AWS新企业AI推进计划，OpenAI与博通达成合作，科技巨头AI广告布局 | 2025年10月13日

欢迎大家收看Information TI TV。我是Akash Pesritsha。今天是10月13日星期一。希望你们周末过得愉快。今天我们为大家准备了一场精彩的节目。

Welcome everyone to the Informations TI TV. My name is Akash Pesritsha. It is Monday, October 13. Hope you had a great weekend. We have got a big show planned for you today.

OpenAI和博通宣布了一项为期四年的重大芯片合作协议。我们的云计算记者很快就会上线，为大家解读这条新闻的背景。亚马逊网络服务的首席营销官几分钟后就会登场，所以请别走开。我对这场对话非常期待。我们还将讨论现实世界资产的代币化，说实话这是我一直在努力理解的概念，所以很期待这场讨论。

OpenAI and Broadcom are announcing a major chip deal over the next four years. Our cloud reporter will be up very shortly to put up the news in context. The chief marketing officer of Amazon Web Services is coming on in just a few minutes, so do not go anywhere. I'm excited for that conversation. We are also talking about the tokenization of real world assets, which frankly is something I'm really trying to wrap my head around, so I'm excited for that chat.

之后，我们将与一位在高管招聘领域建立了大型企业的人士探讨AI人才争夺战。最后，我们还有一个关于Salesforce、谷歌和微软如何规划其AI驱动的广告技术推进的精彩故事。内容非常丰富，让我们直接请出第一位嘉宾。OpenAI和博通正在联手合作。他们宣布计划在未来四年内推出10吉瓦的定制AI芯片。

After that, we're going be talking about the AI talent wars with someone who has built a big business in the land of executive search. And finally, we have got a great story about how Salesforce, Google, and Microsoft plan are planning their AI powered ad tech push. There is a lot to get to, so let's get right into our first guest. OpenAI and Broadcom are teaming up. They announced a plan to roll out 10 gigawatts of custom AI chips over the next four years.

现在请我们的云计算与计算记者Anissa Gardizi来为我们解读这条新闻的背景。Anissa，今天早上很忙碌。你怎么样？

Here to put the news into context is Anissa Gardizi, our cloud and compute reporter here at The Information. Anissa, it's a busy morning. How are doing?

我很好。很高兴来到这里，Akash。

I'm doing well. Happy to be here, Akash.

那么我们来谈谈OpenAI与另一家芯片公司达成的另一项芯片协议。先告诉我们已知的细节，然后再讨论更宏观的背景。

So let's talk about another chip deal that OpenAI has done with another chip company. Give us the details of what we know, then we'll talk about the bigger picture here.

今天早上，OpenAI和博通宣布了一项重要合作伙伴关系，将为OpenAI部署10吉瓦的定制AI芯片。业内普遍知道OpenAI正在与博通合作开发自己的芯片，以减少对英伟达的依赖。但我认为，今天公司公开谈论此事并给出具体数字——四年内10吉瓦——真正显示了两家公司的认真态度。而且，OpenAI确实需要为这项努力筹集大量资金。所以我认为，可能接下来的几个星期一我们都会在TI TV上讨论他们。

This morning, OpenAI and Broadcom announced a major partnership to deploy 10 gigawatts of custom AI chips for OpenAI. And it was broadly known within the industry that OpenAI was working with Broadcom on its own chip effort, to help reduce its reliance on NVIDIA. But I think, you know, the publicly the company is publicly talking about it today and putting a figure on it, 10 gigawatts over four years really shows how serious the two companies are. And, you know, OpenAI does need to raise a lot of money for this effort. So I think we should expect maybe, you know, the next couple of Mondays we might be on TI TV talking about them.

这有点有趣，因为在过去几周里，我们看到OpenAI与英伟达达成协议，或者说英伟达宣布有意向OpenAI追加投资。接着我们又看到了OpenAI与AMD的交易。我的意思是，我们一直在问大家的问题是，这对OpenAI自己的芯片计划意味着什么？因为我们知道他们打算自主研发芯片。而我想这大概是我们最接近确认'是的，我们正在做'的一次表态了。

And it's kind of funny because over the last couple of weeks, we've seen OpenAI do a deal with NVIDIA or NVIDIA announcing its letter of intent to invest more money into OpenAI. Then we saw the OpenAI AMD deal. I mean, the question that we kept asking folks is, well, what does this mean for OpenAI's own chip efforts? Because we knew that they were going to be working on their own chip. And I guess this is sort of the closest look we've had at saying, yeah, we're doing it.

而且我们正在与博通大规模合作推进这个计划。

And we're doing it in a big way with Broadcom as well.

没错。100亿瓦特确实不是开玩笑的。这正好是OpenAI与英伟达战略合作的规模。当然，OpenAI还期望通过其他交易获得英伟达芯片。但考虑到现在内部芯片计划的规模与战略合作相当，我认为这充分说明了OpenAI多么不希望依赖单一公司甚至两家公司。

Right. I mean, 10 gigawatts really isn't a joke. That's the exact amount of the strategic partnership between OpenAI and NVIDIA. Of course, OpenAI expects to get NVIDIA chips through other deals. But, you know, given that this now internal chip effort is the same size as the strategic partnership, I think it really puts into the context how much OpenAI does not want to be reliant on one company or even two companies.

他们，他们似乎希望有多家公司帮助他们实现算力目标。

They, they sort of want many companies helping them reach their compute goals.

黄仁勋对此肯定不会高兴。

And Jensen can't be happy about that.

我猜确实不会高兴，特别是考虑到今天的宣布方式。我认为主要信息是，OpenAI和博通不仅仅是在合作开发芯片，他们是在打造完整的数据中心系统，包括网络和其他运行系统所需的组件。而这正是英伟达的核心卖点。

Guess is is not really, especially given the way that this was announced today. I I think the main takeaway was that, you know, OpenAI and broadcomcom are not just working on a chip. They're working on the entire data center system, networking and other things you need to run run a system. Right. And that is sort of NVIDIA's pitch.

他们总是说我们做的不仅仅是制造芯片。而今天博通宣布的也正是这一点。

They they always say that we do more than just building a chip. And so today that is kind of what Broadcom announced as well.

我们在节目中讨论过的一点是，博通确实有一些产品有助于构建完整的数据中心基础设施。这不仅仅是芯片本身。

And this is one of the things that we've talked about on the show is that Broadcom has sort of some of those products that help build out sort of that full data center infrastructure. It's not just the chip itself.

没错。我认为这很可能就是OpenAI被博通这样的合作伙伴吸引的原因。当然，我们还得看事情如何发展。我们还没有真正见过这些博通芯片的实际表现。所以，你知道，随着所有这些公告的发布，我们必须观察后续进展，但意图非常明确。

Exactly. And, and I think that's probably why OpenAI was drawn to a partner like Broadcom. Of course, we'll have to see how this all shakes out. We haven't really seen any examples of these Broadcom chips in action yet. So, you know, with all these announcements, we're gonna have to see what happens, but the intent is very clear.

对。随着这个故事进一步发展，你在关注哪些方面？

Right. As you're looking for this story to develop further, what are you watching for?

嗯，今天早上我们注意到，博通的总裁今天早上在电视上与Greg Brockman交谈。他被问到，哦，这是不是CEO Hock Tan在上次财报电话会议上提到的那个100亿美元的客户？他似乎在暗示OpenAI并不是那个100亿美元的客户。所以今天的一大问题就是，这是真的吗？那么谁才是那个100亿美元的客户？

Well, one thing that we noticed this morning was, Broadcom's president, was on TV this morning talking with Greg Brockman. And he was asked the question, oh, well, is this your $10,000,000,000 customer that CEO Hock Tan talked about on the last earnings call? He kind of made it seem like OpenAI was not that $10,000,000,000 customer. Definitely one of the big questions today is, is that true? Then who is the $10,000,000,000 customer?

因为博通可能还有另一个他们未公开谈论但依然重要的合作关系。

Because Broadcom might have another relationship that they aren't publicly talking about that is still going to be important.

对。Anisa，非常感谢你临时赶来。这就是突发新闻的魅力。我们期待在故事进一步发展时再次邀请你。这位是Anisa Gardizi，我们TI TV的云与计算领域记者。

Right. Well, Anisa, thank you so much for coming on a short notice. That is the beauty of breaking news. We look forward to having you back on as we see more of the developments in the story playing out. That is Anisa Gardizi, our cloud and compute reporter here on TI TV.

好的。亚马逊云科技（AWS）上周发布了重磅消息，推出了一套新的以企业为重点的AI工具，可能会挑战像Glean这样快速发展的企业搜索公司的势头。AWS的一些工具是新的，但也有一些是对市场上已有AI工具的重新包装。当然，AWS凭借其云业务和自研芯片努力还有更多底牌，但在这两个方面的竞争从未如此激烈。所以我想请来AWS的首席营销官Julia White。

Okay. Amazon Web Services made big news last week with a new suite of enterprise focused AI tools that could challenge the traction of fast growing enterprise search companies like Glean. Some of AWS's tools are new, but some of them are also a repackaging of older AI tools that has already had in the market. Of course, AWS also has a lot more under the hood with its cloud business and its own chip efforts, but never before has there been more competition on both those fronts. So I want to bring on Julia White, the Chief Marketing Officer of AWS.

这是她第一次上节目。欢迎你，朱莉娅。很高兴你能来。

It is her first time on the show. Welcome, Julia. It's great to have you.

嗯，非常高兴来到这里，阿卡什。谢谢你。

Well, so great to be here Akash. Thank you.

所以我非常期待讨论你们上周发布的一些公告。我有一个基本问题，你们推出了QuickSuite。QuickSuite与我们之前在The Information多次讨论的另一款产品Q有何不同？

So I'm excited to talk about some of the announcement you guys made last week. One of the fundamental questions I do have is you guys unveiled QuickSuite. How is QuickSuite different from Q, which is another product that we talked a lot about here at The Information.

嗯，QuickSuite确实建立在我们从Q for business以及QuickSight（正如你也提到的）中获得的经验基础上。它源于观察我们内部员工使用的工具和他们所面临的需求，我们将所有这些整合在一起。正如你比任何人都更了解的那样，这个领域发展迅速。

Well, QuickSuite really builds on the learning we've gotten from Q for business, as well as, QuickSight, as you also alluded to. And then it really germinated from watching our internal employees and the tools they were using and the needs that they had. And we brought all that together. As you know better than anyone, right? The space is moving fast.

因此，我们能够真正观察、学习、调整和适应，并将它们整合成一个连贯的体验，我们称之为Amazon Quick Suite，这正是我们推向市场的演进成果。

And so our ability to really watch, learn, pivot, and adapt and bring them into a cohesive experience, we call Amazon Quick Suite, is really the evolution that we're bringing to market

本周。那么Q是否包含在Quick Suite中

this week. So does Q fit inside Quick Suite

或者它是如何运作的？

or how does that work?

这确实是下一代产品。因此，我们的Q业务客户正在升级为Quick Suite应用程序。它继承了这些功能。当然，如果您正在使用Q业务，就像我们对所有企业客户一样，我们会继续提供支持。但这实际上是该产品的演进版本，随着时间的推移，它将最终取代原有产品。

It's really the next generation. So our Q business customers are being evolved into the Quick Suite application. It takes over those capabilities. Of course, if you're on Q business, as we do with any enterprise, we continue to support that. But really it is the evolution of that and it will replace it in the fullness of time.

我们的一位记者上周对此进行了报道，他提到的一点是，这感觉更像是一次品牌重塑而非新产品发布。您不这么认为吗？

Well, one our reporters wrote about it last week, and one of the things he mentioned is it felt a little bit more like a rebranding than an introduction of new products. Do you not see it that way?

实际上我们整合了许多全新功能。例如，行业领先的快速研究功能——这是其中的一项能力，您可以深入挖掘，全面了解整个行业动态，或者为您制定完整战略。但更重要的是，整个用户体验和应用界面都是全新的，这源于我们对内部客户和外部客户的观察，并将这些要素整合在一起。

Well, we bring a lot together that is brand new. For example, when you have like industry leading quick research, which is one of the capabilities in it where you can go deep, deep, deep and understand what's happening across the whole industry sector or put a whole strategy together for you as an example. But then the entire user experience and the application experience itself is new and kind of again germinated out of watching our internal customers as well as our external customers and bringing those pieces together.

QuickSuite的一个亮点是企业搜索工具，以及能够在您安装的所有其他软件中使用该产品的能力。我们在节目中讨论过快增长初创公司如Glean时提到过这个。The Information报道过的一个挑战是，某些软件公司可能会阻止或限制AI公司访问其程序内部托管的数据——这就是企业数据战争的整个议题。这对您目前来说有多大挑战？

One of the neat parts of QuickSuite is sort of the enterprise search tool and the ability to use this product across all of your other software that you have installed. It's something that we've talked about in the show in the context of fast growing startups like Glean. One of the challenges that we've written about here at The Information is this idea that that some software companies may block or may throttle access to their own to the data that's hosted inside their own programs from AI companies who are looking to access them. This is the whole issue around corporate data wars. I mean, how much of a challenge is that for you right now?

我们的索引功能已经上市，现在作为Quick Suite的组成部分——Quick Index，使客户和我们自己能够接入Salesforce、Slack等第三方平台，当然还有存储在AWS的大部分世界数据。我们可以访问所有这些数据。但新的方面还包括接入您的个人信息，如Microsoft 365、文档、PPT和电子邮件。我们通过公开API与这些机构合作，不存在访问障碍。

We've had in market our index. It's now part of the Quick Suite again, Quick Index, that is enabling, you know, customers ourselves and others to tap into things like Salesforce and Slack and third party and obviously all of the data sitting in AWS, which is where most of world's data actually sits. So we have access to all of that. But then the new aspect of it as well is also your kind of your own personal information like Microsoft three sixty five, your docs, your PowerPoint, your email. And, we don't see in terms of we're using public, APIs, we're working in partnership with these organizations.

因此，针对您提到的担忧，我们目前没有看到这方面的问题，但理解这些关切。

And so, to your point of, we don't see that on the horizon, but understand the concerns.

理解这些关切。但您的意思是即使可能存在这种风险，您也不认为这会成为问题？

Understand the concerns. But you're saying that you don't foresee it being an issue, even though it could be one way it goes?

我认为我们再次与众多这些公司合作进行，其中许多公司也是AWS的客户和合作伙伴。因此，很大程度上是与他们携手合作完成的。

I think we were doing it in partnership with so many of these companies again, and so many of them are customers and partners with AWS as well. And so very much doing it in partnership with them.

没错。我想谈谈一些企业试图从AI中获得的投资回报率（ROI）。这对某些企业来说一直是个难题，因为这些项目可能成本高昂，而且你可能不知道使用这项技术的正确方式。智能体（agents）尤其是一个让人们对AI感到困惑的领域，人们会说，'嘿，我试过了，但它太慢了。'

Right. I want to talk about the ROI that some businesses are trying to get out of AI. It's something that has been difficult for some businesses, given that these projects can be expensive. And also, you might not know the right ways in which to use the technology. And agents are specifically one area of AI where people have kind of been scratching their heads saying, Hey, I'm trying it and it's slow.

我的意思是，你知道，我还没看到效果。你的客户真的看到了ROI，还是这些目前都只是他们在试用技术的试点项目？

I mean, you know, I'm not seeing the impact just yet. Are your customers actually seeing ROI or are these all just sort of pilot projects that they're just playing with the technology right now?

但我们确实看到了人们所说的那种'试点炼狱'，对吧？我认为这就是为什么我们总结了经验教训，再次通过Quick Suite观察、学习并灵活调整。但启动和使用它是零摩擦的，对吧？作为用户，你已经有了数据设置。他们发送了你的组织信息并进行了配置，但你也可以立即再次引入你的文档、BI仪表板的访问权限，甚至是Snowflake中的数据。

But we've definitely seen the kind of what people call it, that the pilot purgatory, right? And I think that's why we made the learnings we've had, again, that we've been able to watch, learn, pivot with Quick Suite. But getting it up and started is like zero, zero friction, right? So as a user, you already have your data setups. They sent your organizations, put that in place, but you can also just immediately bring in again, your documents, your access to BI dashboards, even the information sitting in like Snowflake.

因此，用户可以非常快速地行动起来，这能让你摆脱'我卡在试点阶段'的困境，真正在实际中使用它，对吧？这些工具可以访问所有业务数据。你不需要绕开它工作，而这通常是获得ROI的问题所在。所以，再次以我自己的组织为例，我们现在使用QuickSweet进行每一次营销评审，因为团队可以立即把所有内容整合在一起。我们知道我们想要什么样的洞察，然后它可以将其放入评审中供我们所有人分享。

And so the user can get moving very, very quickly, which can get you out of just, I'm stuck in pilot and I'm actually can use it in a real world way, right? These tools get access to all the business data. You're not just trying to work around it, which is usually the problem of getting ROI. So again, just within my own organization, we now run every marketing review using QuickSweet because then a team can pull everything together instantly. We know what kind of insights we're looking for, and then it can put it into a review for all of us to share.

这样一来，你现在就可以从ROI的角度来衡量了。好的，我的团队现在花一半的时间就能完成业务评审。这有什么价值？他们可以利用这些洞察去开展另一个营销活动，而不是花两个小时仅仅寻找洞察。

So then that's, you're now measuring from an ROI perspective. Okay. My team now takes half the time to get their business review pulled together. What's the value of that? Their ability to go instead work on another marketing campaign using those insights versus that two hours to actually just find the insights.

没错。

Right.

但在与客户交流时，他们面临的最大挑战是什么，或者说目前阻碍他们在AI上投入更多资金的最大因素是什么？

But as you're talking to customers, what is the biggest challenge that they have, or what is the biggest factor that is preventing them from spending more on AI right now?

主要是关于，这很有趣。这是个老生常谈的问题，但确实是数据孤岛，对吧？而这正是拖慢许多工具效益的原因——获取正确数据、整合数据并使其有用。因此，我们花了大量时间在快速索引上，确保数据孤岛能够协调统一。而且，我们采取了不同的方法，对吧？

Mostly it is about, it's interesting. It's such an old world problem, but about data silos, right? And that's what slows down the benefit of so many of these tools is getting access to the right data, bringing it together, making it useful. And so again, one of the things we spent so much time on was quick index, making sure that the data silos could be harmonized. And again, take a different approach, right?

这个领域的许多其他公司都在做应用特定或数据孤岛特定的代理体验，而我们则采取了非常广泛的视角，再次借鉴了我们作为AWS的历史，以及我们广泛的、多样化的基础设施和数据系统，我们可以将这些也带到应用层。因为正是这些拖慢了人们的进度，使得工具不那么有用，并且在无法获取正确数据时，投资回报率（ROI）就会受到影响。

A lot of the other people in this space are doing it application specific or data, silo specific kind of agentic experiences where we looked very broadly, again, you know, taking from our history of being a, AWS and a broad, broad set of infrastructure and data systems that we could bring that forward into the application layer as well. Cause that's what slows people down. And that's what makes it not as useful and where the ROI struggles when you can't get access to the right data.

没错。AWS有自己的工具来帮助人们开发自己的代理。我们上周也看到OpenAI发布了类似类别的工具。你对他们上周的发布有什么看法？

Right. AWS has its own tools to help people develop their own agents. We also saw last week OpenAI unveil a similar tool in that category. What did you make of their release last week?

我认为，你知道，代理领域发展得非常快。我认为我们会看到大量的实验和持续的演进。正如你看到的，我们推出了Curo，我们的开发者代理IDE，并在开发者采用率和他们用它做的事情方面取得了非常非常好的成功。现在有了面向所有员工和各种组织用途的QuickSeat Suite。甚至就在今天，我们名为Bedrock Agent Core的新代理平台也正式发布了（GA）。

I think, you know, the AgenTic space is moving incredibly fast. I think we're going to see a lot of experimenting and then continuing to evolve. And as you've seen us bring out, you know, Curo, our AgenTic IDE for developers and seeing really, really wonderful success in terms of adoption with developers and what they're doing with it. Now with QuickSeat Suite for all of the employees and kind of uses that organization. And then even just today, our new agentic platform called, Bedrock Agent Core is in GA.

所以，所有这些不同的工具，无论你是开发者，还是在构建代理系统的整个基础设施，或者你是最终用户，都覆盖了所有这些不同的方面。

So all the different tools, whether you're a developer, whether you're building out the whole infrastructure for AgenTic systems, or you're an end user, covering all those different bases.

没错。我们The Information这里报道的另一件事是，考虑到租用这些AI芯片的一些底层技术可能非常昂贵，云提供商面临的利润率压力。你们在自己的业务中是否也看到了这种利润率压力？

Right. And one of the other things that we've written about here at The Information is sort of the margin pressure that comes up for cloud providers, given how expensive some of the underlying technology can be for renting out these AI chips. Are you guys seeing any of that margin pressure in your own business?

不，我们的业务依然非常健康，正如您在财报中所见，以及我们看待和报告的方式，它继续保持相当稳定。

No, our business continues to be quite healthy, and as you see in our earnings, and the way we look at it and report, it continues to be quite steady.

那你们拥有的Trainium芯片呢？我们刚才在您之前的环节讨论了OpenAI自主研发芯片的雄心。我们一直在等待更多细节。当然，亚马逊在这方面已经努力了很长时间。您能否谈谈AWS客户实际要求的程度，比如他们说‘嘿，我们想使用那种芯片’，或者‘我们想使用与该芯片相关的计算资源，而不是像过去两三年习惯使用的NVIDIA产品’，他们现在真的在提出转换的要求吗？

What about the Trainium chip that you guys have? Were just talking earlier on the segment before you about OpenAI's own ambitions to develop their own chip. It's something that we were waiting for more details on. Of course, Amazon has had this effort going for a long time. Can you talk about the extent to which AWS customers are actually asking to say, Hey, we want to use that chip, or, you know, we want to use the compute associated with that chip instead of something like NVIDIA, which they might have been used to doing for the last two or three years, are they actually making the ask to transfer right now?

嗯，正如您所说，我认为我们对自有芯片的长期投资，以Trainium作为最新范例，从性价比角度来看确实是我们的一大优势。如果您看看使用Bedrock（我们的AI平台）的客户，其中超过一半是由Trainium驱动的。所以许多使用Bedrock的客户中，超过一半已经在使用它了。而我们与Anthropic合作的大型投资项目Project Rainier，我们的超级AI构建，也主要由Trainium驱动。因此，我认为Trainium的成效和我们能提供的性价比就是最好的证明。

Well, as you said, I think our investment, our long term investment in our own chips, with Trainium being kind of the most current example, is really a wonderful advantage for us, right, from a price performance perspective. And so if you just look at our customers using Bedrock, right, our AI platform, over half of that is powered by Tranium. So over the half of customers of many, many that are using Bedrock are already using that as well. And then our big, big investment called Project Rainier, our super AI, kind of build out with in partnership with Anthropic, also powered largely by Tranium as well. And so I think proof's in the pudding in terms of seeing Tranium pay off and the price performance we can provide.

当然，顺便说一下，我们与NVIDIA是优秀的合作伙伴。我们托管他们的芯片比任何人都多，但这为客户提供了多样化的选择。

Of course, by the way, we're wonderful partners with NVIDIA. We host, more of their chips than anyone, but, it's an opportunity for customers to have, variations.

对。我的意思是，我只是想知道公司内部是否设定了目标，比如说，我想我刚刚没听清那个细节。您说一半的Bedrock客户正在使用，是的，

Right. And I mean, I just wondered if internally the company had a goal in saying, you know, we, I think I just missed that detail. You said half of Bedrock customers are using Yeah,

超过一半的Bedrock是由Trainium驱动的，对吧？

over half of Bedrock is powered by Tranium, right?

所以通过

So by

按定义来说，那么使用Bedrock的客户中有一半是由Tranium提供支持的。

definition, then half the customers using Bedrock are powered by Tranium.

是的。太好了。嗯，朱莉娅，感谢你来到我们的节目。上周是新闻激动人心的一周，我们一直很关注事态的发展。感谢你来到节目。

Right. Great. Well, Julia, I want to thank you for coming on the show. It was an exciting week of news last week, and it very much is something that we've been interested to see how it plays out. Thank you for coming on the show.

我们非常感谢。如果你有更多消息，请再次来到节目告诉我们更多细节。这位是AWS的副总裁兼首席营销官朱莉娅·怀特，做客TI TV。我们在节目中多次讨论过AI如何改变广告格局。这也意味着广告技术领域将迎来重大变革。

We appreciate it. As you have more news, please come back on the show and tell us more about it. That is Julia White, the Vice President and Chief Marketing Officer at AWS here on TI TV. We have talked a lot on this show about ways in which AI is changing the advertising landscape. It also means big changes are coming for the ad tech sector.

今天，《信息报》发表了一篇报道，不仅涉及谷歌和亚马逊等现有广告技术巨头如何使用AI，还谈到Salesforce和微软等其他大型科技公司如何加入这场游戏。我想请我们的广告记者凯瑟琳·珀洛夫来详细介绍她写的这篇报道。同时参与对话的还有Tau Marketing Solutions的首席执行官罗伯特·韦伯斯特。凯瑟琳和罗伯特，很高兴你们两位来到节目。欢迎来到TI TV。

Today, the information published a story not just about how existing ad tech giants like Google and Amazon are using AI, but also about how other big tech companies like Salesforce and Microsoft are getting into the game. I want to bring on Katherine Perloff, our advertising reporter, to tell us more about the story that she wrote. And also joining us in the conversation is Robert Webster, CEO of Tau Marketing Solutions. Katherine and Robert, it's great to have you both on the show. Welcome to TI TV.

是的，能来这里真的很棒。

Yeah, it's actually great to be here.

那么，凯瑟琳，让我们从你写的这篇报道开始聊起。你知道，我们之前讨论过广告市场的整体情况。这篇报道很有趣，因为它提升了一个层次，讲的是公司如何规划和评估他们进行的广告活动。请告诉我们一些在规划这些活动时存在的挑战。

So, Catherine, let's start about let's let's talk about this story that you wrote. You know, one of the things that we've talked about is sort of the marketplace for ads altogether. And this was kind of an interesting story because this is a story one level up. It's about how companies are sort of planning and evaluating these advertising campaigns that they do. And so tell us a little bit about some of the challenges that exist with respect to people planning these campaigns.

我的意思是，有这么多不同的平台。有哪些挑战呢？

I mean, you've got so many different platforms. What are some of the challenges?

是的。你知道，购买广告的系统非常复杂。涉及大量不同的技术，特别是如果你想在网页或电视上购买广告。你需要使用一整套不同的广告技术系统。另一个挑战是，通常认为在Meta或YouTube上购买广告相对容易一些，但很难比较这些渠道间广告活动的效果，因为谷歌可能使用不同的指标或计算方式与Meta不同。

Yeah. You know, so the system for buying ads is very complicated. There's a ton of different technologies involved, especially if you want to buy ads on the web or on TV. There's a whole different system of different ad technologies you have to use. The other challenge is, you know, it's typically seen as a little bit easier to buy ads on, like, Meta or YouTube, but it's very hard to compare the effectiveness of campaigns across those channels because, you know, Google might use different metrics or count things differently than Meta.

所以很难确切知道应该把钱投在哪里，以及广告活动的效果如何，这形成了一个循环，因为如果一个广告活动效果好，你就应该在该渠道投入更多资金。因此很难进行全局规划。而人工智能代理可能通过简化部分流程来帮助解决这个问题，

So it's very hard to sort of know where exactly you should put your dollars and how well campaign the campaign worked, which then sort of is like a loop because, you know, if one campaign worked, then you should spend more money in that channel. So it's very hard to kind of plan across the top. And, AI, you know, agents can help sort of simplify some of that potentially by

没错。

Right.

创建更简便的工作流程，并能更智能地基于数据做出决策。

Creating an easier workflow and being able to be smarter about making decisions about the data.

但你报告中一个有趣的现象是，尽管有许多大型科技公司参与广告游戏，但实际上似乎出现了一种趋势，连更多科技公司，比如我从未与广告联系起来的Salesforce，也在考虑进入这个领域。他们打算怎么做？告诉我们你的发现。

But one of the interesting things that you reported is despite how many big tech companies are in the advertising game, there actually seems to be a movement here where even more tech companies, companies like Salesforce that I have never associated with advertising, they are also looking into getting into this space. How are they looking to do that? Tell us about what you found.

是的。需要澄清的是，Salesforce之前一直在营销领域，但更多是像，我的意思是，他们有一些媒体分析能力，但大多数营销人员熟知他们的主要业务是电子邮件营销，然后是存储数据，这显然与他们存储客户信息的核心业务密切相关。我认为，随着他们最近推广的这种Agent Force技术，这项技术不仅能分析哪些广告活动有效、哪些无效，并能以更复杂的方式实现，还能为你采取行动。所以如果你的谷歌广告活动效果不佳，它可以主动停止它。

Yeah. So Salesforce, to be clear, has been in the marketing space before, but it's been more sort of like, I mean, they've had some media, analysis capabilities, but their kind of main bread and butter that most marketers know them for is email marketing and then, like, storing your data, which is obviously very related to their core business of just, like, storing customer, information. And I think that, you know, with, their their new kind of they have this agent force technology that they've been pushing recently. And with that technology, it doesn't just analyze which campaigns are working and which aren't and maybe do that in a more sophisticated way, but it also can take an action for you. So if your Google campaign isn't working, it can go ahead and like stop it.

我认为这种技术虽然有点术语化，但行业里一直存在两类技术：营销技术（MarTech）和广告技术（AdTech）。营销技术更像是存储你的信息，可能是客户信息，发送电子邮件或短信。而随着人工智能的发展，这种与更侧重于媒体执行的广告技术之间的区别正在逐渐模糊。我认为这是我们在企业技术中看到的一个趋势，人工智能正在模糊不同类型公司之间的界限。在广告领域也是如此，这意味着更多不同的参与者可以参与进来。

And I think this kind of technology, there it's kind of jargony, but there's kind of been two different sets of tech in the industry, MarTech and AdTech. MarTech being sort of this more just sort of storing your information, maybe, your customer information, you know, sending them emails, sending them texts. And I think with AI, those sort and those, that distinction from ad tech, which is more about, executing on media, is sort of collapsing a little bit. And I think this is a story we're seeing across enterprise technology that AI is sort of bleeding these distinctions between different types of companies. And we're seeing that kind of in the advertising space as well, which means more different players can get involved.

罗伯特，你的客户是如何考虑在这个故事背景下使用人工智能的？

Robert, how are your clients thinking about using AI in the context of of this story?

是的。正如凯瑟琳刚才所说，我认为关键在于如何整合数据以做出更全面的决策。很多方面都围绕着如何提高效率？如何消除那些耗时冗长的繁琐工作？以及如何真正利用你的才能去做更具创造性、更出色的工作？

Yeah. So I think as Catherine just said, it's about how you bring data together to make more holistic decisions. And a lot of it is around how do you drive efficiencies? How can you remove a lot of that busy work that has to happen that takes a long time? And how do you actually use your talent to do more creative, better work?

所以这里的目标确实是节省时间提高效率，但同时也推动更好的结果。是的。我们提到了像Salesforce、Adobe这样的公司进入这一领域。当你利用客户数据来做广告决策时，这将带来更好的效果。所有这些都是以非常安全的方式完成的。

So the objective here really is definitely an efficiency saving on time, but also driving better results. Yeah. We mentioned the people like Salesforce, Adobe getting into this space. When you've got customer data also being used to make advertising decisions, that's just going to drive better results. All done in a very safe fashion.

我很好奇，我们在节目中经常讨论的一点是使用人工智能和智能体带来的投资回报率（ROI），这是企业真正在努力寻找的东西，毕竟人工智能在很多情况下可能非常昂贵。而成本节约、收入提升，在某些情况下可能有点模糊。你是否看到了在广告领域使用这些智能体所带来的真正战术性的ROI？还是说仍然处于‘嘿，我们还在摸索如何使用它’的阶段？

And I'm curious, one of the things that we've been talking a lot on the show is the ROI that comes with using AI and agents, and it's something that businesses are really trying to find, really, given that AI in many cases can be very expensive. And the cost savings, the revenue uplift, it can be a little bit vague in some cases. Are you seeing, you know, really tactical ROI that is coming from using these agents in the advertising space? Or is it still sort of, hey, we're just trying to figure out how to use it in the first place?

不，不。ROI现在已经实现了。你得知道智能体实际上已经准备好大约十二个月了。营销工作流程相当专业化。这是一种相当定制化的技能组合，涉及大量行业术语，过去需要经验。

No, no. The ROI is here now. You've got to think the agents already really been ready for about twelve months. And marketing workflows are quite specialized. It's quite a bespoke sort of skill set with some awful lot of industry jargon and in the past required experience.

所以如果智能体已经准备就绪并可用了大约一年，那么今年大部分时间可能都花在了让它们投入使用上。但现在你看到早期采用者在效率上获得了巨大回报，同时，也获得了ROI。并且谈论如何实现。

So if agents have been ready and available for a year, it's probably taken most of this year to get them used. But you're now seeing early adopters getting big returns on efficiency, but also, ROI on this. And Talk about how.

那个ROI是从哪里来的？

Where is that ROI coming from?

那么，如果你现在试图做出竞争性决策，你可以更快地做出更好的决策。比方说，你正计划购买所有想要的广告位。我还没遇到过哪个策划人能同等精通电视、搜索、Meta、TikTok所有渠道，并且能同样出色地运用所有这些顶级数据集，同时还要实现全球化运作。

Well, so if you're trying to make competitive decisions now, you can make better decisions faster. A world, let's say you're trying to plan all the beauty you want to buy. I haven't met a planner yet who knows TV, search, Meta, TikTok, all equally well. And equally is able to use all of the data sets equally well across the top. Then also making that global.

假设你要在全球50个市场统一决策如何投放所有媒体资源。没有人类能做到这一点。但有了强大的人工智能配合人类专家，就能在10%的时间内以高度准确性完成这项工作。

Let's say you make a decision globally about how to run all your media in like 50 markets. No human can do that. But an AI with a great human alongside them can do that in 10% of the time to a high degree of accuracy.

凯瑟琳，最后我想听听你的看法。谷歌是这个领域的巨头。仅次于谷歌，目前谁是最紧追其后的公司？谈谈罗伯特刚才提到的投资回报率这一点，因为我认为这很重要——如果罗伯特说投资回报率就在这里。这实际上是我们尚未充分讨论的人工智能企业应用场景，它可能是唾手可得的成果，值得我们更多关注。

Kathryn, I want to end with you here. Google is a giant in this space. Second to Google, who is the company closest on their tail right now? Talk about that ROI point that Robert was talking about here, because I think this is it's important if Robert is saying, hey, the ROI is here. This is actually something it's an enterprise use case of AI that we haven't really talked about as much as, you know, it might be the low hanging fruit, something that we should be paying more attention to.

是的。在广告技术领域，谷歌无疑是领导者。亚马逊今年一直在追赶他们，这已成为优先事项。行业内还有一些其他知名且广泛使用的较小公司，比如The Trade Desk。

Yeah. You know, Google, I guess in ad tech, qua ad tech, you know, Google probably is the is the leader. Amazon has been catching up to them this year. It's been a priority. There's some other smaller firms that are well known and well used in the industry like The Trade Desk.

但在人工智能媒体策划这个新领域，我认为这项能力可能尚未成为科技公司的重点。或许就像...罗伯特不知你怎么看，但这似乎更多是广告代理商和买家自己处理的事情。所以我认为这只是增加了科技公司竞争的新层面，目前还没有明确的赢家。

But, you know, in terms of this sort of new area for media planning with AI, I think that this is a capability that hasn't really been as as much a focus for tech maybe. It's maybe been like, you know, I don't know if Robert, you know, what you think here, but, like, you know, it seems like it's been something more kind of like that agencies and ad buyers would just do themselves. So I think it's just adding a new layer where tech companies compete. And I don't think that there is a clear winner right now. Right.

这就是为什么看起来令人兴奋。关于投资回报率，我认为就像那句经典的营销格言——贯穿历史，或许二十世纪以来一直在说：我知道50%的预算有效，但不知道是哪50%。技术曾承诺解决这个问题，因为现在我们知道谁看了广告并能追踪到购买行为。但说实话这让事情更复杂了，因为渠道变得更多，人们不再只看一个电视节目。

That's why it's kind of exciting to see. In terms of return on investment, I mean, I think that like, yeah, the the sort of like classic marketing adage that, is has been said throughout, history or I don't know, maybe the past twentieth century is like, you know, I know 50% of my budget work, but I don't know which 50%. And I think that like there was a promise of technology to solve that because, oh, now we know who's looking at the ads and we can trace that to the purchases. It's honestly made it a lot more complicated because there's way more channels. People aren't just watching one TV show anymore.

媒体生态系统确实非常复杂。数据也非常复杂。我不确定有了所有这些技术后，我们是否更接近回答这个问题：到底是哪个广告推动了消费。我认为目前存在大量浪费的支出，因为营销人员不知道应该把钱投在哪里。所以，如果我们能真正解答这个问题，将存在巨大的收益潜力。

Like the the media ecosystem is really complicated. Data is really complicated. And I don't know if we're actually closer with all this technology to answering that question, which ad actually drove, spend. And I think there's lot of wasted spend going on right now because marketers don't really know where to put their money. So I, I, there's a lot of potential for gain if we can really answer this question.

我的意思是，我认为有一点类似，你如何真正衡量某事物是否具有说服力？有些可能确实无法衡量。我认为其中一些可能超出了科学技术的范畴。但我认为有些方面我们可以更好地衡量。这就是为什么我觉得这很有趣。

Mean, something that I think is a little bit like, how do you really measure if something is persuasive? Some of it might not really be possible. Think some of it's kind of outside of the realm of science and technology. But I think some of it we could really measure a lot better. And I think that's why this is interesting.

嗯，看，这是一个迷人的领域，也是人工智能的一个应用，我认为我们在节目中讨论得还不够。所以我期待在未来几周和几个月里，随着故事的发展，再次邀请你们两位回来深入探讨。谢谢凯瑟琳，谢谢罗伯特加入我们。这里是TITB的资讯频道凯瑟琳和TAO营销解决方案的罗伯特。好的。

Well, look, it's a fascinating space, and it's an application of AI that I don't think we talk enough about on this show. And so I'm excited to have you both back on in the coming weeks and months as the story develops to talk more about this. Thank you, Catherine, and thank you, Robert, for joining us. That is Catherine from the Information and Robert from TAO Marketing Solutions here on TITB. Okay.

当加密领域这些天不讨论稳定币时，现实世界资产代币化是另一个让人兴奋的想法。我们马上会深入探讨这个概念的实际含义，但越来越多的公司已开始在这一类别中开发产品，其中不乏Robinhood。Securitize是该领域的另一家公司。据彭博社报道，该公司正考虑通过SPAC以10亿美元的估值上市。我想邀请创始人兼CEO卡洛斯·多明戈来谈谈他对业务发展的看法。

When the crypto sector isn't talking about stablecoins these days, real world tokenization is another idea that has everybody energized. We're going to get into what this concept actually means in a second, but more and more companies have started to build products in this category, not the least of which is Robinhood. Securitize is another company in the arena. The company is reportedly considering going public through a SPAC at a $1,000,000,000 valuation according to Bloomberg. I wanna bring on founder and CEO Carlos Domingo to talk about where he sees his business going.

卡洛斯，欢迎来到TI TV。很高兴你能来。

Carlos, welcome to TI TV. It's great to have you.

是的。谢谢邀请。我很荣幸能在这里。

Yeah. Thanks for inviting me. It's my pleasure to be here.

所以我很兴奋能和你聊聊现实世界资产代币化这项业务。不过我想先从新闻开始。彭博社有报道称，你们正寻求通过SPAC以10亿美元的估值上市。彭博社的报道属实吗？

So I'm excited to talk to you about this business of real war real world tokenization. I do want to start with the news though. So Bloomberg has a report out saying that you are looking to go public through a SPAC at a $1,000,000,000 valuation. Is the Bloomberg report true?

我无法对此发表评论。我只能说，你知道，这个行业一直在爆炸式增长，我们可能是最大的参与者，也是存在时间最长的。我们从中受益匪浅。而且，显然公开市场非常开放。Circle的IPO非常成功，对吧。

I cannot comment on that. The only thing I can say is that, you know, the industry has been exploding and has been probably the largest player and the the one that has been around for the longest. We've been benefiting greatly from that. And, obviously, public markets are very open. You know, Circle IPO was amazing and Right.

然后Bullish和其他许多公司都上市了。我们正在考虑所有选项。

Then bullish and many other companies went public. We're considering all the options.

所以，好吧。那么你们近期不会上市吗？

So, okay. So you are not going public in the near future?

我无法评论我们的

I can't comment on our You

即将上市。公众虚假信息。

are going public. Public disinformation.

好的。不过，我确实想广泛谈谈公司的发展轨迹。我的意思是，当你看到这个决定可能即将到来时，无论是上市还是不上市。你觉得你的业务可能采取的不同发展路径以及上市的不同选择有哪些？我们看到Coinbase选择了一条路。

Okay. Well, but I do want to talk broadly about, you know, the trajectory of the company. I mean, as you see sort of this decision possibly coming down the line, whether or not to go public or not. I mean, how do you think about the different trajectories your business could take and the different options of going public? And we saw Coinbase chose one route.

我们还有SPAC路线，还有IPO，这似乎有点无聊，对吧？所以你怎么看待这些不同的选择？

We also have the SPAC route and we have the IPO, which seems to be like, it's boring. Know? So how do you think about the different options there?

我认为首先有两件事。对吧？一是是否上市的决定，每个公司都需要分析自己的具体情况等等。但是，卢卡，我显然比你年长，我记得以前上市是大多数公司的目标。对吧？

I think that the first, there's two things. Right? One is the decision to go public or not, that every company needs to analyze their own, you know, particular situation, etcetera. But, you know, Luca, I'm older than you, obviously, and I remember the times when going public was the goal of most companies. Right?

像亚马逊这样的公司上市时规模非常小，比如市值只有几亿或两亿左右等等。但不知何故，在这个过程中，大家都尽可能长时间地保持私有状态。嗯。所以我认为，正如你提到的，有了更多上市途径，比如SPAC（特殊目的收购公司）——它们从2021年卷土重来——以及像Coinbase那样的间接IPO或传统IPO，现在公司有了更多选择。是的。

And companies like Amazon went public when they were very small, like, couple of 100,000,000 market cap or 200,000,000, etcetera. And somehow throughout the way, you know, it just became that everybody stayed private for as long as possible. Mhmm. So I think that, you know, with more avenues to go public, as you mentioned, you know, SPACs and which are back from the 2021 time and indirect IPOs like Coinbase did or or just traditional IPOs, I think there's more options for for companies now. And Right.

显然，上市后你能够利用资本市场，提供财务透明度等等。但当然，每家公司都需要进行自己的分析。我的意思是，就选择何种机制而言，我认为只要执行得当，机制本身并不重要，公司上市后重要的是它们后续的表现。对吧？所以首先，我希望它们上市，然后看它们之后的表现如何。

Now, obviously, being public, you have the ability to tap capital markets, provide transparency towards your financials, etcetera. So but, obviously, every company needs to do their their own analysis. I mean, and in terms of what's the right mechanism, I would say that the mechanism is as far as you execute it correctly, it doesn't matter, like, the the what it matters for a company when it goes public is how do they perform after. Right? So first, I want them to go public and how they perform after.

你知道，2021年，很多可能本不该上市的公司上市了，并且

The, you know, 2021, a lot of companies that maybe shouldn't have been public went public and have

这就是为什么报告中让我最惊讶的部分是关于SPAC的。我认为我们见证了SPAC时代的兴起与衰落。现在它又重新成为话题。你如何看待SPAC作为一种上市机制？

And that's sort of why the part of the report that surprised me most was that the SPAC part of this, I I think we saw the SPAC era come and go. We're seeing it come back into the conversation. How do you think about the SPAC as a mechanism of going public?

我认为，你看，许多在2021年上市的公司，无论是通过SPAC还是IPO，其中一些表现非常好，一些则表现不佳，对吧？所以机制不应该是决定是否上市的关键因素。公司应该分析什么对它们最有利。我对IPO或SPAC没有特别的偏好或反对。我只是认为，不同的上市机制都有，重要的是你之后做了什么。

I think that, look, many companies that went public in 2021, whether they did SPACs or they did IPOs, some of them have performed very well, some of them have underperformed, right? So the mechanism shouldn't be the deciding factor for going public or not. You should say the company should just analyze what's best for them. I don't have anything particularly in favor against IPOs or SPACs. I just think that different mechanisms to go public, and what you do after is what matters.

那么我们来谈谈业务的基本面。你从事的是现实世界资产代币化的业务。向大家解释一下Securitize是做什么的，以及你在这个故事中扮演什么角色。

So let's talk let's talk about the fundamentals of the business. You are in the business of real world tokenization. Explain to everyone what it is Securitize does and how you fit into that story.

你可以把我们看作是一家服务提供商，负责将现实世界资产——主要是基金、股权或债券等——引入这种名为区块链的新账本技术，以实现这种现代账本技术的诸多优势。资本市场的一切都是关于更新账本，对吧？所以你买了一只股票，有人需要更新账本，说明股票已经易手，他们需要汇款，还需要更新现金账本等等。所以行业中的账本非常陈旧，并且彼此之间是脱节的。

So you can think of us as a as a service provider for, you know, taking, you know, real world assets, which for the most part is either, you know, funds or or equities or bonds, etcetera, and then bring them into this new ledger technology called a blockchain to be able to manifest a lot of the advantages of this very, you know, modern ledger technology. Everything capital mark markets is about updating ledgers. Right? So you buy a stock, somebody needs to update the ledger saying the stock has changed hands, and they need to send money, and they need to update the ledger of the cash, etcetera. So so ledgers are very antiquated in the industry, and they're disconnected with each other.

所以区块链有一个巨大的承诺，就像是这个早期分布式加密安全账本，资本市场可以借此实现现代化，而这基本上就是我们所做的事情。

So so blockchain has a a massive promise of, like, being this early distributed cryptographically secured ledger where capital markets can be modernized, and that's essentially what we do.

没错。你在之前的采访中谈到的一个观点是，金融体系所依赖的基础设施已经老旧过时。确实有理由更新它。也许区块链在其中扮演了角色。我想问的是，从客户和消费者的角度来看，为什么向代币化转变是有益的。

Right. So one of the things you've talked about in previous interviews is this idea that, look, the infrastructure on which the financial system is built, it is old, it is outdated. There is certainly an argument for updating that. Maybe blockchain plays a role in that. The question I want to ask you is why it's beneficial to move towards tokenization, for example, from the customer and the consumer's perspective.

我们听说有公司在研究代币化股票，例如。为什么这会有益呢？我的意思是，据我所知，人们现在就在交易股票。看起来对他们来说运作得挺好的。

We've heard companies look into tokenizing stocks, for example. Why is that beneficial when, I mean, as far as I could tell, people are trading stocks right now. Seems to work fine for their purposes.

确实如此。首先，我认为这取决于你所在的地理位置。比如，显然在美国，从终端用户的角度来看，股票交易非常高效，尽管幕后存在很多低效之处，像Robinhood这样的公司做得很好，让你感觉不到这些。但并没有一个场景表明代币化股票或其他代币化资产比非代币化版本更有实用性，对吧？

That's true. So first, I guess it depends on the geography where you live. Like, obviously, in The US, from the perception of an end user, trading stocks is very efficient even though there is a lot of inefficiencies behind the scenes that that the companies, like Robinhood, do a very good job of of isolating you from. But there isn't a scenario where, you know, tokenized stocks or tokenized other assets have more utility than the non tokenized versions. Right?

你可以随意转移它们，轻松地进行转让。比如，如果你今天想将股票从一个券商转移到Robinhood，可能需要两三天时间。如果你想用它们作抵押借款，会非常困难。而且，你知道，你虽然没有支付费用，但幕后的一些流程成本是有人在承担的，等等。

You can move them around. You can transfer them easily. Like, if you try to move today's stocks from a shop to Robinhood, it's gonna take you, like, two or three days. And if you wanna borrow against them, it's gonna be very difficult. And, you know, the you're not paying fees, you know, payment for other flow behind the scene that is something that somebody's paying for, etcetera.

所以我不认为——我认为美国的股票确实被认为非常高效，但我认为还有改进的空间。但在其他地区，这纯粹是一个可访问性问题，对吧？比如，你实际上怎么买股票？

So I don't think that I think that definitely stocks in The US are perceived as something very efficient, but I think there is room for improvement. But also in other geographies, this is a pure accessibility problem, right? Like, how do you actually buy stocks?

加密市场很忙——过去三天加密市场度过了一个繁忙的周末。我们应该说明，你知道，我们几周前就预定了与你的这次对话。我们不知道会发生什么。你周围的人在谈论什么？他们对过去三天加密市场的波动有什么看法？

We had a busy market in the crypto it was a busy weekend in the crypto markets the past three days. And we should say, you know, we we booked this conversation with you weeks ago. We didn't know what was gonna happen happen. What are people around you in your orbit talking what are they saying about the past three days in in crypto market movements?

我认为这恰恰更凸显了我们所做事情的价值，对吧？正如你所说，我们做的是现实世界资产。这些不是那些没有内在价值的代币，它们纯粹是投机性资产，而且显然流动性非常差。

I think this just shows more the the benefit of what we do. Right? Because what we do, as you've said, is the real world assets. Right? These are not you know, that like, a lot of these tokens that went out, these are tokens that don't have any intrinsic value that they you know, they're just pure speculative assets, and, obviously, they're very illiquid.

而当它们下跌时，就会暴跌，对吧？就像周末发生的事情，人们被平仓，然后情况加速恶化等等。所以我认为，如果说有什么启示的话，那就是验证了我们的观点：将具有内在价值和坚实支撑的现实世界资产引入加密经济，实际上是更多人应该考虑的方向。

And then when they go down, they go down hard. Right? Like, what happens on the on the weekend? And people get liquidated, and, you know, then it goes on faster, etcetera. So I think that if anything, what we see is is validating our thesis that bringing to the crypto economy real world assets that have intrinsic value and solid backing, it's actually something that more people should be considering.

太好了。卡洛斯，非常感谢你参加节目。我们非常感激。这是一个有趣的业务，对你来说也是一个有趣的时机。

Great. Well, Carlos, thank you so much for coming on the show. We really appreciate it. It's an interesting business and an interesting time for your business as well. Look.

我不会再追问了，但如果你们决定上市，请务必回到节目中来，告诉我们更多关于业务发展的计划。你会是其中之一

I'm not gonna press you further on it, but with if and when you do decide to go public, come back on the show and tell us more about your plans for the business. Be one the folks

会听到我的消息。你会是其中之一

to hear from me. You'll be one with

那就这么说定了。好的，这位是TI TV的卡洛斯·多明戈，Securitize的创始人兼首席执行官。

There you go. All right. Well, is Carlos Domingo here on TI TV, the founder and CEO of Securitize.

谢谢。

Thank you.

好的。人才争夺战一直是AI热潮中最有趣的部分之一，而很少有人比高管猎头顾问更能近距离观察这场‘抢椅子游戏’，他们帮助企业寻找所需人才。我想请来高管猎头公司Russell Reynolds Associates的董事合伙人克里斯·戴维斯，谈谈他在市场上的观察。克里斯，欢迎来到TI TV。很高兴你能来。

Okay. The talent wars have been one of the most interesting parts of the AI boom, and few people have a closer seat to these musical chairs than executive search consultants who help companies find the talent that they need. I want to bring on Chris Davis, managing partner at executive search firm Russell Reynolds Associates, to talk about what he's seeing in the market. Chris, welcome to TI TV. It's great to have you.

嘿，很高兴见到你，谢谢邀请。

Hey, great to see you, and thanks for having me.

我正想说，你我经常电话交流，但从未真正见过面，所以终于能见到真人真是太好了。真的很高兴见到你。多年来我们经常讨论科技界普遍存在的‘抢椅子’现象。听着，我确实想谈谈AI和人才争夺战，我们看到大型科技公司抛出天价薪酬包。同时，在这个节目中，我们有很多初创公司创始人正迅速吸引大公司的人才加入他们的团队。

I was going to say, you you and I have talked a lot on the phone, we've never actually seen each other face to face, so it's great to finally put a face to the name. Real positive to see you. We've talked a lot over the years about the musical chairs that happen in tech broadly. Look, I do want to talk about, you know, AI and the We've talent wars in seen these huge pay packages being thrown around by big tech companies. You know, at the same time on this show, we have a lot of startup founders who are quickly attracting people from big tech companies to come join their companies.

所以我在想，当你广泛观察AI人才市场时，你的感觉是，现在更多人倾向于加入资源无限（在某些情况下包括算力）的大型科技公司，还是更多人转向初创公司，认为‘我无法足够快地实现我想构建的东西，现在是我行业的关键时刻’？你是如何看待这个故事的展开的？

And so I wondered, know, as you sort of look at the market broadly for AI talent, what's your sense of are there more people interested in working at the big tech companies right now where there is like unlimited resources, in some cases for compute? Or on the flip side, are you seeing more people move to startups and saying, Look, I just can't build what I want fast enough. It's such an important time for my industry. How are you seeing that story play out?

说实话，我认为这可能就像其他职位一样细分，你知道，在科技类业务中，有些人倾向于高增长机会，他们想改变世界，潜力无限，可能是独角兽企业。而有些人会说，‘嘿，我想真正规模化地做这件事，改造传统组织’。所以这确实取决于个人，我认为当你区分那些倾向于大组织和小组织的人时，会看到不同的画像。小公司的人，我认为，往往是那些真正希望将眼前的AI机会产品化和商业化，并愿意承担一定风险的人。而倾向于大公司的人可能更倾向于逐步转型，推动组织变革，而非专注于构建新产品，如果这说得通的话。

You know, honestly, I think it probably just segments out like you would see in other roles where, you know, people in a tech for type of business, some gravitate to high growth opportunities where they want to change the world and, you know, the sky is the limit, it could be a unicorn. And some will say, Hey, you know, I want to really do this at scale and, know, transform like a legacy organization. So it does really depend, I think, you tend to see different profiles, I would say, when you segment out those that gravitate to the large orgs versus the smaller ones. The smaller ones, I think, tend to be folks that are really looking to productize and commercialize the AI opportunities that you see before you and really, you know, take on some level of risk. Whereas I would say that folks that gravitate to the larger FIs are probably looking to maybe more incrementally transform things, perhaps drive more organizational transformation than necessarily focus as much on building new product, if that makes sense.

对。研究人员最看重什么？我相信你和很多这些高知名度研究人员谈过。他们是人人追逐的人才。除了‘谁付我最多钱’，他们在考虑下一份角色时还会关注什么？

Right. What are the researchers looking for most? I'm sure you talk to a lot of these high profile researchers. They are the talent that everyone is after. What do they look for insofar as how they're considering their next role beyond just, Hey, who's going to pay me the most?

我认为，归根结底是提示工程的质量，以及在某种程度上还有好奇心。我的意思是，很多是技术技能，但也有一些是创造性技能，真正思考这些模型可能实现的范围。而且，坦白说，不仅仅是局限于研究领域，还要与更广泛的技术组织互动，甚至更重要的是与业务部门交流，说‘嘿，我们实际上可以用我们的模型想法开发新的收入模式、新的商业模式’。所以我会说，这结合了既有记录证明非常擅长提示工程和构建这些模型，也有能力与业务人员互动，弄清楚什么是可能的范围，我们可以在哪里真正改变增长或降低成本，你知道，创造新的建模方式。对。

I mean, I think really it just comes down to, you know, the quality of the prompt engineering, the quality of, you know, in some ways it's the curiosity too. I mean, you know, a lot of this is technical skills, but some of it is the creative skills as well to really think about the scope of what's possible with these models. And frankly, not just to be siloed within the world of research, but also to engage with the broader technology organization and maybe even more importantly, the business to say, hey, like, you know, we could actually develop new revenue models, new business models with model ideas that we have. So I would say it's a combination of just having sort of had the track record to really understand how to prompt engineer very, very well and build these models, but also the ability to kind of engage with folks in the business to figure out like what is the scope of what's possible and where could we really step change our growth or take the cost for that matter, you know, creative new modeling. Right.

你是否与芯片生态系统中的任何人合作，那些正在寻找下一个职位的人？

Do you work with folks at all in the chip ecosystem, folks that are looking for the next role there at all?

我个人没有。罗素雷诺兹公司的一些人会与制造商合作。

I personally don't. Some of the folks at Russell Reynolds will work with manufacturers.

我之所以问这个问题，Kashyuan，我想知道你是否对此有任何见解，就是与模型研究人员之间正在上演的同样的人才争夺战。我的猜测是，能够很好设计AI芯片的人仍然有限。我想人才争夺战一定也在那里上演，这些巨额薪酬包也一定流向了那些硬件工程师，对吧？

And and the reason I was asking, Kashyuan, I I wonder if you have any insight into this at all, is just the same talent wars that are playing out with the model researchers. I mean, my guess was that there are still a limited number of people that know how to design AI chips very well. I imagine that the talent war must be playing out there and these huge pay packages must be going to those hardware engineers as well, no?

我绝对认为是这样。我的意思是，我在硬件方面的工作不如软件方面多，我不想说得太绝对。我认为归根结底，人才争夺战确实在AI世界中发生着，你知道，这导致价格水涨船高，待遇，你知道，真的在升级，你知道，外面有什么替代选择？而且市场现在相当流动。所以人们，我的意思是，不一定像以前那样忠诚了。

I would definitely think so. I mean, I don't really work on the hardware side as much as the software side, I don't want to say definitively. I think at the end of the day, I mean, the talent wars are really happening in the world of AI and, you know, they are resulting in sort of prices ratcheting up, boats, you know, really sort of sizing up, you know, what are the alternatives out there? And the market's pretty fluid right now. So people are, I mean, not necessarily as loyal as they used to be.

他们流动得相当频繁，你知道，去寻找下一个最好的机会。

They move around quite a bit, you know, to the next best opportunity.

最后一个问题。我确实想和你谈谈，除了这些，AI初创公司和快速发展的AI公司最希望招聘哪些其他的C级职位。我想大约一年前我们聊天时，我们谈到了对首席营销官的需求，例如，或者AI公司正在组建他们的销售团队。你知道，那些仍然是需求量最高的C级职位吗？还是仍然非常注重技术，你知道，在某些情况下寻找CISO或CTO？

And last question for you. I do want to talk to you about what other C suite positions AI startups and fast growing AI companies are looking to hire most for. I think when you and I had spoken about a year ago, we talked about the need for chief marketing officers, for example, or AI companies sort of building out their sales teams. You know, are those still the C suite positions that are highest in demand? Or is it still very technical focused, you know, looking for CISOs in some cases or CTOs?

我想说可能已经从市场营销方面转移了一点。最肯定的是，CTO或CIO的角色往往是，你知道，负责大量AI甚至，你知道，一些更广泛的AI和组织转型。但另一个在AI领域真正，你知道，做了大量工作的领域是产品，对吧？因为归根结底，你知道，你看到大量投资涌入AI，而人们，你知道，寻求回报，这通常是通过，你知道，将这些AI用例商业化成为产品来实现的。所以无论是在金融服务还是科技或金融科技领域，你知道，我会说现在的产品角色，首席产品官，非常专注于，比如，我们如何将AI嵌入到所有不同类型的工作流程中？

I would say probably it has shifted a little bit from marketing actually. Most definitely the CTO role or the CIO role is one which tends to, you know, run a lot of the AI and even, you know, some of the broader kind of AI and organizational transformation. But the other area that's really, you know, really doing a lot of work in AI is product, right? Because at the end of the day, you know, you see a lot of investment going into AI and that the, you know, one is looking for a return and that often comes through, you know, the commercialization of these AI use cases into products. So in both in financial services as well as in tech or fintechs, you know, I'd say that the product roles now, the Chief Product Officer, is very focused on like, how do we embed AI in all the different kind of workflows?

实际上，我们如何将产品AI化？我们让产品更具自主性。所以我会说，你知道，可能比我们一年前交谈时产品化程度更高了。而且我认为，除了CTO之外，产品方面确实受到了大量关注，你知道，获得了许多

Actually, how do we AII's our products? We make our products more agentic. So I would say that, you know, maybe it's even more product than it was a year ago when we spoke. And I would say probably product next to the CTO is what's really getting a lot of attention, you know, getting a lot

关注。嗯，考虑到OpenAI聘请了Fiji Shimo担任应用部门CEO，这确实很有道理。这实际上是在承认：嘿，我们拥有这项底层技术，但必须弄清楚实际用它来制造什么，这样我们才有东西可卖。我认为这个观点很棒。

of attention. Well, mean, that would certainly make sense given that OpenAI hired Fiji Shimo as the CEO of applications. And that really is an acknowledgment that, hey, we have this underlying technology. We've got to figure out what to actually make with it so that we have things to sell. I think it's a great point.

Chris，非常感谢您参加节目。我们非常感激。接下来还会有更多招聘新闻，所以我很期待您再次做客节目深入讨论。这位是Chris Davis，Russell Reynolds Associates的董事总经理。好的。

Chris, thank you so much for coming on the show. We really appreciate it. There's going to be a lot more hiring news to come, so I'm excited to have you back on the show to talk more about it. That is Chris Davis, a managing partner, managing director, I should say, at Russell Reynolds Associates. Okay.

那么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。我要感谢本次节目的首席赞助商亚马逊云科技，也感谢各位的收看。我们非常珍惜您的观看。我已经开始期待明天的节目了。

Well, that does it for today's show. A reminder that we are 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, and I want to thank you for tuning in. We really do appreciate your viewership. I am already excited for our next show tomorrow.

那么在此之前，祝大家周一剩余时光愉快。暂时再见啦。

And so until then, have a great rest of your Monday. Bye bye for now.