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欢迎各位收看Informations TI TV。
Welcome everyone to the Informations TI TV.
我叫阿卡什·佩斯里查。
My name is Akash Pesritcha.
今天是11月21日，星期五。
It is Friday, November 21.
我们今天有一期内容丰富的节目。
We have a busy show ahead of us.
首先，我们将为您揭秘OpenAI首席执行官萨姆·阿尔特曼在最近一份备忘录中向员工发出的警告。
First up, we've got the inside scoop on a warning OpenAI CEO Sam Altman shared with employees in a recent memo.
接着，红点创投将做客节目，探讨2025年对早期投资的评估；此外，Booking Holdings的首席执行官也将登场，讲述人工智能如何重塑旅游经济。
We've then got Redpoint Ventures coming on the show to talk about assessing early stage bets in 2025, and we've got the CEO of Booking Holdings coming on to talk about how AI is reshaping the travel economy.
我们还将为您带来《编辑精选》第二期，带您走进Informations的编辑会议，深入剖析科技行业最重大的问题。
We're also bringing you the second installment of the Editor's Cut, where we take you inside the information's edit meetings to unpack the biggest questions inside the tech industry.
今天，我们将聚焦于各大前沿模型公司之间的激烈竞争。
Today, we're focusing on the fierce rivalry among the big frontier model companies.
最后，我们将以对埃隆·马斯克与OpenAI诉讼案的最新进展作为本周的收尾。
And finally, we're closing out the week with a status check on the Elon Musk OpenAI lawsuit.
鉴于最近的进展，双方现在究竟还有多少或多少利益牵涉其中？
Given recent developments, how much or how little is at stake now for both parties?
这是一期内容丰富的节目，让我们马上进入正题。
It is a big show, and so let's get right on into things.
昨晚，我的同事斯蒂芬妮·帕拉佐洛和吴Aaron发表了一篇精彩的文章，讲述了OpenAI首席执行官萨姆·阿尔特曼发给员工的警示信息。
Last night, my colleague Stephanie Palazzolo and Aaron Wu published a great piece about a cautionary note that OpenAI CEO Sam Altman sent his employees.
这是一次罕见地窥探公司内部运作的机会，我想邀请斯蒂芬妮和Aaron来为我们详细讲述。
It is a rare look into the inner workings of the company, and I want to bring on Stephanie and Aaron to tell us more about it.
斯蒂芬妮和Aaron，欢迎再次回到节目。
Stephanie and Aaron, welcome back to the show.
很高兴你们能来到这里。
It's great to have you here.
嘿，很高兴见到你们。
Hey, great to have you.
谢谢。
Thanks.
那么，我们来谈谈这条消息吧，Steph。
So let's talk about this message, Steph.
萨姆·阿尔特曼发给员工的那条消息内容是什么？
What was the note that Sam Altman sent to his employees?
嗯。
Yeah.
正如亚伦和我昨天报道的那样，我们获得了萨姆·阿尔特曼上个月底发给OpenAI员工的内部备忘录。
So as Aaron and I reported yesterday, we were able to get ahold of an internal memo that Sam Altman sent OpenAI employees late last month.
这仍然是在Gemini 3发布前数周的事。
So this is again, weeks before Gemini three even was released.
所以当时他们显然已经听到了关于该模型将非常出色的传言。
So they were clearly already hearing rumors then that the model was going to be very good.
而在备忘录中，萨姆对员工非常坦诚，他确实承认Gemini模型将会非常出色。
And, you know, in the memo, Sam is honestly pretty upfront with employees and he does admit that the Gemini model will be very good.
他还告诉员工，发布后会有一段暂时的经济逆风和整体氛围不佳的时期。
And he tells staff to expect temporary economic headwinds as well as kind of just generally rough vibes for a while after the release will come out.
他也承认，Gemini团队在模型训练过程中的一个特定环节——预训练方面，做得非常出色。
And he does also admit that you know the Gemini team has done really good work especially on a certain part of the model training process called pre training.
但结尾仍带有一丝积极的语气，表示他仍然相信OpenAI最终会胜出。
But it does end on a somewhat positive note saying that he still expects OpenAI to come out on top.
公司正在做出许多雄心勃勃的投入，他认为这些最终都会取得成功。
There are lots of ambitious bets that the company is taking that he thinks will pan out for it in the end.
我过几分钟再回过头来谈预训练。
I'm going to come back to pre training in a couple minutes here.
但Steph，这其实是我们《信息》一直在报道的一个更广泛的故事：OpenAI此前在所有其他前沿模型公司中处于领先地位。
But Steph, this is kind of a broader story here that we've been covering at The Information, which is that OpenAI had this lead ahead of all these other frontier model companies.
这不仅仅是相对于谷歌而言。
And it's not just Google.
我的意思是，现在其他公司正在迎头赶上，对吧？
I mean, companies are catching up now, right?
是的，没错。
Yeah, no.
过去几年真是疯狂极了。
It's been a very crazy past couple of years.
但随着我们逐渐远离ChatGPT的发布，我们看到OpenAI与其他玩家如Anthropic和谷歌之间的差距确实缩小了。
But definitely as, you know, we get further away from the ChatGPT, you know, release, we see that gap between OpenAI and other players like Anthropic and Google has definitely narrowed.
据我们从开发者和创始人那里听到的消息，似乎每隔几个月，就会有一个实验室推出一个超越其他公司的模型。
And I think from what we hear from developers and founders, it does feel like, you know, every couple months or so maybe one lab will come out with a model that leapfrogs the others.
但本质上，大家现在都处于差不多的水平。
But essentially everyone is at around the same place.
我想，显然不同之处在于这些公司推出的产品的实际使用情况。
I guess like where things do differ obviously is in the actual usage of the products that these companies are coming out with.
尽管谷歌和OpenAI的模型如今看起来非常接近，但从使用数据来看，OpenAI的ChatGPT每周有8亿活跃用户，而Gemini应用的月活跃用户只有6500万。
So even though Google and OpenAI's models do seem very like neck and neck these days, we do see from usage that, you know, OpenAI's ChatGPT has 800,000,000 weekly active users while the Gemini app has six fifty million monthly active users.
所以不仅用户数量更少，而且这些用户使用应用的频率似乎也更低。
So both a lower number of users, but also these users are not going to the app as often, it seems.
那么，埃琳，谷歌是怎么做到的？
So Erin, how did Google do it?
因为感觉十二到十八个月前，我们还不会围绕谷歌展开这样的对话。
Because it feels like twelve to eighteen months ago, this was not the conversation we were having around Google.
当然。
Absolutely.
我的意思是，这是个很好的问题。
So I mean, this is a great question.
这是一个价值数十亿美元的问题，准确说是价值数千亿美元的问题。
This is the multibillion dollar question, like a multi $100,000,000,000 question.
不幸的是，我认为我们并不完全清楚。
Unfortunately, I think we don't totally know.
当我们审视谷歌的说法，以及Gemini的技术负责人阿里尔·维涅尔在模型发布时的表述时。
When looking at what Google said, looking at what one of Gemini's tech leads, Ariel Vignel, said when this model was released.
他说，我们取得突破的秘诀就是，在预训练和后训练上取得了巨大进展。
He said, you know, the secret the way we did this, we just made a ton of progress on pre training and post training.
好吧，就是这样。
And it's like, okay.
这基本上就是全部了。
That's sort of the whole thing.
所以谷歌正在推出欢迎来到AI的时代。
And so Google's doing Welcome to AI.
有预训练、后训练，还有推理。
There's pre training, post training, it's inference.
这是一整套东西。
It's a whole thing.
恭喜。
Congratulations.
我们做出了一个更好的模型。
We made a better model.
所以谷歌目前在AI训练栈的多个层面都做得非常出色。
So Google's doing a really good job on a lot of different levels of the AI training stack right now.
我经常和很多谷歌研究人员交谈，很多人都说，关键在于我们拥有正确的人才。
And I'm talking to a lot of Google researchers and a lot of people are saying, look, it's a question of like, we have the right people.
我们正在追求正确的理念。
Like, we're going after the right ideas.
我们写过一些文章，讨论过某些具体人员带来的各种影响。
We've written some about like how specific people have had various impacts.
几周前，我的同事西尔维娅和我采访了诺亚·沙齐尔，他在很多方面都是一个颇具争议的人物，但人们也告诉我们，你看。
A couple weeks ago, my colleague Sylvia and I profiled Noam Shazir who's a very controversial figure in a lot of ways, but people are also telling us, look.
不。
No.
他加入后，对预训练架构进行了改进，这证明了花费30亿美元、27亿美元收购他这笔交易的合理性。
He came in and he did this improvement to the pre trading stack that justified the whole $3,000,000,000 the 2,700,000,000.0 billion dollar price of the character deal that brought him in.
所以我认为这其中涉及许多不同的因素。
So I think there's a lot of different pieces that come into this.
但我最怀疑AI的一位消息来源说，你看，这似乎证实了这样一个观点：如果一个足够大的实验室正在追求正确的事情，并以正确的方式聚集人才，那么AI的潜力似乎还没有达到极限。
But what one of my most skeptical AI sources said was like, look, this feels like it vindicates the idea that if a big enough lab that is going after the right things, like, its people in the right ways, it doesn't seem like we've hit a limit yet to what AI can do.
所以，斯蒂夫，这让我们回到了一个非常核心的问题，实际上这正是故事下最早的一个评论：看，模型正在变得商品化。
So Steph, this kind of brings us back to a very core question, which actually was it was one of the first comments on the story was, See, the model was just being commoditized.
实际上，Gemini 3 是否比 GPT-5 或其他什么模型更好，并不那么重要。
It actually doesn't really matter whether Gemini three is better than, you know, GPT-five, whatever.
我的意思是，这些模型推出得太快了。
I mean, they're coming out so fast.
我们最终会停止讨论这些模型的。
We're going to stop talking about these models eventually at some point.
这就是你的意思吗？
Is that the idea?
我的意思是，这又是一个大问题。
I mean, again, this is the big question.
每当投资者决定向这些实验室投入数十亿美元时，他们都会思考这个问题。
This is a question that many investors are thinking of whenever they decide to pour billions of dollars into these labs.
数千亿美元。
Hundreds of billions.
是的。
Yes.
到目前为止，已经是数千亿美元了。
Hundreds of billions at this point.
这太疯狂了。
It's very crazy.
我认为可以说，目前所有实验室都差不多处于同一水平。
I think it's fair to say that at this point it seems like all the labs are kind of at around the same place.
因此，由于研究人员经常在不同实验室之间流动，很难让任何一种技术在某个实验室长期保密。
And so I think because, you know, researchers are jumping from lab to lab all the time, it's very difficult to keep some sort of technique, you know, secret at a lab for any amount of time.
所以，基本上我认为不同实验室的研究人员都了解其他实验室在做什么。
And so basically I think all the researchers at the different labs like know what the other ones are doing.
那里根本没有真正的独家秘方。
No really like secret sauce there.
不过，我认为正如埃琳所提到的，这些实验室里确实有非常出色的研究人员，他们仍在对不同技术方向做出略有不同的选择。
I do think though that like, you know, as Erin was kind of talking about, there are really amazing researchers at these labs and they're still making slightly different bets on different types of techniques that they want to focus on.
因此，这正是帮助 Anthropic 在 OpenAI、谷歌以及其他所有公司都渴望在编程方面表现出色的同时，仍能保持其模型在编程上的卓越表现的原因。
And so for instance, this is what has helped Anthropic continue to keep its model to be so good at coding even while OpenAI, Google, everyone else also wants to be really good at coding as well.
所以，是的，它们总体上处于差不多的水平，但每个公司仍有机会在某些细分领域占据微小优势。
And so yes, they're all generally at about the same place, but each one can still have the opportunity to have a little edge in certain niches.
亚伦，我最后一个问题给你。
Aaron, last question for you here.
让我们回到谷歌相对于 OpenAI 的一些根本性优势，其中最明显的一点是，谷歌不仅产生现金，而且数额巨大，而 OpenAI 有时甚至需要筹集与谷歌一年内产生的现金相当的金额。
Let's come back to sort of some of the fundamental advantages that Google has compared to OpenAI, not the least of which is the fact that Google generates not just cash, but a whole lot of it, and OpenAI has to raise almost the same amount of cash that Google produces in a single year in some cases.
你能谈谈你的消息来源如何看待谷歌仅凭其商业模式，可能在一两年内迅速拉开差距吗？
Can you talk a little bit about the you know, how your sources are thinking about just how quickly Google can pull ahead maybe a year or two from now, just based on how the business is structured?
是的。
Yeah.
正如你所说，谷歌的巨大优势在于它拥有巨额资金。
So I mean, like you said, Google's big advantage is that Google has so much money.
谷歌根本不需要融资，因为其过去十二个月的自由现金流约为 750 亿美元，这比 OpenAI 有史以来筹集的总资金还要多。
Like, Google does not need to raise money because Google's trailing free cash flow over the past twelve months is around 75,000,000,000, which is more money than OpenAI has raised in its entire existence.
而且，显然，这必须支持比OpenAI更多样的业务。
And, obviously, this has to go to a business that's supporting a lot more things than OpenAI.
但关键是，即使AI不是直接的收入来源，谷歌依然拥有可持续的商业模式，仍能投入大量资金用于AI模型的训练。
But the idea is Google has a sustainable business even if AI is not directly even if they're still able to pour a ton of money into training AI models.
因此，本质上谷歌拥有诸多优势。
And so the idea is essentially Google has a lot of advantages.
它们具有庞大的规模。
They have huge scale.
它们拥有数以十亿计用户的各种产品。
They have all of these products with over 2,000,000,000 users already.
因此，我认为谷歌目前处于一个非常有利的位置，能够开始制定其产品战略，将Gemini整合到所有这些产品中。
And so I think that Google is in a really good place right now to be able to start figuring out its product strategy, to be able to start putting Gemini into all of these things.
一旦它能做到这一点，它就比OpenAI处于更可持续的境地，因为OpenAI需要不断融资。
And, like, once it's able to do that, it's in this much more sustainable place than OpenAI is where OpenAI needs to keep raising money.
OpenAI预测，在未来几年内，它的亏损将超过1000亿美元。
Like, OpenAI has predicted that it's gonna burn more than a $100,000,000,000 in the next few years.
所以所有这些资金都必须进来，而谷歌并不处于这种境地。
And so that's all money that has to come in, and Google's just not in that place.
对。
Right.
很好。
Great.
好了，Steph 和 Erin，你们的报道非常出色。
Well, Steph and Erin, it was some great reporting.
感谢你们的到来，我们很快还会再邀请你们做客节目。
I want to thank you for coming on, and we'll have you back on the show again soon.
谢谢。
Thanks.
好的。
Okay.
接下来我们的嘉宾是红点创投的管理合伙人。
Well, our next guest is Managing Director at Redpoint Ventures.
她曾是GitHub的首席执行官，并在网络安全、开发工具和人工智能等领域进行了大量令人瞩目的投资。
She was previously the CEO of GitHub, and she has made a ton of cool investments in sectors like cybersecurity, developer tools, and, yes, AI.
她还曾共同创立了自己的软件公司，并将其出售给了VMware。
She also previously co founded a software company of her own that she sold to VMware.
埃里卡·布雷西亚，欢迎来到TI TV。
Erica Brescia, welcome to TI TV.
很高兴你能来。
It's great to have you on.
非常感谢。
Thanks so much.
很高兴来到这里。
Great to be here.
顺便说一下，我以前是GitHub的首席运营官，不是
I was COO of GitHub, by the way, not
首席运营官。
COO.
我刚才说什么了？
What did I What did I say?
我觉得你说的是CEO，但这种情况经常发生。
I think you said CEO, but it happens all the time.
我从未遇到过任何人，然后我就想，我应该说清楚，因为他们
I've never met with anyone, and I'm like, I should probably make it clear because they
不。
No.
不。
No.
不。
No.
谢谢你的关注。
Thank you for look.
实际上，我面前的提词器上写的是COO。
I I had COO on on the the the teleprompter in front of me, actually.
所以，这纯粹是我周五的思维混乱，谢谢您纠正我这一点。
So that's just Friday brain from my end, so thank you for correcting me on that.
听好了，埃里克，我想和你谈谈几件不同的事情。
Look, Eric, I want to talk to you about a number of different things.
我想和你聊聊你对风险投资的方法，以及你所覆盖的领域。
I want to talk to you about your approach to venture investing, sectors that you cover.
但快速地说一下，我确实想接续我们上一个环节的讨论，那就是OpenAI在前沿模型上的领先优势，以及随着其他模型公司不断进步，这一优势正在逐渐缩小。
But very quickly, look, I do want to pick up on the discussion we just had in the previous segment, which was around the lead that OpenAI had in frontier models, and how that's narrowing a bit as the other model companies get better and better.
我更想向你提出一个更广泛的问题，那就是模型的同质化问题。
And the broader question I just want to ask you is this question of commoditization in models.
我们现在正在大量讨论这些模型。
We are talking a lot about them now.
三年后，我们还会这么大量地讨论它们吗？
Will we be talking a lot about this three years from now?
如果不会，你认为这些大型AI公司的长期结构会如何变化？
And if not, how do you think the structure of all these big AI companies changes in the long run?
这是个很好的问题。
It's a great question.
我认为，从我的角度看，我不确定是三年还是五年，因为我们还处于这场竞赛的早期阶段。
And I think the question my view is I don't know if it's three years or five years because we're still so early in this race.
但我觉得你说得对。
But I think you're right.
我认为我们不会那么频繁地谈论模型了。
I don't think we're gonna be talking about the models as much.
我认为模型在很大程度上会被商品化，但这种商品化会像云服务商那样发生。
I do think they're largely gonna be commoditized, but I think they're gonna be commoditized in the way the cloud vendors have been commoditized.
对吧？
Right?
你知道，仍然有一些非常赚钱的企业，它们的现金流源源不断，利润率随时间提升，并在平台的基础架构之上构建了各种各样的服务，每家都有不同的风格和不同的增长方式。
You know, there's still incredible businesses that are printing cash, whose margins have improved over time, who have built all kinds of different services on top of the base substrate of the platform, and they all have a different feel and different ways that they spike.
对吧？
Right?
人们使用Azure的原因与使用AWS或Mhmm的不同。
People go to Azure for different things than AWS, than Mhmm.
协议等等。
Protocol, etcetera.
这实际上从一开始就是我的观点。
And that's been my thesis actually since about, you know, day zero of this.
这是我迄今为止对AI和模型供应商如何随着时间演变的最佳思维模型。
It's the best mental model that I've come up with for how to think about how AI and the model vendors in particular evolve over time.
对。
Right.
所以这种向应用的转变，每个人都在谈论这件事。
And so this shift to applications, you know, this is something everyone's talking about.
我的意思是，你看，OpenAI刚刚聘用了Fiji Simo担任应用部门的CEO。
I mean, seems to you know, OpenAI just hired Fiji Simo as the CEO of applications.
我们有编程作为一个应用。
Look, we have coding as one application.
我们有智能代理。
We have agents.
目前在投资方面，你关注哪些应用领域，认为哪些会真正崛起？
Where are you looking right now in your investing with respect to what applications you think are really gonna take off here?
当然。
Sure.
作为一家公司，我们大约一半投资于基础设施，一半投资于应用。
Well, as a firm, we invest about half in infra and half in apps.
我想说清楚。
I wanna be clear.
我认为在基础设施层面上仍然有大量投资机会。
I think there's a ton of opportunities still at the infrastructure layer for investing.
你知道吗？
You know?
如果你看一下Snowflake这家公司，它是在AWS成立六年后才出现的。
If you look at a company like Snowflake came along six years after AWS was founded.
我认为我们所有人都需要记住，构建应用程序或从这些模型中获取价值所需的关键基础设施还有很多尚未开发。
And I think it's important for us all to remember that, like, a lot of the key infrastructure for building applications or getting value out of these models has yet to be developed.
很多时候，这些基础设施是由人们在大公司中尝试构建产品并投入生产时，不得不围绕它开发一系列工具，然后将其独立出来。
A lot of the times, it comes from people trying to build something and put it into production in a big company, having to build a bunch of tooling around it, and then spinning it out.
因此，我仍然花了很多时间在网络安全和基础设施领域。
So I'm still spending a good amount of my time in cyber and infra.
与此同时，我们和所有同行公司一样，在应用层也非常活跃。
We also have been very active along with all of our peer firms at the application layer.
那里有几个关键的主题。
And there's a couple key themes there.
其中之一是我们非常关注这些企业的可防御性。
One of them is we're really looking at defensibility in these businesses.
我们对这一点的思考方式是：你正在接管哪些工作流程？又在哪些系统之间进行集成？
And the way that we think about that is what workflows are you are you taking over and across what systems are you integrating?
我认为仅仅作为一个API调用会变得非常困难，我知道曾经有一波关于API包装器的广泛讨论。
I think just being an API call gets really challenging, and I know there was a whole, you know, wave of discussion around API wrappers.
在这些基础模型之上构建本身没有问题，但我们认为，真正的护城河在于你能否深度整合公司内部的不同系统，使得移除你的解决方案变得非常困难。
There's nothing wrong with building on top of these foundation models, but we think the defensibility comes when you're really integrating with different systems across a company that make it, you know, much harder to rip something out.
没错。
Right.
关于这一点，我想提出一个有趣的观察：如果你是首批进入该领域的公司之一，比如我们投资组合中的保险领域公司Liberate，他们能够实现比现有流程高出十倍的效率提升，因为他们完全取代了人工劳动，并自动化了多个不同系统的工作流程。
I think an an interesting observation on that front is, you know, if you're one of the first companies to get in, take one of our portfolio companies, this company, Liberate, in the insurance space, you know, they can deliver, like, a 10 x improvement over existing processes because they're completely replacing human labor and automating workflows across a bunch of different systems.
现在，如果另一家AI公司试图向他们的客户销售产品，将很难再提供十倍的性能提升。
Now if another AI company comes in and tries to sell to their customers, it's going to be really hard for them to deliver a 10x improvement over that.
开始只能带来渐进式的改进。
Starts getting to be incremental improvements.
让我问你关于网络空间的问题，这是你投资时非常关注的一个领域。
Let me ask you about cyberspace, which is an area that you focus on a lot with your own investing.
当然。
Sure.
目前网络安全领域的故事是什么？
What is the story here in cybersecurity right now in this moment?
我们看到了Anthropic报告中关于AI可能对网络安全构成的威胁。
We saw the Anthropic Report about the threats that AI could pose to cybersecurity.
当然，人们都说，是的，他们可以利用它进行攻击。
Of course, are people saying that, yeah, they can use it to attack.
我们也可以用它来防御，两种方式都可以。
We can also use it to defend in both ways.
但我们曾邀请过一些网络安全公司的CEO做客节目，他们坦率地表示，目前来看，威胁在某种程度上实际上超过了收益。
But, you know, we've had cybersecurity CEOs on the show that have been open about the fact that said, look, the threat is, you know, in some ways actually outweighs the benefits as of right now.
你认为这是一个让你担忧的问题吗？
Do you see this as a concern for you?
当然。
Absolutely.
这是我们已经思考了很久的问题。
It's something we've been thinking about for quite some time.
你知道，这是一场不断升级的军备竞赛。
You know, there's this escalation war.
每次我们创造出伟大的东西，伟大的技术也会进入开源领域，总有一些坏人会想办法用它来做坏事。
Every time we create something great and, you know, great technology makes its way into open source too, There are bad people out there that will figure out how to do nefarious things with it.
因此，我们在网络安全领域的投资理念之一就是：攻击面正变得越来越激烈和活跃，我们需要帮助企业和正面力量掌握工具，以最大限度地加强自身防御。
And so a big part of our investment thesis in cyber has been, look, the the attack landscape is getting ever more violent and active, and we need to help companies and good actors with tools that allow them to do everything that they can to beef up their own defenses.
这包括从每年进行一次渗透测试，升级为自动化、AI驱动的渗透测试。
And that goes from, you know, doing pen tests once a year to automated AI driven pen testing.
还包括企业级工具，帮助建立网关、控制访问权限，并应对日益增长的威胁，提供更好的保护。
It goes to, you know, enterprise tooling to help provide gateways and control access and provide better protections against, you know, ever increasing threats out there.
还包括投资于人为风险平台，帮助公司培训员工或防止他们上钓鱼攻击的当，因此我们在这一领域非常活跃。
It includes investing in human risk platforms that help companies either teach employees or preventing them from falling for phishing attacks and things So like we've been very active.
在你离开之前，我想问你最后一个问题。
Let me ask you one one last question before you go.
我之前读了你的个人简介，了解到你在加入GitHub之前创办了自己的公司，而且早在十多年前你就参加了Y Combinator，我只是想问问，你对2025年普遍意义上的加速器有什么看法？
I I I was reading up on on your bio, and before you were at GitHub, you you started your own company, and you actually went through Y Combinator more than ten years ago now at I this just wanted to ask you how you think about accelerators in 2025 broadly.
谁应该参加加速器？
Who should do an accelerator?
谁不应该参加加速器？
Who shouldn't do an accelerator?
我们有很多观众正在考虑创办自己的公司。
We have a lot of people watching the show that are thinking about starting their own companies.
关于如何思考这个问题，其结构、价值主张或方法论有发生变化吗？
Has the structure or the value prop or the sort of the methodology around thinking about that changed at all?
是的。
Yeah.
这是个很好的问题。
It's a great question.
对于所有考虑创业的人，现在就是最好的时机，最好的时机。
And to all those thinking about starting a company, no time like the president or the president.
现在是历史上创业的绝佳时机。
It's an incredible time in history to do that.
我对YCombinator的经历非常不同。
I did have a very different experience with YC.
我的那一届有42家公司。
My my batch was 42 companies.
现在已经有好几百家了。
They are several 100 now.
我认为你真正获得的是陪伴、人脉，以及一个可以随时讨论想法的智囊团。
I think what you really get is the companionship, the connections, a kind of brain trust that you can bounce ideas off of.
而且，老实说，这里存在着很多健康的竞争。
And, honestly, there's a lot of very healthy competition.
你知道的？
You know?
有人比你跑得更快，发布产品更快，增长也更快。
Somebody is going faster than you, shipping faster, growing faster.
这是一个非常强大的激励因素。
It's a really powerful motivating factor.
我认为，你能加入的这个社群，看到这么多非常能干、极具驱动力的优秀人才在做什么、不做什么，是非常宝贵的。
And I think the community that you get to be a part of and see what's working and what's not across a lot of, you know, very highly capable, highly driven special people.
所以让我问你一下。
So let me ask you.
谁不应该参加加速器？
Who who who shouldn't who shouldn't do an accelerator?
也许这个问题更好。
Maybe that that's a better question.
是的。
Yeah.
你知道吗，看。
You know, look.
如果你在高增长、成功的公司里待过很长时间，并且觉得自己已经拥有一个强大的同行网络，可以互相交流建议、分享经验、倾诉困难，那你可能不需要为了参加加速器而放弃股权。
If you have spent a lot of time in very high growth successful companies and you feel like you already have a peer network that is very strong of people who are building companies, you can share advice with, share learnings, commiserate with, you might not need to give up the equity to an accelerator.
它对我很有帮助。
It was useful for me.
我没有去斯坦福。
I didn't go to Stanford.
我的父母并不在科技行业。
My parents weren't in tech.
我们是在美国以外的地方创办了我的第一家公司的。
We started my first company outside of The US.
我有一位西班牙联合创始人。
I had a Spanish co founder.
因此，我确实感觉自己是个硅谷的局外人，而加入一个我可以向之学习的群体，建立我的人脉网络，对我帮助很大。
And so I really felt like a Silicon Valley outsider, and it was really helpful for me to build my network and just get in with a group of people I could learn from.
如果你不需要这些，那你可能也不需要参加加速器。
If you don't need that, you probably don't need an accelerator.
很好。
Great.
好了，艾丽卡，感谢你来参加这个节目。
Well, Erica, thank you for coming on the show.
我们非常感谢你，这是一场非常精彩的讨论。
We really appreciate it, and it's a great discussion all around.
我们很快还会邀请你回来。
We'll have you back again soon.
很好。
Great.
谢谢。
Thank you.
Booking Holdings 是全球最大的旅行科技公司之一。
Booking Holdings is one of the biggest travel tech companies around.
虽然我们在这档节目中很少谈论它，但它是 Booking.com、Priceline、Kayak 和 OpenTable 的母公司。
It is not one that we talk about a lot on this show, but it is the parent company of booking.com, Priceline, Kayak, and OpenTable.
作为背景信息，即使你把 Airbnb 和 Expedia 的市值加在一起，也仅相当于 Booking Holdings 市值的三分之二左右。
For context, even if you combine Airbnb and Expedia, that would still only be about two thirds the size of Booking Holdings market cap.
然而，许多人对人工智能对旅游行业企业构成的威胁提出了质疑。
And yet, many have raised questions about the threat that AI has to the travel industry's businesses.
本周，谷歌发布了新的AI驱动工具，导致许多旅游股股价下跌。
Google unveiled new AI powered tools this week, causing many travel stocks to stumble.
当然，Booking 一直在推进自己的人工智能战略，并与 OpenAI 达成了重要合作。
Of course, Booking has been embarking on its own AI strategy with a big partnership with OpenAI.
现在邀请来和我们讨论这一切的是 Booking Holdings 的首席执行官格伦·福格尔。
Joining me now to discuss all of this is Glenn Fogel, CEO of Booking Holdings.
格伦，欢迎来到 TI TV。
Glenn, welcome to TI TV.
很高兴你来到这里。
It's great to have you here.
我非常高兴能来到这里。
Well, I'm so happy to be here.
我对这次对话感到非常期待。
Well, I'm excited for this conversation.
我想从本周早些时候发生的新闻开始谈起。
Look, where I want to start is the news that happened earlier this week.
谷歌发布了这些酷炫的人工智能工具。
Google came out with all these cool AI tools.
我们前面已经提到了。
We mentioned it up top.
我们看到一些股票略有下跌。
We saw some of the stocks take a bit of a dip.
您如何看待这些AI工具对您业务的竞争威胁？
How are you thinking about those AI tools as a competitive threat to your business?
让我们先谈谈AI本身，它对旅游行业来说有多么令人兴奋，以及我们多么高兴能参与其中，并继续在AI领域进行建设，这非常棒。
Well, let's start with just AI in general and how incredibly exciting it is for the travel industry and how pleased we are to be part of it and what we're continuing to build out in AI, which is fantastic.
与谷歌这样的合作伙伴合作非常愉快，我们期待在未来在AI领域继续深化合作。
Now, working with our partners like Google has been really great, and we envision a great partnership going forward in the AI area.
我非常喜欢昨天他们发布的一则小新闻，说‘我们并不打算成为在线旅行社’，我很欣赏他们做出这样的澄清，因为我认为可能存在一些误解。
I loved yesterday when they came out with a little bit of a news piece saying, Listen, we're not planning to be an OTA, which I love for them to qualify because I think there may be some misunderstanding.
对于不太了解旅游行业的人，OTA是什么意思？
And OTA for the people who aren't as versed in the travel industry.
OTA是指？
OTA is?
在线旅行社。
Online travel agent.
哦，原来如此。
Oh, there you go.
好的。
Okay.
很简单。
Pretty simple.
我想这周初有点混淆。
That that was a little confusion, I think, at the beginning of the week.
不。
No.
这根本不是新闻。
This isn't news at all.
我们一直在合作。
We've all been working.
我们如何利用人工智能？
How can we use AI?
我的意思是，我们所有人。
Say all of us.
我是说，整个旅游行业的所有人，以及那些创造这些出色新技术的前沿企业，无论是谷歌、OpenAI还是其他任何公司。
I mean, all the people in the travel industry and also the people that are frontier players who are creating these wonderful new technologies, whether it be Google or or OpenAI or any of them.
我们一直与所有人合作。
And we have been working with everybody.
你知道，你一开始提到了我们与OpenAI的关系，以及我们与ChatTbt的合作，这很棒，我们与他们做的那些事情。
It's you know, you started off you mentioned about our relationship with OpenAI and what we're doing with ChatTbt, which is great, the things we've done with them.
但我们也在与谷歌，当然还有其他公司进行大量合作。
But we're doing work a lot of a lot of working together with Google, of course, and also others.
看看我们与亚马逊以及他们在Alexa上的工作。
Look, we're with Amazon and what they're doing with Alexa.
这个领域的每一个参与者，包括我们自己，都在与从事技术开发的不同公司合作。
Every single player in the space, us included, of course, we're all working with the different players who are doing the technology.
所以这里根本没有新消息，尽管如果你从股票估值的角度来看市场，可能会觉得有什么新动向。
So there's no new news here at all, though it does seem if you look at the market in terms of stock valuation, you would think there was something new
对，对。
Right, right.
不过，我确实想稍微了解下你的想法。
Well, I do want to get sort of inside your head a little bit.
OpenAI的这笔交易在我们新闻室里非常令人兴奋，因为我们非常好奇哪些公司会与OpenAI合作，支持他们将一切整合到自己平台的努力。
The OpenAI deal was really exciting for us here in the newsroom because we were really curious to see which companies would partner with OpenAI and all their efforts to sort of bring everything into their platform.
我想知道，当你考虑是否要达成这项合作时，支持的理由有很多。
I'm curious, when you were thinking about whether or not to do that partnership, there were a lot of arguments for.
在董事会里，有没有人提出反对这笔交易的理由？
Was there anyone in the boardroom that raised arguments against doing the deal?
如果有，那些理由是什么？
What were those arguments if there were some?
首先，这根本不需要提交到董事会层面。
Well, first of all, doesn't go to the board level per se.
我不是在说董事会，我指的是会议室里的讨论。
Well, I'm not talking about the board, I'm talking about the conference room fine.
对。
Right.
听好了，我们总是希望出现在客户所在的地方。
Look, we always want to go where the customers are.
如果客户想开始他们的旅行搜索、旅行调研，或者他们想在旅行中做些什么，我们都希望在那里，帮助他们确保获得所需的一切，确保我们继续提供过去二十五年来我在这个公司一直提供的服务。
And if customers wanna begin their travel search, their travel investigation, what they may wanna do in travel, we wanna be there for them to help make sure they get what they need, make sure we continue to provide the service we've done over the last twenty five years I've been at this company.
无论是他们最初从谷歌上那个蓝色链接的旧网站开始，还是现在想通过大型语言模型开始他们的调研，对我们来说，这都只是客户启动方式的变化。
And whether it was they wanted to start off at just the beginning with the old website with a blue link at Google, or now wanting to go to a large language model to begin their investigation, that to us is just a way that customers are starting.
我们只想确保自己在那里，让他们能获得真正需要的东西——一个比以往没有技术时好得多的旅行体验。
What we wanna make sure we're there, we're there so they can get what really is necessary, which is a great experience in producing a travel thing they want that is so much better than it used to be before there was technology.
对。
Right.
跟我谈谈这个合作给你的业务带来的成果。
Talk to me about the results that you've seen from that partnership on your business.
天啊，这才刚刚开始。
My God, it just started.
一年后再来找我，我告诉你进展如何。
Come back to me in a year, I'll tell you how it's going.
但这并没有对流量造成负面影响。
But it hasn't adversely affect traffic.
你在财报电话会上提到过，你们自有搜索产品的流量仍在增长。
You mentioned this on the earnings call, traffic for your own search product has still been growing.
增长得非常显著。
Tremendously so.
而且自从谷歌成立以来，常规搜索一直在增长。
And over the last, whatever, since Google started, regular search continues to grow.
与谷歌的合作关系非常美好。
It's been a wonderful relationship with Google.
我想象我们会与所有为旅行者探索需求提供新方式的人保持良好的关系。
I imagine we'll have a wonderful relationship with everybody who's coming up with new ways for travelers to investigate their needs.
对。
Right.
我想谈谈你们业务中我们很少讨论的另一面，也就是你们的B2B业务。
I want to talk about a side of your business we don't talk about a lot, which is the B2B side of your business.
对于不太关注贵公司的人，你们的客户是谁？
For people who aren't following the company as much, who are you selling to?
你们的产品是什么？
What is the product?
这一块业务目前发展得怎么样？
And how is that side of the business faring?
嗯，这里的B2B业务，弗蕾亚，是指我们与那些拥有自己客户并希望获得旅行服务的公司合作，一个明显的例子就是银行。
Well, the B2B business here, Freyja, is when we partner with somebody who has their own customers who want to have travel services, An obvious one would be a bank.
我们以花旗银行为例。
So let's take an example, Citibank.
我们为花旗银行的客户提供服务，这些客户希望享受某些福利，作为花旗银行的用户，无论他们是在那里开账户，还是持有信用卡，都能获得旅行服务的保障，而花旗银行本身需要有人来实际提供这些服务。
We provide for Citibank customers who want to get certain sort of benefits, being a Citibank consumer, whether it be an an account there or they have perhaps a credit card, and they are able to get their travel services fulfilled, well, Citi needs somebody to actually do that.
那就是一个例子。
That would That's be an example.
或者，如果你是一家航空公司，自己销售航班，但需要有人提供酒店服务，我们就会为大型航空公司做这件事。
Or if you're an airline and you sell flights on your own, but you need somebody to provide the hotel benefit, we would do that for a big airline.
这就是这种B2B业务的性质。
That's the nature of that type of B2B business.
现在这个业务规模有多大？
And how big is that business now?
规模不小。
It's big.
我们还没有达到全球领先者的规模，但正在增长，只是我们不单独披露数据。
We're not as big as the leader in the world, but it's growing, but we don't break it out.
对。
Right.
回到AI话题，我很好奇，公司现在员工已经超过两万人了。
Going back to AI, I am curious, have more than 20,000 employees now at the company.
我相信你们正在使用各种软件来管理员工，帮助他们完成日常事务。
You're using all types of software, I'm sure, to manage employees, help them carry out their day to day activities.
你们有没有在内部使用人工智能来降低成本、提高效率？
Have you used AI at all internally to cut costs, make things more efficient?
你们是如何看待这一点的？
How are you thinking about that?
我们在之前的通话中已经讨论过这个问题。
Well, we talked about this on our call.
事实上，你们可以回溯到几个季度前，我们一直在讨论人工智能如何提升公司的效率。
In fact, many calls, you go back several quarters and we've talked about how much AI is improving the efficiency of the company.
所以我们目前大约有25,000名员工。
So we do have about 25,000 employees.
其中非常重要的一点是提供优质的客户服务。
One of the really important things is providing great customer service.
而在这一领域，我们看到生成式人工智能带来了巨大的好处，能够以多种方式改善这一对许多人来说可能非常令人沮丧的体验。
And that's an area where we see incredible benefits using GenAI to make so many ways to improve that, what can be for many people, a very frustrating experience.
所以，对于客户来说，客户服务中最让人烦心的事情莫过于等待别人接电话。
So just right away, nothing's more annoying in customer service if you're a customer is waiting for somebody to pick up the phone.
现在有了生成式AI，就不再需要等待有人接电话了。
Now with GenAI, you don't have anybody waiting to pick up the phone.
电话是由我们的技术来接听的。
It's being picked up by our technology.
或者，您只是想自动获得某个问题或疑问的简单答案，而无需拨打电话。
Or just wanna get that simple answer to a problem or a question you have automatically without even having to deal with a call.
我们也提供这些服务。
We provide those services too.
这是我们在其中看到巨大效益的领域之一，而且这种效益只会越来越好。
It's one of those areas where we see incredible benefits that's only gonna improve.
OpenTable 是我们旗下的一家公司。
OpenTable's one of our companies.
所以，有时候您打电话给餐厅预订座位，以为自己是在和接待员交谈以获取预订信息。
So sometimes you call a restaurant for a reservation, you think you're talking to a host to get their reservation.
那不是人类。
That's not a human being.
那是人工智能。
That's AI.
或者如果餐厅对我们提供给他们的OpenTable服务有任何疑问，当他们打电话时，也不是在和真人交谈，而是与一个AI代理交流。
Or if a restaurant needs some questions about the service that we provide to them at OpenTable, the restaurant, when they make a phone call, is also not talking to a human being, it's to an AI agent.
这些技术将会持续改进。
These things are gonna just continue to improve.
无论是在编程方面，还是在我们提供的任何类型的服务中，人工智能都将不断提升效率。
And whether it be coding, whether it be any type of service that we're providing, AI is gonna continue to improve the efficiency.
对。
Right.
我很好奇，你已经在公司工作了二十五年了吧，我认为，很少有人能在一家公司待这么久。
I am curious, you've been at the company for twenty five years now, I think, and it's rare for anyone to stay at a company for that long.
很多观看这个节目的人希望创业，而你却一直在公司里步步高升。
A lot of people watching this show, they have hopes to start their own businesses, and you continue to climb the corporate ladder.
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从你的角度来看，2025年人们为什么应该追求职场晋升，而不是创业？
What is the perspective from your end on why people should aim to climb the corporate ladder in 2025 versus starting their own business?
我认为这取决于个人。
Well, I think it's up to the individual.
我不是那种会给任何人职业建议的人。
I am not the person to give any advice to anybody in career.
就连我孩子进入职场后，我也不给他们任何建议。
I don't even give my kids advice in terms of they're out in the work world themselves.
每个人都要自己决定想要什么样的生活方式，愿意承担多大的风险。
It's up to individuals on what kind of lifestyle you want to have, what kind of risks
你想承担什么样的风险。
you want to take on.
但在2025年，追求职场晋升的理由是什么？
But what is the argument for climbing the corporate ladder in 2025?
对我来说，‘职场晋升’这个词总带着某种负面的意味。
Climbing the corporate ladder just has such, to me, some sort of, let's say, negative connotation.
我认为持续提升自己的能力、知识，找到更高效的工作方式，并看到自己努力的成果，是非常棒的。
I believe continuing to develop your abilities, your knowledge, providing a better way to do your work and provide or see the results of what you put your effort into is a great thing.
无论是在一家公司内实现，还是你觉得这家公司已无法再为你提供继续成长所需的条件，于是你换到另一家公司，这都没问题。
Whether that be done in one company or you feel that company is no longer providing you what you need to continue to advance, so you go to another company, that's fine.
我自己一直非常满意。
I myself have been very satisfied.
你知道，我加入了这家公司。
You know, I joined this company.
你知道，在我第一年的时候，我们的股价是一美元一股。
You know, point in my first year, our stock price was a dollar a share.
那时我们不得不进行反向分割，因为股价跌到了一美元以下。
Now that was pretty reverse split that we had to do because we get below a dollar.
所以，我们把反向分割后的股价称为每股六美元。
So let's call after the reverse split $6 a share.
到了夏天，股价一度接近六千美元。
In the summer, we got close to 6,000.
对吧？
Right?
现在从那个高点略微回落了一点。
Now it's a little bit down right now from that high.
但想想看。
But think about that.
看看这种增长。
Look at that growth.
在我的整个职业生涯中，我始终有机会做不同的事情，面对不同的挑战，学习不同的东西。
And in every single part of my journey, I've had the opportunity to do different things, have different challenges, learn different things.
这真的非常有成就感。
And just it was just it's just been so rewarding.
我从未感到无聊。
I've never been bored.
我跟你说，真的。
I'll tell you that.
对。
Right.
对。
Right.
好了，格伦，感谢你来参加这个节目。
Well, Glenn, I wanna thank you for coming on the show.
这是一次很棒的对话。
It was a great conversation.
而且，昨晚我还在平台上。
And look, I was I was on the platform last night.
我下周去平台时有一些预订。
I I have some bookings for next week for my trip on the platform.
所以这是一个每个人都与之有联系的平台。
So it's one that I know everyone has a relationship with.
非常感谢你的支持。
Well, thank you very much for the business.
我们非常感激。
We appreciate it.
如果你有客户服务问题，试试那个客户服务功能。
And if you have a customer service issue, try that customer service thing.
你会感到非常
You'll be remarkably
不过，格伦，我得告诉你，归根结底我还是希望找真人。
I have to tell you though, Glenn, I still ask for a person though, at the end of the day.
我的意思是，即使用了客户服务系统，最后我还是
I mean, that's with the customer service thing at the end of it, I
我还是想要一个真人。
still I want a person.
好的。
Okay.
你可以给我打电话。
Well, you can call me.
那怎么样？
How about that?
好的。
Okay.
行吧。
All right.
非常感谢你来参加，格伦。
Well, thank you so much, Glenn, for coming on.
真的很感谢。
Really do appreciate it.
这是一次很棒的对话。
It was a great conversation.
谢谢。
Thank you.
再见。
Bye bye.
很快见。
See you soon.
好的。
Okay.
现在是我们每周的《编辑精选》节目。
It's time now for our weekly edition of The Editor's Cut.
每周五，来自《The Information》的几位资深编辑会轮流与我一起带您走进我们的新闻编辑室，向您展示我们如何讨论最重大的科技新闻，如何争论什么才是真正重要的，以及我们如何确定下一步该问哪些最有价值的问题。
Each Friday, a rotating group of senior edit ors from The Information will join me to take you inside our newsroom to give you a look at how we talk about the biggest tech stories, how we debate what really matters, how we figure out what the smartest questions to ask next are.
今天讨论的主题是我们一直在探讨的，在打造和完善新AI模型的过程中，哪些领导者拥有成功所需的工具，而哪些领导者会逐渐失去兴趣。
The topic of the conversation today is one that we talk about all the time in the battle of building and perfecting new AI models, which leaders have the tools to succeed and which leaders will start to lose interest?
今天，我们邀请到了《The Information》的联合执行主编马丁·皮尔斯和阿米尔·埃弗拉蒂。
Today, we have the information's co executive editors, Martin Pearce and Amir Efrati.
马丁和阿米尔，欢迎来到《编辑精选》——或者我该说，联合执行主编精选。
Martin and Amir, welcome to the Editor's Cut, or as I should say, the co executive editor's cut.
我们非常高兴你们能来到这里。
We are very excited to have you here.
马丁讨厌这个。
Martin hates it.
我早就看出来了。
I can see it already.
他总是说：天哪。
He is like, Oh my gosh.
别废话了，直接问吧，阿卡什。
Just start asking the question, Akash.
好的。
Okay.
就冲这个，我先问阿米尔，因为阿米尔，你对前沿模型的关注比任何人都更密切。
Well, just for that, I'm going go to Amir first, because Amir, you follow this space closer than anyone with the frontier models.
目前，我们有五大玩家。
Look, we've got five big players as of now.
你有OpenAI、Anthropic、谷歌、Meta和xAI。
You've got OpenAI, Anthropic, Google, Meta, and xAI.
我想问你的问题是，当你思考这些模型取得的进展时，我们刚刚写了这篇报道，曾邀请Steph和Aaron讨论谷歌如何缩小差距。
The question that I want to ask you is, as you're thinking about the progress that these models are making, and we just wrote the story, we had Steph and Aaron on talking about how Google is closing the gap.
你觉得在未来三年，这些模型中哪些会依然具有重要意义？
How do you think about which of these models will know, which of these efforts will still be as significant three years from now?
随着竞争日益激烈，你是否看到任何公司会退缩？
Do you see any of these companies pulling back as the competition gets more tight?
你认为会有一家独占鳌头吗？
Do you see one player winning out?
你是怎么看待这个问题的？
How do you think about that?
这周在很多方面都非常重要。
Well, this is a pretty important week, in a couple of ways.
首先，谷歌发布的Gemini 3获得了非常好的反响。
First of all, you know, Google's release of Gemini three was very well received.
还有，我们昨天关于OpenAI的萨姆·阿尔特曼承认谷歌在模型训练初期掌握了一些非常重要的训练技术的报道。
And, our story yesterday about Sam Altman at OpenAI acknowledging that Google figured out some pretty important training techniques in the kinda early phase of training a model.
这确实表明主要AI开发者之间仍然存在差异。
It really showed that there are still differences between the major AI developers.
这并不是说其中任何一方正在远远超越其他对手。
Now it's not saying that any one of them is racing beyond the others.
他们仍然都处于这个精英群体中，但看到他们之间存在差异，非常有趣。
They're all still in this, like, elite pack, but it was very, very interesting to see that there are differences between them.
我认为，就能力而言，这周对AI整体来说是非常乐观的，因为谷歌显然取得了重大进展，尤其是在视觉向量方面——比如生成图表、流程图等任何视觉内容，都得到了显著提升。
And I think it was extremely kind of bullish week for AI in general in terms of capabilities because, Google clearly made some big improvements, especially on, visual, vectors, if you will, kinda creating, charts, flowcharts, anything visual, seem to be, much, much improved.
而这一点一直以来都是大型语言模型难以处理的难题。
And that's always been a very tricky thing for large language models to handle.
因此，考虑到当前的宏观担忧和股市压力，我认为这周对整个行业来说是非常积极的。
So, overall, a very, positive week, I would say, for this for this industry given the kind of, macro concerns and stock market concerns.
至于你问的谁会脱颖而出、拉开差距之类的问题，我认为目前没有任何迹象表明这种情况正在发生。
As far as your question about who's who's going to jump out of the others or run away with it or or or whatnot, I don't think we have any indication that that that's the case.
显然，OpenAI曾表示希望自动化AI研究本身的过程，他们对此似乎相当有信心。
Obviously, OpenAI has talked about wanting to automate the process of AI research itself, which, you know, they seem to be pretty confident about it.
我们真的不确定这会是什么样子，但他们甚至为此设定了非常具体的时间表。
We're really not sure exactly what that looks like, but they've even set some very specific timelines around that.
显然，如果你能自动化AI研究，那你就是在赌自己能遥遥领先。
Obviously, if you can automate AI research, you're trying to make a bet that you can run away with it.
我认为我们离那一步还远得很。
I don't think we're we're we're anywhere near that yet.
你知道，马丁可能会谈一下这些公司及其经济或财务状况，以及这些因素如何使它们难以跟上步伐。
You know, I I think Martin is is gonna talk a little bit about some of the companies and their kind of economic or financial status and how that that that can kind of make it difficult for them to to keep up.
在你提到的五家公司中——OpenAI、Anthropic、xAI、Meta和Google——目前最突出的是Meta，因为它还没有一款先进的前沿模型。
The one out of the five that you mentioned, OpenAI, Anthropic, xAI, Meta, and Google, the the one that stands out right now that just sort of nowhere is Meta because it, you know, it doesn't have a frontier model that is advanced.
它真的正在努力追赶。
It doesn't you know, it's it's really trying to catch up.
我认为他们
I think they
雇用了这么多人才，现在我们只能等待。
hired they hired hired all these people, and and and now we're we're waiting.
我们正在等待。
We we are waiting.
我认为那里唯一的亮点或希望在于，就像你看到中国初创公司和阿里巴巴、DeepSeek等大公司，通过借鉴OpenAI的进展并融入自己的一些创新，在模型构建过程中后来居上，逐渐接近那些前沿水平。
I think the the only silver lining there or or kind of hope there is, you know, just in the same way that you saw Chinese, startups and big companies like Alibaba and DeepSeek, figure out a way to draft off of the progress of OpenAI plus include some of their own, you know, innovations in in the kind of model building process, allowed them to kind of, you know, bring up the rear and get get close to those those frontiers.
我认为这确实给Meta带来了一些希望，因为目前它是这五家公司中的异类。
I think that does probably give Meta some hope, they're kind of the outlier right now among the five.
所以，马丁，从财务角度来看，你怎么看这个问题？
So Martin, what's your take on this from a financial I
我想提醒你一下，这是我们开会讨论问题的方式：阿米尔其实并没有回答你的问题。
just wanna point out to you, and this is how we do discuss things in the meeting, Amir didn't really answer the question.
他扯了一大通关于这一周的事，而那根本不是你问的内容。
He went on a ramble about the week, which was not what you were asking about.
我来实际回答一下这个问题。
I will actually answer the question.
答案是，正如阿米尔试图抢我的风头那样，部分回答了：Meta显然面临着一个大问题。
And the answer is, as Amir tried to steal my thunder, partly answering, Meta has obviously got a big problem.
他们没有其他公司那样的资金资源。
They don't have the financial resources that the other companies have.
正如阿米尔指出的，他们的模型已经落后了。
And as Amir points out, their models have fallen behind.
我认为另一个长期面临问题的公司是XAI。
The other company I think that really has a long term problem is XAI.
他们也没有其他公司的资金资源。
They also don't have the financial resources of the other companies.
埃隆正试图亲自完成所有事情。
And Elon is trying to do everything himself.
我认为他没有足够的资金。
I don't think he's got the money.
我认为试图重新发明所有东西的想法是行不通的。
I think the idea of trying to reinvent the wheel on everything, that's not going to work.
所以我的预测是——当然，做预测是有风险的，但我愿意这么做，不像阿米尔。
So my prediction And look, it's obviously hazardous to make predictions, but I am willing to do that, unlike Amir.
我的预测是，谷歌将会胜出。
My prediction is that Google will come out on top.
他们在实际技术上显然已经领先。
They are clearly ahead now on the actual technology.
他们拥有广泛的业务。
They have the range of businesses.
他们正是OpenAI试图成为的样子，但他们已经做到了。
They are what OpenAI is trying to become, but they're already there.
我认为OpenAI在五年后也可能达到那个水平，但他们试图涉足堆栈的每一个环节，这很可能行不通。
And OpenAI, I think, will probably also They'll be there in five years' time, but their effort to be in every part of the stack probably is not going to work.
我认为Anthropic也会成功，但他们已经确立了一个特定的利基市场，这没问题。
And I think Anthropic will be there, but they've carved out a particular niche, that'll be fine.
我的意思是，我想说，是的。
I mean, I wanna Yeah.
请说。
Go ahead.
你请说。
Go ahead.
这里有有一个
There's an there's
这里有一个关于资源与商业模式的重要区别。
an important distinction here around resources versus business model.
我认为马丁真正想表达的是，Meta并不是没有资源，也不是没有AI的商业模式。
And I think what what Martin's really getting at is it's not as if Meta doesn't have any resources, and it's doesn't have a business model for AI.
它可以将AI作为其现有产品的附加功能。
It can it can have AI as an add on to its existing products.
但这并没有奏效。
That's not really working.
我们并没有任何证据表明这行得通。
We don't really have any evidence that that's working.
至少与其他一些大型科技公司如微软等相比，他们并没有围绕AI建立一种新的商业模式。
They don't have a new kind of business around AI, at least with, some of the other big tech companies like Microsoft and others.
比如，他们有一个可以运行AI的云业务。
Like, they have a cloud business that can run AI.
而我们所讨论的这些公司，实际上拥有大量收入。
And then with the companies we're talking about, they actually have a lot of revenue.
XAI也是一个巨大的未知数。
XAI is also another big question mark there.
我认为，如果他们能证明自己有一个真正受欢迎、人们愿意付费的产品，他们就会拥有大量资源。
Like, I do think they would have a lot of resources if they could show that they have a product that's really catching on and that people want to pay for.
但他们目前还没有做到这一点。
They just don't quite have that yet.
他们认为AI会变成色情内容。
Think they think it's gonna be pornography.
我们拭目以待。
We'll see.
但他们缺乏的正是这一点。
But but they that's what they don't have.
所以我认为，只要这些公司有业务支撑，就能获得资源。
So I think all these companies can get resources if they have a business behind it.
我想
I want to
是的，还有一点值得注意，Meta的股价今年至今持平。
Yeah, and look, it's also worth pointing out that Meta stock price right now is flat for the year.
截至七八月，股价曾上涨了约30%。
As of July, August, it was up like 30%.
股价已经大幅下跌。
The stock has really fallen.
我认为投资者对扎克伯格一味继续增加支出的做法显然并不满意。
I think it's pretty clear that investors are not happy with Zuckerberg's desire to just keep spending more and more.
我认为，如果他真的在意股价，最终不得不削减开支。
I think that if he cares at all about the stock price, he's going to have to eventually pull back.
是的，他今年雇了这么多人，赚了一大笔钱。
Yes, he's got a fortune this year hiring all these people.
他说他打算在真正需要之前先大力提升产能。
He's saying he's going to really try to build capacity before he actually needs it.
他今年初曾表示，今年将证明Meta是否能在AI竞赛中领先。
Mean, he said at the start of the year, this will be the year that demonstrates whether or not Meta will lead the AI race.
到目前为止，这完全没成功。
So far, this has not worked out at all.
因此，我在想他年底会如何解释这一点。
And so I'm kind of wondering how he's gonna frame that by the end of the year.
我的意思是，他会承认今年没成功吗？
I mean, is he going to admit that this year didn't work?
他会重新调整策略，还是会继续花钱？
And is he going to retool, or is he just gonna keep spending?
我暂停一下，因为实际上我根本不需要向你们两位提问。
I'm pausing because actually I don't even need to ask the questions with the two of you.
这是一场很棒的对话。
It's a great conversation.
我知道你们俩在电话里聊得太多，有时候甚至都用不着我。
I know the two of you talk to each other so much on the phone that sometimes you don't even need me.
听我说，阿米尔，我想回到你这里，因为名单上完全没提到的公司是亚马逊，它是最大的云服务商。
Look, Amir, I want to come back to you because the company that's not on this list here at all is Amazon, which is the biggest cloud player.
你看，我们甚至都不提他们。
And look, we don't even talk about them.
你觉得他们在这里面有什么策略吗？为什么没有站在前沿？
You know, is there a strategy here for them, you know, and and not being at the forefront of this?
我的意思是，他们是一家云服务提供商。
I mean, they're a cloud provider.
他们正专注于这一点。
That's what they're leaning into.
我认为他们曾经希望开发自己的模型。
I think they had some hopes and dreams around developing their own models.
他们确实这么想过，但并没有成功。
They they really did, but it it hasn't panned out.
所以对他们来说，这更像是锦上添花。
So that's, you know, that's sort of a nice to have for them.
并不是必需的。
It's not a must have.
这意味着谷歌作为云服务商有一定优势，因为他们拥有自己的内部模型Gemini，越来越多的企业正在向它靠拢，而亚马逊却没有这样的模型。
It does mean that Google as a cloud provider has a bit of an advantage because they have their in house model, Gemini, that more and more businesses are gravitating toward, and Amazon doesn't really have that.
他们真的在很多方面都依赖Anthropic。
They really lean on Anthropic for for so many things.
但这并不是彻底的灾难，因为他们还有其他业务。
But it's it's not a total disaster because they have these other businesses.
所以你可以把他们看作是类似微软那样的公司。
So you can think of them more as like a, you know, Microsoft, if you will.
对。
Right.
马丁，你认为亚马逊为什么没有做得这么好呢？
Martin, why do you why do you think it's it's, you know, not gone so well for Amazon?
你知道的？
You know?
显然，拥有一个庞大的云业务对任何试图构建人工智能的企业都是巨大优势。
Obviously, having a big cloud business is a big benefit to anyone trying to build an AI.
你认为为什么它没有成功呢？
Why hasn't it panned out, do you think?
我不知道。
I don't know.
我的意思是，我认为亚马逊的游戏还没结束。
I mean, I think firstly, I think that the game is not over for Amazon.
他们也是一家非常大的公司。
They're also a very big company.
他们显然拥有最大的云业务。
They've got a very they obviously got they've got the biggest cloud operation.
我认为我们不应该排除他们。
I think we probably shouldn't rule them out.
但我还认为，他们没有像谷歌那样能赚大钱的业务。
But I also think that they don't have a business like Google has, which makes a huge amount of money.
他们的电商业务利润率相当低，因此他们不像谷歌甚至微软那样拥有充足的资源。
Their commerce operation is a fairly low margin business, so they don't really have the resources that Google has for instance, or even Microsoft.
所以我不确定。
So I'm not sure.
但我认为我们还不应该排除他们。
I think we shouldn't rule them out yet though.
对。
Right.
他们从未像其他人那样大规模招聘。
They've never really recruited like the others.
所以当你听到关于人工智能领域的招聘大战时——这实际上是整个游戏的核心——你看看今年夏天，一切焦点都在招聘上。
So when you hear about recruiting battles in AI, which is really the whole game, you saw this summer, it was all about recruiting.
亚马逊根本没参与这场竞争。
Amazon's not in that conversation.
对。
Right.
阿米尔，最后一个问题给你。
Amir, last question for you.
在新闻室里，你和其他人讨论哪些重要的报道问题？你最想了解这五家前沿公司的情况是什么？
What are the big reporting questions that you are talking to other other folks in the newsroom about the answers that you really want with respect to any of these of these five frontier companies?
我认为，从根本上说，我们最关注的是这项技术在能力方面的演进轨迹。
I think just fundamentally, we continue to focus the most on what is the trajectory of the technology in terms of the capabilities that it has.
这是我们的读者最想了解的事情。
That's the thing that, you know, our readers want to know about the most.
因此，当我们撰写深入探讨某些细节的文章时，比如强化学习过程，以及OpenAI在这方面所做的工作，这正是人们真正关心的，因为最终，我们想知道事物改进的速度有多快。
And so when we do articles that get into the weeds of, you know, let's say, the reinforcement learning process and what OpenAI's been doing there as an example, that's what people really, really care about because, you know, ultimately, know, we we wanna know how quickly are things gonna improve.
你听到了来自不同AI开发者的各种声明。
You have all these statements from the different AI developers.
很难分辨哪些是真实的，哪些不是。
It's hard to know what's real, what's not real.
有时他们承诺过多。
Sometimes they overpromise.
有时他们承诺不足。
Sometimes they underpromise.
所以我认为这正是我回到最初所说的原因。
So I think that's why I come back to what I said in the beginning.
我认为，对于整个行业来说，这是一周不错的时光，
It was a good week, I think, for the entire industry to see
在家里。
At the home.
是的。
Yeah.
从一个角度来看，比如实际研究的角度，这周对行业来说是不错的。
It was a good week for the industry from one perspective, which might be from the actual research perspective.
但从股票角度来看，这周对行业来说糟透了。
It was a terrible week for the industry as far as stocks.
我们现在看到了一些真正的问题。
We've seen there are real questions now.
投资者显然已经变得紧张。
Investors have clearly gotten nervous.
英伟达的股价在过去三周大幅下跌。
Nvidia's stock is down a lot in the last three weeks.
正如我所说，Meta的股价也大幅下跌。
As I said, Meta has fallen a lot.
我认为整个市场都非常紧张。
I think the market overall is very nervous.
因此，从这个角度来看，这并不是一个好周。
So from that perspective, it has not been a good week.
是的。
Yeah.
如果你说市场可能把价格抬得过高了，那这是另一个问题。
If you're saying that the market may have bit, you know, bit up prices too high, that that's sort of another another question.
而且我认为，在此过程中我们可能会看到一些起伏。
And and I think we can expect, you know, kind of ups and downs along the way.
但如果底层技术持续进步，从长远来看，这对这个领域的每个人都会是好事。
But if the underlying technology does continue to improve, that's that's just gonna be good for everyone in the long term that is in this field.
它可能对正在毕业、试图
It may not be good for young people graduating, trying
找工作的世界各地的年轻人不利。
to get jobs rest of the world.
没人会有工作。
No one will have a job.
将没有任何电力可用。
There won't be any power available.
我们所有人都得为电力支付更多费用。
We'll all be paying more for power.
所有这些人都将依赖人工智能和聊天机器人来进行心理治疗。
All these people will be dependent on AI and chatbots for their therapy.
这对世界来说会很糟糕，但嘿，萨姆·阿尔特曼会变得富有。
It'll be awful for the world, but hey, Sam Altman will be rich.
不会。
No.
我认为第二阶和第三阶的影响存在很大争议。
The second and third order effects, I think, are very heavily debated.
别忘了，萨姆·阿尔特曼从非营利组织只拿十万美金的薪水，我认为他没有获得任何
Don't forget Sam Altman only gets a salary from the nonprofit of 100,000 I don't think he gets any
公司的股权。
equity from the company.
如果OpenAI成为一家万亿美元的公司，他一分钱也赚不到。
He will not make any money if OpenAI becomes a trillion dollar company.
我完全相信这一点。
Completely believe that.
好吧。
Okay.
嗯，再次强调，是间接的，不是直接的。
Well, again, indirectly, not directly.
但没错。
But yeah.
好的。
Alright.
好吧，我们本来可以继续聊下去，但我真的相信，我们一挂电话，你们俩就会立刻打电话交流。
Well, we could keep it going, but I actually fully believe you're gonna pick up the phone and talk to each other right after we but as we hang up.
谢谢你们两位的到来。
So thank you both for coming on.
我会鼓励你们俩多来参加，因为你们的协作和编辑互动非常棒。
I'm going to encourage you both to come on more because it's a great co executor editor dynamic.
我们很快就会再和你们两位聊。
We will talk to you both again very soon.
谢谢。
Thanks.
对。
Right.
谢谢，阿卡什。
Thanks, Akash.
好的。
Okay.
我们一直密切关注埃隆·马斯克对OpenAI提起的诉讼，而我的同事罗基特·德鲁最新的一篇报道——他一直密切关注此事——清楚地表明，目前OpenAI所面临的利害关系，可能并没有最初看起来那么重大。
We've been closely covering Elon Musk's lawsuit against OpenAI, and a new story from my colleague Rocket Drew, who has been following along very closely, makes clear what the stakes now are for OpenAI and why they might not be as significant as they may have originally been.
罗基特，欢迎再次做客我们的节目。
Rocket, welcome back to the show.
很高兴你来到这里。
It's great to have you here.
谢谢邀请我，阿卡什。
Thanks for having me, Akash.
周五快乐。
Happy Friday.
你也周五快乐。
Happy Friday to you as well.
你是本周的最后一段，我们正在谈论我们最喜爱的话题——阿尔特曼与马斯克的 rivalry。
You are the last segment of the week, and we are talking about our favorite topic, the Altman Musk rivalry.
不错。
Nice.
以一个有趣的话题收尾。
Ending on a fun one.
没错。
That's right.
没错。
That's right.
所以，简而言之，这起诉讼我其实并不是每天都去跟进。
So look, in twenty seconds, I mean, this lawsuit is not something that I refresh myself on every single day, frankly.
所以请你用二十秒简单回顾一下，这起诉讼是什么情况，目前进展到哪一步了。
So just give us the twenty second refresher on, you know, the lawsuit and where it stands right now.
当然。
Sure thing.
是的。
Yeah.
所以对于那些没有密切关注的人，比如幸运的阿卡什。
So for those who haven't been following it so closely, who are fortunate, like Akash.
我们上一集的片段。
Scenes from our previous episode.
对，对。
Right, right.
季回顾。
Season recap.
事情是这样的。
Here's what happened.
你可能还记得，好像
You might remember, seems like
很久以前
a long time
但现在，埃隆·马斯克实际上是OpenAI的联合创始人。
ago now, but Elon Musk was actually a co founder of OpenAI.
所以在早期，他帮助建立了这家公司。
So in the early days, he helped set it up.
他捐了钱。
He donated money.
他说他还捐出了自己的时间，以及特斯拉和他的声誉。
He says he also donated his time for Tesla's, his reputation.
他帮助设立了这家公司。
He helped set up the company.
他做这一切的前提是，OpenAI将是一家以特定使命为宗旨的慈善非营利组织，即确保强大AI造福人类。
He did all this on the understanding that OpenAI was going to be a charitable nonprofit with a particular mission to ensure that powerful AI benefits humanity.
现在，在他看来，自那以来的这些年里，OpenAI做了些与该协议不一致的事情。
Now, in his view, in the years since, OpenAI has done things that are inconsistent with that agreement.
他特别指出的一个具体问题是，OpenAI 设立了一个营利性子公司来发布产品。
So some specific ones he calls out are that OpenAI set up a for profit subsidiary that releases products.
这些产品通常没有像他原本认为的那样以开源方式发布。
Often those products have not been released open source, as he thought was the intention.
该子公司与微软建立了密切关系，而微软显然是一家营利性科技公司。
That subsidiary has established a close relationship with Microsoft, which is of course a for profit tech corporation.
他认为，萨姆·阿尔特曼已经某种程度上边缘化了 OpenAI 内部的 AI 安全团队。
He argues that Sam Altman has sort of sidelined the AI safety teams inside OpenAI.
而最近，OpenAI 完成了这种公司重组。
And then most recently, OpenAI has completed this kind of corporate restructuring.
这意味着投资者现在在 OpenAI 拥有传统的股权。
That means that the investors have traditional equity in OpenAI now.
他们不再拥有之前那种利润上限的股权份额。
They don't have these sort of capped profit ownership shares that they had before.
因此，所有这些加在一起，他说，这违背了我们之前的协议，于是他将他们告上了法庭。
So all of this together, he said, this sort of betrays the agreement we had and he takes them to court.
他针对他们提起了诉讼，指控包括反垄断和违约等多项罪名。
And he takes them to court for many claims, including antitrust claims and breach of contract.
其中一些指控现在看起来可能最早在三月进入审判阶段。
And a handful of those claims now look like they could go to a trial as early as March.
因此，我们想探讨一下，如果他在庭审中赢得其中一些指控，可能会产生什么结果
So we wanted to take a look at, well, in the event that he does win some of those claims at that trial, what could come out
呢？
of it?
而且可能会产生什么结果？
And what could come out of it?
顺便说一下，这段话超过了二十秒，但没关系。
By the way, that was longer than twenty seconds, but it's fine.
我们继续。
We'll keep going.
这是一个漫长的案件。
It's a long case.
这是一场漫长的诉讼。
It's a long case.
但这件事可能带来什么结果呢？
But what could come of it?
是的。
Yeah.
我们先从金钱方面说起。
Let's start with the money side.
我觉得那稍微简单一点。
I think that's a little simpler.
如果他胜诉，最低限度他可以拿回早期投入OpenAI的资金，或许还能加上一些利息。
At the low end, if he wins, he could get repaid for the dollars that he put into OpenAI in the early days, maybe with some interest.
这个数字有所变动，但目前我们认为他投入了大约3800万美元，所以他可能拿回本金再加上一些零头。
The number has slid around a little bit, but right now we're thinking he put in about $38,000,000 So maybe he gets that back and some change.
也许还有那四辆特斯拉。
And maybe the four Teslas.
对。
Right.
也许他仍然想要那些车。
Maybe he still wants those.
他还可能被判予所谓的惩罚性赔偿。
He could also be awarded what they call punitive damages.
这不仅仅是试图让马斯克恢复原状。
So it's not just trying to make Musk whole again.
而是要惩罚OpenAI涉嫌的某种不当行为。
It's trying to punish OpenAI for some sort of wrongdoing that they have allegedly done.
另一种结果，这也是本案中最重要的一个。
The other outcome, and this is sort of the big one.
这是本案中所谓的‘十亿美元级’的关键词。
This is you know, billion dollar word in this case.
那就是非返还性的没收。
It's non restitutionary disgorgement.
这话说起来真拗口。
And that's a mouthful.
我的意思是，连说十遍试试。
I mean, to say that 10 times fast.
非返还性，嗯，我可说不来。
Non restitutionary yeah, I can't do it.
没错。
Exactly.
对。
Yeah.
所以‘非返还性’的意思是，它并不是为了弥补马斯克在过程中所遭受的任何损失。
So it's non restitutionary in the sense that it's not trying to make Musk whole for anything that he has lost along the way.
但即便如此，OpenAI 也必须交出其非法所得的利润。
But nonetheless, OpenAI would have to disgorge its ill gotten profits.
所以这个想法是：OpenAI 目前所有能追溯到他最初那笔 3800 万美元的资金，都不该属于它，因此他们不该保留这些钱。
So the idea is anything that OpenAI has now that's traceable back to that $38,000,000 he gave initially is something that OpenAI should not have, and so they I should not give it
我觉得，从你的报道来看，最有趣的部分是，这是一笔十亿美元的资金。
think, you know, the most interesting part for me, from your reporting, was that, look, this is a billion dollars.
对双方来说，这笔钱现在算不上特别多了，但在此之前， stakes 要高得多，它本可能真正扰乱 OpenAI 的整个重组以及治理结构。
It's not exactly that much money to either party anymore, whereas the stakes were much higher before that it could have actually disrupted the entire restructuring of OpenAI and the way that governance worked.
我的意思是，我们谈的不过是区区十亿美元而已。
I mean, we're talking about, dare I say, only $1,000,000,000 money.
那
The That's
我对你有个更广泛的问题，罗克特，你觉得这件事在萨姆·阿尔特曼和埃隆·马斯克心中还占多大分量？
broader question I have for you, Rocket, is how much mindshare do you think this actually operates for Sam Altman and Elon Musk anymore?
你认为他们真的还在意这件事吗？
Is this even something that you think they care about that much?
我觉得是的。
You know, I think it is.
我真的觉得是的。
I think it really is.
自从OpenAI完成重组后，法院介入并试图阻止或推翻这一重组的可能性似乎变小了。
Since OpenAI has completed its restructuring, it looks a little bit less likely that the court would interfere and try to prevent or reverse that restructuring.
但这件事仍然在考虑之中。
But it's still on the table.
你真的不能排除任何可能性。
You really can't count anything out.
我与一些讨论此案的律师交流过，他们说：‘我通常建议客户，在大多数情况下，任何事情发生的概率大约是20%。’
A number of the lawyers that I talked to about this case said, Well, I advise my clients that in most cases, there's a 20% chance that anything could happen.
陪审团是不可预测的。
Juries, they're unpredictable.
谁知道未来事情会如何发展呢？
Who knows how things will play out down the road?
所以我认为这对双方来说仍然是一个非常现实的问题。
So I think it is very much a live issue for both of the parties.
如果这不是一个问题，他们也不会如此激烈地争夺。
And I think if it wasn't, they wouldn't be fighting it so hard.
意思是，他们正在投入大量资源在法庭上与之抗争。
Mean, they're putting a lot of resources into fighting this out in the courts.
如果对他们来说利益没那么大，也许我们就看不到如此坚定的立场。
And if the stakes were smaller for them, maybe we wouldn't see that same level of conviction.
所以再重申一下，除了金钱方面——在极端情况下可能超过10亿美元之外，法院还可能判处其他补救措施。
So just to reiterate, in addition to the money side, which in the extreme scenarios could exceed $1,000,000,000 there could also be other remedies that the court awards.
例如，法院可能会试图改变OpenAI与微软之间的关系性质，因为这是马斯克一直抱怨的问题。
It could try to sort of change the nature of the relationship between OpenAI and Microsoft, for example, because that's something Musk has complained about.
它还可能试图撤销重组，或对重组施加新的条件。
It could also try to reverse the restructuring or try to put new conditions on the restructuring.
好的。
Okay.
所以，利益仍然相当高，
So the stakes still pretty high then,
我想是的。
I'd say.
很好。
Great.
好的。
Okay.
嗯，火箭，我期待看到这个案件后续的发展以及你还能挖出什么更多信息。
Well, Rocket, I look forward to seeing what more comes of the case and what more you dig up.
感谢你今天来做客。
I want to thank you for coming on.
祝你周末愉快。
Have a great weekend.
我们很快再见。
We'll see you soon.
谢谢，阿卡什。
Thanks, Akash.
嗯，那这就
Well, that does
今天的节目就到这里。
it for today's show.
提醒一下，我们每周一至周五上午10点（太平洋时间），下午1点（东部时间）直播。
A reminder, we are on this stream Monday through Friday at 10AM Pacific, 1PM Eastern.
我要感谢亚马逊网络服务公司，作为本节目的冠名赞助商，也感谢各位的收看。
I want to thank Amazon Web Services, who is our presenting sponsor for this production, and I want to thank you for tuning in.
我们非常感谢大家的支持。
We really do appreciate your viewership.
我已经迫不及待期待周一的下一期节目了。
I am already excited for our next show on Monday.
祝大家周末愉快。
Have a great weekend.
暂时再见。
Bye bye for now.
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