Markets Weekly February 14, 2026
发布时间 2026-02-15 02:29:09 来源
Hello my friends, today is February 14th and this is Market's Weekly. So this past week was a very volatile week in markets as we've been discussing over the recent weeks. It really seemed to me that the market was losing momentum. Now this past week we saw the S&P 500 lose the 50 day moving average. On Friday it came very close to losing the 100 day moving average as well. That kind of reminded me of a wise person who traded through the dot com boom and bust that during the dot com a lot of people wouldn't broke selling it in a few years later, even more people wouldn't broke buying it. Now I'm getting the sense just the guess that we probably have to test the 200 day moving average around a 6500 because we really this trend doesn't doesn't look that great.
你好，我的朋友们，今天是2月14日，欢迎收听《市场周报》。在过去的一周，市场波动异常剧烈，就像我们最近几周一直谈论的那样。我感到，市场似乎正在失去动力。在过去的一周，我们看到标准普尔500指数跌破了50日均线。周五，它还差点跌破100日均线。这让我想起一位精明的投资者，他经历过互联网泡沫的兴衰。在互联网泡沫时期，很多人因卖出股票而破产，几年后，甚至更多的人因买入而破产。现在我猜测，我们可能不得不测试6500点附近的200日均线，因为眼下的趋势看起来确实不太乐观。
This past week we got a lot of tier one data. We got the non-farm's payroll spread. We got retail sales and we also got CPI. So first let's talk about the data. And secondly I started using cloud AI last week. Of course we saw huge amounts of selling in the SaaS stocks and even some bulk management stocks. Everyone that all the stocks that were perceived to be disrupted by AI. So I had to try the latest AI myself and I'm beginning to think that AI is going to be very good for bonds.
在过去的一周里，我们得到了大量一类重要数据。其中包括非农就业数据、零售销售数据以及消费者价格指数（CPI）。首先，让我们讨论这些数据。其次，我上周开始使用云端人工智能。大家都看到软件即服务（SaaS）股票以及一些大宗管理股票被大量抛售，因为所有被认为可能被人工智能颠覆的股票都受到了影响。所以，我也尝试了最新的人工智能技术，现在开始觉得人工智能对债券市场可能会非常有利。
All right starting with the data. So we got a huge three huge prints last week. First of all, of course the non-farm's payroll sprint, the January print was delayed until last week and it was much better than expected. However it also came with the annual benchmark revisions and the benchmark revisions basically erased one million jobs created last year. So as we've been discussed before the market really doesn't care about revisions. It only cares about the monthly prints. If the monthly prints last year were accurate we would have had zero or negative monthly prints. And that would have been very upsetting to the markets. But now that we a year later we revise them all away the market really doesn't care.
好的，先说数据。上周我们得到了三个重要的数据。首先是非农就业数据。原定于一月公布的数据被推迟到上周发布，而且表现远超预期。然而，这次数据也伴随年度基准修正，而这些修正基本上抹去了去年创造的一百万个就业岗位。正如我们之前讨论过的，市场其实不太关心修正数据，它只关注每月公布的数据。如果去年的每月数据是准确的，那么我们可能会看到零增长或负增长的月数据，那会让市场非常不安。但现在，一年后我们对这些数据进行了修正，市场其实并不在意。
What it does care about though is that it seems like the job market is improving. So the January report was better than expected and maybe we'll be right advised away a year from now. But at the moment it's better than expected and the market is going to perceive that to be good and that the economy is less likely to go into recession. But it also of course reduces the odds of fed rate cuts. Now we also got the retail sales and CPI last week. But people were talking about that we have to mention a little bit about seasonal adjustments. So throughout the year data is uneven because of seasonal effects.
它真正关心的是，工作市场似乎正在改善。因此，一月份的报告比预期要好，也许一年后的我们会感到欣慰。 但是目前来看，情况好于预期，市场会将此视为好事，并认为经济陷入衰退的可能性降低。 当然，这也减少了美联储降息的可能性。上周我们还看到了零售销售和消费者价格指数（CPI）的数据。不过大家提到，我们必须稍微谈一下季节性调整。因为一年中由于季节性影响，数据会不均衡。
For example people use tended to do a lot of shopping in November and December. That's a big holiday season. So retail sales there are going to be a lot more. And in January people tend to reset their prices. For example if you're a company and you want to raise or lower prices on your products or services you tend to do that in the beginning of the year. So there is some seasonality to how these the data is computed. And to make data more comparable month to month economists or statisticians tend to do these seasonal adjustments. So keep that in mind when thinking about the data.
例如，人们往往在十一月和十二月进行大量购物，因为这是一个重要的节日季节，所以那段时间的零售额会大幅增加。而在一月，人们通常会调整他们的价格。例如，如果你是一家公司，想要提高或降低产品或服务的价格，你通常会在年初进行调整。因此，这些数据的计算是有季节性的。为了让数据在每个月之间更具可比性，经济学家或统计学家往往会进行季节性调整。所以，在分析这些数据时，需要把这些因素考虑进去。
So for retail sales the data was much lower than expected. They were basically flat month to month. And some people think that could be due to aggressive seasonal adjustments. Which are difficult to make because of course the economy is changing. Behavioral changes as well sometimes seasonal adjustments can be overdone or underdone. Moving on to CPI data CPI was better than expected. But still at the end of the day it's still about 2.5% above the Fed's target. One thing to note of course is that companies do raise their prices in January. And so these seasonal adjustments make the January print less accurate than other prints as well.
零售销售的数据远低于预期，基本上是从一个月到另一个月持平。一些人认为，这可能是由于激进的季节性调整造成的。因为经济变化，做这个调整很难。而且由于行为变化，有时候季节性调整可能做得过多或不足。
继续说到消费者价格指数（CPI）数据，表现好于预期。然而，总的来说，它仍然比美联储的目标高出约2.5%。值得注意的是，企业通常在一月份提价，所以这些季节性调整使得一月份的数据不如其他月份的数据准确。
So all in all though this is I don't data that is no kind of positive right. You have better than expected job growth and you have inflation that's coming down. Of course the market didn't seem to really care about this. They were really more cared about what seemed to be happening in the AI world. And that is the AI is cannibalizing current companies. So that brings us to our next topic. So I've talked about AI before. I started trying to use AI to help my workload.
总的来说，这些数据并没有带来什么积极的影响。虽然就业增长好于预期，通胀也在下降，但市场似乎并不关心这些。这是因为大家更加关注人工智能领域所发生的事情，看起来人工智能正在吞噬现有公司。这也引出了我们的下一个话题。之前我谈到过人工智能，我已经开始尝试利用人工智能来帮助处理我的工作量。
And in the beginning it was very disappointing. So I asked the AI to do basic things like tell me when Fed is just speaking and it really couldn't do that. It was amazing to me that I asked it to go on the Federal Reserve's website to look up who's going to be speaking this week and it could not do that. So that was very disappointing. But last week we had the release of the latest cloud model and we also had a carnage in a lot of software as a service companies.
起初，这让我非常失望。所以，我让人工智能做一些基本的事情，比如告诉我美联储什么时候发言，但它真的无法做到这点。令我惊讶的是，我让它去美联储官网查看本周有谁要发表讲话，它也无法做到。这让我非常失望。不过，上周我们有最新的云模型发布，同时还有许多软件即服务公司遭遇重创。
The market, at least people who follow this, was thinking that the latest AI is really going to be very destructive to the value of these companies. Maybe there's more competition. Maybe consumers are going to move to spoke AI created, vibe coded platforms and so forth. We even saw some wealth management companies like Swaps go up aggressively because maybe AI can provide taxish fishing strategies in place of wealth advisors. So again I had to try this for myself. So I signed up for the cloud max plan. So that's like $100 a month. I got to use it. So what did I use it for?
市场上，至少那些关注这个市场的人，认为最新的人工智能可能会严重影响这些公司的价值。也许会有更多竞争，也许消费者会转向由人工智能生成的、更具个性化的平台等等。我们甚至看到一些财富管理公司，如Swaps，这类公司的价值大幅上升，因为可能人工智能可以提供税务优化等策略，替代传统的理财顾问。因此，我决定亲自试试。我注册了一个Cloud Max计划，每月大约100美元。那么，我用它做了什么呢？
Well, as you guys know, I am writing the second edition to my books such as Banking 101. The last one was five years ago. So between data now, a lot of things happen. So I updated all the data, added a whole bunch of new sections about you know, the Silicon Valley bust, Silicon Valley bank buzz, you know, treasury buybacks, QT all that stuff. So I basically updated everything and I felt like I was basically done with the mounting strip.
好，大家都知道，我正在撰写我的书籍的第二版，比如《银行学101》。上一本是五年前写的。所以在这段时间内，发生了很多事情。因此，我更新了所有的数据，增加了很多新章节，比如关于硅谷的衰退、硅谷银行的风波、国债回购、量化紧缩等等。因此，我基本上更新了所有内容，并感觉自己基本上完成了这个稿子。
So usually what I would do is I would hire an editor, a freelancer, and pay him a few thousand dollars to go through this. And I would also hire some artists to make a new book cover for a few hundred dollars. And these are people that I was sourced through upwork.com basically sites that post freelancers. But this time I decided I would give AI a try. Since that's what all the cool kids are doing right now.
所以通常我会请一个编辑，一个自由职业者，付给他几千美元来处理这个。而且我还会花几百美元请一些艺术家设计一个新的书封面。这些人基本上都是我通过upwork.com这样的自由职业者网站找到的。但这一次我决定尝试使用人工智能，因为现在这是一种很流行的趋势。
So I uploaded everything into cloud and asked him to kind of, you know, be my editor and proofread it. And he said that it would take six hours. And so I waited for six hours. And what I got back was, you know, I guess he gave me like a few suggestions, updated some data points and things like that. Some very general stuff. I thought it was actually pretty, you know, just not that special.
所以我把所有东西上传到了云端，让他帮我编辑和校对。结果他说需要六个小时。于是我等了六个小时。可他给我反馈的是一些建议，更新了几个数据点之类的。都是些很普通的东西。我觉得没什么特别的。
But you know, maybe it's my fault. Maybe I'm not prompting cloud correctly. So this is what I did. I pumped him in a more precise way. I said, could you look at the reviews that I that are posted on Goodreads on Amazon? And there are a lot of reviews. And can you bring that feedback in mind? Can you go through the manuscript and can you give me some suggestions? And also just no broad suggestions as to what work you do better and so forth like that.
但是你知道，也许是我的错。也许我没有正确地引导云服务。所以这是我做的事情。我以更精确的方式引导了它。我说，你能看看我在Goodreads和亚马逊上发布的那些评论吗？评论很多。你能考虑那些反馈，然后浏览一下我的手稿并给我一些建议吗？而且不仅仅是笼统的建议，还有哪些方面可以做得更好等等。
So this time it only took a few minutes. Maybe it's already in his memory or something like that. He came back with actually something that was pretty helpful. Give me a list of suggestions. Give me a separate word document detailing this. And you know, looking through it, some of them were not that great. Silas, the good course. Some of them were pretty good.
这次只花了几分钟。也许已经在他的记忆里或者类似的情况。他回来时提供了一些相当有用的信息：给了我一个建议清单，并且还附上了一个详细说明的Word文档。看了一遍之后发现，其中有些建议不太好，而有些则相当不错。Silas的建议不错。
One of them, for example, was that in your reviews, people suggest you having a gloss read gloss. So did they can look at these acronyms, QT, FOMC stuff like that. That was pretty good suggested. And some of them also suggested that, hey, maybe you could have summary chapter for bullet points, you know, kind of like a textbook at the end of the textbook, you kind of give you a summary as to what you should be, what you should have learned from this chapter.
其中一个建议是，在您的评论中，有人建议您增加一个术语表，以便读者可以查阅这些缩略词，比如QT、FOMC之类的。这是一个不错的建议。另外，有人也建议说，或许您可以在章节末尾添加一个要点总结，就像教科书的最后一章，为读者提供一个总结，让他们知道应该从这一章节中学到些什么。
I thought that was pretty good suggestion as well. And so I asked Cloud, could you do that for me? And like just like that, it created wonderfully made glossary, wonderfully made bullet points. I thought that was pretty cool. I'm guessing that it could do more to help me with my manuscript, but I'm probably not prompting it well enough.
我觉得那也是个不错的建议。所以我就问Cloud，你可以帮我做到吗？结果它很快为我创建了一个精美的词汇表和项目符号。我觉得这非常酷。我猜它还可以在我的手稿方面提供更多帮助，只是我可能没有很好地引导它。
It did tell me though that it was very good and well written. And so I think it's just part of its job, like any employee. When I went to ask it about helping me create a new cover from an updated version, I gave it my prior cover and you know, gave it some ideas and it immediately basically like rock gave me a number of ideas and ways to pursue.
它告诉我这本书非常好，而且写得很好。所以我认为这只是它作为员工的一部分职责。当我去请它帮我为更新版本设计新封面时，我给了它之前的封面，提供了一些想法。然后，它立刻就像火箭一样，给了我很多点子和可行的方法。
And that's actually exactly what my like a real human cover designer would have done. He would have given me a few design choices and then I would have no decided which one to go and how to advance it. So I'm probably just going to use Cloud as an editor. I think it's really good enough. And honestly, I don't know some of the human, it's hard for me to know if the human editors that are good or not until after the fact. But for the artistic stuff, I think I'm still going to hire a real designer. I think having that human artistic touch, she is something that I'm not really sure that Cloud can fully do right now. The covers he's shown me are very good. But I guess I'm just not competent enough in my own judgment and prefer someone who I, a proper artist to do that.
这其实就像我真正的人类封面设计师会做的那样。他会给我提供几个设计方案，然后我再决定选哪个以及如何推进。所以我可能会把Cloud当作编辑来使用。我觉得它真的已经足够好了。老实说，在事情完成之前，我也难以判断人类编辑的好坏。但对于艺术方面，我还是打算雇佣真正的设计师。我认为拥有那种人类的艺术触觉是云可能现在还不能完全做到的。Cloud给我展示的封面非常不错，但我对自己的判断没有太多信心，还是更喜欢由一位专业的艺术家来完成。
But that immediately got me thinking as to just what the implications of this are. So just, you know, first, first, first principle, first level thinking. So I would have spent a few thousand dollars on a editor, freelance editor and now I'm not going to do that. I'm going to use Cloud instead, Cloud which costs $100 a month, which of course, does not cover its operating costs, right Cloud Anthropic continues to lose money. So first impact of course is that I get fast service and better service like goods and services are produced by Cloud AI. And immediately everything is, is my readers supposedly benefit and I benefit as well. However, this is not really going to show up in GDP data because I'm just playing Cloud $100 a month and Cloud is losing money.
这让我立刻开始思考这件事可能带来的影响。首先，就是进行基础的第一层思考。我原本会花几千美元请一个自由职业编辑，而现在我不打算这样做了。我决定使用Cloud，而这每月仅需100美元，当然，这个费用并不足以覆盖其运营成本，Cloud Anthropic仍在亏损。所以，首先的影响是我获得了快速且更好的服务，因为Cloud AI生产的商品和服务质量较高。这样一来，我的读者和我自己都能从中受益。然而，这种情况并不会体现在GDP数据中，因为我每月只支付Cloud 100美元，而Cloud本身是亏损的。
And it's kind of like how people who use AI and create all sort of funny videos and memes. These are actually goods and services that are produced, but of course you don't really pay for them. And so, and they people don't pay to see them. And so you don't really impact GDP. However, this editor that I would have hired, he's not going to be hired. So that is going to increase unemployment and actually reduce GDP because he would have produced goods and services that I paid for, but he's not. And so maybe someone else hires in maybe not. My guess is just that on macro scale on the margins people like him are just not going to be working.
这有点像，那些使用人工智能制作各种有趣视频和表情包的人们。他们实际上在创造商品和服务，但当然你并不真的为此付费，因此人们观看它们也不需要付费，所以这并不会真正影响国内生产总值（GDP）。然而，我本来会雇佣的一位编辑，现在却不会被雇佣。这会增加失业，实际上减少GDP，因为他本来是会生产我支付过的商品和服务的人，但现在没有。所以也许其他人会雇佣他，也许不会。我猜，在宏观层面上，这类人只会在边缘上无法找到工作。
And so obviously, slight upward pressure on unemployment, improvement in goods and services, the quality of it, but improvements that don't show up in GDP. So that's kind of an interesting combination, but honestly kind of common when we think about technology over the past few decades, right? So your iPhone, for example, is much better than was 10 years ago. It doesn't really cost that much more. So when you think about paying for stuff, it doesn't really show up in GDP, but the quality of the services is better. And I think this seems to be an extension of that.
显然，失业率略有上升，对商品和服务的质量有所改善，但这些改善并未在 GDP 中体现出来。这是一种有趣的组合，但在我们回顾过去几十年的技术发展时，其实蛮常见的。比如说，你的 iPhone 比 10 年前好多了，但价格并没有涨很多。所以当你考虑消费支出时，这种质量的提升并不会反映在 GDP 中。我认为这就是这种情况的一个延伸。
Now thinking more broadly, let's say, how does this impact business assistance or for that give you an example of what I'm doing with my, with the second edition of the book. But you can generalize this, for example, to writing a newsletter, right? So if I use AI to help me with my workload and sometimes I do, for example, the Fed released a lot of confidential documents, I believe in 2020. And they do that on a five year lag. And so I had AI look through it to see if there was anything interesting. Now otherwise, I either would not have done this or would have taken me a long time because it's literally hundreds and hundreds of pages to look through. And the AI was helpful in looking through that. So that helps me in that it makes me a little bit smarter and more able to provide a slightly better product to people who subscribe.
现在，从更广泛的角度来看，比如说，这如何影响商业援助，或者让我给你举个例子，说明我在第二版书籍中的做法。但是你可以将其泛化，举个例子，可以应用于写新闻通讯。比如说，如果我使用人工智能来帮助我完成工作，有时候我确实这样做了。例如，美联储在2020年发布了很多机密文件，通常会有五年的滞后期。我让人工智能去查看这些文件，看看有没有什么有趣的内容。否则，我可能根本不会做这件事，或者会花很长时间，因为这些文件有几百页。而人工智能在查看这些文件时非常有用。这对我有帮助，因为它让我变得更聪明一些，能够为订阅者提供更好一点的产品。
However, I'm not able to charge more for that and it does not increase the amount of subscribers. So it's an improvement, but it really doesn't show up in GDP. So I think there's that's probably going to be really common for a lot of industries. Just thinking back through the industries that I've been involved in in the past. For example, my first job was at a law firm and at a law firm, a lot of the work that lawyers do, well, it depends. But broadly speaking, if you're a junior associate in litigation, you would be spending a lot of time researching legal cases on Westlaw, Lexus Nex says or something like that.
不过，我无法因此收取更多费用，也无法增加订阅者的数量。因此，这项改善虽然有意义，但实际上并没有反映在GDP中。我认为这可能会在许多行业中普遍存在。回想起我过去参与过的行业。比如，我的第一份工作是在一家律师事务所。一般来说，在律师事务所里，如果你是诉讼部的初级合伙人，你会花很多时间在Westlaw或LexisNexis这样的平台上研究法律案件。
AI can definitely do that very well and much better than any associate can. If you are someone on the transactional side, you would be editing contracts, for example, on honestly, it would be basically getting a contract that the firm did for like JP Morgan and then updating the terms for contract for Morgan Sally deal, you know, fine and replace literally fine and replace JP Morgan and Morgan Sally, updating the numbers, you know, 100 million to 200 million in the conforming changes in case of law change, like that. The AI can do that really well as well. So from a junior associate perspective, you're not going to need as many of them.
AI 完全可以胜任这些任务，而且比任何助理做得更好。如果你是处理交易事务的人，比如说你要编辑合同，通常的工作就是拿一份公司为类似摩根大通量身制作的合同，然后更新它的条款以适用于摩根·萨利的交易。基本就是查找并替换的工作，比如，把“摩根大通”替换成“摩根·萨利”，然后更新一些数字，比如从1亿美元改成2亿美元，还要根据法律变化进行调整。AI在这些方面也做得非常出色。因此，从初级助理的角度来看，可能不再需要那么多人力了。
From a partner, senior associate perspective, it's going to make you a lot more efficient. So at the end of the day, though, what happened, it seems, yeah, the first thing that will happen is that it's going to save your time. One thing you can do with your time is to do other productive things or you can simply shrink your time.
从合伙人或高级合伙人的角度来看，这将让你变得更高效。所以到头来，似乎第一个结果就是能够节省你的时间。你可以用省下的时间去做其他有成效的事情，或者简单地减少工作时间。
On an individual basis, it's me watching more TV. On a firm level basis, it's having a small head count, which anecdotally we hear firms are doing. Now, from a productivity standpoint, the firm is not going to be charging less because it, you know, it's using AI more about the junior associates. Okay, so law firms are a little bit different because they're built by the hour, but generally a corporation, it's not going to adjust its pricing, revenue structure immediately. So it's probably going to be reaping those efficiency gains through higher profits and lower higher profits to lower head count.
个人层面上，这意味着我看更多的电视。在公司层面上，则表现为员工数量较少，据说不少公司正在这样做。从生产力角度来看，公司并不会因为更多地使用人工智能来处理初级助理的工作，而降低收费。好比律所有些不同，因为它们是按小时计费的，但通常来说，一个公司不会立即调整其定价和收入结构。因此，公司可能通过更高的利润和减少员工数量来获得效率提升所带来的好处。
But when you think to the second stage of this, though, I mean, at the end of the day, there's not going to be more aggregate demand, right? It's kind of like going to my newsletter example. If I'm able to produce this more efficiently, it doesn't necessarily mean that I'm going to have more subscribers. And so from a law firm or any other services business, even though you are more efficient, you need fewer people can have higher profits. It doesn't necessarily mean that you expand your customers. It doesn't mean that you can charge higher prices.
但当你考虑到第二阶段时，我的意思是，到头来，总需求并不会增加，对吧？这有点像我之前提到的新闻通讯的例子。如果我能够更高效地制作这个产品，并不一定意味着我会有更多的订阅者。因此，对于律师事务所或其他服务行业来说，即使你更有效率，需要更少的人力或获得更高的利润，但这并不意味着你会增加客户数量，也不意味着你能提高收费价格。
So first off, it's going to be GDP neutral because you continue to produce the same amount of services and instead of and you have higher profits, but then again, it's kind of you kind of cannibalizing what you would have what the what the worker you laid out would produce. But afterwards though, you know, unless you have greater demand so that you actually produce more goods and services, you're not going to increase your active GDP. And if you're firing workers, you're going to reduce your active demand eventually.
首先，这将对GDP没有影响，因为你仍然生产相同数量的服务，并且利润更高，但这实际上是在消耗那些被裁减员工本可以生产的东西。但是，除非你有更大的需求以便实际增加商品和服务的生产，否则你的实际GDP不会增加。而且，如果你解雇员工，你最终会减少实际需求。
And the economy, so it seems like this would ultimately be on the second step. Just kind of demand negative. It would actually shrink GDP because it doesn't actually increase the aggregate demand of the economy because you're firing more people who in theory would have been sources of demand. At the end of the day, everyone will have higher quality, good, high quality services, right? You would be able to access like some of the smartest, what, like the smartest, advice smartest information you could with a click of a button, either through AI directly or through some kind of professional who is employing AI.
看起来，这样的经济措施会成为第二步。总体上看，这会对需求产生负面影响。因为它并没有增加整体经济的总需求，反而因为裁员而减少消费需求，这些被裁员的人群本来是经济中的需求来源之一。最终，大家会获得更高质量的商品和服务。无论是通过人工智能直接获取，还是通过使用人工智能的专业人士提供服务，你都能轻松获得最聪明的建议和信息。
So your quality of life will be higher. But it's, I don't see, I don't think it's going to show up in GDP for the reasons I cited earlier. So that's kind of an interesting conundrum. And the implications for markets is that, well, some, of course, we already see this creative destruction happening right now. Companies first again are going to have higher profit margins. So that's good. But then some companies will be completely superseded. And so that's about for them.
所以你的生活质量将会提高。但是，我认为这不会体现在国内生产总值（GDP）上，原因如我之前所说。这是一个很有趣的难题。对于市场的影响是，我们已经看到现在正在发生的创造性破坏。首先，一些公司将获得更高的利润率，这很好。但与此同时，一些公司将被完全取代，对它们来说这就不那么好了。
Eventually, though, you're going to have competition and those high profit margins will be completely lower. You know, it doesn't level the playing field a little bit. And that's small companies will have access to tools and resources that they would not have had access to before. So if you have higher unemployment, you know, and maybe massive disruption to be in the financial markets, as we've stored through all this creative destruction, who's winning, who's losing, and even the winners eventually have low profits, that seems like it's going to be soft market negative.
最终，你将面临竞争，高利润率将会大幅下降。虽然这可能会让市场环境更加公平，一些小公司会获得以前无法获得的工具和资源，但与此同时，高失业率和金融市场的大幅波动也可能会出现。在经历了这种创造性的破坏后，谁在获胜、谁在失利，即便是获胜者，利润也将变低，这似乎对市场来说是不利的。
So when you put that together, I'm beginning to think that the ultimate AI trade is, it's going to be bonds. You're going to have a lot more rate cuts, lower employment, higher unemployment, lower stock prices, more financial market volatility. So I'm getting the sense that maybe that is going to actually be the ultimate good AI trade. But we'll see. In any case, those are my thoughts right now. Thanks so much for tuning in and I'll talk to you next week.
当你把这些因素结合在一起时，我开始认为，最终的AI交易可能是债券。我们可能会看到更多的利率削减、更低的就业水平、更高的失业率、更低的股票价格以及更多的金融市场波动。因此，我觉得这可能会成为最终的最佳AI交易。但我们拭目以待吧。不论如何，这就是我目前的想法。非常感谢你的收看，我们下周再见。