E165: Vision Pro: use or lose? Meta vs Snap, SaaS recovery, AI investing, rolling real estate crisis
发布时间 2024-02-09 19:56:45 来源
摘要
(0:00) Bestie intros! (2:08) Apple Vision Pro breakdown (20:46) Meta vs Snap: god-king CEO, dependent on ad revenue, ...
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中英文字稿 
All right, Freeburg is back. Welcome back to the All in podcast episode 160 something your favorite podcast in the one old yada yada yada yada with me again the chairman dictator from off polyhopetea. The rain man. Yeah, definitely David Sachs is here and back from his time in the metaverse. We found him somewhere out in space in the solar system in his apple goggles, your favorite.
好的，Freeburg回来了。欢迎回到All in播客的第160期或其他一些你最喜欢的播客中。我是再次加入的来自offpolyhopetea的主席独裁者，雨人。是的，无疑地，David Sachs在这里，从元宇宙返回。我们在太阳系的某个地方找到了他，他戴着他最喜欢的苹果眼镜。
So open of science David freeburg is back from the metaverse. I missed you guys. Welcome home. Thanks for having me. What did you discover when you went to your anus in Google class? Sorry. Happy. I use the Apple vision pro take out. I ordered them. I ordered them and I walked by the apple store and I was going to go in and try them. And there were so many lunatics in there. I was like, yeah, I'm not doing it. But I ordered them. You use you actually use them. I ordered one online to be delivered and it was like delayed by a month. So I went down to the apple store and picked one up. Okay. And my kids cannot stop using it. Really?
开诚布公的科学家大卫·弗里伯格从虚拟现实世界回来了。我想念你们。欢迎回家。感谢你们接待我。你在Google班上去你的anus时发现了什么？抱歉，我很开心。我用的是苹果的视觉专业版外卖。我订购了它们，并经过苹果店时想要进去试试。但里面有很多疯子，所以我就算了。但是我订购了它们。你实际上使用它们了吗？我在线上订购了一个，但要延迟一个月才能送到。所以我去了苹果店自己拿了一个。好的，我的孩子们停不下来使用它。真的吗？
I went down to the apple store, but I got cleaned out by the thief to stole everything. So. That's the only one. Let your winter ride. Rain man, David Sachs. We open sources to fans and they've just got crazy. Love you guys. I'm queen of king. I'm going home. That was crazy. That was crazy. Well, put the video in here to the idiots who are robbing apple stores. All the devices get pricked when you steal them. And they all have GPS in them. Have you tried it? Shama? No, it's too busy working out, making love and winning. Oh, okay. Got it. So you were making sweet love. You were watching your portfolio go up and you were just generally winning. Got it. Got it. Yeah.
我去了苹果商店，但是我的东西被偷了一空。所以，这是唯一的一个。让你的冬天过得愉快。雨人，大卫·萨克斯。我们向粉丝开放资源，他们变得疯狂。爱你们。我是王后的女王。我要回家了。那太疯狂了。那太疯狂了。好吧，把这个视频放在这里给那些抢苹果店的白痴们看。你们偷了设备后都会遇到麻烦。而且它们都有GPS定位。你试过吗？夏玛？不，他忙着锻炼身体、谈恋爱和获胜。哦，好的。明白了。所以你在享受甜蜜的爱情，看着你的投资组合增长，总体上都在获胜。明白了。明白了。是的。
So, Freberg, the rest of us were being men in the world, accomplishing stuff. But do tell us about your time in the men of Earth. Do those goggles come with a lifetime prescription of SSR eyes? You guys sound like one of these tech journalists that are actually anti-tech people. You guys are. Actually, tech journalists like it. Talk to you. It seems like an computing platform.
那么，弗雷伯格，我们其他人都在世界上充当男子汉，完成事业。但请告诉我们你在地球上的时光。那些护目镜带的是终生配方的超级强劲视力吗？你们听起来像是那些实际上反对科技的科技记者之一。而你们就是这样。实际上，科技记者们喜欢它。跟你聊一聊。它看起来像是一个计算平台。
I remember when the iPad came out and everyone poo poo poo the iPad. I thought it was stupid. I tried to use it. I couldn't get any value out of it. And in 2010 or 2011, when did it come out? 2010, 2011, we started using it with our sales team selling to farmers. And we gave every sales guy an iPad and they went out in the field with 3G. And they were able to close sales in the field meeting with farmers, which had never been done before. Usually had to get a farmer to come into an office. How many iPads sold in the product? So we had like 9,000- No, not on the Macom software. We had dozens of these sales guys. We gave them out to our sales agents as well, the independent agents. They started using them. And it was like a real game changer in how sales was done in agriculture. And I had never even contemplated that when I first used the iPad.
我还记得iPad刚出来的时候，每个人都对它持怀疑态度。我当时认为它很傻。我试着使用了一下，但是无法获得任何价值。在2010年或者2011年，它是那个时间出来的吗？2010年？2011年？我们开始将它用于销售团队，去向农民销售。我们给每个销售员发了一台iPad，然后他们带着3G去外地与农民会面并完成了销售。这在以前从未发生过。通常都需要把农民请到办公室。产品销售了多少iPad？我们大约卖出了9000台，不，不是在Macom软件上。我们有几十名销售员，我们也把它们分发给了我们的销售代理商。他们开始使用iPad。这真的改变了农业销售的方式。而当我第一次使用iPad时，我甚至没有想到这一点。
So let's get to brass tax here. What is the killer app? What do you think? In the next five years, people are going to be doing with this thing on a daily basis. Is there a daily use case? I'll say a couple things. One is like, I feel the same way I did about the iPad, which is I don't know what it is today. But I can tell that there's something there. And I'll give you an example of something I thought about.
来说说我们关心的核心问题吧。那么什么是杀手级应用？你有什么想法？在接下来的五年里，人们每天会用这个东西做什么呢？有每日使用场景吗？我可以说一些观点。其中一个是，我对iPad的感觉和现在一样，我不知道它今天是什么样的。但我能感觉到其中潜力。我给你举个我考虑过的例子。
First of all, the AR is game-changing. OK. If you've used like the meta, the Oculus Quest, it makes me super dizzy, makes my head hurt, makes my eyes hurt. Like you're super disoriented. What Apple solved is that you're like still in reality. But then you get to interact with these three-dimensional kind of objects in reality. And it's like really well done. It's definitely V1 and there's going to be incredible changes in the next couple of generations. But it gets rid of all that dizziness, disconnected kind of stuff that happens with the full VR experience, which I thought was really incredible.
首先，增强现实（AR）是具有革命性意义的技术。如果你用过像是Oculus Quest这样的AR设备，可能会感到非常头晕，头痛，眼睛痛。就像你完全迷失方向一样。而苹果解决的问题是你依然处在现实中，但可以与现实中的三维物体互动。这点做得非常出色。虽然这只是第一代产品，未来几代产品将会有令人难以置信的变革。但它摆脱了全面虚拟现实体验中可能出现的头晕、脱离感等问题，我觉得这真的很不可思议。
Then last week, and I'm sorry I missed the show, we have a facility with my company in North Carolina. We have this giant greenhouse facility and I was doing meeting with farmers and stuff.
上周，我很抱歉错过了节目，我们公司在北卡罗来纳州有一个设施。我们有一个巨大的温室设施，我正在与农民们进行会议等活动。
I go to the greenhouse facility and there's so much work that the greenhouse techs and lab techs are doing, where they're using an iPhone and a barcode scanner and a printer and they're holding all these pieces of equipment, scanning the QR codes on flowers, taking the pollen out, putting it in the next flower, training each other how to do it. And I was like, I put this Apple Vision Pro on and I was like, man, all the apps and all the tools that we had all these different pieces for that was taking people tons of time.
我去温室设施，那里有那么多的工作要做，温室技术人员和实验室技术人员正在使用iPhone、条码扫描仪和打印机，他们手里拿着所有这些设备，扫描花朵上的二维码，取出花粉，放入下一朵花中，并相互培训如何进行操作。我穿上这个苹果Vision Pro设备，心想，哇，我们过去使用多种不同的应用程序和工具，这些都要花费大量时间。
Image collection, data collection could all just be done streamlined while you're working. You could have a task with your report. You have a task with the right. Cameras are taking images in the middle. QR codes are automatically scanned. Data is being ingested. The task list is kind of giving folks next steps.
图像收集、数据收集都可以在你工作的同时进行。你可以在报告中设置一个任务。你可以拥有正确的任务。摄像机在中间拍摄图像，二维码自动扫描。数据被摄入。任务列表可以提供给大家下一步该做什么的指导。
They could listen to music while they're working. And I realized for that job, and I met with all the team out there and spent time with them, and I actually did the work that they do to get a better sense for the workflow. And I was like, man, literally every aspect of this job will be massively improved and productivity will go up by 10x with these goggles.
他们在工作时可以听音乐。我意识到了这份工作的情况，然后与团队的所有成员见面，并与他们一起度过了一段时间，还亲自进行了他们的工作，以更好地了解工作流程。我发现，使用这些护目镜，这份工作的每个方面都将得到极大改善，生产力将提高10倍。
Will it happen in the next couple of weeks or months? I don't know, but my engineering team is looking into it. Can we take it? Can we use some software? Can we build some software and can we put this on folks to give them a better work experience, increase our productivity to do automated data capture? So I don't know exactly where it goes, but I could start to see how this can become a more ubiquitous part of a workforce setting and not just be a video game and movie tool for consumers.
这会在接下来的几周或几个月内发生吗？我不知道，但我的工程团队正在调查。我们可以使用吗？我们可以使用一些软件吗？我们可以开发一些软件，并将其应用于员工，以提供更好的工作体验，提高我们的生产力来实现自动化数据捕捉吗？所以我不知道它会走向何方，但我可以看到它如何成为工作环境中更普遍的一部分，而不仅仅是消费者的电子游戏和电影工具。
So I'm reasonably optimistic about where this goes. It's definitely V1. I feel like it's the iPad days where no one's really sure where the applications are, but yeah. Enterprise applications. Unbelievable. Makes total sense.
所以，对于这个发展的方向，我是相当乐观的。这绝对是V1版本。我觉得这就像是iPad时代，没有人真正确定应用的方向，但是，是的，企业应用。难以置信。完全合理。
And also training, training, right? Assembly line workforce, sure house workers, where you're getting real-time kind of task updates, data is being ingested, all in real-time. And and by the way, the other thing I'll say is training is incredible. There's spatial video recording on it. So it looks like you're living through the experience that someone else had. So you can train someone how to do a difficult task. And rather than have a human go spend hours training a workforce, the workforce can be trained by the goggles in a way that you cannot do with two-dimensional video today.
而且还有培训，培训，对吧？装配线工人，家庭劳动者，你可以获得实时的任务更新，数据会实时被吸收。还有，顺便说一句，培训是非常神奇的。它具备空间视频录制功能。因此，看起来就像你正在亲身经历别人的经验。你可以通过这种方式培训某人如何完成困难的任务。而不是让一个人花费数小时培训一个工作队伍，工作队伍可以通过眼镜进行培训，这是今天的二维视频所无法实现的。
So I don't know. I'm I'm I'm pretty optimistic. Very strange days, right? I don't know. You're you're a fan of five member strange days. Totally. From off, what's going to happen first here? Are humans going to become more like robots by putting these on and do this factory work or is Elon with optimists and some of humane, I think, is the other one. There's a couple of other people building a general use robots. Figures. The other one. Figuring out which one wins the day.
所以我不知道。我我我相当乐观。非常奇怪的日子，对吧？我不知道。你是五个成员奇怪日子的粉丝。完全没错。首先会发生什么？人类会通过戴上这些东西变得更像机器人，然后从事工厂工作吗？还是像埃隆和一些人类主义者那样，还有一些其他人在建造通用的机器人。另一个人物。找出最终谁会胜出。
Is it going to be humans having eyes and data collection like robots or robots having appendages like humans? Well, let me let me put two ideas together and see what you think of this argument.
是人类会像机器人一样拥有眼睛和数据收集能力，还是机器人会像人类一样拥有肢体？嗯，让我把这两个想法合在一起，看看你对这个论点的看法。
If you think about the generation of human beings that have. Has close to. Any other generation before it lived in a totally immersive world, I would say the best representation of that are. Current teenagers and 20 year old people and maybe at the upper edge, the early 30s people. And why is that? You know, they've lived inside of social media their entire lives. They've lived inside of immersive video games their entire lives.
如果你思考起以前的人类一代，他们比之前的任何一代都生活在一个完全沉浸的世界中，我会说目前最好的代表就是现在的青少年和20岁左右的人，也许再往上，是30岁左右年龄段的人。为什么这么说呢？你知道，他们的整个生活都在社交媒体中度过，他们的整个生活都在沉浸式视频游戏中度过。
But the question is, are they better off and happier as far as we know from an evolutionary perspective? And I would tell you that the answer is a is a huge gaping no.
但问题是，从进化的角度来看，他们是否变得更好、更幸福呢？我告诉你，答案是一个巨大的"不"。
So if you believe that the rise in depression, the rise in suicide, the dependency on drugs, the dependency on SSR rise, the sexual promiscuity, the lack of marriage, the lack of kids. If all of those things are in some ways. A correlated by product, let's not say it's causal, right? Let's just say it's a correlated byproduct of this entire immersive, almost exclusionary, detached world that these folks have grown up in.
如果你相信抑郁症的增加、自杀的增加、对药物的依赖、对选择性血清素再摄取抑制剂（SSR）的依赖、性乱潮、婚姻减少、没有孩子等等这些问题，在某种程度上是这个人群成长环境中沉浸、孤立、与现实脱节的结果，那么我们可以看作是有一种关联关系，不需要说它是因果关系。
Taking that to the limit. I'm just going to put out there. It may not be the solution to our problems. And so I guess the more directed answer to your question is I would hope that the latter wins so that we take these goggles off and actually learn how to talk to each other and look each other in the eyes. Get married and have children because I think that's actually better for the world.
把这一切推到极限。我只是想提出来。这可能不是解决我们问题的办法。所以，我猜对你的问题来说，我希望后者能胜出，这样我们可以摘下这些“眼镜”，真正学会互相交谈，直视彼此的眼睛。结婚生子，因为我认为这对世界来说更好。
And I would probably say that it's almost better for the world than a 10 Xing of productivity. Interesting. And then you see the correlation to cancer and disease that is disproportionately higher amongst these young people. So I think it's at some point to ask ourselves, what is structurally happening in the lives of these 16, you know, 15 to 31 year olds that is just so poor in terms of outcomes.
我认为，相比提高生产力10倍，这对世界而言可能更好。有趣的是，你会发现这些年轻人中患癌症和其他疾病的比例格外高。所以我认为我们应该考虑一下，是什么在这些16到31岁的人的生活中导致了如此糟糕的结果。
And if you look at some of the environmental variables that they live in and then take some of those and take them to the limit, I think that there's a reasonable argument that their lives get worse before that gets better. Yeah. I mean, the amount of time you spend on social media is correlated with depression. Social media. I'm just saying just this immersive, like, I'm going to detach from the world and live through a microphone and glasses taken to the limit. I'm not sure is the solution to these kids feeling detached. Lonely isolated. I said, yeah. Yeah.
如果你观察一些它们生活的环境变量，然后将其中一些变量推向极限，我认为他们的生活在变好之前会变得更糟。是的。我的意思是，你在社交媒体上花费的时间与抑郁有关。社交媒体。我只是说，这种全身心投入其中，像通过麦克风和眼镜来与世隔绝的方式推向极限，我不确定这是解决这些孩子感到孤立的方法。孤独与孤立。我说的没错，没错。
I mean, it correlates all of these things that we're seeing in this younger generation correlates with the introduction. So could it be a good productivity device? Yes. Of course. I hope it's a good product to device. Yes. But if we try to make it the panacea for anything and everything, I think we're going to we're going to compound the systemic issues that these young people have. And I suspect on the margin, if you were going to bet, all of these things that we see in these young people today will get worse as a byproduct. Of technology, not necessarily get better.
我的意思是，我们在这一代年轻人身上看到的所有现象，都与这种技术的引入相关。所以它可能是一个好的生产力工具吗？是的，当然。我希望它是一个好的产品。是的。但是，如果我们试图将它作为一劳永逸的解决方案应用在任何事物上，我认为我们会加剧这些年轻人的系统性问题。我怀疑，在这方面，如果要打赌，所有这些我们今天在年轻人身上看到的问题将会作为技术的副产品而恶化，而不是得到改善。
So if you can take a different path like optimists or the figure AI robots where that work is done, at least we have a different problem, probably maybe even more existential abundance. But a different problem, which is now how do you find purpose? But maybe you can find purpose through connection and the types of things that humans have been bred over billions of years to actually optimize for.
因此，如果你能像乐观主义者或人工智能机器人一样选择不同的道路，至少我们会面临一个不同的问题，可能甚至是更多存在感的问题。但这是一个不同的问题，现在我们要问如何找到目标？也许你可以通过连接和人类在亿万年中被培育出来的优化事物类型来找到目标。
OK. Sax, I remember when you were starting craft, you fired up like a group for VR and you got pretty heavy into it. You made a couple of small bets. I remember that I don't think any of it worked out. Really, you could tell me if I'm wrong here, but you got in a little bit earlier there.
好的。Sax，我记得你开始研究手工艺时非常热衷于虚拟现实，你投入了很多精力。你进行了几次小的尝试，但我记得好像没有一个成功的。实际上，你可以告诉我这里是否有误，但你在那方面进入得稍微早一些。
Maybe you talk about the business case for this and has that changed because you believed I believed a lot of folks thought, Hey, maybe this is the time when Zuck really started, you know, had bought Oculus and they started putting out some good product. Seemed like it was a false start. Is this the actual starting pistol and is this the start of the VR AR adoption race? I don't think we're quite there yet. OK. We've been talking about VR being a thing for over a decade. Yeah. No, more like 30. Remember the Nintendo VR stuff? It's like always on the verge of happening.
也许你会谈论这个业务案例，因为你相信我相信很多人认为，嘿，也许这是扎克真正开始购买Oculus并开始推出一些好产品的时候。看起来像是一个虚假的开始。这是真正的起跑枪吗？这是虚拟现实（VR）和增强现实（AR）采用竞赛的开始吗？我认为我们还没有完全到达那个阶段。好了。我们已经谈论虚拟现实已经有十多年了。是的。不，更像是30年。还记得任天堂的VR东西吗？它似乎总是即将到来。
I think that the big complaint about the Apple devices has a lot of capability, but it's still a pretty huge device to wear on your forehead. This is not really going to be comfortable enough to be something that people want to use all the time. I mean, there's also a question of use cases, but they're getting there with the use cases. In a event, I do think that Apple Vision Pro is it's like I said last week. It's a useful prototype or proof of concept and it will get better. So I'm glad they did it because I think you need to start somewhere and then just keep iterating. But eventually for this to, I think, really take off, you need to shrink the form factor, miniaturize the technology. Just every version of it make it simpler or lighter, easier to use.
我认为对于苹果设备的主要抱怨是它具有很多功能，但是它仍然是一个相当庞大的设备，戴在额头上并不是很舒适，人们并不愿意一直使用它。我的意思是，还有一个使用情境的问题，但他们正在逐渐解决这些问题。无论如何，我认为苹果视觉专业版就像我上周说的那样，它是一个有用的原型或概念验证，而且会越来越好。所以我很高兴他们这样做，因为我认为你需要从某个地方开始，然后不断迭代。但是最终要使其真正起飞，我认为需要缩小形态，使技术更小型化。每个版本都使它更简单、更轻便、更易用。
Yeah. I mean, eventually it'll feel like sunglasses. And so that is, I guess, if they become like regular glasses, I think we all agree. It becomes a nice computer. I feel like it's pretty damn comfortable. I don't know if you guys haven't really used it, but that's what I've heard. That's a surprise. It was totally surprising online saying it's like any other headset I've ever worn. They did an incredible job designing. I feel like does it feel like ski goggles? It doesn't feel heavy. It doesn't feel pressure compared to ski goggles. If you were wearing ski goggles, it's less constricting than ski goggles. It's more comfortable. It like floats on you a little bit. They did a great job with this cushioning device they built and the band you put on. It feels very natural. It's Apple design, right? It's like a really well designed product that's unlike anything else you've ever tried.
是的，我的意思是，最终它会感觉像太阳镜一样。所以，我想，如果它们变成普通眼镜，我想我们都会同意。它会成为一台好用的电脑。我觉得它非常舒适。我不知道你们是否真正用过，但是这是我听说的。这真是个惊喜。网上有人说它就像其他任何头戴设备一样。他们在设计上做得非常出色。我觉得它感觉像滑雪镜吗？它并不重。与滑雪镜相比，并没有什么压迫感。它更舒适。它像是在你身上漂浮着一点。他们在这个缓冲装置和头带上做得非常好。感觉非常自然。这就是苹果的设计，对吧？这是一个设计得非常出色的产品，不像你以前尝试过的任何其他产品。
I've always felt like when Apple comes into the race, that's the starter's pistol. And I think this is it because I've heard the same thing from everybody. You have to try it. It feels like different than Oculus and some of those versions that came out previously. And they have the app ecosystem. And I would not discount that when the ability to monetize the app ecosystem and have all the people who are already building the com app, the Uber app, whatever notion, you know, all the stuff that people use in love, Spotify, YouTube, and then poured it over here for at night, whatever. I think that's going to be the magic.
我一直觉得当苹果加入竞争时，这就是起跑枪。而且我认为这就是起点，因为每个人都对此表示了同样的看法。你必须尝试一下。它感觉不同于Oculus和之前推出的那些版本。而且它有应用生态系统。我不会忽视能够从应用生态系统中获利以及已经在构建通信应用、Uber应用等等的人们所产生的影响。你知道，所有人喜爱使用的东西，像Spotify、YouTube，然后把它们全部移植到这里，用于晚上或其他时间。我认为那将是不可思议的。
And the statistics are not lying here. I mean, this is unbelievable. They've sold already 200,000 units, which doesn't seem like a lot. But for V one, that is a lot and they're going to sell a half million this year. It's going to be close to like that. Not that many. Well, it's a couple of billion. Metas sells more. They do. Yeah, but you know, this is $4,000. This isn't 500. So to sell that many of a $4,000 devices in. Quite a bit of a concept. It's not like a regular Apple product that is a mass market device that tens or hundreds of millions of people are going to buy, but it puts them on a path to where they can iterate and keep making it better.
而且数据并没有说谎。我是说，这真是难以置信。他们已经售出了20万台，虽然这似乎不多。但对于第一代产品来说，这已经很多了，他们今年将卖出50万台。接近这个数字。不算多。好吧，也就是几十亿。Metas卖得更多。是的，但你知道吗，这个要价是4000美元，而不是500美元。所以能卖出这么多价值4000美元的设备还是很不错的概念。这不像一个大众市场设备，几千万人要购买，但这使他们走上了不断改进的道路。
See, I think, and this is, I guess, what I asked free bird, do you compare this to buying a MacBook Pro, buying an iPhone or buying the Oculus, you know, whatever? They, you know, $500 unit because everybody I see talking about online is comparing it to the purchase of a laptop because of the desktop and you can kind of do your coding or surf the web and do all that. Wait, where do you put this? Is it buying a TV? Is it buying a laptop? Is it buying a smartphone? What would you have to have a keyboard to be really productive on it? Uh huh. If you're going to use it for writing purposes or coding purposes, so it doesn't really work with just the headset, but you could do that. Yeah, it's definitely like buying a new computing device, but people felt the same way about the iPad. Get go back to 2010 when the iPad came out and everyone was like, who's it for? It's a whole new computer. Who's it for? You already have a phone. You already have a computer. Why do you need an iPad? And then they sell tens of millions of quarter now.
你看，我觉得，这也是我问自由鸟的，你觉得这和买MacBook Pro、买iPhone或买Oculus有什么比较，你知道的，任何东西都行？因为他们，你知道的，这个500美元的设备，因为我看到所有人在网上都在将其与购买笔记本电脑进行比较，因为它有台式机功能，你可以做编码、上网等等。等等，你觉得它属于哪种购买？买电视吗？买笔记本电脑吗？还是买智能手机？如果你想要真正提高生产力，那么你需要一个键盘吗？嗯嗯，如果你想要用它来写作或编码，光靠头盔可能不太够，但你是可以这么做的。是的，它确实像是购买一台新的计算设备，但人们对iPad也有同样的感受。回到2010年iPad推出时，所有人都在问，它是给谁用的？它是一个全新的电脑。你已经有手机了，你已经有电脑了。为什么你还需要一个iPad呢？然后，它现在每个季度卖出了数千万台。
So I really, as I do the math on this, I was just kind of doing some back of the envelope stuff. I think they're going to sell $100 billion of Apple vision pros, not this version, but this version plus the next version probably over the next. I would guess for them to get to $100 billion in sales, it'll take them. Less than five years. I think they're going to run the table on everybody. I think they're going to own the entire space. Everyone's underestimating this as a new computing platform. And once these applications, particularly in the enterprise setting, start to kick in.
因此，当我对此进行数学计算时，我只是大致做了一些估计。我认为他们将销售1000亿美元的苹果视觉产品，虽然不是这个版本，而是这个版本加上下一个版本，可能在未来的不到五年内实现。我猜他们会碾压所有竞争对手，将整个市场收入囊中。每个人都低估了这个新的计算平台的重要性。一旦这些应用程序特别是在企业领域开始兴起，情况就会变得不同。
And I will say that the movie watching experience is way better than watching on a TV in your living room. My kids cannot stop asking me to use the goggles to watch instead of an iPad or TV. The cause you see 3D, like all Pixar movies are natively 3D. And so you got the Disney Plus app on there. You watch a Pixar movie and you're watching in 3D. The kids are blown away. So I think we're all going to be surprised by how this Disney is all in on it. Remember when our parents told us not to sit too close to the TV? Now we're just dropping the thing to our face. Yeah.
我要说电影观影体验远比在客厅的电视上观看要好得多。我的孩子们停不下来地要求我用这个眼镜看，而不是用iPad或电视。原因是你可以看到3D效果，就像所有的皮克斯电影都是原生3D一样。你在上面看皮克斯电影的时候，就能看到3D效果。孩子们都被震撼了。所以，我认为我们都会对迪斯尼对这方面的投入感到惊讶。还记得我们父母告诉我们不要坐得离电视太近吗？现在我们只是把它放在面前而已。是的。
I had the most Silicon Valley moment ever. I go to buy a cup of coffee. I was going from a little walk. I see blue bottom. I'm like, you know, I get myself a mocha. You know, I lost a little bit of weight. I'm going to treat myself $9 for a mocha. Number one, that in the city tilted me. Nine dollars from eight dollars. And then I gave a dollar tip and then I felt cheap giving a dollar. You know, it's eight ninety nine for a carton of clover milk, all organic. I mean, you can make infinite lattes at home. Anyway, where did you go for your nine dollar mocha? I was I'm in Palo Alto right now because we lost. Because I could do a bottle. Yeah. And I posted this. I'm like nine dollars. What am I doing? You know, I just I felt like buying a chocolate bar and the stain. Your dirty lips left on the cup. Oh, my God. Look at your own fat. You know what? You're a little obsessed with my lips. Take it easy. Yeah.
我经历了最有硅谷特色的一刻。我去买杯咖啡。我正在散步的时候看到了一个蓝底。我就觉得，你知道的，我给自己来一杯摩卡。你知道的，我稍微减了点肥。我要奖励一下自己，给自己花9美元买一杯摩卡。首先，这个价格在这个城市里让我有些不舒服，从8美元变成了9美元。然后我给了1美元小费，结果觉得自己有些小气。你知道的，一盒有机的脱脂牛奶才卖8.99美元，这足够在家里做无数杯拿铁了。不管怎样，你去哪里花9美元买一杯摩卡啊？我现在在帕洛阿尔托，因为我们迷路了。因为我可以开瓶啊。然后我发了个帖子说“九美元，我在干什么？”你知道的，我就觉得自己想买个巧克力棒，但是被你留在杯子上的嘴唇污迹吓到了。天哪，看看你自己的胖。你知道吗？你对我的嘴唇有点过分迷恋了吧。轻松点儿。是的。
So anyway, then there's a kid in the place wearing the goggles with the keyboard. No, no, stop sounding. He's getting work done. This kid was doing work and I tell you, the truth is putting in the hours. He was putting in the hours. No one looks at your laptop. No one looks at your screen. That's what I love about your work without anyone seeing what you're doing.
所以有个孩子在那里戴着带有键盘的护目镜。不不不，别发出声音。他在忙着工作。这个孩子正在做工作，我告诉你，他确实花了很多时间。他付出了很多时间。没人会看你的笔记本电脑。没人会看你的屏幕。这就是我喜欢你工作的地方，没人看到你在做什么。
This kid had four desktops up. This guy was probably on porn hub, Spotify, writing code. How many words did this person say to another human being while you were there? No, zero. And you know, when they're on a laptop, they're the same. What's the difference? He's he's coding. Nobody bad. And I think this is going to they're going to run the table on this. I think it's a hundred billion sales. A hundred billion sales. Under five years. Yeah. I take the over. I take the over.
这个孩子同时使用了四台台式电脑。这个人可能正在浏览色情网站(porn hub)，听音乐(Spotify)，写代码。在你在场时，这个人对其他人说了多少话？没有，一句都没有。你知道，在他们使用笔记本电脑时也是一样的。有什么区别？他在写代码。没有坏事。我认为这个公司将会取得巨大的成功。我认为它将实现一千亿的销售额。在不到五年的时间里。是的。我押大。我押大。
==========
What do you got? The over the under because they keep it at three grand. They got to sell 30 million units to get to a hundred billion. They're going to make up a lot of money on this app store too.
你有什么得到的东西？之所以保持在三千大关是因为他们得要卖出三千万部设备才能达到一千亿的目标。这个应用商店也会给他们带来很多利润。
But I think that you guys are right that it's going to be successful in terms of revenue. What I'm asking is a more societal question is do you guys actually think it's better?
但我认为你们是对的，从收入的角度来看，它会成功。我问的更是一个社会性的问题，你们真的认为这是更好的吗？
No, I don't want my kids in this all day. No, I could see this becoming super.
不，我不想让我的孩子整天都参与这个。不，我可以看出它会变得非常好。
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I can. Hey, free, bro. Guy, can I buy three for your kids? Just have them walk around with them.
没问题，兄弟。可以的，兄弟，我买三个给你的孩子吗？让他们随身携带。
No, I have a no. I have a house rule as well. But wait a minute. Hold on.
不，我有个“不行”的规定。我也有一条家规。但等一下，等一下。稍等一下。
What about productivity, free, my kids aren't trying to be productive. They're using a burn. You don't have a productive childhood. It's supposed to be not productive.
生产力怎么样？免费的，我的孩子不在追求生产力。他们只是用自由自在地度过时光。你没有一个充满生产力的童年。童年本就不应该是充满生产力的。
You guys understand that at some point you guys will be the only six kids whose parents haven't given them the stupid thing to put on their face. No, this is going to be time restricted.
==========
I have a no iPad, no phone, no, like to I let the headset but it's so good for them. So good. No, no, it burns their burns their brain away burns their brain away. I mean, man, I totally agree with you. Social interaction, the loss of our ability to communicate is critical. And it's a fail point. I do think that there are applications where these things create great unlocks. I think this is an enterprise device. Can you imagine giving the sales team on the farm to go there? They can take off their sweaty headset when the sun is shining and then give it to the farmer to put on and then he can put it on and feel the sweat and the the headband will be wet. No, that's not the use case.
你们明白吗？在某个时候，你们将是仅有的六个孩子，他们的父母没有给他们那个愚蠢的戴在脸上的东西。不，这会有时间限制。
我没有iPad，没有手机，也不喜欢让他们带耳机，但它对他们来说太好了。太好了。不，不，它会烧掉他们的大脑，烧掉他们的大脑。我的意思是，兄弟，我完全同意你。社交互动、我们沟通能力的丧失是至关重要的，这是一个失败的点。我确实认为，这些设备在某些应用中能够发挥巨大作用。我认为这是企业设备。你能想象给销售团队在农场上使用吗？他们可以在太阳下把湿透了的头箍从脸上摘下来，然后交给农民，他可以戴上它感受到汗水，头带会湿透。不，那不是使用场景。
It does it. By the way, it's a very personal device in order to log in, you know, it does like a eye scan or you have to have like a lock in like log in like you do with your phone, but then you got to reset the eye because it automatically sets the eye position. So when you put on someone else's headset, you got to reset the eye. It's a whole thing. So it's not a transferable device. It's a very personal computing, you know, kind of thing. I don't think it's going to be the same as like an iPad or a phone. It's a very different kind of thing. I don't know what it's going to look like yet.
它这样工作。顺便说一下，这是一个非常个人化的设备，为了登录，你知道，它会进行眼部扫描，或者你必须像手机一样设置一个密码，但是然后你必须重新设置眼睛，因为它会自动设置眼睛的位置。所以当你戴上别人的头戴式显示器时，你必须重设眼睛。这是一整套流程。所以它不是可转让的设备。它是一种非常个人化的计算设备，你知道，是一种非常不同的东西。我还不知道它会是什么样子。
I don't know. I say next week we do the show inside of these or at least me and you free bird will be will be there. So it's actually very funny. There's a there's an avatar thing. And so what it does, it scans your face while you're talking and what all four of us can see each other as the avatar. Yeah. Now let's do it. It'll be hilarious.
我不知道。我说下周我们在这里或者至少我和你自由鸟会在那里做演出。这样实际上很有趣。有一个阿凡达的东西。它会在你说话的时候扫描你的脸，然后我们四个都可以以阿凡达的形象看到彼此。是的，我们来试试吧。这将会很搞笑。
I had a moment this week in parenting. I had a moment this week where I told one of my children that when I send a text message, I expect an immediate response. Otherwise I am going to cancel that child's phone and take it away. And then separately, when they respond, it has to be in structured, well thought out, perfectly formatted English. And then then third, I said every single email I see from you interacting with your teachers or anybody else that's there to help you needs to be incredibly well written and formatted. And if I see garbage English, I'm going to take your phone away.
这周我在育儿方面有了一个体悟。有一个时刻，我告诉我的其中一个孩子，当我发短信时，我期望立即得到回复。否则，我会取消孩子的手机使用权并收回手机。然后，当他们回复时，回复内容必须具有结构性、深思熟虑，并且格式完美的英文。另外，我还说了，我希望看到你与老师或其他人交流的每一封电子邮件都要写得非常好，并且格式正确。如果我看到糟糕的英文，我会收走你的手机。
Oh, okay. So you don't want them on their phones, but they have to respond right away. Well, they have very strict rules and what they can use. They're there for literally that all they can do is communicate like they can use eye message.
==========. But it is shocking to me that despite the lack of games that they have or whatever, how poor they are in being able to communicate and what little access to devices they have have already made them orders of magnitude less able to communicate than frankly, I was able to when I was there, and so I can just imagine what happens when you become even more ensconced in something that you can cocoon yourself with and not have to interact with the rest of you.
好的，所以你不希望他们一直用手机，但又希望他们必须立即回复。嗯，他们有非常严格的规定，只能使用什么。他们在那里实际上只能像使用iMessage那样进行沟通。
然而，令我震惊的是，尽管他们没有很多游戏可以玩，但他们在沟通能力上却非常差，以及他们对设备的极少访问权限已经使他们的沟通能力相比之下非常有限。而说实话，在我那个时候，我能够进行的沟通要比他们好得多，所以我可以想象当你沉浸在一种可以隔绝与其他人互动的东西中时，会发生什么。
I don't disagree with you. Not to say that it's not going to be a revenue generator, but I think that you could just as easily, frankly, instead of impacting Apple as revenues, you can probably go along the makers of SSRIs. Pause. Here comes the spread trade pot. Bumble and Tinder, and you'll get to the same place economically. All right. All right. Here we go. We got a lot on the what a great leap forward for humanity. I can't wait. I just see this as a laptop replacement.
我不反对你的观点。并不是说它不能成为一个盈利来源，但我认为，说实话，可以找到其他方法，而不是影响苹果的收入，你可能可以倾向于选择选择选择性5-羟色胺再摄取抑制剂的制造商。暂停。现在我们来谈谈投资利润。比如Bumble和Tinder，你可以从经济角度达到相同的目标。好吧，我们对人类的伟大飞跃有很多看法。我迫不及待地想看到它作为笔记本电脑的替代品。
Okay. I wanted to talk a little bit about what apparently is going to be the spread trade of the last year.
好的。我想谈谈似乎会成为去年交易趋势的东西。
Meta is continued their unbelievable run and snap dropped like 30%. Here's a chart for y'all of snap versus meta. You can take a quick look at it here and just for context, both companies did great during COVID and ZIRP hit all-time highs in 2021, but they both got crushed due to the ad spend pullback, obviously, but then meta started to get less focused on their headsets and more focused on AI.
Meta继续着令人难以置信的行情，而Snap则暴跌了约30%。这里有一个Snap与Meta相比的图表，你们可以在这里快速浏览一下。为了背景信息，两家公司在COVID期间都表现出色，并且在2021年达到了历史最高水平，但由于广告支出的减少，它们都遭受了重创。显然，Meta开始不再过分关注他们的头戴式设备，而更注重人工智能。
Started doing their reduction in headcount 22% year over year from 86,000 to 67,000. The last quarter for meta and their quarterly profits have increased to an all-time high of $14 billion. That's profits, folks, in Q4 for meta, all-time high for the stock price, $470 a share, $1.2 trillion market cap, snap down 60% from its closing price on a 5PO day in 2017.
从86,000人减少到67,000人，年度裁员率达到了22%。 Meta公司上个季度的季度利润创历史新高，达到了140亿美元。这是Meta公司Q4的利润，也是股价的历史新高，每股价格达到了470美元，总市值达到了1.2万亿美元。与2017年5PO日的收盘价相比，Snap公司的股价下跌了60%。
Let me just jump to Chumap before I get into more charts and everything. You pointed out Chumap, and maybe you could explain to the audience just how ridiculous the voting rights were and the massive dependence that the snap team and the executives had on stock based two issues for you, Chumap.
在我深入讨论更多图表和其他内容之前，让我先谈谈Chumap。你提到了Chumap，也许你能向听众解释一下投票权有多荒谬，以及快照团队和高管如何极度依赖基于股票的两个问题，针对你们来说，Chumap。
Well, I mean, I think I said it before. I think that case studies had been written about how tilted the governance is in snap. I think the point is that they basically have infinite to zero voting power over common shareholders. So there's no real feedback loop. And I think that that has probably adversely affected the types of people that traffic in their stock.
嗯，我的意思是，我想我以前说过了。我认为已经有关于Snap的治理存在失衡的案例研究被撰写出来。我的观点是，他们基本上对普通股东拥有从无限到零的投票权力。所以没有真正的反馈机制。我认为这可能对交易他们股票的人群产生了不利影响。
Now, look, activists and short sellers sometimes have a very bad reputation. But if you steelman their side of it, what they are there to do is the shine a light on inefficiency and in the short seller case, sometimes in propriety. But it should all lead to companies being better run. Right. I think meta had this example where they had a really big hiccup and everybody, including us sort of pointed out the levels of spend that they were making really didn't make any sense. I think we had a chart that compared the level of spend of meta second only to like the spaceship program, right? Just like bonkers an enormous amount of money. And look, Mark got the message. He heard it loud and clear. I think he got fed up with whatever was going on there and he fixed it. And it's in the numbers.
现在，听着，活动人士和空头卖家有时会有很坏的声誉。但是，如果我们从正面看待他们的立场，他们的目的是照亮低效率和不当行为，而在空头卖家的情况下，有时是不当行为。但这应该导致公司更好地运行。对的。我认为Meta有一个很好的例子，他们遇到了一个非常大的挫折，我们包括在内都指出了他们的开支水平看起来毫无意义。我记得我们有一个图表，将Meta的开支水平与太空飞船计划仅次于的进行了比较，对吧？简直是疯狂的巨额资金。而且，看吧，马克明白了这个信息。他听到了清晰的声音。我想他对那里发生的事情感到厌倦，并进行了修正。这一切都反映在数字上。
Now, I don't know snap because to be honest with you, I've never taken more than one second to look at that company. And the reason is there is just zero ability for me to have any useful say. So I've never honestly looked at its performance. I've never studied a single characteristic. I've never trended it. And I think the point is that I am probably where a lot of other reasonably smart folks who could give a reason to opinion on how to make it better land.
现在，坦率地说，我不了解Snap，因为我从来没有花超过一秒钟的时间去研究过这家公司。原因是我没有任何有用的发言能力。所以我从来没有真正关注过它的表现。我从未研究过它的任何特点，也从未关注过它的趋势。我认为我的情况可能和其他很多相当聪明且有能力提出改进方法的人一样。
And part of the reason is because there is no feedback loop that matters. Yeah. And when you know that, why would you waste your time? At least in the other options, right? There are other options and then meta was another one. You know, you can write a letter. It gets picked up on CNBC and Bloomberg and whatever. And all of a sudden they kind of pay attention.
部分原因是因为没有什么重要的反馈机制。是的，当你知道这一点时，为什么要浪费时间呢？至少在其他选择中，对吧？还有其他选择，比如meta（元信息）。你知道，你可以写一封信，它会被CNBC和Bloomberg等媒体报道，然后突然间他们就会关注起来了。
And I think and you look at Disney, Nelson Peltz goes and gets like Perlmutter shares by some more takes a lot of position. Peltz. Yeah. We'll see whether that fixes itself. The point is that when all of these other cases, people are investing the time because they think that there's even a small shred of a chance that the company listens. But if you literally have no say, you couldn't even do a proxy. You couldn't vote the shares. Why would you bother? And I think that that's more of an example where maybe there is a.
我认为你看看迪士尼，Nelson Peltz去买了更多的Perlmutter股份，并且采取了很多立场。 Peltz。是的。我们将看看是否会自动解决。问题是，当所有这些其他案例出现时，人们会投入时间，因为他们认为公司甚至有一丝机会听取意见。但是如果你真的没有发言权，甚至不能进行代理投票，为什么还要费心呢？我认为这更像是一个例子，或许在这种情况下会更……
So I don't even know why snapped it poorly. And again, I'm not going to really take the time because it's like why bother taking the time.
所以，我甚至不知道为什么拍得那么不好。再说一次，我真的不会花时间去调整，因为感觉没必要。
So should should they unwind this like no voting, common shares, super voting shares, nonsense? And should this go away as a concept in the stock market? Well, I mean, Facebook or meta has a pretty similar concept. I mean, I guess Zuckerberg has 60% voting control, whereas Evan Spiegel is 99%. So snap is more egregious. The difference is that Zuckerberg is listening and Spiegel is not.
所以他们应该取消这种无需投票、普通股和特殊股权的不合理设计吗？这种设计在股市中应该被废除吗？嗯，我是说，Facebook或Meta有一个相似的设计。我是说，扎克伯格拥有60%的投票权，而埃文·斯皮格尔则拥有99%。所以Snap更过分一些。不同之处在于扎克伯格在倾听，而斯皮格尔则不在。
The reason why snap is doing poorly is not because its revenue has deteriorated. So I looked up, let's put this back, chat GPT for their key metrics. So assuming GPT is not hallucinating. If you compare 2021 to 2023, their total revenue went up from 4.1 to 4.5 billion and gross profit went from, call it 2.4 to 2.5 billion. So not a huge increase, but revenue and gross profit were slightly up.
Snap做得不好的原因并不是因为其收入恶化。所以我查找了一下，让我们将重点指标聊天GPT放回去。所以假设GPT没有产生错觉。如果你将2021年与2023年进行比较，它们的总收入从41亿增加到45亿，毛利润从24亿增加到25亿。因此增长幅度并不大，但收入和毛利润稍微有所增长。
But if you look at operating expenses, they went from 3 billion to 4 billion a year. And that is why their operating income or operating loss went from a $700 million loss to $1.4 billion loss in two years. So that's the source of the problem is that they increase their operating expense by a billion dollars a year from 2021 to 2023. Yeah. It's pretty simple. They seem like they're the last ones to get the memo.
但是如果你看着运营费用，它从每年30亿增加到每年40亿。这就是为什么他们的经营收入或经营亏损在两年内从7亿美元的亏损增加到14亿美元的亏损的原因。所以问题的根源就是他们从2021年到2023年每年将运营费用增加了10亿美元。是的，很简单。他们似乎是最后一个收到备忘录的人。
And just to finish the point. So you saw that a few days ahead of this quarterly announcement where their stock got crushed, they put out a press release saying they're going to cut their head count 10%. It's too little too late. Yeah, they knew, right? They need to have a problem. So they released the press release saying, oh, we're going to cut. Well, you should have done what Zuckerberg did. Zuckerberg did a 20% cut last year. He got serious. He got lean and fit. And instead, these guys held out did nothing. And then when they know that the markets going to crush them, they put out this lame announcement 10%, no, not 10%. Really, if you just want to get back to where you were two years ago, in terms of operating expense, you need a 25% reduction. Yeah. Yeah. But it's more than that.
只是为了强调一下。因此，你在这个季度财报宣布之前几天，他们的股票遭到抛售，他们发布了一份新闻稿，称他们将削减10%的员工人数。这已经迟了。是的，他们知道，对吧？他们需要解决问题。所以他们发布了新闻稿，声称他们要进行裁员。嗯，他们应该像扎克伯格那样去做。去年扎克伯格削减了20%的员工人数。他变得认真起来，变得敏捷而高效。而相反，这些人拖延不做任何事情。然后当他们意识到市场会抛售他们的股票时，他们发布了这个无足轻重的10%裁员公告，不，不是10%。实际上，如果你只是想回到两年前的运营费用水平，你需要削减25%。是的。但事情不仅仅如此。
If you look at the numbers, let's use operating cash flow with 165 million for SNAP for the quarter. So their operations generated 160 million. A profit. But for the entire year, because they lost money in the quarters prior, they generated free cash flow of only $35 million. So the business net produced $35 million of incremental cash. You know how stock based comp accounting works? The charge happens when it vests. So this is what employees are vesting.
如果你看看数字，让我们用SNAP这一季度的经营现金流165百万来解释。所以他们的经营活动产生了160百万的利润。但是对于整个年度来说，由于前几个季度亏损，他们只产生了35百万美元的自由现金流。所以该业务净产生了35百万美元的现金增量。你了解股票报酬的计算方式吗？这个费用会在归属期时发生。所以这就是员工获得的东西。
During the year of 2023, employees vested $1.3 billion of stock based comp. So that means new shares of the stock based comp. So that means new shares or options were issued that on an accounting basis, the options are valued using black shows and the shares are valued based on the share price. So they issued $1.3 billion of stock based comp. So they generated 35 million of free cash and they used $1.3 billion to compensate employees beyond their topics.
在2023年，员工股权奖励价值13亿美元被解除限制。这意味着新的股权或期权被发行，按照会计准则，期权根据Black-Scholes定价模型进行估值，而股权则根据股价进行估值。因此，公司发行了13亿美元的股权奖励。他们创造了3500万美元的自由现金流，并使用13亿美元以超出期权范围之外的方式来补偿员工。
So that means that they paid employees 40 times the free cash flow that was generated for shareholders during the year, which is also equivalent to 10% of the cost of the stock to 10% of the enterprise market value of this company. So the enterprise value of the company is $15 billion, 10% of that was issued to employees to compensate them.
这意味着他们支付给员工的薪资是公司在这一年为股东创造的自由现金流的40倍，相当于该股票成本的10%或该公司市值的10%。所以该公司的企业价值为150亿美元，其中10%用于向员工进行补偿。
Now let me give you the story of another city, meta. And by the way, snaps share count because they issued all the stock. The number of shares outstanding increased by 4% during the year. During the year, meta's number of shares outstanding decreased by half a percent because they used cash to go and buy back stocks. So they were able to reduce the shares outstanding.
现在让我给你讲一个叫"Meta"的城市的故事。顺便说一句，"Snap"的股份数量因为发行了所有的股票而得到计算。在过去的一年中，股份总数量增加了4%。在同一年中，"Meta"利用现金回购股票，使得股份总数量减少了半个百分点。因此，他们成功减少了股份总数量。
Now, as you guys talk about meta cut employee count by 22% and snap cut employee had counts by 3% during the year. But here's the crazy difference in performance. The stock based comp expense for meta during that year was about $14 billion that tested that year. That company generated 71 billion of operating cash flow. So while snap gave employees 40 times the free cash flow, meta gave employees about 20% of the free cash flow. And then meta went around and they used some of that extra cash to buy back $20 billion of stock. So they bought back more shares than what the employees were issued back at your work. So it shows such a difference in looking out for shareholders.
现在，当你们谈论Meta削减员工数量22%，而Snap则削减了员工数量3%的同时，这里有一个疯狂的绩效差异。Meta在那一年的股票基础补偿费用约为140亿美元。该公司产生了710亿美元的经营现金流。所以Snap为员工提供的自由现金流相当于Meta的40倍，而Meta为员工提供的则仅相当于自由现金流的20%。然后Meta又用一些额外现金回购了200亿美元的股票。所以他们回购的股份比员工在你工作地点分配的股份还要多。这显示了对股东利益关注的差异。
So if I'm an investor, and by the way, meta is creating it like 25 times free cash flow, which is not a crazy multiple, given all the new businesses that they have in llama to and the progression to cloud and other things that they might do. If I'm looking at those two businesses as a shareholder, you got this guy that controls the whole stock. He's giving employees a billion three of shares a year when he's only making $30 million of free cash flow year. And then the other guy is issuing $14 billion of shares, buying them all back and he's making 70 billion of free cash flow year. I don't know. It's very hard to decide which one to go after.
如果我是一位投资者，顺便说一句，Meta正在以大约25倍的自由现金流来创造价值，考虑到他们在母驴以及向云端和其他可能的领域的拓展，这并不是一个疯狂的倍数。如果我身为股东关注这两个业务，你会发现有这样一个人控制着整个股票。他每年给予员工价值13亿美元的股票，而他每年只创造3000万美元的自由现金流。另一方面，另一个人发行了140亿美元的股票，将其全部回购，并每年创造700亿美元的自由现金流。我不知道如何决定去追随哪个人。
Still brought it up in an interview I saw in a lot of the layoffs were top heavy. So he got rid of a lot of the top people who had these huge comp packages. And then what I'm hearing from a lot of executives is cutting these highly stock comp executives who are also have big cash comp, cutting them, putting lieutenants in charge and then moving more jobs to other locations where people don't expect stock based comp. If you're in India, where you're in South America, whatever, you know, stock based comp is not like the obsession it is here. So as everybody optimizes these businesses, I mean, Facebook, even give it. Why do you need 5,000 employees? So they announced roughly 500 job cuts out of what? 5,500 employees. That's crazy. I mean, should that company be operating with 2,000 employees? Good question. So we've been seeing long cut the number of Twitter employees from 8,000 to 1,500. When you look at the number of apps that they're running and the number of products that they're running compared to Meta, right? Meta has far more apps, far more infrastructure. Meta is serving 3.2 billion daily active users. Snap is about 400 million. So Meta is 8x the users with many more applications and much more infrastructure. So I think it's a it's another great kind of ratio to look at the performance of these 2, 12 times. You're exactly right. Yeah.
在一次采访中，他依然提到这个问题，我看到很多裁员都是顶层职位过多所造成的。所以他解雇了很多拥有巨额薪酬方案的高层人员。我从很多高管那里听说的是，他们裁掉了那些持有大量股票并且薪水也高的高级雇员，让副手接管他们的职务，并将更多的工作岗位转移到人们不指望获得以股票为基础的薪酬的其他地方，比如印度，南美等地。所以当每个人都在优化这些业务时，我指的是，就连Facebook也是如此。你为什么需要5000名员工呢？所以他们宣布了大约500个岗位的裁员，而他们有多少员工呢？5500人。这太疯狂了。我是说，这个公司应该用2000名员工经营吗？好问题。我们已经看到Twitter将员工人数从8000人减少到1500人。当你看看他们管理的应用数量和产品数量与Meta相比，对吧？Meta有更多的应用程序，更多的基础设施。Meta为32亿每日活跃用户提供服务，而Snap则约为4亿。所以Meta的用户是Snap的8倍，拥有更多的应用程序和更多的基础设施。所以我认为这是另一个很好的比率来衡量这两个公司的表现，12倍。你说得对，没错。
The other advantage that Meta has is because they're so profitable, they have the resources to go big in AI. Big time. Which is very expensive. So yeah, so they are the leader. You get all this option value at Meta, which you don't get it snap. There's all this infrastructure that they can leverage much like Amazon did with AWS into things like cloud, AI tools for third party developers, third party applications. And then obviously the, you know, Meta is the biggest advertising platform next to Google in the world now. And there's much more that they can start to do to extend further into the platform. They did get an awesome save. Remember Apple screwed them and was like, you can't track devices now. And like that just took a massive hit in the ad network and it was all those headwinds. They were like, okay, we're just going to use AI to optimize ads. And supposedly the AI optimization of ads, I was talking to somebody on the inside. They said like, yeah, we got it all back. We gained it back. We've got massive AI advertising optimization going on. So totally. Yeah, that's great. That Jim Cook, you know, kicked us in the nuts, but we don't care.
Meta拥有的另一个优势是因为他们非常赚钱，所以他们有能力在人工智能领域大举投资。非常大的投资。而这是非常昂贵的。所以是的，他们是领导者。在Meta，你能获得所有这些选择的价值，而在Snap你得不到。他们有这些基础设施，可以像亚马逊在AWS方面所做的那样，将其应用于云计算、面向第三方开发者的人工智能工具和第三方应用程序。而且很明显，现在Meta是仅次于谷歌的世界上最大的广告平台。除此之外，他们还可以进一步扩展平台。他们确实在逆境中做出了惊人的转变。还记得当时苹果坑了他们，说不能追踪设备了吗？结果他们的广告网络遭受了巨大打击。但他们选择了使用人工智能来优化广告。根据我和内部人员的对话，他们成功地将广告优化回来了。我们现在正在大规模使用人工智能进行广告优化。所以没关系，Jim Cook踢了我们一脚，我们不介意。
By the way, that's a great point, JTAL. It really says a lot about how Meta was able to respond to that change, which a lot of people speculated would destroy the advertising business. And the fact that they were able to engineer solutions to drive advertising revenue up to $40 billion is just mind blowing. It's a really kind of impressive outcome for the team. And I think it speaks a lot to the quality of the engineers there. I think it's a great point.
顺便说一句，JTAL你提出了一个很好的观点。这真的充分说明Meta是如何应对那种可能摧毁广告业务的变化的，许多人都曾猜测会这样。而且他们能够设计解决方案，将广告收入推高到400亿美元，这真的是让人难以置信。这对团队来说是一个相当令人印象深刻的成果。我认为这很大程度上说明了那里工程师的质量很高。我认为这是一个很好的观点。
Yeah. SACs, you tweeted that you're seeing a little SACs bounce back all of a sudden. That's interesting. I am seeing something similar. Last year, last two years, you had a ton of people cutting their SACs spend, maybe removing the number of SACs vendors they had, consolidating vendors. You tweeted many public and private software companies are experiencing accelerating growth after six to seven quarters of deceleration. SACs recession appears to be over according to the SACs master, David SACs.
是的，你发推说你突然看到了一点SACs的回弹。这很有趣。我也看到了类似的情况。在过去的一年或两年里，有很多人削减了他们的SACs支出，也许减少了他们的SACs供应商数量，整合了供应商。你在推特上说，许多公开和私人软件公司在经历了六到七个季度的放缓后，正在经历加速增长。据SACs掌门人David SACs称，SACs的衰退似乎已经结束了。
You want to unpack this for us? What do you say? Well, it's still pretty early because not everyone's reported. But if you looked at the big tech cloud performance in Q4, you could see that there's a bounce back in here. This is NetNew ARR added for AWS Azure and Google Cloud. So you see here in Q4. There's a huge increase in NetNew ARR for the big cloud computing platforms. And then I think another bell weather is Atlassian. So we're still waiting to hear from HubSpot, Salesforce, Zoom, Adobe companies like that. They haven't reported yet. But if you look at Atlassian, it makes JIRA amongst other products. They're based in Australia. Yeah, exactly. Yeah, exactly. Collection of SACs companies, right? It's a collection of SACs products.
你想为我们解读一下吗？你有什么说的？嗯，因为还有人没有报告，所以现在还很早。但是如果你看一下第四季度大型科技云服务的表现，你会发现这里有一个反弹。这是AWS、Azure和Google Cloud新增的净新合同年度再收入。所以你可以在第四季度看到这里大型云计算平台的净新合同年度再收入有巨大增长。然后我认为另一个重要指标是Atlassian。所以我们还在等待来自HubSpot、Salesforce、Zoom、Adobe等公司的消息。但是如果你看一下Atlassian，他们是在澳大利亚设立的，制作JIRA等产品。是的，完全正确，这是一系列的SaaS公司，对吗？是一系列的SaaS产品。
Yeah. NetNew ARR would be the amount of growth in that quarter. And this is on a year over year basis. So you can kind of see, Q4 of 21 was the absolute peak and then plummeted. And then it actually went negative for about a year. That's tough to be in a company with NetNew AR going negative. Yeah. Yeah. It doesn't mean, by the way, the company's shrinking. It just means that the amount of NetNew ARR, which is the amount of growth, is actually smaller than that same quarter a year before. Yeah. And then in Q4, you could see there's some acceleration here that they're starting to add more, they added more NetNew ARR, I guess 33% more in Q4 than they did over the previous year. And part of that SACs is because the comps are lower and they kind of bottomed out. Yeah. They bottomed out and now they're re-accelerating.
是的。NetNew ARR指的是季度增长的金额。这是按照年度基础来计算的。所以你可以看到，21年第四季度是绝对的高峰，然后急剧下降。然后实际上在一年左右的时间内出现了负增长。对于一家NetNew AR出现负增长的公司来说，情况是很艰难的。是的。是的。顺便说一下，这并不意味着公司在缩小。只是意味着NetNew ARR的增长金额实际上比一年前的同一季度要小。是的。然后在第四季度，你可以看到这里有一些加速度，他们开始增加更多的NetNew ARR，我猜比之前一年增加了33%。部分原因是因为比较较低，他们已经触底反弹。是的。他们已经触底反弹，现在正在重新加速增长。
Yeah, it's great. We're starting to see this in some of my board meetings as well, where in 2022, everybody was missing their numbers and re-forecasting down and then they would miss the re-forecast. Yeah. So by 2023, the forecasts were very, very conservative. And I would say, now I'm seeing companies beat the sort of the lower forecasts in Q4. This wasn't happening earlier in the year, but finally, I think people are starting to beat their sort of their lower forecast for Q4. That's the question that I was curious about. What do you actually think is happening? Is that we've re-baseline these businesses? So now what would have looked like just a massive miss over the last two years now look like a beat because we've just completely reset expectations? Is it that or is it that the economy is actually expanding and we can count on some reasonable growth rates? Is it a combo of the two? What do you think it actually is?
是的，太棒了。我们在我的一些董事会会议上也开始看到这种情况，在2022年，每个人都没达到他们的目标并下调了预测，然后他们又没达到下调后的预测。是的。所以到2023年，预测非常保守。我想说，现在我看到公司在第四季度击败了较低的预测。这在今年年初并没有发生，但最终，我认为人们开始超越他们较低的第四季度预测。这是我感到好奇的问题。您认为究竟发生了什么？我们是重新评估了这些企业吗？所以现在，过去两年看起来只是巨大的失误现在看起来是一个胜利，因为我们完全重设了期望值？还是经济实际上正在扩张，我们可以依赖一些合理的增长率？还是两者的结合？您认为实际情况是什么？
Yeah. I mean, it's definitely a new baseline in the sense that, and you can go back to 2020 or 2021, we considered good growth to be two to three X year over year. And now if it's going from 60 to 80% growth year over year, you're happy. So there's definitely been a lowering of expectations. That being said, you still see in these numbers, there has been a bottoming out and we're starting to not grow from this new baseline. So for example, I think with Atlassian here, we are seeing an increase in span basically and in growth. So the way our recession is typically defined is two quarters of negative growth. We had six to seven quarters of decelerating or negative growth. In SAS, in tech. In SAS, which is why I call it the SAS depression or B, that yeah, it was actually kind of a depression, you're right. But now we're seeing quarter over quarter growth. So growth is re accelerating. Growth is higher than it was. So is it going to get to where it was? That probably will take some time, but it feels like the problems in the ecosystem worked themselves out and now we're back to growth again.
是的。我的意思是，就这个意义而言，它绝对是一个新的基准，而且你可以回顾到2020年或2021年，我们认为良好的增长是年同比增长两到三倍。现在，如果年同比增长从60%增加到80%，你会感到满意。因此，人们的期望明显有所降低。话虽如此，我们仍然可以从这些数字中看出，增长已经触底，并且我们正开始不再从这个新基准增长。例如，我认为在Atlassian（一家软件公司）这里，我们看到了跨度和增长的增加。所以我们通常定义衰退的方式是连续两个季度的负增长。在SAS（软件即服务）和技术领域，我们经历了六到七个季度的增速放缓或负增长。在SAS领域，这就是我称之为SAS萧条或B的原因，是的，它实际上有点像是一场萧条，你是对的。但现在我们正看到季度增长。增长正在重新加速。增长比以前更高。那么它会达到以前的水平吗？这可能需要一些时间，但感觉上生态系统的问题已经得到解决，我们又回到了增长轨道上。
Yeah, I can add psychologically because I'm on a couple of SAS boards as well. And psychologically, it felt like you tell me if I'm right, SaaS, if you saw the same thing, there were two years of calling up customers and they were like, we're accelerating vendors and by the way, we did a riff. And so we need 20% less seats. So we're going to have 20% less SAS companies that we're buying from and we're going to have 20% less seats. So you start putting that all together. Man, everybody was just in psychological triage mode. We cannot spend money. I don't want to lose my job. So if you're a procurement person, you're the CTO, you don't want to lose your job. You don't want to have more cuts. So you're like, well, I can cut some software costs. Do I get points for that? The points you would score for the last two years was cutting costs. But the market ripping and you now got a really efficient company, you're like, hey, can we spend a little bit on SAS to make the remaining employees even more productive? Okay, maybe that's a reasonable discussion.
是的，我可以加上心理因素，因为我也在几个SAS论坛上。从心理上来说，如果你看到了同样的情况，两年来我们一直在联系客户，而他们却说我们正在加速供应商，并且顺便进行了重组。因此，我们需要少20%的席位。所以你把这些加在一起，所有人都处于心理治疗模式中。我们不能花钱。我不想失去我的工作。所以如果你是采购人员，你是首席技术官，你不想失去你的工作。你不想再有更多削减。所以你可能会想，好吧，我可以削减一些软件费用。这样我能得到积分吗？过去两年你可以得分的就是削减成本。但是市场在迅速崛起，你现在拥有一个非常高效的公司，你可能会想，嘿，我们能花一点点钱在SAS上，让剩下的员工更加高效吗？这可能是一个合理的讨论。
And then people are playing ball in terms of negotiating prices. So that's the other thing I see is people are like, we'll take your software, but here's what we want to pay. And then they're coming to the board and saying, can we do this deal? It would have been a million dollar deal, but it's a 200,000 dollars. So yeah, take the money. Take the money. Let's bear hug that customer. The market is generally an escalator on the way up and elevator on the way down. So the recovery is going to take a long time. But at least we've bottomed out and we're in recovery as opposed to continuing declines. Yeah.
然后人们在价格谈判中开始玩起了投机游戏。我观察到的另一件事是人们喜欢这样说：“我们会使用你们的软件，但这是我们愿意支付的价格。”然后他们来到董事会问：“我们能达成这个交易吗？”原本可能是一笔百万美元的交易，现在只有20万美元了。所以，是的，收下这些钱。我们要抱紧这个客户。市场通常是上升的扶梯，下降时则像电梯一样迅速。所以恢复需要很长时间。但至少我们已经触底反弹，开始复苏，而不是继续下滑。是的。
By the same token, if you're a startup and you're not seeing improvement in your Q4 sales, then you no longer have a macro excuse for why you're not doing well. Interesting. So in the freeberg you added, you're like, I'll make my own software. You said some SAS software is too expensive. I'll put a developer on it. And so how's that working out for you? Are you still in that mindset of like, yeah, maybe we just build our own software?
同样的道理，如果你是一个创业公司，但是你的Q4销售没有改善，那么你就没有宏观上的借口可以解释你的业绩不佳了。有趣。所以在你追求自由的过程中，你决定自己开发软件。你说有些SAS软件太贵了。于是你找了一个开发人员来开发。那现在情况怎么样了？你还在想着自己建立软件吗？
Yeah. I mean, it's not just us. I think we're seeing a lot of companies pursuing this path. A couple engineers can rebuild the functionality of core applications, particularly because I think if you think about the business model that makes SAS so great is they could value share rather than charge the cost of an engineer plus some margin, the great business model, the equity value that comes in software is you can build something once that creates a hundred dollars of value. You could probably charge your customer $30, $40 for that product because it's saving them $60, $70 and they'll make that switch to software. So the ROI driven value share model in SAS has made it incredibly valuable. The problem now is that an engineer can be hired to build the replacement and so it creates price compression. So the SAS company can no longer capture that much value because the savings is actually less than that because the enterprise might say, hey, I'm going to hire someone and instead of spending 60 grand a year on your software, I'm going to allocate a quarter of an engineer's time to build that software and it's going to replace that cost. So I think that that's still the case. So while there might be bookings, they're still which are driven largely by a search for efficiency gains, a search for more profitability, for more productivity within an enterprise. There are other options for that enterprise to realize that productivity gain today and that's what's going to cause perhaps price compression and more competition than has been the case. But I don't think that the adoption of software is going to slow down. It certainly seems to be accelerating, which is more competitive. We're moving into a hyper competitive market, right? Especially with AI.
是的，我的意思是，不只有我们一个公司在这条道路上追求。许多公司都在追求这个路径。一些工程师可以重建核心应用程序的功能，特别是因为我认为，如果你考虑到使软件即服务(SAS)变得如此伟大的商业模式，它们可以进行价值共享，而不是仅仅收取一个工程师的成本加一些利润，这是一个伟大的商业模式，“股权价值”指的是软件所带来的建设一次，创造一百美元价值的能力。你可以为你的客户收取30、40美元的产品费用，因为这个产品为他们节省了60、70美元，所以他们会转向使用软件。因此，在SAS中，以回报率为驱动的价值共享模型变得非常有价值。但现在的问题是，一个工程师可以被雇来构建替代品，这就导致了价格压缩。因此，SAS公司无法再捕捉到那么多的价值，因为实际上的节省比这还要少，因为企业可能会说，嘿，我要雇用某人，而不是每年花6万美元购买你们的软件，我要将四分之一的工程师的时间分配到建设该软件上，并且它将取代这笔费用。所以我认为这仍然是事实。因此，尽管可能有预订，但这些预订很大程度上是为了寻求效率提升、寻求更多的利润和生产力。但企业在今天有其他选择来实现这种生产力的提升，这可能会导致价格压缩和竞争加剧。但我不认为软件的采用会放缓。它似乎正在加速，这意味着更加竞争激烈。尤其是在人工智能领域。
It's a mix of internal software. It's a mix of internal software. As you guys know, there are very few traditional non tech enterprises now that don't have a software team that can write code. So now that so many companies have software teams that write code, they're all going to be asking the question, should we be buying the software or should we be building something internal? It's a classic buyer build situation.
这是一种内部软件的混合体。正如大家所知，现在很少有传统的非技术企业没有能够编写代码的软件团队。所以现在许多公司都会问自己一个问题，我们应该购买软件还是自己构建内部系统呢？这是一个经典的买还是造的情况。
Let's talk a little bit about VCs and how they're investing in AI. There seems to be three camps shaping up here, Chima. One group is like being competent to going to win. Microsoft Google, Amazon, everybody, they're going to win the day. So they're going to wait and see. Then there's another group who's sitting it out because they're like, hey, open source is going to win. Metas committed to open source and collaborative platforms I've been playing with hugging face with Sundeep as well as you Chima and it's pretty amazing what's happening over there. And then a bunch are obviously placing bets right now. The valuations are absurd. Founders fund and Andreessen Horowitz, two notable firms are approaching it differently.
让我们稍微谈一下风险投资（VC）和它们在人工智能领域的投资。Chima，似乎有三派正在形成。一派认为真正有竞争力的公司会得胜。像微软、谷歌、亚马逊这样的公司，都会取得成功。所以他们选择等待并观望。另一派则选择保持观望，因为他们认为开源技术会胜出。Metas致力于开放源代码和协作平台，我一直在与Sundeep和你Chima一起研究使用hugging face技术，那里正在发生的事情非常惊人。当然，还有一批正在现在下注的投资人。估值已经变得荒谬。Founders Fund和Andreessen Horowitz是两家知名的风险投资公司，它们在对待人工智能的投资上采取不同的方式。
Founders fund bought into open AI at a $29 billion valuation. But aside from that investment, they're generally avoiding the AIDLs. On the other hand, Andreessen is betting heavily. Real AI, Replit, 11 Labs, Mishro. You're also in Replit, Saks. So what do you think is open source going to win the day? You've been picks and shovels the whole way. You've been talking about compression. Maybe this is an actually a good market. What you're thinking as a capital allocator, Chima? I think foundational models will have no economic value. I think that they will be an incredibly powerful part of the substrate and they will be broadly available and entirely free. Wow. If you think about that, any closed model, especially a closed model that operates on the open internet is not very valuable. And any open source model that trains on the open internet will make that so. So in that world, things like Mistral and Lama will essentially decay the market to zero.
创始人基金以290亿美元的估值入股了open AI。但除了这项投资，他们一般会避免AIDL领域的投资。另一方面，安德里森则大举押注。Real AI、Replit、11 Labs、Mishro。你也在Replit工作，Saks。那么你认为开源会赢得胜利吗？你一直在挑选和铲子开荒。你一直在谈论压缩。也许这实际上是一个好市场。作为资本配置者，你怎么想，Chima？我认为基础模型没有经济价值。我认为它们将成为基础设施的一个极其强大的部分，将广泛可用且完全免费。哇。如果你想一想，任何封闭模型，特别是在开放互联网上运作的封闭模型，都不是很有价值。而任何在开放互联网上训练的开源模型都将使其如此。因此，在这个世界中，像Mistral和Lama这样的东西将会使市场归零。
So if you're looking at any economic value that has been captured up until today, if it has been captured by having a proprietary closed model trained on open data, that economic value will go away. And I think Google and Microsoft and Facebook and Amazon and all these startups have a deep economic incentive actually to make that so. So now you can evaluate what that means. So if you get an open model from Hugging Face, that's just kickass, where do you spend money? Well, you're going to have to spend money to actually train it, to fine tune it, maybe to have some pretty zippy inference. And all of that means that there's a new kind of substrate that has to be built, which is all around the way that the tokens per second are provisioned to the apps that sit on top of the model. What that means is you need to go back to 2006 and 2007 and say, okay, when we first created the cloud, who made money? And fast forward 18 years later, it's the same people that are still making money.
所以，如果你关注到目前为止所获取的任何经济价值，如果是通过使用专有闭源模型训练开放数据来获取的，那么这个经济价值将会消失。而且我认为，谷歌、微软、Facebook和亚马逊以及所有这些创业公司实际上有很大的经济动机来实现这一点。现在你可以评估一下这意味着什么。所以，如果你从Hugging Face获得了一个开放模型，简直棒极了，你会花钱在哪里呢？嗯，你将不得不花钱来真正训练它，微调它，也许还要进行一些相当迅速的推理。所有这些都意味着必须建立一种新的基础设施，它围绕着每秒标记（tokens）的供应向模型顶层的应用以及它们所依赖的应用构建。这意味着你需要回到2006年和2007年，问问自己，当我们第一次创建云时，谁赚钱了？快进到18年后，仍然是同样的人在赚钱。
So the people that made money in 2006 and seven were Amazon principally because of EC2 and S3. The perfect analogy of EC2 and S3 in 2024 is the token per second provider. Now there you have to double click and say, okay, well, what does a token per second provider need to do to make a lot of money? And I think the ultimate answer is you need your own proprietary hardware. So who is in a position to do that? Amazon has announced that they have an inference and training solution for training. Soreebras has announced a pretty compelling solution. Google obviously has TPU. Then there's a handful of startups, including one that I helped get off the ground in 2016 that I funded called Grock. All of those companies are in a position to build a token per second service. Then you have companies like Together AI, which basically just go and take venture money and wrap NVIDIA GPUs. And you can debate what the advantage will be there. One could say, well, it's not really a huge advantage over time.
因此，在2006年和2007年赚钱的人主要是亚马逊，因为EC2和S3的存在。在2024年，EC2和S3的完美类比是每秒创建的令牌提供商。现在你要双击并问，好吧，一个每秒创建的令牌提供商需要做什么才能赚很多钱呢？我认为最终答案是你需要自己的专有硬件。那么谁有能力这样做呢？亚马逊宣布他们有一个推理和训练解决方案。Soreebras宣布了一个非常吸引人的解决方案。谷歌显然拥有TPU。然后还有一些初创公司，包括我在2016年资助帮助起步的一家叫做Grock的公司。所有这些公司都有能力建立每秒创建令牌的服务。然后还有一些像Together AI这样的公司，他们只是去拿风投资金然后包装NVIDIA的GPU。关于那里的优势是什么，人们可以争论不休，有人可能会说，它并非长期来说真的有很大的优势。
So my refined thoughts today are sort of what my initial guess was when we started talking about AI a year ago, which is the picks and shovels providers can make a ton of money. And the people that own proprietary data can make a ton of money. But I think open source models will basically crush the value of models to zero economically, even though the utility will go to infinity, the economic value will go to zero. Did any of you guys see Chemox interview with Jonathan Ross? No, no, yeah. You put it out right, Chemox. You made it public. I did it just for my subscribers, but Jonathan is the founder and CEO of Grock, the company that I just mentioned. And the quick version of that story is I would pour over the Google earnings results in the mid teens of 2000, because I was pretty actively investing in a bunch of different public equities.
所以，今天我经过思考得出的结论与我们一年前讨论人工智能时的初步猜测相同，那就是提供工具和平台的供应商可以赚很多钱。拥有专有数据的人也能赚很多钱。但是我认为开源模型将会将模型的经济价值压缩至零，尽管其效用会达到无限，经济价值却趋近于零。你们中有谁看过Chemox对Jonathan Ross的采访吗？哦，没有，对了，Chemox。你公开发布了吧。我只是为了我的订阅者而做的，但是Jonathan是Grock公司的创始人兼首席执行官，这个公司我刚刚提到过。故事的简短版本是，我在2000年中期密切关注谷歌的盈利结果，因为我当时在积极投资各种公共股权。
And Sundar said in a press release, he mentioned that they had rolled their own silicon for machine learning, called TPU. I was like, what is going on? That Google thinks that they can actually roll their own silicon? What must they know that the rest of us don't know? And so it took me about six or nine months, but through Sunny, I got introduced to Jonathan and then we were able to get Jonathan to leave Google and he started and he, Jonathan, was the founder of TPU at Google. And then he started Grock, which I was able to lead that funding round in 2016, so eight years ago.
在一份新闻发布会上，Sundar提到他们已经为机器学习自主研发了自己的硅芯片，名为TPU。我当时很惊讶，谷歌居然认为他们能够自行开发硅芯片？他们究竟知道了什么，我们其他人不知道的东西？于是，经过六到九个月的时间，通过Sunny的介绍，我结识了Jonathan，然后我们成功地让Jonathan离开谷歌，并在2016年启动了Grock。而Jonathan是谷歌的TPU的创始人。然后他开始了Grock，而我在2016年为该公司领导了融资轮，也就是八年前。
Anyways, I did a spaces with Jonathan talking about the entire A.I. landscape and A.I. acceleration to my subscribers, but it was so good. I got to say he is, he was so impressive that we kind of like figured out a way to just play the space and tape it and then we published it to everybody. So it's on, it's on my Twitter for anybody that wants to listen to it. It is awesome. Amazing. He is really impressive. I was sitting on the 17 going to Santa Cruz, not moving for an hour and a half and I listened to it. So I kept me alive, but I thought it was really great. Yeah. He's great. No, he's great. He's great insights. And I think he's very compelling in arguing why some of the big cloud providers today that are offering infrastructure for A.I. model training and inference are going to be challenged if someone can build full stack and do it successfully. So it was a really good interview. I actually think it's really worth listening to. But I enjoyed it.
不管怎样，我和乔纳森讨论了整个人工智能领域和人工智能加速的问题，我把这个对话分享给了我的订阅者们，但效果非常好。我必须说他，他非常令人印象深刻，我们想出了一种方法将这个对话记录下来，并发布给大家。所以现在我的Twitter上有这个对话，任何人都可以去听。真是太棒了！他真的很厉害。我当时在17号路上去圣克鲁斯的路上动弹不得坐了一个半小时，但我在那边听了整个对话。这让我保持了活力，我觉得真的很棒。是的，他很厉害。不，他很厉害。他给出了很有见地的观点。而且，他还以很有说服力的方式论证了为什么现在一些提供人工智能模型训练与推理基础设施的大型云服务提供商，如果有人能够成功构建全栈，他们将会面临挑战。所以这次采访真的很好。我真的觉得很值得一听。但我很喜欢这个采访。
Yeah, thanks for putting it out there. I was like literally just sitting in the car, browsing Twitter and I saw your thing and I clicked on it and I just ended up listening. Yeah, it was a little hard actually. When you do a space for your subs, you can't actually just flip a switch and then release it to all of your followers. So we actually had to literally play it and then just capture the audio out and then republish it. But anyways, despite that inconvenience, if anybody's interested in learning about A.I. hardware, he is very compelling and he's very educational. So sacks your thoughts on just how you're approaching investing in A.I. if you're specifically investing in the underpinnings of A.I. picks and shovels, yada yada, or if you're just looking on the application level and it's that kind of approach.
是的，谢谢你把它发布出来。我当时正在车里，浏览推特，看到了你的东西，就点了进去，结果就一直听下去了。嗯，实际上有点困难呢。当你为字幕设置了一个片段时，你不能只是轻轻一按就把它发布给所有的关注者。我们实际上必须要播放它，然后将音频捕获并重新发布。但是无论如何，尽管有这种不便，如果有人对了解人工智能硬件感兴趣，他的演讲非常有吸引力和富有教育性。那么，对于你在投资人工智能的方式，你是专注于投资人工智能的基础技术还是只看应用层面，你有什么想法？
Well, we divided it the space into three categories. One is the models themselves, the foundation models, which can be either open source or closed source. There's infrastructure. So like Jamal saying, it could be like model training. It could be vector databases, tools that developers use to create the A.I. stack typically inside their enterprise. And then the third would be applications, which can be things like copilot or it could be a pre-A.I. app that's using A.I. to kind of turbocharge its capabilities. Yeah. Most SaaS would be in the application bucket. And so that's principally where we're focused. Although we do look at infrastructure plays and models.
好的，我们将其空间分为三个类别。第一个是模型本身，即基础模型，可以是开源的，也可以是闭源的。第二个是基础设施。就像贾迈勒所说，它可以是模型训练，可以是向量数据库，可以是开发者在企业内部使用的用于创建人工智能堆栈的工具。第三个是应用程序，可以是像合作伙伴或者是使用人工智能来提升能力的预先存在的应用程序。是的，大多数SaaS都在应用程序类别中。因此，那是我们主要关注的地方，虽然我们也会关注基础设施和模型。
However, I do think there is an argument for, I mean, really with the question of commoditization, well, like all the model companies just get totally commoditized. Well, really, we're talking about open A.I. These are the leader. So the question is, can they maintain their lead? I do think there is an argument that open A.I. will stay in the lead and actually do quite well. And I think there's a few points there. One is that if you're a consumer, you just want to use the best GPT. You want to use Google? It's just like search, right? If Google is a little better or the perception is a little better than Bing or the other search engines, you don't win a plurality of search traffic. You actually end up winning it all because consumers just want the very best one. So most of the tests show that open A.I. is still ahead of the open source models. And I think even people in the open source movement will tell you that open A.I. is called six months ahead. They have no doubt that open source will get to where open A.I. is now in six months. Nonetheless, if open A.I. just maintains a little bit of a lead over open source, then it could compound. Yeah, it could basically win the vast, vast majority of the call of consumer search or consumer GPT market. So that's point number one.
然而，我确实认为有一个论点，就是说在商品化的问题上，所有的模型公司都变得非常商品化。而我们正在讨论的是OpenAI，他们是领导者。那么问题是，他们能够保持领先地位吗？我确实认为OpenAI将保持领先地位并取得很好的表现。我认为有几个观点可以支持这一点。首先，作为一个消费者，你只想使用最好的GPT。你想使用谷歌吗？就像搜索一样，对吧？如果谷歌稍微好一点，或者在人们心中的印象稍微好一点，你就能赢得大量的搜索流量。因为消费者只想要最好的一个。所以大多数测试显示OpenAI仍然领先于开源模型。而且我认为即使是开源运动中的人也会告诉你，OpenAI比开源领先六个月。尽管如此，如果OpenAI仅仅保持对开源的一点点领先，那么这个差距就会逐渐增大。是的，它可能赢得绝大多数消费者搜索或GPT市场。这就是第一点。
Point number two is now that open A.I. has these hundreds of millions of consumers using it. And it's a pretty attractive audience for developers to want to reach. And open A.I. has done a really good job creating a platform for developers to create what are called custom GPTs. So most developers don't want to go through the hassle of training a model, fine-tuning a model, doing all of that work that you would have to do in the open source ecosystem. They just want to point chat GPT at a repository of data or documents information.
第二点是现在OpenAI已经有了数亿用户使用它。对于开发人员来说，这是一个非常有吸引力的受众群体。而且OpenAI在为开发人员创建自定义GPT（通用预训练模型）方面做得非常好。因此，大多数开发人员不想经历在开源生态系统中训练模型、微调模型以及所有可能的繁琐工作。他们只是希望将Chat GPT指向一个数据或文档信息的存储库。
Have it learn what it needs to learn, fine-tune it in that way, maybe add some lightweight functionality using open A.I. platform to create a custom GPT. That's what I think most developers want is they just want a simple stack to work with. And they're going to prize, again, simplicity and the power of the developer tools over the theoretical control they get by rolling their own models, training and functioning their own models in open source.
让它学习它需要学习的东西，以此来调整它，或许使用开放的人工智能平台添加一些轻量级的功能，来创建一个定制的GPT模型。我认为大多数开发者希望的就是一个简单易用的技术栈。他们更看重的是简洁性和开发者工具的功能性，而并非通过自己构建、训练和操作模型来获得理论上的控制权。
And so I think what you're seeing now is how many custom GPTs have already been created on the platform? I mean, that might be tens of hours. I mean, there's so many millions. Yeah, it's so easy to create them. So you have a classic developer network effect where you've got open A.I. aggregating hundreds of millions of consumers because they perceive that chat GPT is the best. And you've got developers wanting to reach that audience. So they build custom GPTs on the open A.I. platform. That actually gives chat GPT more capability. Yeah. And that's something that open source can't easily catch up with.
所以我认为你现在看到的是平台上已经创建了多少定制的GPT？我的意思是，可能有数十个小时。 我的意思是，有那么多百万个。是的，创建它们非常容易。因此，你有一个经典的开发者网络效应，即OpenAI正在聚集数以亿计的消费者，因为他们认为Chat GPT是最好的。而开发者则希望触达这个受众。因此，他们在OpenAI平台上构建了定制的GPT。这实际上为Chat GPT提供了更多功能。是的，这是开源所难以追赶的。
Well, actually, actually, it's not just the point. So yeah, so it is a flywheel where, you know, a classic operating system developer network effect where you want to use the operating system that is the most programs written for it. Yeah. So interestingly, hugging face has realized this and hugging face released this week, their own version of GPTs, which is really interesting.
实际上，并不仅仅是这一点。是的，它是一个类似于飞轮的东西，你知道，传统操作系统开发者的网络效应，你想要使用那些有最多程序适配的操作系统。有趣的是，Hugging Face已经认识到了这点，并且在本周发布了他们自己的GPT版本，这真的很有趣。
And you can pick sacks, which open source project you want to use to make it. So unlike GPTs on chat, GPT, we have to pick theirs on the hugging face one, you could pick, you know, llama or whichever one you want. There's an account called artificial analysis that you can follow.
你可以选择一个开源项目来创建它，比如chatGPT就必须选择hugging face上的，但你可以选择任何你想要的，比如llama。还有一个名为artificial analysis的账号，你可以关注。
The thing to keep in mind, Saks, is that for any of this to be true, these APIs need to be usable. I mean, I don't know if you remember, but when we were building apps, even as back as the late 2000s and early 2010s, one of the things was there was a pretty important paper that was published by Google about attention span. And it would look at page load times in a cold cash environment, right?
Saks，要记住的是，为了让这些说法成立，这些API必须是可用的。我的意思是，我不知道你是否还记得，但当我们构建应用程序时，即使是在2000年以后，2010年代初，Google发布了一篇关于注意力持续时间的重要论文。它会考虑在冷启动环境下的页面加载时间，对吧？
And it basically said you have to be at like 150 milliseconds, right? That's like best in class performance or faster. And I remember when we read that at Facebook, we went crazy. So much so that at one point, a small team and I kind of actually launched a stripped down version of Facebook to compete with Facebook. If there's a Nick, you can probably find this article on TechCrunch and we did it without telling everybody was called like Facebook zero.
基本上，它说你必须要在150毫秒左右的速度上才行，对吧？那意味着要达到最佳的性能水平或更快。我还记得当我们在Facebook阅读到这一点时，我们都兴奋得不行。甚至有一次，我和一个小团队实际上推出了一个简化版的Facebook，与Facebook竞争。如果有一个Nick，你可能可以在TechCrunch上找到这篇文章，我们在未告知其他人的情况下实现了这个，它被称为Facebook Zero。
Anyways, the point is speed matters because in the absence of having very snappy response, you could have the best model in the world. But if it takes 10, 20, 30 seconds to basically initiate and get back data from a fetch request, it's an impossible thing to do.
无论如何，关键是速度很重要，因为如果没有非常迅速的反应，你可能拥有世界上最好的模型。但是，如果从获取请求开始到获取返回数据需要10、20、30秒之久，那就是一件不可能的事情。
So I think one of the things that you have to keep in mind is that there are these two things that need to move at the same time. One is the quality of how the model is, but two is the speed and its responsiveness, which is a function of, again, hardware and your ability to basically tokenize tokens per second very, very quickly.
我认为你需要记住的是，有两个需要同时提升的方面。首先是模型的质量，其次是速度和响应性，这取决于硬件以及你快速分词化的能力。
So that developers are incentivized to not just play around in a sandbox, but to actually build production code. And I don't think we've seen that second thing happen because nobody is delivering it. And that's the big thing that nobody talks about.
为了鼓励开发人员不仅仅在沙盒中玩耍，而是真正构建产品代码。我认为我们还没有看到第二点的发生，因为没有人在提供这个。而这就是没有人谈论的重要问题。
For example, like AWS, if you look inside of how expensive it is to build an app there, I've tried, even when they give you credits, the credits they give you aren't sufficient enough to even pay for half the power. And then the way that they schedule and the way that they try to orchestrate you to use hardware makes building production apps unless you are willing to spend millions and millions of dollars for a very slow app, unfeasible.
举个例子，就像AWS一样，如果你了解在那里构建一个应用程序的费用有多高，我试过了，即使他们给你优惠额度，但这些优惠额度根本不足以支付一半的费用。而且他们安排使用硬件和编排你使用硬件的方式，使得除非你愿意花费数百万美元来构建一个非常缓慢的应用程序，否则构建生产应用是不可行的。
And so if you go back to a startup economy raising money here, the venture investor should start asking the question, well, what is the speed and usability of these services that I'm funding? And the reason is because you could build the best experience in the world that runs on local hosts.
所以，如果你回到一个创业经济体中，筹集资金，风险投资者应该开始问自己一个问题：我正在资助的这些服务的速度和可用性是如何的呢？原因是因为你可以构建世界上最好的体验，但这只在本地主机上运行。
But if all of a sudden you actually try to launch it as an app and the thing takes 35 and 40 seconds to generate something, it's DOA. And I don't think enough people ask those questions or understand that that's true.
但是，如果突然间你真的试图将它作为一个应用程序启动，而生成某些内容需要35到40秒的时间，那将是一个死胎。而且我认为没有足够多的人提出这些问题或者理解这是事实。
So this is why I think you have to sort of be looking at both of these two things at the same time. But this account is interesting because it kind of just strips things down to the bare facts and they start to allow you as a third party to understand what you can do. Yeah, speed is just such a critical component of this. And what Google found was, as you know, free brokers, you were there every time they lowered a certain number of milliseconds usage went up, right?
所以这就是为什么我认为你必须同时关注这两个因素。但这个账户有趣的地方在于，它将事情简化为基本事实，并让你作为第三方能够理解你可以做什么。是的，速度在这里非常关键。而谷歌发现的是，当他们降低了一定毫秒数时，你知道的，免费经纪人的使用量就增加了，对吧？
People did more searches, which makes sense. If you get your results back faster. Yeah, it was a key metric from day one at Google, Marissa Mayer, she ran all the consumer facing products at Google during this, you know, earlier era. She was like beat it into the team. I mean, if you guys remember one of the first, the, the first kind of early feature of the Google results page was the amount of time it took to load the results. They'd show you how many milliseconds you show you that. Yeah, they literally put your North Star metric exposed to the consumer, which code. That must a little fire under the asses of all the develop versus server people.
人们进行了更多的搜索，这是有道理的。如果你能更快地获得搜索结果。是的，这是Google从一开始就关注的关键指标。Marissa Mayer在这段时期负责Google的所有面向消费者的产品。她坚持要求团队做到这一点。我的意思是，如果你们还记得Google搜索页面最早的一个特点，就是加载结果所需的时间。他们会向你显示需要多少毫秒。是的，他们实际上将你的北极星指标暴露给了消费者，这是种怎样的代码。这必定在开发人员和服务器人员中点燃了他们的斗志。
Well, I mean, they were kind of showing off the quality of the infrastructure and the way they did indexing and everything. But the result.
嗯，我的意思是，他们有点炫耀基础设施的质量以及他们进行索引等一切工作的方式。不过结果却有些让人失望。
Really played out in usage, the faster the results, the more frequently you would use the search engine and the more likely you were to come back. And it's amazing how much consumer behavior drifts based on milliseconds. Like you have a few milliseconds. Yeah. I mean, if you look at the, if you ever see the movie, the founder, where they explain the McDonald's process, they learned it to guys look at this. This is really interesting on this analysis.
在使用中真的玩烂了，结果越快，你就会越频繁地使用搜索引擎，并且越有可能再次回来使用。令人惊讶的是，消费者行为在毫秒级别的差异下会有多大的漂移。比如你只有几毫秒的时间。是的。我的意思是，如果你看过电影《创办人》，他们解释了麦当劳的流程，你会发现这个分析真的很有趣。
I mean, Chamath, are you saying that you don't think open AI can achieve the necessary levels of performance? No, I'm saying two things. Open AI is three different businesses. Open AI has a closed model that's trained on the open internet. I think economically it's going to be very hard to sustain that unless they start buying all number of apps so that they can get some fine tunes that they control that are proprietary to them.
我的意思是，Chamath，你是在说你认为Open AI无法达到必要的性能水平吗？不，我是说两件事情。Open AI是三个不同的业务。Open AI有一个在开放互联网上训练的封闭模型。我认为从经济上来说，要支持这一点非常困难，除非他们开始购买各种应用程序，这样他们就可以得到一些他们专有的、能够由他们控制的微调。
So for example, if open AI were to buy all of Reddit, that would be a really interesting development that would improve the quality of open AI in a unique and differentiated way relative to where things like llama and mr. We'll get to at the same time as well as X is grok. I think they're all going to converge to the same quality in the next probably 12 to 18 months. That's point number one.
举个例子，如果Open AI购买了Reddit的全部股份，这将是一个非常有趣的发展，将以一种独特和区别性的方式提高Open AI的质量，相对于像llama和mr.以及X is grok这样的产品。同时，我认为它们将在接下来的12到18个月内趋于同样的质量水平。这是第一点。
Your belief there is there's enough data in those pools that everybody reaches parity. No, did you guys, okay, Nick, did you so I published this primer on every primer? There is a slide in their neck that you can pull out, but it just shows you that there is a converging in the quality of the results as the number of the parameters of the model gets higher and higher. And what it effectively shows you is that we are already in the land of diminishing returns when models are trained on the same underlying data.
你们的信念是这些信息库中有足够的数据让每个人都能达到平等。不，你们，好吧，尼克，你们有没有看到我在每一个入门教程中发表的内容？其中有一张幻灯片可以展示出，但它只是告诉你随着模型参数数量的增加，结果的质量会趋于一致。而这实际上向我们展示的是，当模型在相同的基础数据上进行训练时，我们已经陷入了收益递减的领域。
So if you are using the open internet, llama, mr. We'll open AI. They're all getting to the same quality code point and they will be there within the next six to nine months. So that's business number one on open AI. Business number two is a consumer facing app called chat GPT. That has a lot of legs because I think people are, you know, develop habits. It'll be very sticky and I think it'll get better and better.
所以，如果您正在使用开放的互联网，llama先生，我们将使用Open AI技术。它们都将达到相同的优质代码水平，并将在接下来的六至九个月内实现。所以这就是Open AI的第一个业务。第二个业务是一个面向消费者的应用程序，名为chat GPT。这个应用有很大的潜力，因为我认为人们正在培养习惯。它将非常有吸引力，而且我认为它会越来越好。
And then the third business that they're in is selling enterprise services to large fortune 500s. In fact, if you look at their open AI day, what they talk about is they sell, they've sold already to like 94% of the fortune 500. What does that mean? I think what that actually means is they've sold a lot of test environments and sandboxing. But again, in order to translate that into functional production code that's used by Bank of America, right, or Boeing in production, you have to have zippy, zippy fast SLAs and a level of performance that no cloud providers are in the world.
然后他们第三个业务是向财富500强的大型企业销售企业服务。实际上，如果你看看他们的开放AI日，他们所谈论的就是他们已经向94%的财富500强企业销售过。这意味着什么？我认为这实际上意味着他们已经销售了许多测试环境和沙盒环境。但是，为了将其转化为银行美国或波音等企业在生产中使用的功能性代码，你需要拥有非常快速的SLA和世界上任何云服务提供商都无法匹敌的性能水平。
Cloud provider yet has delivered. None, nobody. So Nick, if you just go to that, please, the thing, I just wanted to show you this because it's really interesting. Sure, this is not mine. This is theirs. If you look at quality versus price tax, it starts to start to show you like, where do you want to be? You want to be in the upper left quadrant in their analysis, right?
云服务提供商尚未交付。没有任何一个，没有任何人。所以Nick，如果你只是去看看那个东西，我只是想向你展示这个因为真的很有趣。当然，这不是我的，是他们的。如果你看看质量对价格的税收，它开始展示给你，你想要在哪里呢？你想要在他们的分析中处于左上象限吗？
And so the point is what you can see is that a ton of different models are getting to this same place. And so obviously you'd want to use the model that's the cheapest or most convenient. Well, who's going to pay for that? If you and your LPs want to pay for that, the person that figures out the way that it's the cheapest to give you the same answer will actually end up winning because you will run out of money and they will not.
所以问题是，你可以看到有很多不同的模型都达到了相同的地点。显然，你会希望使用最便宜或最方便的模型。那么，谁来付钱呢？如果你和你的有限合伙人愿意支付费用，找到最廉价的方式来给你相同的答案的人实际上会成为赢家，因为你会用光钱，而他们不会。
I don't know. I mean, I think that there's a lot of business problems inside companies where people just want to very quickly set up their own, again, custom GPT without having to go through the business. Without having to go through the time, the cost, the hassle of trying to do model training or fine tuning.
我不知道。我的意思是，在公司内部存在许多业务问题，人们只是希望能够非常快速地自己搭建自己的定制GPT，而无需经历企业方面的流程、时间、成本和麻烦，例如模型训练或微调。
So let's just back up. Here's the path that OpenAI is on. So step one, get hundreds of millions of consumers using it and getting them to view OpenAI or CHAT GPT as the Google in this area. Right? Strong presumption. This is just the one you go to when you have a question.
好的，让我们来回顾一下。这是OpenAI迈出的道路。第一步是让数亿消费者使用它，并让他们将OpenAI或CHAT GPT视为这一领域的谷歌。对吧？这是你遇到问题时去的首选。
Step two, these same people, these same consumers now want to use CHAT GPT at work because there's some research they want to do. So OpenAI has just rolled out both enterprise licenses and teamwork spaces. So you can work collaboratively on the same queries in a teamwork space.
第二步，这些同样的人，这些同样的消费者现在想要在工作中使用CHAT GPT，因为他们想要进行一些研究。因此，OpenAI刚刚推出了企业许可和团队协作空间。这样，您可以在团队协作空间中共同处理相同的查询。
Step three is rolling out a very easy use dev platform that allows developers to, again, create custom GPTs by just pointing OpenAI at repositories. Okay. And so let's say that you are the customer support team and you want to create a GPT to help customer support answer cases. You could basically then train CHAT GPT on, let's say, every customer support ticket and email that the company has ever produced. Right? Now, you could wait for the company's IT department to get its act together and figure out how to train an open source model on the same thing. But do you really want to wait for that or do you just want to get going? And now OpenAI has given you the enterprise license that you need to pacify the concerns about security and privacy and all that kind of things. To some degree, there's always going to be those super paranoid Fortune 500 companies that will insist on owning everything and doing it open source.
第三步是推出一个非常易于使用的开发平台，使开发人员能够再次通过指向存储库来创建自定义的GPT。好的。所以，假设你是客户支持团队，并且你想创建一个GPT来帮助客户支持回答问题。然后，你可以训练CHAT GPT，例如使用公司曾经生产的每个客户支持票和电子邮件。对吧？现在，你可以等待公司的IT部门整合并弄清楚如何在相同的事情上训练开源模型。但是你真的想等吗，还是只想开始进行？现在OpenAI已经为您提供了所需的企业许可证，以缓解安全和隐私等方面的担忧。在某种程度上，总会有那些极度多疑的财富500强公司坚持拥有一切并采用开源方式做事。
Let me build on your example. So I run a small software company during the day called Hustle. And we saw a lot of tickets related to this specific legislation that exists whenever you're texting or you're doing auto dialing stuff called 10 DLC. And so we wanted to eliminate those tickets, right? So I actually went and I built a GPT, which was called the privacy policy generator because a lot of these trouble tickets were because the privacy policies were bad. And we trained them using a handful of ones that were good and a handful of ones that are bad with a bunch of rules. And I trained them all. And it's wonderful, except I can't run it in production because it's not the kind of thing that is usable in that way right now. It's still very difficult.
让我以你的例子为基础来解释一下。白天我经营一家名为Hustle的小软件公司。我们遇到了很多与特定立法相关的问题，这个立法与你发送短信或进行自动拨号时所称的10 DLC有关。因此，我们希望消除这些问题。所以我实际上构建了一个名为隐私政策生成器的GPT，因为很多这些问题是由于隐私政策不好所导致的。我们使用了一些好的和一些不好的样本以及一些规则来进行训练。训练结果非常好，但我无法将其投入生产，因为它目前还无法以这种方式使用，仍然非常困难。
And so all I'm saying is I'm happy to keep spending a few hundred dollars a month, a few thousand bucks a month, whatever it is that I'm spending. I don't quite exactly know. And I agree with you. It was very easy. I think opening eye does an excellent job of getting off the ground. But what I'm also saying is that when you actually translate that into a mainline use case, right, where I want to now give it to my support team and say this is now a tool you can rely on. It's integrated into your workflow, into your other tools. It's integrated into how you pipe out data into Salesforce or what have you. It's just very hard. And I'm not saying it's not going to get fixed. I'm saying we're just not buried yet. And one of the rays in which it's not there is that there is no place I can go, including open AI, that actually makes it fast enough to be usable in production.
所以我想说的是，我很乐意每个月花几百美元，几千美元，无论我花了多少我也不太确定。我同意你的观点，它非常容易上手。我认为Opening Eye在启动方面做得非常好。但我想说的是，当你把它应用到主流场景中，比如我现在想把它交给我的支持团队，并告诉他们这是你们可以依赖的工具。它整合到了你们的工作流程和其他工具中。它整合到了你们将数据导入Salesforce或其他工具的方式中。这真的很难。我并不是说它不会得到修复。我只是说我们还没有完全解决这个问题。而其中一个问题就是，包括Open AI在内，没有一个地方能够使它的速度足够快，以便在实际生产中使用。
You wrote this on open AI stack. You wrote a custom GPT. Yeah, built myself. Yeah. And you can do the monohugging face now. It's going to be a lot of options. In terms of integrating into your workflows, I think it's a really interesting point because I saw a demo somewhere where now, actually, I think open AI announced this, that you can at mention a custom GPT. Yeah. Yeah. Sunny showed me that this week on the part. Yeah. In chat GPT, you can now at mention a custom GPT to kind of invoke it. Yeah. So how it works is you would say, hey, I'm heading to New York. What flights can I get at Expedia, at kayak, whatever? And then it gives you, you know, the results here. And you're kind of pulling that up.
你在OpenAI堆栈上写了这个。你自己构建了一个定制的GPT。是的，是我自己做的。是的。现在你可以使用单臂拥抱的表情了。选项会很多。关于将其整合到你的工作流中，我认为这是一个非常有趣的点，因为我在某个地方看到了一个演示，现在我想OpenAI已经宣布了这一点，你现在可以@提及一个自定义的GPT。是的。是的。Sunny本周在视频中向我展示了这一点。是的。在Chat GPT中，你现在可以@提及一个自定义的GPT来调用它。就是这样的工作原理：你会说，嘿，我要去纽约，我能在Expedia、kayak或者其他地方找到什么航班？然后它会给你这里的结果。你会提取这些信息。
Just to the point about where data advantages lie, and that's ultimately going to drive value. I cannot. I've tried to think a lot about this. I cannot think about a better data advantage that is orders of magnitude better than anything else. Say YouTube, say YouTube. Yeah.
关于数据优势所在的观点，简单来说，它将最终推动价值的提升。我无法找到更好的数据优势，它可以比其他任何东西更加卓越，尽管我已经努力思考了很多次。以YouTube为例，就拿YouTube来说吧。是的。
It is tricky. So here's the numbers. I pulled this up. You guys know like GPT three and three and a half were trained with a heavy waiting on common crawl, which is this open source. Yeah, we talked about this before. Kill all that runs it. Open source. Crawling of the web, the total amount of data in common crawl, which I think accounted and I could be off on this something like 40 to 60% of the waiting in GPT three or three, five. I'm off on this probably. So the total amount of data in that common crawl data set is about 10 petabytes. Okay.
这有点复杂。这些是数字。我找到了它们。你们都知道像GPT三和三点五这样的东西是通过对Common Crawl进行大量训练得到的，这是一个开源项目。是的，我们之前谈过这个。是由Kill All维护的开源项目，用于对网络进行爬取。Common Crawl数据集中的数据总量约为10个拍字节，我可能不太准确。
Based on YouTube's public statement recently, they're seeing about 500 hours a minute of video uploaded or 720,000 hours a day. And if you assume somewhere between, you know, just under 1080p on that video, we're talking about probably one to two petabytes of data being uploaded to YouTube her day. So if you assume like over time, the definition of the videos gone gotten better and the amount of uploads gone up, you could probably assume that there's roughly, I'm guessing, there's probably somewhere between 2000 and 3000 petabytes of data in YouTube growing by one to two petabytes per day, which makes YouTube data repository 300 times larger than common crawl, which makes it bigger than anything else that anyone else has.
根据YouTube最近的公开声明，他们每分钟上传约500小时的视频，即每天上传720,000小时的视频。而且如果你假设这些视频的分辨率在刚好低于1080p之间，那么每天上传到YouTube的数据量可能达到1到2个拍字节。因此，如果你认为随着时间推移，视频的清晰度提高了，上传量增加了，你可以推测YouTube大约有大约2,000到3,000个拍字节的数据，并且每天增长1到2个拍字节，这使得YouTube的数据存储库比常见的网络抓取（common crawl）大300倍，比其他任何人（公司/组织）拥有的任何其他数据集都要大。
And here's the amazing thing about it. It has video. It has image. It has audio. It has text. It has everything. And it is growing. So if you were to take a bet or build a thesis around this point that the data advantage is going to drive value creation, if Google gets its act together and leverages the data repository at YouTube, it is an insurmountable moat that will only continue to extend because the quality of the YouTube experience and the network effects continue to accumulate for them.
这件事还有一个惊人之处。它包含视频、图像、音频和文本等各种元素，应有尽有。而且它还在不断增长。所以，如果你要打赌或者建立一个关于数据优势将推动价值创造的观点，假如谷歌能够整合并充分利用YouTube的数据仓库，这将构筑起一道无法逾越的壕沟，而且随着YouTube体验的提升和网络效应的积累，它只会不断扩大。
So I think it's the most valuable asset in the world today based on this thesis that AI value is going to accrue to the data on it. I think you're making such an important point. This is why the counterfactual is true and it's actually showing up in the data. And Nick will show you this slide again from the AI primer. But that is why we're seeing these diminishing returns for you, in all of these third party benchmarks of these models. It's all using the same data set.
所以我认为基于这个观点，即人工智能的价值将积累在其数据上，它是当今世界上最有价值的资产。我认为你提出了一个非常重要的观点。这就是为什么反事实是真实的，并且实际上在数据中有所体现。尼克将再次向您展示这张来自AI入门的幻灯片。但这也解释了为什么在所有这些第三方模型的基准测试中，您会看到这些收益递减。这都是使用同样的数据集。
So what we are proving is not that the underlying hardware can't scale, nor that transformers are only efficient to a point. That's not what all of this convergence is showing. It's that in the absence of proprietary data, you're just going to get to the same model quality. And we're seeing a bunch of different models get to a very early finish line, which, again, if people like Facebook are doing for free, that's much easier to underwrite because you don't have to underwrite it being a differentiator in five years. But if you have a startup with equity value tied to a model, I think it's very, it's much more of a tenuous place to be in the absence of proprietary data.
所以我们证明的不是底层硬件不能扩展，也不是Transformer只能在某个点上高效。这些聚合展示的并不是这些。实际上，我们要说的是，在没有专有数据的情况下，你只能得到相同的模型质量。我们看到许多不同的模型都能在很早的阶段达到相似的结果，如果像Facebook这样的公司免费提供这些模型，那很容易获得支持，因为你不需要在未来五年内将其作为差异化因素。但是，如果你创办一家与模型相关的初创公司，没有专有数据的情况下，这种境况就会更加脆弱。
And everyone in the world has a camera and a microphone in their pocket and high-speed internet now from the phone in their pocket. And more and more people are uploading that content, that data that's being generated. YouTube's got this free data vacuum and they're just out in the world. And most of it's getting up. Well, it is public facing now. So it's not just true for text. It's also true for all of the image generation. So they can train more than just an LLM on it, right? They can build all sorts of.
如今，全世界的每个人都随身携带着一个相机和一个麦克风，以及手机内的高速互联网。越来越多的人开始上传生成的内容和数据。YouTube如今就像一个免费的数据吸尘器，在全球范围内存在着。大部分内容都变得公开可见了。所以这不仅仅适用于文本，也适用于所有图片生成的内容。因此，他们可以对这些内容进行更多的训练，不只是像LLM那样的模型，他们可以构建各种各样的模型。
Yeah, go ahead. No, no, no, I was just going to say like the version of Common Crawl for training these image models also exists. And so to your point, it's like we are all operating from the same brittle, very fixed small quantum of training information. And so that is why I think like Facebook and Google are doing a really important job by deciding that these models should be free. And then being able to. So then the question that just accentuates their data advantage. It does. And I think it allows them to decide how much to leak out.
是的，继续吧。不，不，不，我只是想说训练这些图像模型的版本也存在，就像Common Crawl的版本一样。所以就像你说的，我们都是从相同脆弱、非常固定的一小部分训练信息中运作的。所以我认为Facebook和Google通过决定这些模型应该是免费的，并能够......所以这就强调了他们的数据优势。是的。我认为这让他们能够决定泄露多少数据。
So for example, whenever like, if you were using a lot of Google services like GFS, Bigtable, BigQuery, TensorFlow, the versions that you had access to via GCP was always one or two generations behind what the Google employees are doing. But it was still so much better than anything else that we could get anywhere else that you would still build to those endpoints. And I think there's a similar version of this where Facebook and Google probably realize like, look, we'll have version five running internally to optimize ads and all of this other stuff that makes our business that much better. And we'll expose version three to the public. But version three is still trained on so much proprietary data that it's so much better than version 10 and anything else that's just operating on the open internet.
所以举个例子，比如说，如果你经常使用很多谷歌服务，比如GFS、Bigtable、BigQuery、TensorFlow，那么你在GCP上能够访问的版本总是比谷歌员工使用的版本晚一代或两代。但是，它仍然比其他任何地方提供的东西要好很多，所以你仍然会构建到这些端点上。我认为Facebook和谷歌可能意识到了类似的情况，他们明白，我们会在内部运行版本五来优化广告和其他让我们业务更好的东西。而对外公开的版本可能是版本三。但是版本三仍然是基于大量专有数据进行训练的，所以它比在开放互联网上运行的版本十和其他任何东西都要好得多。
And you know, to your point, Freberg, that's the outward-facing stuff. YouTube is a collection of things people want to share. What Google also has is Google Docs and Gmail, things that people say privately. So they have another data resource there that they can tap, you know, and there'll be regulations and privacy around that. But maybe there's a difference there, but I honestly can't think of the quantum coming close to YouTube, not even close.
而且，就像你说的那样，弗伯格，这是面向外界的东西。YouTube是人们想要分享的东西的集合。Google还拥有谷歌文档和Gmail，这些是人们私下说的东西。所以他们还有另一个数据资源可以利用，你知道的，对此可能会有法规和隐私保护的规定。但也许在这方面有所不同，但我真的想不到有什么能够与YouTube相提并论，甚至没有接近的。
Well, the thing to Jason's point, which is really interesting, is like, you know, there's a modality in AI called RAG where you can actually just augment with very specific training on a very specific subset of documents to improve. It's like a hacked version of a fine tune. But the beautiful thing about that is like, if you have a Google workspace, my entire company runs on Google workspace. In fact, most of my companies do at this point to click a button where all of a sudden now all of that stuff and all of my G drives, all of a sudden is trainable so that the N plus first employee comes in and has an agent that's tuned on every deck, every model. Spread every document. That's a huge edge. Huge edge. Huge edge. By the way, and as a CEO, if you gave me that choice, I don't think anybody underneath that reports to me has any right to make that decision. But as a CEO, I would click that button instantly and I have that right as a CEO.
嗯，关于Jason提到的问题，非常有趣的是，你知道，在AI中有一种叫做RAG的模态，你可以通过非常具体的训练来增强它，针对某个特定的文档子集进行改进。这有点像一种改进的版本。而这其中美妙的地方是，如果你拥有一个Google Workspace，我的整个公司都在使用Google Workspace。实际上，我目前的大部分公司都在使用。只需要点击一个按钮，突然间所有的东西，以及我所有的G驱动器，都可以进行训练，这样N加上第一个员工进来时，就会有一个在每个演示文稿、每个模型、每个文档上进行调整的代理人。这是一个巨大的优势。一个巨大的优势。一个巨大的优势。顺便说一句，作为首席执行官，如果你给我这个选择，我觉得在我之下的任何人都没有权力做出这个决定。但作为首席执行官，我会立即点击那个按钮，作为首席执行官，我有这个权力。
And so like, that's the CEO pitch. It's like, look, I can just give you these agents that are that are like the next version of a knowledge base that we've always wanted inside of a company. Notion has this, you know, they've basically, you can start asking your entire notion instance questions about notion, which is incredible. And yeah, you can just, and as a CEO, you can see across everything, Chamop, because as you know with Google Docs, if you're in a compliance based industry like finance, you can see everything, every message, every email, every document, and you can start the security model and the data model becomes very complicated and all of that stuff.
所以就像这样，这就是CEO的宣传。就像这样，看，我可以给你们这些代理人，他们就像是我们在公司内一直期待的知识库的下一版本。Notion就有这个功能，你知道的，基本上你可以开始问你的整个Notion实例关于Notion的问题，这真是令人难以置信。是的，作为CEO，你可以跨所有事物进行观察，就像谷歌文档一样，如果你在合规行业（比如金融业）工作，你可以看到一切，每一条消息，每一封电子邮件，每一个文档，安全模型和数据模型开始变得非常复杂，以及其他所有的东西。
Like, for example, like, how do you know that this spreadsheet is actually, you should learn on it, but who gets to actually then have that added to the subset of answers, right? All of a sudden, like salaries, right? The HR information information gets put into the training model. Very dangerous. Or subset A of a company's working on a proprietary chip design, but they actually like the way that Apple runs highly, highly segregated teams where nobody else can know. So there's all kinds of complicated security and data model and usage questions there, but yeah, brave new world.
举个例子，你要怎样才能知道这个电子表格是真实的呢？你应该在上面学习，但是谁有资格将其添加到答案的子集中呢？突然间，比如薪水问题，人力资源信息被加入到培训模型中，非常危险。还有一种情况是公司A正在开发一种专有芯片设计，然而他们实际上喜欢苹果高度隔离团队的管理方式，其他人不能知晓。所以这里涉及到种种复杂的安全性、数据模型和使用问题，说真的，真是个崭新的世界。
So there's been a lot of discussion real estate. You shared a video with us. Why don't you kick it off for us here, Prabhir. What's going on in commercial real estate and sacks? You've got holdings and a lot of those as well. So let's kick up the commercial real estate challenges of the moment.
所以房地产方面有很多讨论。你和我们分享了一个视频。Prabhir，你为什么不在这里开始给我们介绍一下商业房地产和股票的情况呢？你还持有很多这些方面的资产，所以让我们来讨论一下当前商业房地产面临的挑战。
Well, I mean, I think we're teeing off of Barry's comments at this event last week. He and I met backstage because I spoke right before him and then he gave this talk, which is available on YouTube, where he talked about the state of the commercial real estate market. Particularly, he talked about the office market. Just to take a step back to talk about the scale of commercial real estate as an asset class in the US, Nick, if you'll pull up this chart, the total estimated market value of commercial real estate in the US. Across different categories is about $20 trillion with about $3 trillion being in the office market, which is specifically what he was talking about. And he was saying that in the US, we're seeing people not coming back to work and all these offices are empty and we've talked a lot about these offices being written down. So how significant of a problem is this?
嗯，我的意思是，我认为我们是在针对巴里上周在这个活动上的评论展开讨论。他和我在后台见面了，因为我在他之前演讲，然后他发表了这个演讲，可以在YouTube上观看，他在演讲中谈到了商业地产市场的现状，特别是办公市场。让我们先来谈谈美国商业地产作为一种资产类别的规模，尼克，如果你能打开这张图，美国商业地产的总估计市值在不同类别中大约为20万亿美元，其中大约有3万亿美元是办公市场，这正是他谈到的。他说，在美国，我们看到人们不再回到办公室，所有这些办公室都是空置的，我们已经反复谈论过这些办公室被折旧的问题。那么，这个问题有多严重呢？
So $20 trillion asset class, obviously, the multifamily market is probably not as bad as office and retail, which are the most heavily affected, each of which are about $3 trillion. A piece, the rest of these categories seem relatively unscathed in comparison, industrial, hospitality, healthcare, you know, those real estate sectors are probably pretty strong. Data centers, obviously, growing like crazy self storage, the great market. If you pull up the next image, so it turns out that of the $20 trillion of market value, there's about $6 trillion of debt. So you can kind of think about that $20 trillion being $6 trillion owned by the debt holders and $14 trillion by the equity holders. And the debt is owned roughly 50% by banks and thrifts. And this was this concern that we've been talking about with higher rates is the debt on office actually going to be able to pay the debt on retail going to be able to pay. When half of that debt is held by banks and thrifts that as we talked about, have such a close ratio to deposits that you can actually see many banks become technically insolvent if the debt starts to default.
所以，这个20万亿美元的资产类别中，很明显，多家庭住宅市场可能不像办公和零售市场那样糟糕，后两者都是最受影响的，每个市场价值约为3万亿美元。其他类别相对来说似乎相对较为安全，比如工业、酒店、医疗保健，你知道，这些房地产行业可能相当强大。数据中心显然在飞速增长，自储设施市场也很好。如果你看下一张图，你会发现在这20万亿美元的市值中，大约有6万亿美元的债务。你可以想象一下这20万亿美元中，债务持有者拥有的是6万亿美元，而股权持有者拥有的是14万亿美元。这些债务大约有50%属于银行和储蓄机构。我们一直在讨论的一个问题是，如果办公室的债务不能偿还，零售市场的债务能否偿还。当这一部分债务有一半由银行和储蓄机构持有，而这些机构与存款之间的比例如此密切，以至于如果债务开始违约，你实际上会看到很多银行可能会陷入技术性破产。
Barry's point that he made was if you look at the office market, which is marked on everyone's books as $3 trillion of market value, he thinks it's probably worth closer to $1.8 trillion. So there's $1.2 trillion of loss in the office category. And if you assume 40% of that $3 trillion is held as debt, you're talking about $1.2 trillion of office debt.
巴里所提出的观点是，如果你看看办公市场，它在每个人的账本上标注的市值为3万亿美元，他认为它可能更接近1.8万亿美元。所以办公室行业损失了1.2万亿美元。而且如果假设这3万亿美元中有40%以债务形式存在，那么你所指的办公债务就达到了1.2万亿美元。
A reduction from $3 trillion to $1.8 trillion means that the equity value has gone down from $1.8 trillion to $600 billion. So they've lost equity holders in office real estate have probably lost two thirds of their value, two thirds of their investment.
市值从3万亿美元降至1.8万亿美元意味着资产净值从1.8万亿美元减少到6千亿美元。因此，办公房地产的股东可能已经损失了三分之二的价值，三分之二的投资。
And who owns all of that? Most of that 60% call it two thirds of that is likely owned by private equity funds and other institutions where the end beneficiary is actually pension funds and retirement funds. And so if two thirds of the value has to be written off in these books and it hasn't happened yet, what's going to happen to all these retirement funds. And this is we're going back to my speculation a couple months ago kind of gets revisited. If you're actually talking about a two third write down on the value in these funds and most of that being pension funds, you're not going to see governments let that happen.
那个是由谁拥有的呢？其中大部分60%中的三分之二很可能是由私募股权基金和其他机构所拥有，最终受益人实际上是养老金和退休金基金。因此，如果这些账本上还没有发生的价值的三分之二必须被注销，那么所有这些退休基金会发生什么呢？这就是我几个月前的一种推测又被重新考虑的原因。如果实际上谈到这些基金价值的三分之二被摊销，并且其中大部分是养老金，政府是不会允许这种情况发生的。
You're going to see the federal government. There's going to be some action at some point. And it's unlikely the office market is going to suddenly rebound overnight. If this stays the way it is, who's going to fill that hole for retirees and pensioners because we're not going to let that all get written down. Someone is going to step in and say, we've got to do something about this. And there's going to need to be some sort of structured solution to support retirees and pensioners because that's ultimately who ends up holding the bag in this massive write down.
你将会看到联邦政府。在某个时刻，会发生一些行动。而且办公市场不可能一夜之间突然复苏。如果情况继续保持现状，那么谁会来填补退休人员和养老金领取者的空缺，因为我们不会让那些都被写下来。必定会有人站出来说，我们必须对此采取一些措施。而且肯定需要一种有结构的解决方案来支持退休人员和养老金领取者，因为最终他们将承担这种巨大的写下风险。
You didn't go all the way there in his statements. He was talking more about his estimate of three trillion to one point eight trillion. And then I tried to connect the dots and what that actually means. And ultimately, there's going to be some pain felt by retirement funds that's going to need to be dealt with somehow. So I don't know if that if that sits right with you.
他在他的陈述中并没有完全说明清楚。他更多地谈论了他对三万亿到一万八千亿的估计。然后我尝试联系这些点，并了解它们的实际含义。最终，养老基金将会感受到一些痛苦，这种情况需要以某种方式处理。所以我不知道这是否合你的心意。
I mean, I think the big picture is right. I think you're applying a lot of averages. Right. I think in the office market in particular, the typical office deal is more like one third equity and two thirds debt. There's a lot more leverage. Right. So that'd be point number one, which makes the situation worse. Even worse. Yeah. So I would say that there's a huge amount of equity that's been written off. But in addition to that, there's a lot of debt holders who are in trouble too. Yeah.
我的意思是，我认为总体情况是正确的。我觉得你在运用很多平均数。对的。我认为特别是在办公市场上，典型的办公楼交易更多地是三分之一的股本和三分之二的债务。杠杆使用更多。对的。所以这将是第一点，让情况更糟糕了。甚至更糟糕。是的。所以我会说，有大量的股权已经被冲销了。但除此之外，还有很多债权人也处于困境中。是的。
And that debt is held by regional banks. So these commercial loan portfolios are significantly impaired. That's what we saw with Community Bank of New York is that their stock cratered when they reported higher than expected losses in their commercial real estate portfolio.
这些债务由地区银行持有。因此，这些商业贷款组合受到了重大的损害。这就是我们在纽约社区银行看到的情况，当他们报告商业房地产投资组合的预期之上的损失时，他们的股价暴跌。
So, freeberg, I think the point is just the pain from this is not just going to be on the equity holders, but also on these banks, which can't afford to lose. They're actually distributed. Yeah. Right. Yeah. Right. And we saw this in San Francisco where some of these buildings have 70% debt equity ratios and, you know, the value puts them in the hole and the equity is wiped out completely. And the debt holders have to take ahead.
所以，弗里伯格，我认为重点不仅是股东会遭受痛苦，而且这些银行也会承受不起损失。它们实际上是分散的。是的。对，没错。我们在旧金山就看到过这种情况，一些建筑物的债务股本比例达到70%，而其价值会使它们陷入困境，股权将完全被抹去，债权人必须承担先行风险。
Normally, you know, that debt is not really written off very often. Well, this is why the debt holders, the debt holders don't want it foreclose. They don't want to get these buildings back because when they do, they're going to have to write down the loan. As long as the loan is still outstanding and they have a foreclose, they can pretend that the value of the building is not impaired. Kick the can down the road is the best strategy for them. So it's called pretend and extend.
通常情况下，债务并不经常被注销。这就是为什么债权持有人不想要逼迫对方归还债务。他们不希望收回这些建筑物，因为一旦这样做，他们就不得不减记贷款。只要贷款仍未偿还且他们没有收回，他们可以假装这些建筑物的价值没有受到损害。把问题拖延下去对他们来说是最好的策略。因此，这被称为虚假延期。
So what we're going to do is they'll work out a deal with the landlord, the equity holder that the equity holder say, listen, I can't pay the interest. So they'll just tack on the interest basically as principal at the end of the loan and they'll extend out the term of the loan. Which would wipe out the equity at a certain point. Yeah. And I'll let you know what it does. It allows the equity holders to stay in control on the building, right?
所以我们要做的是与房东达成协议，让权益持有人说，听着，我无法支付利息。所以他们将把利息基本上作为本金加在贷款末尾，并延长贷款期限。这样会在一定程度上抹去权益。是的。我会让你知道它的效果。这样一来，权益持有人可以保持对建筑物的控制，对吧？
Because, yeah, the equity holder can't pay make their debt payments today, but they're going to postpone those debt payments till the end of the loan. And again, in the meantime, just kind of hope that the market. Yeah, it's getting that debt at some points. And they have so little equity in these buildings typically just exceed the value of the property. And it's like, I'm just working for the bank now. And why am I even putting this working? Because everyone kind of hopes that the market will recover. The value of their equity will go up and they'll be able to make their debt payments again.
是的，股权持有者今天无法偿还债务，但他们将把这些债务支付推迟到贷款期末。而且，在此期间，只能期望市场情况好转，能够获得某种债务。这些建筑物通常几乎没有股权，仅超过物业价值。就好像我现在只是在为银行工作一样。我为什么还要做这份工作呢？因为每个人都希望市场会恢复，他们的股权价值会上升，他们就能够再次偿还债务了。
Yeah. So if you're the equity holder, you'd rather hold on and have a chance of your equity being worth something in recovery, then definitely lose the building. And if you're a regional bank, you'd rather. Blend and extend or pretend and extend as opposed to having to realize the loss right now. Yeah. And showing the market that your solvency may not be as good as you thought.
是的。所以如果你是股权持有者，你宁愿坚持住，并有机会在恢复中让你的股权有所价值，而不是彻底失去建筑物。而如果你是一家区域银行，你更愿意进行债务再融资或者假装延期，而不是现在就要承担损失。是的。因为这样会使市场看到你的偿付能力可能没有你想象的那么好。
The same thing happened with government bonds. Remember that with S.V.B. and these other banks, they had these huge held to maturity bond portfolios. Yeah. These are mostly just T bills that were worth, I don't know, $0.60 on the dollar when interest rates spiked from zero to 5%. But they didn't have to recognize that loss as long as they weren't planning to sell them. Right. And then when they had the bank run, they had to sell. Well, yeah, that's right. So when depositors left because they needed their money or because there was a run or because they could get higher rates in a money market fund, all of a sudden these banks had to sell their held to maturity portfolio. They had to recognize that loss. And that's when everyone realized, oh, wait a second, they're not actually solving.
政府债券也发生了同样的情况。还记得S.V.B.和其他银行持有大量到期持有债券组合的情况吗？是的。这些主要是国库券，在利率从零飙升至5%时，价值可能只有原价的60%。但只要他们不打算出售，就不必认可这个亏损。对，但当银行面临挤兑时，他们必须出售这些债券。是的，没错。当存款人因为需要钱或慌乱而离开，或者能够得到货币市场基金的较高利率时，这些银行突然不得不出售他们的到期持有债券组合，开始承认这个亏损。于是大家意识到，哦，等一下，他们并没有真正解决问题。
Okay. So, Jamal, supply demand matters in real estate. We have a tale of two cities here on one side in real estate for commercial real estate, no demand for office space, which is in way too much supply paradoxically on the other side. We have this incredible market for developers, which is, gosh, there's not enough homes. I think we need 7 million more homes and the demand is off the charts for homes.
好的。所以，杰马尔，供需在房地产业很重要。在商业地产方面，我们有两个截然不同的城市故事。一方面，办公空间没有需求，供应过剩反而问题突出；而另一方面，对于开发商来说市场却非常火爆，住房短缺，我们需要增加700万套住房，需求超乎想象。
Yeah. Yeah. I mean, I think you're basically right. It's not. I keep trying to explain residential. It's not a great market either because interest rates have spiked up. So there's not a vacancy problem. Multi-family developers are still able to lease the units. They're still able to rent. The problem is their financing costs have shot through the roof. So again, let's say you were a developer who built multi-family in the last few years. You took out a construction loan. That construction loan might have been at three, four percent. Yeah. Now you want to put long-term financing on it. But if you can even find debt right now because there's a credit crunch going on, you may have to pay eight, nine, ten percent. Yeah, but at least you can find a renter. You can find a renter that's true, but only at a certain price. And let's see you under that property to, I don't know, like a five cap, like a certain yield. Yeah. But now your financing costs are much higher than you thought. You might be under water. Yeah. But that situation isn't as bad as what's happening in.
是的。是的。我的意思是，我觉得你基本上是正确的。它并不是很好。我一直试图解释住宅问题。这也不是一个好市场，因为利率已经上涨了。所以并不存在空置问题。多户住宅开发商仍然能够租出单位。他们仍然能够出租。问题在于他们的融资成本飙升了。所以，假设你是最近几年建造多户住宅的开发商。你获得了一笔建造贷款。那笔建造贷款可能是在3%到4%的利率。是的，现在你想对其进行长期融资。但是如果你能够找到贷款，因为目前正发生信贷紧缩，你可能需要支付8%、9%、10%的利率。是的，但是你至少可以找到租房人。确实可以找到租房人，但只有在一定的价格下。而且，如果你按照某种收益率（例如5%）来确定该物业的价值，那么你的融资成本现在比你预想的要高得多。你可能会负债。是的，但是这种情况并不像在其他地方发生的那样糟糕。
Why? I think it's worse in some ways. If you're fully rented and your building is under water because now your debt payments are much higher than you expected, then there's no business model. Yeah, but are we seeing that? Are we seeing tons of multi-family? Yeah, absolutely. Can I make two points? Wonderful. I believe it is right, which is that I don't know this market very well, but just as a bystander, here's what I observed. It seems that the residential market has a feature, and I don't know whether it's good or bad, but that feature is that you reprice to market demand every year. So to the extent that supply demand is changing and default rates are up or whatever, that's reflected in rents. And you see that because rents change very quickly, and most human beings are signing six months to one year leases. So that reset happens very quickly, so it can more dynamically adapt. So to the extent that a market segment is impaired, you see the impairment quickly. On the.
为什么？我认为在某些方面情况变得更糟。如果你的建筑物已经被全部租满，但现在却面临负债偿还额超出预期的困境，那么就没有商业模式了。是的，但我们是否看到了这种情况？我们是否看到了大量的多户住宅？是的，当然。我可以提出两点观点吗？太好了。我的观察是，我不太了解这个市场，但作为一个旁观者，我观察到了一些情况。住宅市场似乎有一个特点，我不知道它是好是坏，但特点就是每年重新根据市场需求定价。因此，如果供需发生变化，违约率上升等等，这都会反映在租金中。你可以通过租金的快速变化来观察到这一点，大多数人的租约签订时间为六个月到一年。因此，这种重新定价会非常快速地发生，从而能够更动态地适应市场。因此，如果某个市场细分受到损害，你会迅速看到这种损害。
On the office side, what I see is that there's been a structural behavior change in COVID that has reset in every other part of the world except for the United States, where there are these, frankly, typically young people who are living in the world. Typically younger, typically more junior employees that have held many of these companies hostage in a bid to return back to office space. And so we know that there is this vacancy cliff that's going to hit commercial real estate. We just don't know when because they're in long-term leases, they're canceling these leases over long periods of time. So the reset cycle was longer. That's just my observation as an outsider. I don't know what that means for prices or anything else, but it just seems that at least the residential market can find a bottoming sooner because you can reset prices every year. But commercial just seems like a melting ice direction.
在办公室方面，从我的观察来看，COVID-19在全球范围内除了美国以外的其他地方都导致了结构性行为变化，而在美国这里，有这些通常年轻的人生活在世界中。通常情况下，这些是相对年轻、相对初级的员工，他们已经将许多公司逼得不得不返回办公空间。因此，我们知道商业地产将面临租赁空置率的悬崖，只是我们还不知道具体是何时，因为他们签订了长期租约，他们正在长时间地取消这些租约。因此，重置周期变得更长了。这只是作为一个局外人的观察，我不知道这对价格或其他方面意味着什么，但至少住宅市场似乎可以更早找到底部，因为你可以每年重新调整价格。但商业市场似乎正面临融化的冰块方向。
Correct to you, Saks? No assessment. Commercial has both a demand problem and a financing problem. Multi-family just has a financing problem, but it's important to have to stay. We're talking about office. Because there's retail and then there's office and then there's other industrial industry.
对你来说没问题，Saks？没有评估。商用地产既面临需求问题，也面临融资问题。而多户家庭房产只面临融资问题，但保留它非常重要。我们正在讨论办公室。因为有零售业，还有办公室，还有其他工业行业。
Did you guys see a China? China has 50 million homes ahead of schedule, only 50 million additional supply that can house 150 million people. So as acute as our issues are, the China issue might be much, much seismic. Can we just give you an example on the multi-family side? Okay. Let's say that you buy a building. Okay. Let's say you bought a building in 2021, the absolute peak of the market. And you could get debt at, say, 4%, okay? And you penciled out, let's call it a 6% yield that with the debt you're getting. So let's say you did 2-thirds debt at 4%.
你们有看到中国吗？中国提前建造了5000万套住房，只有额外的5000万套住房可供1.5亿人入住。所以，尽管我们的问题很严重，但中国的问题可能要严重得多。我们能给你一个关于多户住宅方面的例子吗？好的。假设你在2021年购买了一栋楼。假设你以市场的绝对高峰期购买，并能以4%的利率贷款，好吗？假设你计算了一个6%的收益率，包括你获得的贷款。假设你使用了2/3的4%利率贷款。
You could now level up that 6% yield to 10%. Okay. That's like sort of the math, right? Now all of a sudden, and to get there, you'd have to do some value added work on the property. You have to spruce it up. Okay. Now, as a few years later, and your short-term financing is running out and you need to refi. And you've done your value added work, but here's the problem. The overall valuations in the market have come way down. So before the bank was willing to give you 2-thirds loan to value, now the values come way down, you may not even be able to get 2-thirds loan to values.
你现在可以将那6%的收益提高到10%。好的，这就像是数学上的计算，对吧？现在突然之间，要达到那个目标，你需要对房产进行一些增值工作。你需要改善它的状况。好的，几年过去了，你的短期融资即将用完，你需要进行再融资。虽然你已经做了增值工作，但问题在于市场中的整体估值已经大幅下降。所以以前银行愿意给你2/3的贷款价值，现在价值已经大幅下降，你甚至可能无法获得2/3的贷款价值。
So you're going to have to do what's called an equity in refinancing. You're going to have to produce more equity. You're going to have to pony up more money instead of taking equity out, like when the deal goes well. You're going to have to put equity in. You may not have that equity if you're the developer. The other thing is that your financing costs now might be 10%. So now you've got negative leverage. You're generating a 6% yield, but you're borrowing a 10% to generate that 6% yield. So the debt no longer makes sense. Again, you're not positively leveraged. You're negatively leveraged.
所以，你将不得不进行所谓的股本再融资。你将需要提供更多的股本。你将需要支付更多的钱，而不是像当交易顺利时一样提取股本。你将需要注入股权。如果你是开发商，你可能没有这种股权。另外，你现在的融资成本可能是10%。这样一来，你就产生了负杠杆效应。你产生了6%的收益率，但是你却借入了10%的资金来产生这6%的收益率。所以这笔债务不再合理。再次强调，你不是正杠杆化，而是负杠杆化。
So you're not going to want to take out that debt. And if you do take out that debt, the buildings that may be underwater, it's not going to be generating net operating income. It's going to be generating losses. So that's why even categories like multifamily, where you don't have a vacancy problem, there's strong demand. Those properties still don't make sense. If you had long-term debt on your multifamily, if you were able to lock in that 4% loan for 10 years, you're fine. But for all the people who are refinancing now, who are coming up this year, last year, next year, they're in deep trouble. And that's why there's a rolling crisis in real estate is because the debt rolls over time. It's not like everybody hits the wall. And that's refinanced at the same time.
所以你不会想要背负那笔债务。如果你真的背负了那笔债务，那些可能会被水淹没的建筑物将无法产生净营业收入，而是会亏损。所以，即使是像多户住宅这样的领域，你并没有闲置问题，需求也很高。这些资产仍然不合理。如果你的多户住宅有长期债务，如果你能锁定那个4%的贷款，持续10年，那就没问题了。但是对于那些现在正在重新融资的人们，今年、去年和明年要重新融资的人们，他们将陷入严重困境。这就是为什么房地产行业存在滚动危机的原因，因为债务随着时间推移。不是每个人都同时面临危机，并且同时进行再融资。
With that, God, right? I mean, this would be cataclysmic if it was, if it was. And can you imagine if Silicon Valley and San Francisco had to say, here's actually the reality. Anybody want to actually pay for this office? All in the same year? Right. That would be insane. But the crisis is growing is as the leases roll and those old rents that were higher in the market roll off, and now you have to take on new leases if you can even get them. It's going to be bad. And I'm much lower rate. And as the old loans roll that were at a much lower interest rate, you have to get financing, even if you get it at a much higher interest rate, that's when all of a sudden these buildings go from being basically solvent to insolvent.
这些都是上帝的安排，不是吗？我的意思是，如果真是这样的话，那将是一场灾难。你能想象如果硅谷和旧金山不得不承认现实的话，有谁愿意为这个办公室付费吗？还都发生在同一年，对吧？那简直就是疯狂。但是随着租约到期和原来较高市场租金的过去，现在如果你能得到的话，你必须承担新的租约，情况会变得很糟糕。我要低得多的利率。随着原来较低利率的贷款到期，即使你得到了更高利率的融资，这时候这些建筑物就从基本上还可以偿债变成了无法偿债。
Yeah. I mean, Janet Yellen's just going to bail these folks out. That means you won't bail out the banks themselves, but she'll bail out the creditors, obviously, the people holding the bag. They'll get bailed. Yeah. That's everybody agrees. Janet Yellen. Yellen. Our Treasury Secretary. I don't know if she's going to be the one to do. I think there's going to be congressional action on this stuff. Yeah. I mean, they tend to lead it.
是的，我的意思是，珍妮特·耶伦将会挽救这些人。这意味着她不会挽救银行本身，而是会救助债权人，显然是那些承担风险的人。他们将会得到援助。是的，每个人都同意。珍妮特·耶伦。耶伦。我们的财政部长。我不知道她是否会亲自处理这个问题。我认为国会会对这个问题采取行动。是的，我指的是他们倾向于领导这方面的行动。
All right.
For the Sultan of Science, David Preberg and David Sacks and Shama, probably, Hapatea, the Chairman Dictator.
I am the world's greatest moderator.
We'll see you next time.
And we'll end up.
Bye-bye.
Bye-bye.
Let your winners ride.
Brain man, David Sacks.
Oh, I'm going home.
And it said we open source it to the fans and they've just gone crazy with it.
Love you, S.
I'm the queen of Kinwan.
I'm going home.
I'm going home.
What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What? What?
You're a B.
You're a B.
What?
We need to get merges.
I'm going home.
I'm going home.
I'm going home.
I'm going home.
好的。
对于科学苏丹，David Preberg和David Sacks和Shama，可能是Hapatea，主席独裁者。
我是世界上最伟大的调解人。
我们下次再见。
然后我们会结束。
再见。
再见。
让你的获胜者继续前进。
大脑人，David Sacks。
哦，我要回家了。
它说我们向球迷开放源代码，他们对此疯狂。
爱你，S。
我是金湾女王。
我要回家了。
我要回家了。
什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？什么？
你是个傻瓜。
你是个傻瓜。
什么？
我们需要合并。
我要回家了。
我要回家了。
我要回家了。
我要回家了。