Workday的AI战略、AI"同事"、IPO回暖与消费者加密的未来 | 2025年9月17日

欢迎大家收看Information's TI TV节目。我是Akash Pashracha。今天是9月17日星期三，各位观众，今天我们为大家带来科技行业的全面报道。我们有Workday的首席技术官做客节目，谈论公司的最新收购案。我们还将讨论本周发布的一篇重要报道，关于Anthropic和OpenAI为何要去健身房，以及这与强化学习有何关联。

Welcome everyone to the Information's TI TV. My name is Akash Pashracha. It is Wednesday, September 17, and we have got a full tour of the tech sector today, folks. We have got the CTO of Workday coming on to talk about the company's latest acquisition. We are also gonna talk about a big story we published this week about how Anthropic and OpenAI are headed to the gym and what that has to do with reinforcement learning.

随后我们的朋友Ty Haney和Dave Moran将做客节目，全面探讨消费级加密货币话题。最后但同样重要的是，我们将对当前IPO窗口期的情况进行内部分析。今天的节目内容非常丰富。让我们直接进入第一个环节。Workday昨天以11亿美元收购了一家名为Sana的AI智能体公司，成为新闻焦点。

We've then got our friends Ty Haney and Dave Moran coming on the show to talk all about consumer crypto. And last but not least, we are going to get some inside analysis of what we are seeing in the IPO window right now. It's going to be a busy show. Let's get right on into our first segment. Workday made news yesterday with a $1,100,000,000 acquisition of an AI agents company called Sana.

这家公司总部位于瑞典，为律师事务所、矿业公司和金融科技公司开发工具。现在有请Workday首席技术官Peter Baylis为我们详细介绍他看中这家公司的原因。Peter，很高兴见到您。

The company is based in Sweden. It makes tools for law firms, mining companies, and fintech companies. I want to bring on Workday's CTO, Peter Baylis, to tell us more about what exactly he saw in the company. Peter, it's great to see you.

谢谢邀请。

Thanks for having me.

那么，我的意思是，天啊，瑞典。你们最初是怎么发现Sonog的？我都不知道瑞典竟然是AI智能体的热点地区。

So look, I mean, gosh, Sweden. How did you even find Sonog in the first place? I didn't know Sweden was a hotspot for AI agents.

事实证明Suite的技术相当出色。我们最初实际上是通过Workday Ventures了解Sana的。Sana成立于2016年，最初是一家学习公司。创始人Joel Hallmark在16岁后就没有再上学，但通过自学成为程序员，并基本上建立了一家利用AI进行学习的公司。这逐渐发展成为今天的Sana。

Turns out Suite's tech is pretty good. And we got to know Sana actually originally through Workday Ventures. So Sana started in 2016 as a learning company. So Joel Hallmark, the founder, never actually went to school after age 16, but you know, self taught, you know, programmer and basically built a learning company where you use AI for learning. And that morphed into what Sana is today.

明白了。那么请告诉我，Sana的AI智能体与我们听说过的其他AI智能体公司有何不同？

Got it. And so tell me, how is it that Sana's AI agents are different from all of the other AI agent companies that we hear about?

是的。首先，它们提供了真正消费级的体验。我的意思是，乔尔和团队打造了一个非常棒的体验。我认为从学习开始就很出色。学习这个领域通常相当枯燥。

Yeah. So one, they're really consumer grade experience. I mean, it's a beautiful experience that Joel and team have built. I think starting from learning. Learning's a space that's pretty boring.

我不认为人们喜欢上学习课程。但不知何故，他们凭借Sonata Learning的基因构建的体系，让企业学习和企业培训变成了一种极佳的体验。

I don't think people like to take learning classes. And somehow what they built with Sonata Learning kind of from their DNA is they were going to make this an awesome experience to actually do, like, corporate learning and corporate

等等。抱歉。当你说学习时，我想确认下我的理解。AI智能体和学习，这具体是如何运作的？

Wait. And wait. Sorry. When you say learn I just want to make sure I understand. So AI agents and learning, how does how does it work?

是的。智能体不能替你学习，对吧？

Yeah. The agent can't learn for you, can it?

这家公司最初是一家学习公司。想象一下，你要参加新员工信息入职课程。你们公司应该也有类似的东西，对吧？

So the company started as a learning company. So think, you know, you're going to take your information onboarding course. You guys probably have something like that, right?

所以它

So it

会是一个选择，让你去实际完成那些课程学习和作业。他们做的就是把打造优质体验——就像与内容互动时的美妙体验——作为公司的核心部分。所以在过去几年里，他们更多转向了智能体方向，主要是搜索、工作流以及低代码智能体构建。这种基因已经传承过来，并在产品中体现得非常明显。

would be an option to go and actually do that coursework and that course learning. And what they did is they made it a core part of their company to basically make this a great experience, like a beautiful experience for working with that content. So, in the last couple of years, they moved over more toward the agent side, which is really search, workflows, and then sort of lower code agent building. Got That DNA transferred over and is really clear in the product.

明白了。所以这不是Workday第一次进行与AI代理相关的收购。你们几个月前还收购了一家公司。你们在Workday究竟想通过这项技术构建什么样的客户体验？

Got it. So this is not the first AI agents related acquisition that Workday has made. You also acquired a company a couple months ago. What exactly is the customer experience that you are trying to build here at Workday with this technology?

是的。人们对Workday的客户体验有很多看法，包括在座的各位。与Sana合作的愿景其实很简单。我们认为他们可能拥有处理组织数据的最佳用户体验——无论是进行企业搜索、提出问题、创建内容还是消费内容。

Yeah. So people have a lot of opinions about the Workday customer experience, present company included. The, you know, the the vision with Sana is is is really simple. You know, they have probably what we think is the best user experience for working with organizational data. So doing enterprise search, getting your questions asked, creating content, consuming content.

比如我想知道与Acme公司的交易进展如何。Sana会深入挖掘我的企业数据来进行研究。显然，对于公共数据（所有基础模型都基于此训练），我们有强大的网络搜索API。Sana构建了后端系统，可以连接Salesforce、整合Google Drive、搜索Outlook和Gmail——将所有数据汇聚在一起。因此在Workday基础上，通过Sana你能获得两大提升。

So, I want to know, you know, what's going on with my deal with Acme company. You know, Sana will go and do that deep research against my enterprise data. So, obviously, if public data, which all the foundation models are trained on, you've got great web search APIs. Sana's built the back ends to go and pull onto Salesforce, go and federate into Google Drive, to go search my Outlook, to go search my Gmail, like to go pull all that together. And so with Sana, you get kind of two things on top of Workday.

第一，对于当前在Workday中进行的操作，你将获得更优质、更直观、更美观的用户体验。第二，通常用户每月最多只会几次访问Workday（比如请假）。而现在，这变成了一个你会想每天使用的系统。采用Sana Aegis平台的客户，基本上将其设为浏览器的新标签页。

One, for those stuff you do in Workday today, you're going get a much better user experience, much more intuitive, much more beautiful. Two, you typically come to Workday to take time off or, you know, you have a couple times a month max as an end user. Here, it becomes a system where you think you want to come on a daily basis. The customers that have adopted the Sana Aegis platform, it's basically their new tab in the browser.

没错。我们节目中来过很多与你们处境相似的公司——他们试图自研技术，但到市场上发现想直接购买。现在似乎每家大型科技公司都在收购。在这种环境下，问题是：购买是否比自建更容易？

Right. You know, we've had a lot of companies on the show that have been in a similar position to you, which is that they're trying to build their own technology. They go to the market, they find something that they want to buy. I mean, it seems like every big tech company is buying now. And I guess the question in this environment, is it just easier to buy rather than build?

我认为这是

I think it's

两者结合。我们会寻找能加速实现路线图的最佳方案。Workday处理的某些业务深度嵌入平台——我们每年处理涉及人力与财务数据的万亿级交易。这需要极其核心的数据模型和对象事务处理能力。

a mix. So, you know, we look for the best things that let us accelerate our roadmap. For some of the stuff that Workday does, it's pretty deep in the platform. Like, we do a trillion transactions a year across people's people and money data. And that has really, really in the the guts, you've got a ton of data model, object model transactions.

我们一直在做很多工作，包括本周在我们年度会议上宣布的内容，你可以去应用GenAI来优化内部业务流程。市场上可能没有人会去构建这种技术，但它为客户节省了数十万小时。当涉及到像体验层或Sana这样的东西时，我认为这是一种新的，正如乔尔所说的，AI的用户界面。我们觉得，是的，我们可以去构建这个，但机会成本是什么？对我们来说，我认为公司，尤其是最近领导层的变动，我们变得非常积极。

It's a lot of stuff we we've been working on stuff we announced, you know, at our annual conference this week, where you can go and say apply GenAI to go and optimize an internal business process. Like no one really in the market's probably gonna go and build that tech, but it saves hundreds of thousands of hours for customers. When it comes to something like an experience layer or something like Sana, which is, I think, you know, kind of a new, as Joel would call it, UI for AI. You know, that's something where we feel like, yes, we could go and build this, but what's the opportunity cost? And for us, I think the companies, especially with, you know, recent leadership, we're extremely aggressive.

我们认为我们有权在这个领域获胜，即AI应用于工作。我的意思是，还有谁在这个领域竞争？我们可以很快推出产品。去Sana基本上是引入了更多创始人级别的能量，而且坦白说，也是一个互补的部分，我们可能可以在此基础上加速18到24个月。

Like we think there's a right to win in this, you know, AI for work. I mean, who else is playing in this space? We could ship pretty quickly. And going to going to sauna is basically bringing in, you know, more founder level energy. And also, frankly, like a complementary piece where probably could build up, we accelerate for, you know, eighteen to twenty four months.

彼得，我想问你的一个问题是，Workday涉足招聘业务。招聘现在是一个非常有趣的领域，因为AI确实在加速招聘过程。但你也会听到所有这些故事，比如AI生成简历，以及AI在筛选这些简历时可能存在偏见。我想知道你是否能谈谈Workday是如何在构建技术时考虑这些问题的。

Peter, one of the questions that I wanted to ask you was Workday is sort of involved in the business of recruiting. And, you know, recruiting is such an interesting space right now because AI, it is certainly helping to accelerate the process of recruiting. But then you hear all these stories about, well, you know, AI is generating resumes, and also AI can have some bias as it relates to, you know, scanning through these resumes. I wondered if you could talk a little bit about how at Workday you are building your technology with those problems in mind.

是的，这是个很好的问题。我认为这在很多应用AI的地方都是如此，尤其是在工作中。如何利用这些在许多方面都非常出色的模型，特别是如今在编码方面，越来越多地应用于后台任务，而不会在这个过程中搞砸？因此，我们花了很多时间与一个专门负责AI伦理的团队合作，这个团队实际上与我们的工程团队分开，以保持独立性。

Yeah, it's a great question. I mean, this is, I think, true of a lot of places where people are applying AI, especially at work. Right? How do you go and take advantage of these models that are really incredible at so many things, you know, especially today, things like coding, but increasing more on back office tasks without actually, you know, screwing it up in the process? So, we spent a lot of time with a whole dedicated responsible AI team that's actually separate from our engineering teams to keep the separation of church and state.

坦白说，我们从客户那里看到的是，他们开始意识到，如果你在适当的地方保持人工干预，这会大大加速招聘过程，并最终使招聘更加公平，因为你能查看更多简历，面试更多候选人。我们提到的Paradox收购非常惊人，他们平均每秒进行一次面试

And frankly, I think what we're seeing with customers is that they're starting to realize that if you keep the human loop at the right places, there's a massive accelerant to go and actually, you know, really make hiring ultimately more equitable because you're able to look at more resumes, look at more candidates. I mean, this Paradox acquisition we mentioned, it's sort of incredible. They're doing one interview on average per

每秒一次面试。哦，哇。在他们的平台上

second. Like that's One interview per second. Oh, wow. On their platform

每年，每一秒，进行3100万次面试。他们能够引入候选人的规模是相当疯狂的。比如Chipotle，作为参考客户，他们使用Paradox后，平均招聘时间从12天缩短到4天。

of the year, every single second, do 31,000,000, million interviews. Right? And the scale at which they're able to go and bring candidates in is, is kind of insane. And you've got people like Chipotle, right? So Chipotle reference customer, they went from twelve days on average of hire down to four days using Paradox.

与此同时，他们的申请量翻了一番。所以，虽然你们确实设置了正确的防护措施，但我认为AI正在进入每个行业。你们仍然让招聘经理来做最终决定，但最终能做的事情要多得多。我再举一个例子，我们推出了这个绩效评估助手。没人喜欢写绩效评估。

And then at the same time, they doubled their applicant volume. So, while there's definitely, you you've put the right guardrails in place, I think that AI is coming for every industry. You still leave it in the hands of a hiring manager to make the final determination, but you ultimately can do so much more. Another example I'll give you, we rolled out this performance review agent. No one likes writing performance reviews.

也没人真正喜欢在Workday里做这些，对吧？如何让它变得更好去做这件事？现实是当你写绩效评估时，如果你赶时间，你只会想到上周从这个人那里听到了什么，对吧？

No one really likes doing them in Workday. Right? How do I make that better to go and do that? And the reality is when you write a performance review, if you're in a rush, you're just thinking about, what did I hear from this person in the last week? Right?

所以我们在绩效评估助手中的做法类似于我们在Asana中的做法。它会收集该员工过去一年的所有信息，包括你所有的一对一笔记、所有的OKR、你提供的所有文档，这样你就能获得更好的视角。所以我认为，正确实施的AI实际上对工作是非常有益的。这也是我四个月前加入公司的原因之一。

So, what we do at the performance review agent is kind of like we do with Asana. You're suck all the information about that employee over the past year, All of your one on one notes, all of your OKRs, all of the documentation that you've provided, and you get a much better perspective. So, I think AI done right actually is really net positive for work. It's one of reason why I joined the company four months ago. Right.

我们基本上只需要确保以聪明的方式来做这件事，一方面要负责任，也许更重要的是，它实际上要符合工作中最重要的事情。

And we basically just need to make sure we do it in a smart way, where one, it's responsible, and maybe more importantly, you know, it actually aligns to, you know, to what's most important for work.

太好了。Peter，就像我说的，你们公司一直很积极地进行收购，现在处于一个令人兴奋的位置。所以我猜想还会有更多收购。所以当你们继续你们的收购狂潮时，我希望你能再次来到节目，谈谈你们正在收购的一些公司。这位是Workday的首席技术官Peter Baylis。

Great. Well, Peter, like I said, you guys have been very acquisitive, and it's an exciting spot to be right now. So, I imagine there are going to be more acquisitions. So when you continue your spree of shopping, I guess, come back on the show and talk more about some of the companies you're buying. That is Peter Baylis, the CTO of Workday.

好的。AI中最有趣的新动态之一是公司现在正在尝试寻找更有创意的方式来训练模型。事实上，我们现在看到公司使用所谓的强化学习训练场来加强他们的产品。我的同事Stephanie Palazzola本周写了一篇相关报道。我想请她上来，同时也想请Jonathan Sadart，他的公司Turing也制作了一些这样的强化学习训练场，来帮助我们解释这到底是怎么回事。

Okay. Well, one of the most interesting new dynamics in AI is the way that companies are now trying to find more creative ways of training models. And in fact, we are now seeing companies use what are called reinforcement learning gyms to fortify their products. My colleague Stephanie Palazzola wrote a story about that this week. I want to bring her on, and I also want to bring on Jonathan Sadart, whose company Turing also makes some of these reinforcement learning gyms to help us explain what this is all about.

Jonathan和Stephanie，很高兴你们能来。

Jonathan and Stephanie, it is great to have you.

很高兴来到这里。

Great to be here.

很高兴来到这里。谢谢你，Akash。

Great to be here. Thank you, Akash.

好的。那么Stephanie，告诉我们你的故事是关于什么的？有很多事情在发生。我们谈论的是健身房，但不是我们通常所了解的那种健身房。告诉我们发生了什么。

Okay. So Stephanie, tell us what was your story about? There's a lot going on. We're talking about gyms, not the gyms that we know about typically. Tell us about what's happening.

完全正确。基本上这里有两件事在发生。第一是，实验室正在耗尽新的大规模、高质量数据来源。所以目前，所有实验室基本上已经对整个网络进行了训练。第二件事是，实验室越来越多地推出这些代理产品，他们说，好吧，在你的电脑或设备上，代表用户执行操作，无论是在你的个人生活中，比如在DoorDash上为你订餐，还是在你的工作生活中。

Totally. So basically there's two things going on here. The first is that, you know, labs are running out of new sources of kind of large scale, high quality data. So at this point, all the labs have pretty much, you know, trained on the entire web basically. The second thing that's going on is that labs are increasingly coming out with these agent products, which they're saying, Well, go on your computer or device and take actions on behalf of users, whether that's actions in your personal life, like ordering food for you on DoorDash or in your kind of work life.

比如，帮你制作Excel电子表格。针对这两件事，实验室在获取训练数据方面变得更加有创意。所以，其中一部分就像你提到的，要求像Turing这样的公司制作应用程序的假副本。比如，一个假的Salesforce版本，一个假的Excel版本，这样他们就可以让他们的AI模型在里面运行，并找出如何完成任务。这些应用程序的假副本就是所谓的RL环境或RL健身房。

So, helping you make an Excel spreadsheet, for instance. And in response to both of these things, labs are getting more creative when it comes to getting training data. So, part of that is, like you've mentioned, asking companies like Turing to make basically fake copies of applications. So, a fake version of Salesforce, a fake version of Excel, so they can let their AI models run around in them and kind of figure out how to complete tasks in them. And those kind of fake copies of the apps are what is known as RL environments or RL gyms.

他们还在聘请更高级的专家，拥有更高学历和工作经验，来为他们标注数据，以改进模型。

And they're also getting even more advanced experts with even more higher level degrees and working experience to label data for them to improve the models on.

明白了。那么，Jonathan，你的公司是建造这些健身房或这些模拟环境之一吗？

Got it. So, Jonathan, your company builds one of these gyms or these simulations?

没错，Akash。就像在普通健身房中人类去训练一样，在口语健身房中，这些企业智能体去进行训练。一旦它们完成训练，就能达到超级智能水平。正如Steph提到的，这是向更广泛范式转变的一部分，除了向人类学习外，我们正在进入智能体通过经验学习的模式。我认为这是其中一个有趣的方面。

That's right, Akash. And just like in a regular gyms, humans go to train, in an oral gym, these enterprise agents go to train. And once they train, you get to superintelligence. And as Steph mentioned, this is part of a broader shift to where we, in addition to learning from humans, we're getting to this paradigm where the agents learn from experience. I think that's one interesting aspect of this.

这些口语健身房就像是商业领域的微型世界模型，健身房本身就是提示、环境和验证器的集合。你需要专家人类来创建这些提示、这些验证器以及那个环境。Steph的故事非常具体地说明了这一点，Steph，你我讨论过一个例子，比如说投资分析师需要为某个投资机会进行DCF分析。要做到这一点，你需要智能体能够使用不同的工具。对吧。

And these oral gyms are like these mini world models for business, where the gym itself is a collection of prompts and environment and verifiers. And you need expert humans to create these prompts, create these verifiers, and create that environment. And Steph's story did a really good job of making this very concrete, where Steph, you and I discussed an example of, let's say, an investment analyst having to work through doing DCF for, let's say, a particular investment opportunity. To do that, you would kind of need the agent to be able to use different tools. Right.

你需要一种方法来验证答案是否正确。因此，我们正在不同的企业消费者用例中创建数千个这样的健身房。这是一次疯狂的建设过程。对吧。而且Akash，健身房主要有两种类型。

You need a way to verify whether the answer was correct. So, we are creating thousands of these gyms across different enterprise consumer use cases. It's been a crazy, crazy build out. Right. And gyms, Akash, like are of two types.

有时它们是为计算机使用智能体而设计的。意思是，模型正在学习如何使用键盘和鼠标来理解图形用户界面上的内容。或者可能是专注于函数调用或工具使用的健身房，这在某些方面甚至更酷，即模型调用不同的函数并找出完成任务的轨迹

Sometimes they are designed for computer to use agents. Right. Mean, the model is learning how to use a keyboard and a mouse to understand what's on a graphical user interface. Or it could be a gym that's focused on function calling or tool use, which in some ways is even cooler, which is the model calling different functions and figuring out a trajectory that results in it completing the

然后，在人类参与循环中，如果智能体点击了错误的按钮，或者DCF分析出现问题，比如单元格链接断开之类的情况，人类会在循环中纠正它们。

task. And then presumably, human in the loop would the agent, I guess, if, you know, if they click the wrong button or if the DCF goes you know, if the cells get unlinked or something like that, you know, then the human would correct them in the loop.

完全正确。当智能体尝试不同路径时，过去的轨迹会展开，人类可以纠正这些轨迹，有时标注这些轨迹，有时以正确的方式引导模型。这些轨迹数据也非常有价值，所以

That is correct. So the past trajectories unfold where the agent is trying out different paths through The this human can correct the trajectories, sometimes label the trajectories, sometimes nudge the model in the right way. And that data is also super valuable, this trajectory So

从宏观角度来看，我想放大视野。所以，你们有了这种新的训练方式。Stephanie，我推测所有这些都变得清晰起来，因为训练这些模型变得越来越困难了，对吧？实际上是在解决模型效率是否开始趋于平稳的问题？我们正在尝试找到方法让它重新提升。

a big picture here, I just want to zoom out here. So, know, you have this new way of training. Stephanie, I mean, I presume, so all of this is really coming into focus because it's getting harder to train these models, right? Mean, really addressing this question of, know, is model efficiency, starting is to plateau? You know, we're trying to get ways to bring it back up again.

这算是我们在这里试图解决的核心挑战吗？

Is kind of the core challenge that we're trying to address here?

我认为这绝对是其中很大一部分。正如我提到的，很多实验室，几乎所有的实验室都已经在所有的网站、所有的书籍上进行了训练。所以我认为他们只是在寻找继续改进模型的新方法。比如在这个故事中，我们提到Anthropic未来一年可能会在这些强化学习环境上花费高达10亿美元。所以他们真的在这方面加倍投入，将其视为继续推动我们看到的人工智能进步的一个非常有前景的方式。

I think that's definitely a big part of it. You know, as I mentioned, a lot of the labs, pretty much all the labs have trained on, you know, all of the websites out there, all the books out there. And so I think they're just coming up with new ways to continue improving models. This is just, know, in the story, for instance, we mentioned that Anthropic could potentially spend up to a billion dollars on these RL environments over the next year. So they are really, you know, doubling down on this as a very promising way to continue kind of the AI improvements that we've been seeing.

没错。乔纳森，你的业务也涉及招募专家来帮助训练这些模型。你是如何考虑招募这些专家并激励他们来为你的公司工作的？

Right. Jonathan, you know, your business also sort of is in the, you know, recruiting experts to sort of help train these models. How do you think about sort of recruiting these experts and then actually incentivizing them to come work for your company?

正如斯蒂芬提到的，这些模型目前从根本上受到数据和计算能力的限制。阿卡什，你可能读过那个关于MIT报告的报道，说百分之九十五的Gini-

So, as Steph mentioned, these models today are fundamentally constrained by data and compute. And Akash, you might have read that story about that MIT report that said like ninety five percent of Gini-

所有人都疯了。

Everyone was going crazy.

所有人都疯了？是的。我的假设是，发生这种情况的一个重要原因是这些模型没有看到足够的企业数据。要做到这一点，你必须从各个可以想象的领域聘请企业领域专家。对吧。

Everyone was going crazy? Yeah. My hypothesis that one big reason that happens is that these models haven't seen enough enterprise data. And to do that, you have to hire enterprise domain experts from every field imaginable. Right.

但图灵，我们正在做的是，想象世界上每一个行业，医疗保健、零售、生命科学、制造业。想象那个行业中的每一个职能，软件工程、销售、市场营销。想象组织架构中对应那个职能的每一个角色。在市场营销下，他们做绩效营销、SEO、产品营销。想象那个角色中的人类经历的每一个工作流程。

But Turing, what we're doing is, imagine every industry in the world, healthcare, retail, life sciences, manufacturing. Imagine every function in that industry, software engineering, sales, marketing. Imagine every role in the org chart to that function. Under marketing, they do performance marketing, SEO, product marketing. Imagine every workflow that that human in that role goes through.

没错。我们正在招聘所有这些人才，对吧？我确实想象，在类似这些起源的领域内评估模型和创建数据，以及其他类型的数据采集，将成为最热门的工作。我们可能在几年内成为世界上最大的人才雇主之一。所以这是一个非常非常庞大的建设。你看到的是计算方面，像OpenAI这样的公司以及其他公司，通过Stargate项目，你谈论的是数千亿美元的计算投入，对吧？

Right. We are hiring all of them, right? I truly imagine evaluating models and creating data inside even something like these origins, as well as other types of data capture, be the So most popular job on we might be one of the largest employers of talent in the world in a few years. So this is a massive, massive build out. You're seeing the compute side of this, where companies like OpenAI and others, with Stargate, you're talking about hundreds of billions of dollars in compute, right?

公司正在以巨大规模建设。所以在数据方面也是如此，公司需要数据来保持这些数据中心运转。在AI圈子里有个笑话，Akash和Steph，有人谈到研究人员说这些模型在数据分布外时推理能力不好。比如，它们真的在泛化吗？还是只是在训练集上识别模式？

Companies building at gigantic scale. So on the data side as well, companies need data to keep those data centers humming. There's this joke, Akash and Steph, among AI circles, where somebody talks about how, a researcher talks about how these models don't do a good job of reasoning when the data is out of distribution. Like, are they truly generalizing? Or are they just patterns at the trading set?

然后第二个研究人员说，那我们就把所有数据都纳入分布。所有数据，对吧？而正如Steph所说，互联网的资源已经枯竭了。所以现在，人们对企业数据非常感兴趣。对于这一点，oral gems（可能是oral gems的误写，推测指某种数据生成方法）真的非常非常有帮助，除了其他类型的模仿学习。

And researcher two says, then we bring all data into distribution. Like all data, right? And to Steph's point, what has happened is the internet well has run dry. So right now, there's a huge amount of interest in, number one, enterprise data. And for that, oral gems are really, really helpful, in addition to other types of imitation learning.

第二是高级STEM数据。很多这些企业领域以及编码和STEM领域的酷之处在于它是可验证的。所以非常适合强化学习。对，对。

Number two is advanced STEM data. And the cool thing about a lot of these enterprise domains, as well as coding and STEM domains, is it's verifiable. So it lends itself very well for reinforcement learning. Right. Right.

这有点酷。就像，我知道每个人都著名——

Which is kinda cool. Like, I know everybody's famous-

不，不，你的思路很快。

No, no, your thought quickly.

每个人都记得AlphaGo的第37步，同样在DeepMind的AlphaZero中，模型通过自我对弈得到改进。Oral gems是企业智能体自我对弈并快速提升的一种方式。

Everyone remembers the Move 37 from AlphaGo, where again, in AlphaZero from DeepMind, the model improved by playing against itself. Oral gems are a way for enterprise agents to play against themselves and get rapidly better.

太好了。乔纳森，这真是个迷人的行业，我想我们可能还能再聊上好几个小时。斯蒂芬妮，你今天早上也有一个很棒的电话访谈，我们没时间讨论，但我建议大家去读一读。那在我们的AI议程通讯里。斯蒂芬妮和乔纳森，感谢你们来节目，告诉我们关于AI领域正在兴起的新健身房的一切信息。

Great. Well, Jonathan, it's fascinating business, and I think we could probably spend hours more talking about it. Stephanie, you had a great call in this morning as well, which we didn't get time to get to, but I suggest everyone goes and reads it. That's in our AI agenda newsletter. Stephanie and Jonathan, thank you for coming on and telling us everything we need to know about the new gyms that are taking shape here in AI.

这两位是斯蒂芬妮·帕拉佐洛和乔纳森·萨达特。好的，我们接下来的嘉宾在消费级加密货币领域花费了大量时间。这个领域我们在节目中谈论得不多，主要是因为它的关注度不如几年前那么高。但如果没人谈论它，从某种角度来说，这正是开始讨论的最佳时机。我想请上Try Your Best的首席执行官泰·哈尼，以及Offline Ventures的戴夫·莫兰。

That is Stephanie Palazzolo and Jonathan Sadart. Okay, well, our next guests have spent a lot of time in the land of consumer crypto. It is not an area that we have talked too much about on this show, mostly because it hasn't got as much attention as it did a few years ago. But if no one else is talking about it, well, that in some ways is the best time to start talking about it. I want to bring on Ty Haney, the CEO of Try Your Best, and Dave Moran from Offline Ventures.

这是他们第一次上节目。泰和戴夫，欢迎来到节目。

It is their first time on the show. Ty and Dave, welcome to the show.

嘿。

Hey.

你们俩是不是商量好了，比如决定一起戴帽子？我们非常

Do you guys do you guys coordinate your your like, you decide we're both gonna wear hats on We're very

我们非常区块链。懂吗？这就是风格。不。

we're very blockchain. You know? This is the look. No.

是啊。不。我们是消费者，我们是搞消费者的人，老兄。

Yeah. No. We're the consumer we're the consumer people, man.

所以Ty戴着一顶TYV的帽子。而Dave，你戴的是Outdoor Voices的帽子吗？我的意思是，这样是不是就能同时拥有两个品牌的最佳体验？

So Ty's wearing a TYV hat. And, Dave, are are you wearing an Outdoor Voices hat? I mean, do do is that how you get the best of both brands?

不是。不过我确实应该这样。

No. I should be, though.

好吧。听着，我得说，我想谈谈消费者加密货币，这也是我联系你们时说的，让我们聊聊这个话题。Ty，我之前真是孤陋寡闻，都不知道你两个月前已经回到OV了。

Okay. Well, look, I have to say, I want to talk about consumer crypto, that's what I sort of reached out to you guys saying, let's talk about it. Ty, I was living under a rock. I didn't know that you are back at OV as of, like, two months ago.

是的。最新消息。先是OV这家初创公司，然后进入2IV（我仍在运营），最近又重新加入了OV。所以这是一个完整的循环，现在非常专注于在这个社区商业机会的核心进行世界构建。

Yes. New news. OV, the first company, and then into 2IV, which I'm still running, and then most recently rejoined OV. So very full circle and very focused on world building at the center of this community commerce opportunity.

简单分享一下，你对OV未来18个月的大致愿景是什么？

And just, I mean, share us here very briefly. I mean, what is your sort of eighteen month vision here for OV, broadly speaking?

和我最初创立时一样，打造头号休闲品牌，这有机会成为超过十亿美元的业务。Dave在第一阶段参与其中，也参与了TYB，现在第二阶段再次加入。TYB本质上是我们称之为社区商业模式的驱动工具，这个模式是链上的。我们可以深入探讨细节。

It's the same as when I started, build the number one recreation brand, and that has opportunity to be well over a billion dollar business. Dave was part of that in chapter one, has been part of TYB, and now, again, part of it in chapter two. And so TYB is fundamentally the tool that drives this model we call community commerce, which is on chain. We can get into details there.

没错。

Right.

这是我们打造这个十亿美元娱乐品牌的重要催化剂。

That's a big catalyst for how we build this billion dollar recreation brand.

现在让我们谈谈TYB。你认为公司在这里解决的核心问题究竟是什么？

And talk about so let's talk about TYB now. What exactly is the core problem that you see the company solving here?

没错，100%是这样。消费者存在关系维护问题。过去十年间，我们在Instagram和Facebook上花费大量资金获取客户，但这些客户并未留存下来。用户获取成本(CAC)急剧上升。市场上一直缺乏能够有效提升用户终身价值(LTV)、维持长期客户关系并持续挖掘客户价值的默认工具。

Yeah, 100%. So consumer has a relationship issue. Essentially, for the last ten years, have spent a lot of money on Instagram and Facebook to acquire customers that don't stick with us. CAC has exploded. There's been no default tool for driving LTV and really longevity of these relationships and value of a customer over time.

这正是TYB的用武之地。它是一个通过游戏化方式运作的社区互动与奖励平台，让品牌能够培养与粉丝和客户的关系，并最终随时间推移提升他们的价值。

And so that's where TYB comes in. It's a community engagement and rewards platform that acts in a game in a way to allow brands to nurture relationships with their fans and customers and ultimately make them more valuable over time.

那么具体来说，请为我描述一下客户体验。比如我在你们网站上看到有Urban Outfitters合作案例。我去Urban Outfitters购物，可能想买他们展示的酷炫唱片之类的东西。然后奖励机制如何运作？我注册了奖励计划。

And so tactically, I mean, so just paint the customer experience here for me. So I go to I saw on your website you've got Urban Outfitters, for example. So I go shop at Urban Outfitters, and maybe I want to buy the cool records that they have on display or something like that. And then, so what happens with the rewards? I sign up for reward.

它是如何运作的？

How does it work?

假设我是Glossier的粉丝。系统会提示我通过TYB加入Glossier社区。我开始参与各种挑战活动，这些作为消费者本来就会自然参与的行为，但此前从未获得过奖励。TYB实际上成为了消费者获取品牌奖励和维系关系的统一入口——多个品牌整合在单一体验中，这与传统忠诚度计划局限于单个品牌网站的模式截然不同。

So I'm a fan of Glossier. I'm prompted to join Glossier on TYB. I start to engage in these various challenges, things that as a consumer are very natural and I already do, but I'm not rewarded for them. And so really, TYB becomes this one portal in on the consumer side to rewards and relationships from brands. So multiple brands all in one experience, versus traditional loyalty programs live on a brand site.

因此对我来说，考虑我的积分以及何时使用它们并不那么重要。所以TYB第一阶段的核心就是提供一个通往多个品牌奖励和关系的入口。我们相信忠诚度的未来在于身份、地位以及你作为粉丝的证明。

And so for me to think about my parade coins and then when to use them, it's not all that relevant. So one portal into rewards and relationships across various brands is really what this phase one of TYB turns on. And our belief is the future of loyalty is all about identity, status, and your proof of fan. And so

所以这就像是，如果我发布关于品牌的内容，基本上就可以在加密领域获得相应的回报。

So And this is like posting like if I post about the brand, then I can get reported for it in crypto, essentially.

本质上，就像是我在进入这个游戏，我在参与，我在赚取积分，并逐步提升在这个品牌等级体系中的级别。然后我在Glossier的等级在Nike也能具有意义。这样地位就变得可互操作了。但归根结底，从TYB的角度来看，我们真正在帮助品牌和消费者创建的是一个链上消费者身份的概念。

Well, essentially, like I'm entering this game, I'm engaging, I'm earning, and I'm progressively leveling up with this brand's tiers. And then that tier within Glossier can mean something within Nike. And so status becomes interoperable. But at the end of the day, really what from a TYB perspective we're helping brands and consumers create is this idea of an on chain consumer identity.

明白了。而且那是

Got And that's

一个我可以随身携带的身份，它有意义，能解锁各种特权、访问权限等等。

an identity that I take with me and means something unlocks various perks, access to things, etcetera.

懂了。Dave，我马上就来和你更广泛地谈谈这个行业。但最后一个问题，Ty，关于这个话题。TYB的商业模式是什么？

Got it. And Dave, I'm coming to you in just a second to talk about the industry more broadly. But last question, Ty, on this topic here. What is the business model for TYB?

是的，第一阶段是B2B模式。所以年度合同将很快转向更多社区消费者货币化的机会，因为我们启动了客户作为 affiliates（联盟成员）的功能。这是我们正在步入的阶段，因为我们已经成功吸引了超过一百万会员以及高价值会员加入平台。

Yeah, first phase has been B2B. So annual contracts will quickly move into this more community consumer monetized opportunity as we turn on customer as affiliates. And so that's a phase we're stepping into right now as we've gotten well over a million members and high value members on platform.

明白了。戴夫，你知道，几年前我们听到了很多关于消费级加密领域的消息，比如NFT和Web3，感觉后来人们不再谈论它了，但你一直在投资这个领域。所以给我们简单介绍一下现状吧。在你看来，哪些初创公司最具吸引力？在更广泛的消费级加密领域，我们应该关注什么？

Got it. So Dave, you know, we heard a lot about consumer crypto a couple years ago with like NFTs, for example, you know, and Web3, it felt like people stopped talking about it, but you have continued to invest in the category. So give us a little bit of the lay of the land here. Are you seeing in terms of what startups are most attractive to you, and what should we be paying attention to as it relates to consumer crypto more broadly?

是的。在消费级加密领域，我们看到真正的重点放在了现实世界的应用场景上。如何将现实世界中的东西上链？就像泰在TYB构建的项目，如她所说，客户获取成本(CAC)已经爆炸式增长。获取客户的成本比以往任何时候都高。

Yeah. On the, you know, on the crypto on the consumer crypto side, we've seen a real focus on real world use cases. You know, how do you take something, put it on chain that is connected to the real world? And in the case of what Ty is building at TYB, like she said, CAC has exploded. It costs more than ever to acquire a customer.

嗯。在这些客户中培养忠诚度，对世界上大多数优秀品牌来说也一直难以实现。因此，将互联网现象——人们成为事物的粉丝、传播他们最爱事物的表情包——转化为品牌忠诚度和更高的终身价值(LTV)，我认为这是加密技术的一个非常强大的应用。更广泛地说，我认为我们看到的是这个模因金融时代，金融资产像模因一样传播。金融资产已经变成了文化。

Mhmm. And generating loyalty amongst those customers has also been largely elusive to most of the great brands in the world. And so the idea that you can convert this Internet phenomenon of, you know, people becoming fans of things, of people spreading memes about what they love the most into loyalty to a brand, and a higher LTV is a really powerful, I think, use of crypto. And so, you know, more broadly, I think what we're seeing is this era of memetic finance where financial assets are spreading like memes. Financial assets have become culture.

你明白吗？看到了吧。抱歉？

You know? See that. Sorry?

我说，是的，我们看到了。这正在到处发生。

I said, yeah, we see that. It's happening everywhere.

是的。所以模因就是市场信号。文化是领先指标。人们想要成为什么事物的粉丝，想要通过社交网络传播什么，这比以往任何时候都更能代表他们的身份。

Yeah. So memes are market signals. You know? Culture is the leading indicator. What people want to, you know, become a fan of, what they want to spread through social networking systems, that is their identity more than ever.

从消费互联网诞生之初我们就一直在这么说。当我最早参与社交网络工作时，我们总是说身份就是一切。但今天你看到的是，这不仅从互联网传播开来，还延伸到了金融资产和各种事物中。而加密技术正处在这一切的核心。过去一年，我们看到了Solana和模因币使用量的大爆发。

We've been saying that since the beginning of the consumer Internet. When I was first working on the earliest social networks, we always said that identity is everything. But what you see today is this is spread not just from the Internet but into financial assets and all matter of things. And crypto is right at the dead center of this. You know, over the last year, we've seen a massive explosion in usage of Solana and meme coins.

很多人觉得这很傻，就像NFT领域发生的事情一样。但我看到的是，消费者正在以极其强大的方式参与跨互联网和金融生态系统的文化行动。没错。所以当我们审视TYB正在做的事情时，它实际上是将所有这些整合在一起，从根本上提升品牌的终身价值（LTV）。

And a lot of people think it's silly just like, you know, the stuff that's going on was going on with NFTs. But what I see is that consumers are engaging in cultural actions in a way that is incredibly powerful across the internet and financial ecosystem. Right. And so when you look at what we're doing with TYB, it's really bringing all of that together to just like radically increase the LTV for brands.

那么Ty，你如何看待世界上已有一定比例的人使用过加密货币这个观点？我不知道具体数字是多少，但假设是某个百分比。可能不多，但正在增长。但我想问的是，你如何看待加密货币的广泛采用。因为你可以提出这样的论点：如果人们一开始就没用过加密货币，他们为什么会想要加密货币奖励呢？

So Ty, how do you think about this idea that some percentage of the world has used crypto now? I don't know what the number is, but imagine it's some percent. It might not be a lot, but it's growing. But my question for you is how you think about adoption about crypto broadly. Because you could make the argument that, Hey, if people haven't used crypto in the first place, why would they want rewards in crypto?

他们为什么会想注册这样的项目？你也可以提出相反的论点：嗯，这正是我们引导他们进入加密货币领域的方式。你如何看待采用问题以及这个'先有鸡还是先有蛋'的困境，就你所处的位置而言，如何让人们使用加密货币？

Why would they want to sign up for a program like this? You could also make the flip side of the argument that, well, this is how we're getting them into crypto. How do you think about adoption and the chicken and the egg in terms of where you sit in that and getting people to use the cryptocurrency?

是的。其实区块链只是底层技术。我们在用户体验方面所做的实际上是将其隐藏起来，但真正围绕价值创造机会创造这些神奇时刻，这从区块链的角度来说是我真正关心的。我的观点是，将会出现一个巨大的——而且我们已经看到这种趋势正在形成——由区块链和加密货币驱动的价值创造机会。如果我们不让女性参与进来，她们将错过整整十年、长达十年的价值创造机会。

Yeah. It's really just blockchain is the underlying technology here. What we've done on the user experience is really obfuscate that, but really create these magic moments around value creation opportunities, which is really kind of what I care about from a blockchain perspective. And my perspective is there's going to be this massive, and already we're seeing this turn on, kind of value creation opportunity powered by blockchain and crypto. And if we don't get women here, they're going to miss out on an entire kind of ten year, decade long value creation opportunity.

因此，品牌是吸引女性受众进入加密货币领域的一个非常好的方式。我个人认为，这是我最关心的事情。

And so brands are a really nice way to attract female audience into crypto. And I think personally, that's what I care most about.

请多谈谈你们为实践这一使命正在实施的一些项目。

Talk more about some of the programs you're putting in place to play out that mission.

是的。我的意思是，如今这个业务的魅力在于，当品牌让客户参与这个TYB游戏时，它们最终会随着时间的推移变得更有价值。我们通过购买频率和终身价值（LTV）看到了这一点。我们与Shopify集成。所以很有趣的是，我们可以开始比较TYB会员与非会员的参与行为，并最终指出哪种参与方式提升了价值。

Yeah. I mean, beauty of the business today is brands, when they engage their customers in this TYB game, ultimately they become more valuable over time. We see that through frequency of purchase and then LTV. We integrate with Shopify. So what's quite interesting is we can start to compare the engagement behavior between TYB members and then non members and ultimately point to kind of what engagement increases that value.

因此，社区首次变得可衡量。这一切都与品牌为何想要入驻该平台有关。然后这些品牌自然地将粉丝带入这个生态系统，在这里他们首次因参与互动而获得奖励，最终以一种真正相关且有回报的方式认可他们的忠诚度。

And so for the first time, community becomes measurable. So all that kind of connected to why brands want to be on the platform. And then those brands naturally bring these fans into this ecosystem where for the first time they're being rewarded for this engagement and ultimately their loyalty in a way that's really relevant and rewarding.

戴夫，最后一个问题。在消费者加密领域，目前还有哪些类型的业务出现在你的视野中，你觉得很有意思，我们应该关注哪些可能在接下来几个月里成为新闻热点的？

Dave, last question for you. You know, in this realm of consumer crypto, what other types of businesses are coming across your desk right now that you are finding intriguing that we should be watching to make news in months to come?

是的。我们目前非常专注于Solana生态系统。要知道，Solana拥有最活跃的开发者活动和最有趣的创意项目。所以我们一直非常专注于那里。

Yeah. I mean, we are really focused on the Solana ecosystem. Know, Solana has the most developer activity, the most interesting creative stuff going on. And so we've been, you know, very focused there right now.

好的。那么专注于那里，但再次问一下，你主要关注哪些类型的业务？

Okay. And so focus there, but like, again, what what types of businesses are are are you sort of paying most attention to?

你知道，预测市场、梦幻体育等领域有很多有趣的事情正在发生，就像TYB一样。在消费者方面，我们最感兴趣的是那些消费者完全不知道加密技术是驱动体验的底层技术，但却是一种超级赋能的技术，使体验成为可能。你知道，TYB就像一个特洛伊木马。人们使用它，通过与喜爱的品牌互动赚取积分和奖励。

You know, there's a bunch of interesting stuff going on prediction markets, fantasy sports, just like TYB. On the consumer side, we are most interested in consumer experiences where the consumer really has no idea that crypto is the underlying technology driving the experience, but is a super empowering, you know, technology that enables the experience. You know, with TYB, it's really a Trojan horse. People use it. They earn points and rewards for inter engaging with their favorite brands.

而且，迟早你将能够交易这些东西。消费者完全不知道这一点。它只是实现了人们一直想做的事情。你知道，我们一直都有航空积分和各种积分，但你从未能够跨品牌交换它们，以在另一个品牌中获得更高地位。而这一切都是由加密技术赋能的。

And, you know, sooner or later, you're going to be able to trade those things. And the consumer really has no idea. It's just enabling something that people have always wanted to do. You know, we've all always had airline points and points of all different kinds, but you've never been able to exchange them across, you know, with to become higher status in a in a different brand. And so all of that's empowered by crypto.

我们看到这种情况也发生在消费者领域的其他一些类别中。我们认为这就是消费者领域的发展方向。消费者不需要了解它。

And we see this going on, you know, across some of these other categories as well in consumer. And we think that's the way that consumer's gonna go. The consumer doesn't need to know about it.

太好了。那么，泰和戴夫，非常感谢你们来参加节目。我想随着有更多新闻需要讨论，我们会越来越多地邀请你们两位上节目，但我不能总是

Great. Well, Ty and Dave, thank you so much for coming on the show. I imagine we'll have you guys both on more and more as there is more news to discuss, but I can't Always

很高兴来到这里。

happy to be here.

祝贺所有出色的工作，戴夫，你知道，我们下次看看你会戴哪顶帽子。我想泰可能会给你一顶比那顶更有品牌标识的帽子。但不管怎样，谢谢你们的到来。以上就是泰和戴夫。好的。

Congrats on all the great work, Dave, you know, we'll see what hat you're wearing next time. Think Ty can probably give you something a little bit more branded than that one. But anyway, thanks for being here, of you. That is Ty and Dave. Okay.

嗯，IPO又回来了。本月我们将看到六家风险投资支持的公司进入公开市场，包括今天首次亮相的Netskope和StubHub。现在的问题是，这些IPO是否足以回报那些坐等退出和等待回报的众多风险基金？我想请我们的副主编凯蒂·鲁夫和Industry Ventures的首席执行官汉斯·舒尔登来给我们一个答案。凯蒂和汉斯，欢迎你们两位。

Well, IPOs are back. This month, we will see six venture backed companies take to the public markets, including Netskope and StubHub, which are debuting today. The question now will be, are these IPOs enough to pay out the many venture funds that are sitting around waiting for exits and waiting for returns? I want to bring on our Deputy Bureau Chief Katie Roof and the CEO of Industry Ventures, Hans Schulden, to give us an answer to that question. Katie and Hans, welcome to you both.

很高兴认识

Great to meet

那么凯蒂，我们今天有Netskope和StubHub。关于这两次IPO我们需要了解什么？

So Katie, we have got Netskope and StubHub today. What do we need to know about these two IPOs?

当然。StubHub今天开始交易，Netskope在今天收盘后定价。它们两者非常不同。Netskope更像是典型的风险投资支持的IPO，在所有权方面，他们有光速、Excel和Iconic，而StubHub是一家有25年历史的企业，曾被两次收购。

Sure. So StubHub begins trading today and Netskope prices after the bell today. They're both very different. And that scope is more of your typical venture backed IPO with in terms of ownership. They have light speed and excel and iconic, whereas SubHub is a twenty five year old business that was acquired twice.

它曾经作为eBay的一部分已经公开过。但它仍然是风险投资支持的，因为Bessemer拥有部分股份，Westcap也是如此。

It was already public as part of eBay at one point. So but it's still venture backed because Bessemer owns part of it, same with Westcap.

没错。那么Hans，为什么是现在？我的意思是，我们看到Katie报道中的数字是6家风险投资支持的科技公司IPO，这是自2021年11月以来我们见到的最多的一次，所以你认为为什么是这个时候？IPO窗口打开了吗？

Right. So Hans, why now? I mean, you know, we see I think the number in Katie's story was six venture backed tech IPOs is the most we've seen since November 2021, and so why do you think this is the moment? I mean, is the IPO window open?

是的，IPO窗口已经开放一段时间了。已经开放了几年。现在的IPO数量基本上超过了2022年和2023年全年的总和，因为那两年只有2家和6家。但是，你知道，我认为市场正处于历史高点。买方对IPO有需求。

Yeah, the IPO window's been open for a while. It's been open for a couple years. There are more IPOs going right now than all of 2022 and all of 2023, basically, because there was two and six in those years. But, you know, I think the market's at an all time high. There's demand on the buy side for IPOs.

很多最近定价的IPO表现良好，所以有了势头，你知道，当IPO市场有势头时，它会加速，所以我们看到加速并不令人惊讶。

A lot of the IPOs that priced recently have performed well, and so you have momentum, and you know, when momentum's in the IPO market, it accelerates, so that's not surprising we're seeing acceleration.

那么跟我说说风险投资的有限合伙人（LPs）是怎么说的。他们在庆祝吗？他们是谨慎乐观吗？还是他们说，嗯，这还不足以让我们获得想要的回报，Hans？他们是怎么想的？

And so talk to me about what venture LPs are saying. Are they celebrating? Are they cautiously optimistic? Are they saying, Well, this is still not enough to sort of get us the returns we wanted, Hans? How are they thinking about that?

是的，我的意思是，我们作为一家公司有点独特，因为我们有一个非常大的LP投资组合。我们拥有350家公司的超过750个基金份额。所以，我们是美国较大的风险基金投资组合之一，作为有限合伙人。我会说，我们不是在庆祝，但这是一件非常好的事情，对吧？我的意思是，我认为所有这些股票都有锁定期。

Yeah, I mean, we're kind of unique as a firm just because we have a very large LP portfolio. There's over seven fifty fund stakes that we own in three fifty firms. And so, we've got one of the larger venture fund portfolios in The US that's an LP. And, I would say, we're not celebrating, but it's a really nice thing to have, right? I mean, I think that there is a lockup on all these shares.

我们仍然在从三年前、四年前的旧IPO中获得分配，那些风险基金因为董事席位而被锁定，现在正在分配，但我会说一旦锁定期结束，情况会好很多，然后风险基金要么分配要么出售这些股票，这样才能获得一些分配。没错。你知道，当一家公司上市时，大多数时候你不会立即获得所有收益，因为

We're still getting distributions from old IPOs three years ago, four years ago, where the venture funds have been locked up due to them being on the board, and they're distributing, but I would say it'll be a lot better once, you know, the lockups are off, and then the venture funds either distribute or sell these, so that it can get some distributions. Right. You know, celebrate, you know, when a company goes public, most of the time, you don't get all your proceeds right up front, because

他们不会

they won't

达不到预期。

fall short.

你得等等。

You gotta wait.

我会说这是2026年的庆祝活动。

I would say it's a 2026 celebration.

对。所以凯蒂，汉斯说的是2026年。跟我聊聊二级市场是如何演变的，作为一种为等待这个窗口的投资者提供流动性的方式。

Right. So Katie, Hans is saying 2026. Talk to me a little bit about, you know, how the secondary markets have evolved as a way to get liquidity for, you know, investors that have been waiting for this window.

没错。你看像SpaceX和Stripe这样的公司拥有非常活跃的二级市场，同时还进行大量公司批准的股权回购要约，让内部人士可以出售股份，而不必等到IPO才能买房。但这也意味着他们上市的压力更小，这也是我们看不到那么多IPO的部分原因。

Right. You see companies like SpaceX and Stripe having very active secondary markets, and then also doing a lot of company sanctioned tender offers as a way for insiders to sell sell their shares and not have to wait for an IPO to buy a house. But that also means that there's less pressure for them to go public, which is part of why we're not seeing so many IPOs.

汉斯，加入讨论吧。我的意思是，你对二级市场的跟踪相当广泛。你最近看到了什么情况？

Hans, join in here. I mean, you've tracked the secondary markets pretty extensively. What's what have you been seeing?

是的。我们是这里最大的二级市场基金之一，也是最大的二级市场团队之一。我们目前正在投资一支15亿美元的二级基金，因此我们参与了所有这些交易流，查看所有交易并参与其中一些。我认为存在一种哑铃型现象。一方面，有些公司选择保持私有化，没有上市计划，它们利用二级市场来获取流动性。

Yeah. We are one of the largest secondary funds here, and one of the largest secondary teams. And it's a billion 5 secondary fund we're investing right now, and so we're in all that deal flow and looking at all those transactions and participating in some of them. I would say that there is a barbell. So, there is, there are companies that are staying private and have no plans to go public, and they're using the secondary market for liquidity.

这种情况已经持续了一段时间，我们认为未来不会有太大变化。现在看到的很多IPO并非市值排名前十的私营公司。对于这些排名前10或20的私营巨头（我们称之为PMEG），它们是否会上市以及何时上市尚不明确。因此二级市场正在为这些公司提供流动性，这些公司的CEO和董事会对于使用二级市场为员工和股东提供流动性感到非常满意。这是一个非常活跃的时期。

That's been going on for a while, and we don't see that as changing much in the future. A lot of the IPOs you're seeing that are coming out now are not the, you know, top 10 market cap private companies, and the top 10 or 20, we call them the PMEG, the private MEG companies, it's unclear whether or not they're gonna go public, and if so, when. And so the secondary market's providing liquidity in that in those names, and and and those CEOs and boards have been very happy with using the secondary market for a means for liquidity for the employees, as well as the shareholders. It's a super active time.

Hans，在我们结束前最后一个问题。我很好奇你对今年上市公司的财务表现和基本面有什么看法。有一段时间，上市门槛在盈利能力和收入方面变得相当高，我的意思是，必须是真正的A+级公司才能进入公开市场。我们看到这个门槛在本月上市的公司中有没有发生变化？

Hans, last question for you before we go. You know, I'm curious what you've made of sort of the financial performance and the fundamentals of the companies that have gone public this year. For a while, was that the bar was getting pretty high in terms of profitability, revenue. I mean, you had to be really an A plus company to take to the public markets. How have we seen that bar shift, if at all, with the companies we're seeing go public this month?

那些在盈利能力等方面证明不足的公司，是否也能勉强过关？

Can you kind of get away with being a company that hasn't proven as much in the way of profitability or anything like that?

是的，资本市场是动态的。你知道，10年、20年前，大多数上市的公司都是不盈利但快速增长的企业。然后有一段时间，公司必须极其盈利且快速增长，还要满足40法则（增长率与盈利能力之和）。但如今，在人工智能和其他技术顺风的推动下，门槛已经降低，开始接纳某些行业中烧钱率高或不盈利但显示快速增长、更具投机性的公司。风险投资业务本身就极具投机性，而过去三年的IPO市场并不太投机。我认为我们现在开始看到这些投资的投机性特质开始出现在公开市场中。

Yeah, the capital markets move, right? So, you know, ten, twenty years ago, most of the companies that would go public were unprofitable, but they were at fast growth, and then we get a period of time where you had to be extremely profitable and fast growth and have a rule of 40 or more, which is the addition of the growth rate and the profitability. But today, I think you're seeing with AI and some other technology tailwinds that the bar's lowered to include companies in certain sectors that have big burn rates or are not profitable but show fast growth and are more speculative. So, I think, you know, the venture business is extremely speculative, as everyone knows, and the IPO market over the last three years has not been very speculative. And I think we're starting to see some speculative nature of some of these investments show up in the public markets.

很好。这确实值得关注。正如你所说，投机性越强，往往波动性也越大。这意味着——确实如此。

Great. Well, it certainly is something to watch. And as you said, you know, the more speculative they get, often the more volatile they get. That means- Absolutely.

无论是上涨还是下跌，对吧？

On the upside and the downside, right?

是的。上涨也好，下跌也罢，都意味着有新闻，也就意味着我们有更多话题可聊。汉斯，我们期待您能更多地参与节目，讨论这些市场动态。凯蒂，我想我们会越来越多地邀请您上节目，因为更多的IPO意味着我们The Information有更多独家新闻可挖。感谢二位今天的光临。

Yeah. Upside, downside, either way, it means there's news, and that means there's more for us to talk about. Hans, we look forward to having you more on the show to talk about some of those movements. And Katie, I think we'll have you on the show more and more, because more IPOs means more things to scoop here at The Information. So thank you both for coming on.

这位是我们的副主编凯蒂·鲁夫，以及来自Industry Ventures的汉斯。好的，今天的节目就到这里。提醒大家，我们每周一到周五太平洋时间上午10点、东部时间下午1点在此直播。我要感谢亚马逊网络服务，他们是本节目的首席赞助商。

That is Katie Ruef, our Deputy Bureau Chief, and Hans from Industry Ventures. Okay. Well, that does it for today's show. A reminder that we are live on this stream Monday through Friday at 10AM Pacific, 1PM Eastern. I want to thank Amazon Web Services, who is our presenting sponsor for this production.

感谢各位的收看，我们真心珍视您的观看。我已经开始期待明天的节目了。届时再见，拜拜。

I want to thank you for tuning in. We really do appreciate your viewership. I am already excited for our next show tomorrow. Until then, bye bye for now.