉拢 OpenAI，试图拉拢其他公司。我（Nvidia）如何进入这个游戏？好吧，我可以某种程度上依赖微软，某种程度上依赖 Oracle。但在一天结束时，如果我想让 GPU 成为王者，部分原因是因为我的芯片是最好的，但部分原因也在于谁来预付资本支出（Capex）。

[原文] [Dylan Patel]: Google and Amazon will pay the capex up front if it's for TPUs or right they won't pay the capex up front necessarily for that same capacity of GPUs so you've got this like challenging aspect and so that's where this this Nvidia and open I deal comes from

[译文] [Dylan Patel]: 如果是为了 TPU，Google 和亚马逊会预付资本支出，但如果是为了同样容量的 GPU，他们就不一定会预付资本支出。所以你面临着这样一个挑战，而这就是 Nvidia 和 OpenAI 这笔交易的由来。

[原文] [Dylan Patel]: sort of this draws back to the OpenAI Nvidia deal because I think most people in the market don't quite get it right they're like "Oh this is just like round tripping." It is to some extent right if OpenAI builds a gigawatt of capac they they they agreed 10 gawatts of capacity Nvidia will do hundred billion dollars of equity investment into OpenAI in the form of cash right and and and Nvidia gets returned capital the first chunk of the deal in the press release is one gawatt $10 billion right so pretty straight line but 10 g one a g one gigawatt to build as we established earlier is like $50 billion so Nvidia is paying 10 billion open still has to come up with other 40 somehow

[译文] [Dylan Patel]: 这又回到了 OpenAI 和 Nvidia 的交易上，因为我认为市场上大多数人并没有完全理解它，对吧。他们会说：“哦，这就像是‘循环交易’（round tripping）。”在某种程度上确实是，对吧。如果 OpenAI 建设 1 吉瓦的容量——他们同意了 10 吉瓦的容量——Nvidia 将以现金形式向 OpenAI 进行 1000 亿美元的股权投资，对吧，然后 Nvidia 会收回资本。新闻稿中交易的第一部分是 1 吉瓦对应 100 亿美元，非常直接。但我们要建立 1 吉瓦——正如我们之前确定的——大约需要 500 亿美元。所以 Nvidia 支付了 100 亿，OpenAI 仍然必须想办法凑齐剩下的 400 亿。

[原文] [Dylan Patel]: the nice thing for Nvidia is they sell you of that 50 billion they capture maybe 35 billion of that is capex that goes directly to Nvidia so year zero openai its partner spends $50 billion on the data center the timing is not exactly that they spend $50 billion on the data center 35 goes it to Nvidia nvidia's gross margin is 75% you know again I'm going to make it simple numbers let's say it's 10 and 40 because 10 billion COGS 40 billion revenue $30 billion of gross profit um if we fix the numbers it's effectively like half their gross profit from that deal is going directly to uh to open in the form of an equity investment the 25% that's COGS is staying uh on in you know Nvidia is paying for that and then they keep the other half of the gross profit on their balance sheet or do buybacks whatever they want to do with it

[译文] [Dylan Patel]: 对 Nvidia 来说，好消息是他们把东西卖给你，在那 500 亿中，他们可能获得了 350 亿，这是直接流向 Nvidia 的资本支出。所以在第零年，OpenAI 的合作伙伴在数据中心上花费 500 亿美元——时间点不完全是那样——他们花费 500 亿美元，其中 350 亿流向了 Nvidia。Nvidia 的毛利率是 75%。再次为了简化数字，假设是 100 亿和 400 亿，即 100 亿是销售成本（COGS），400 亿是收入，那就是 300 亿的毛利润。如果我们修正数字，实际上就像是这笔交易的一半毛利润以股权投资的形式直接流向了 OpenAI。那 25% 的销售成本（COGS）留在了……你知道 Nvidia 支付了这部分成本，然后他们将另一半毛利润保留在资产负债表上，或者进行回购，或者做任何他们想做的事。

[原文] [Dylan Patel]: so Nvidia is not necessarily like they are like roundtpping some of this um but open what effectively is happening is openi gets the opportunity to pay for a big chunk of it in equity y and nvidia's lowering their prices without lowering their prices effectively but and they're getting owners ersship of a company who very likely could just like and and but Nvidia comes out great because they're they're they're getting the capex dollars up front yeah right so all they're really doing is they're saying half of my money that's in this sure it does make its way to me somehow but in reality I still made half of that gross profit and the other half is is is equity in a company that may or may not be worth something a company that may or may not be able to pay hundreds of billions of dollars of compute deals that they've signed right in which case they'd be bankrupt right so this is this is like the the mechanics of that deal

[译文] [Dylan Patel]: 所以 Nvidia 不一定是在完全搞“循环交易”，但实际上发生的是 OpenAI 获得了用股权支付一大笔费用的机会。而 Nvidia 实际上是在没有降价的情况下“降低”了价格，同时他们获得了一家公司的所有权。Nvidia 的结果很好，因为他们预先获得了资本支出的美元，对吧。所以他们真正做的只是在说：“我这里面的一半钱，当然它以某种方式流回了我这里，但实际上我仍然赚到了那一半的毛利润，而另一半变成了对一家公司的股权。”这家公司可能值钱也可能不值钱，这家公司可能付得起也可能付不起他们签署的数千亿美元算力协议，如果付不起他们就会破产，对吧。这就是那笔交易的机制。