SKEPTIC’S GUIDE TO INVESTING
Straight Talk for All, Nonsense for None
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Your Hosts - Meet Steve Davenport, CFA and Clem Miller, CFA as they discus the latest in news, markets and investments. They each bring over 25 years in the investment industry to their discussions. Steve brings a domestic stock and quantitative emphasis, Clem has a more fundamental and international perspective. They hope to bring experience, honesty and humility to these podcasts. There are a lot of acronyms and financial terms which confuse more than they help. There are many entertainers versus analysts promoting get rich quick ideas. Let’s cut through the nonsense with straight talk!
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SKEPTIC’S GUIDE TO INVESTING
DeepSeek: China’s AI Disruptor (Part 2)
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In the second part of our discussion of DeepSeek, we explore the potential investment implications of DeepSeek for U.S. technology companies and the the competitive landscape in AI.
Is DeepSeek really “better” than the models used deployed by U.S. Big Tech? Or are there apples-oranges comparisons at play?
Are DeepSeek’s claims of minimal capital investments accurate? Or do they ignore large undisclosed costs?
How accurate are DeepSeek responses, compared to those of U.S. competitors? Is DeepSeek really a “lite” version of an AI chatbot? Is that really sufficient?
Does DeepSeek really run on fewer, simpler GPUs? If so, what are the implications for all of the investments now being made in data centers and the energy to run them?
Was DeepSeek’s rollout of its R1 model intended to embarrass the Trump Administration after its Stargate AI initiative?
Can we expect more export controls on sale of GPUs to China and a TikTok-style banning of the app?
We discuss these and other issues in this 2-part discussion.
Straight Talk for All - Nonsense for None
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Let me hello everybody and welcome to Skeptic's Guide to Investing. This is the second episode that we're doing this week with regard to the developments regarding DeepSeek and its launch and the reaction of US-related companies to DeepSeek, and we're giving you our you know, tentative thoughts about DeepSeek, about its consequences for US companies and how should investors really be looking at this. So, steve, you know why don't I ask you about the obvious question? You know, ask you the obvious question what does this mean for NVIDIA? I mean, Nvidia is in a lot of our portfolios, it's in mine, I think it's in yours, it's in a lot of our listeners portfolios. It had a strong negative reaction to the news about deep seek on Monday. You know what do you think it means? Uh, sort of. You know, over the medium to long run, like you know, will, will Nvidia look better or look worse?
Steve Davenport:As the months progress, I I think that when we look at this DeepSeek q uestion, the first question question everyone has is how did they get their extra you know efficiency and how did they get such a low energy usage when others, you know, we're talking about an order of 10 in cost and capability in terms of energy, capability in terms of energy. So my question, or my response, would be NVIDIA is still the leader and nobody is really sure anybody could take advantage of something without using NVIDIA's chips. So the fact that we're questioning whether DeepSeek has 10,000 GPUs or 50,000 GPUs tells me that NVIDIA is right. In the middle of this discussion, it's being utilized those chips with a different type of code that's developed in a more open I guess I have trouble saying Chinese company and open in the same sentence, but it looks like it's being developed in a way that is open and I look at that and I still have trouble with that. So when we go underneath the covers and start to ask the model more questions, we get some interesting results, which I see why we decided to put controls on the best chips, because the best chips can lead to the best models, and so when I think about this, I think what it says is so when I think about this, I think what it says is even in China, they're not using their own chips. They're not using chips from another part of the world. They're using NVIDIA chips and it's just a question of which version of the chips are they using and how were they able to get such extreme results using and how were they able to get such extreme results? But I look at the political implications of this and I think that it highlights why controls and tariffs and some of these issues are going to be at the forefront of markets going forward.
Steve Davenport:When we look at the chat, the functionality of DeepSeek, it doesn't answer any questions regarding human rights. It stops the calculations and stops the model when someone asks about Chinese and human rights. You cannot ask a question about Tiananmen Square. You cannot ask a question about Taiwan and Taiwan independence. So when we look at our models and how we develop models, we kind of have this idea that it needs to be fully functional, meaning that it's got data that is, a complete data set. And that's one of the things that some people have talked about is that the data set that they use is really about two years old, and so, while the timing and the performance was good, it was on a problem and on a question that many people have already gone to deeper questions and more complicated ideas and bigger and longer responses.
Steve Davenport:So I think that I would say that what they've done is they've raised a good question in competitive markets worldwide, which is what is the right way to develop? What is the right way to develop, what is the right way to try to have software be as efficient as possible? And for the first time, I think when people look at it and say I'm using one-tenth the energy, that's a pretty nice thing. If you think about China and you don't think of their energy usage or AI being one-tenth the United States and of course I'm extrapolating there. That might not be extrapolatable, but I look at this and say are Chinese software developers and chip developers and technology people, are they approaching this in a better way than we are, or is it just they're approaching a simpler problem and their solution to a simple problem can be very efficient? But as the problems get deeper and more complicated, then the energy that's needed to really come up with an answer in a reasonable time is going to get more difficult and is going to require more more in gpus and more in energy.
Steve Davenport:I'm I'm I'm a little bit suspect or skeptical about the energy usage numbers, and I also don't really understand if it's not answering questions about Taiwan, how many of the answers that it has are not really answers, as much as they are propaganda. Is it possible that propaganda could be at the heart of this, and that they really wanted was to get those millions and millions of downloads on Monday and Tuesday, and they realized that TikTok was having some question, and they want to infiltrate our computers and our phones and try to get linked to more and more people who are on the edge of technology. I believe that the Chinese have a longer term plan and I believe they're longer term thinkers, and so, when I see the reaction here, is it part of a bigger scheme and a bigger idea, or is this just a one off? Do you think this is a one off? Because I'm a little bit skeptical.
Clem Miller:Do you think this is a one-off, because I'm a little bit skeptical. Well, no, it's definitely not a one-off. It's part of an overall I don't know plan. Might be too big a word or too strong a description of what's going on, because I don't think all the different details are being planned out from Beijing. But you know, I do think that it is a centrally planned economy. Well, partially and partially not.
Clem Miller:I do think the Chinese government is putting an awful lot of money into the AI sector, into the semiconductor sector. So there's a lot of money going in and therefore they can hire a lot of computer scientists and you know they're encouraging a lot of you know, private companies within China. You know so-called private companies to do a lot of work but at the same time, you know they make sure that these private companies operate in a way that is consistent with, you know, the government propaganda mechanisms. There are some very important laws the cybersecurity law, the national security law, the data security law you know all of which govern how companies, information related companies, can operate within China. So it's a it's a mix of, you know, of state regulation, state subsidy support and sort of private initiative. So the government there is trying to harness all that to. You know the ends of supporting the state, supporting the Communist Party. You know all of that.
Clem Miller:So are is, are is there likely to be propaganda embedded in the answers? I think the answer to that is is yes. I think you mentioned uh italy before. Uh, italy doing an investigation.
Clem Miller:Well, the new digital Digital Services Act, has a provision, article 36, which is trying to control for disinformation going into the EU, and so I'm sure that the EU will start, you know, looking closely at whether uh deep seek, uh, you know, should be looked at.
Clem Miller:You know, as long as well as Tik TOK, they're already looking at Tik TOK uh as a source of, um, you know, potential disinformation coming into the uh, coming into the EU. We don't have in the U S uh, you know, the same kind of ability and in fact even less so now under the Trump administration to control for disinformation, but the EU certainly has moved in the opposite direction and has moved more toward controlling disinformation. Now, with regard to NVIDIA, my thought there is that as models become cheaper to operate, cheaper to use, I think we're going to see more models out there. I think models will start to proliferate. There will be very specific models, more and more specific models that cover narrower slices of reality, so to speak, and also I think that we're going to see more and more demand for these models.
Steve Davenport:When I was looking before we came on, the latest headline is interesting, and they're both related to this. One headline was that Microsoft is accusing DeepSeek of using openAI technology in their software and they were going to ban or try to do something about the fact that they had taken illicitly some of the code from OpenAI. The second thing was that Alibaba today not wanting to be outdone in a much larger market cap company, which I think would be more concerning to the US market, especially the Amazon of the world Alibaba says they've got a better model than both OpenAI and DeepSeek, and so my question is, as we look at commercial applications, I think that being able to ask a question what is the best t-shirt for wearing when you're working out, or what is the best?
Steve Davenport:lamp that you should use for this size room or, you know, the commercial retail ability of companies to incorporate AI would seem like it could really make shopping much more efficient and much more, positive for consumers. If you ask the question and they give you an answer, what typically happens on Amazon is you get the sponsored link first, and whoever sponsors that particular software is going to get higher on the list, whereas if the list was actually determined by analysis and summary of information, wouldn't our queries be a lot more efficient? And wouldn't benefit ? Wouldn't we be less likely, as consumers, to consume stuff that's not, legitimate? And I mean it could make our retail experience completely different. If the leaders in this space are Amazon and Alibaba, that tells me that we're getting very close to what's affecting American consumers.
Clem Miller:Yeah, I guess so. So you know, I think, that Google and Microsoft and and the other companies will definitely be able to compete and outcompete what Alibaba is doing, what you know, what any Chinese company can do. Really, I think we're so far ahead of them on commercialized AI that I'm really not too worried about China being able to effectively commercialize.
Steve Davenport:Okay. So what do we think is going to be the result? I don't have this existed, I didn't think that this could compete, and so how did so many of us not know about? I mean we were questioning was the whole AI space, you know? Was it getting ahead of itself? Are we way down the line and without any real proof of ability to turn some of these AI ideas into actual businesses and actual improvements in margins? And now we have come to earnings for all of these companies and this shakeup occurred, to earnings for all of these companies, and this shakeup occurred. My question would be did the earnings reports now become a deep seek search engine that we just keep asking each of these companies what did they know and when did they know it? And how are they going to react to deep seek when, in reality, we had a lot of other things we were focused on in terms of these companies, and so if somebody was trying to create a certain amount of chaos in this space, they were very successful.
Steve Davenport:And my question is if we're now getting into Alibaba jumping in with claims, you know how many companies can make how many claims, and is there a global measurement? Is it the University of Waterloo in Toronto, or who is the ultimate decider of what is really good capability and what is not? Because, ultimately, I think it's if a business decides to use a software and pays for it, that tells you that they're serious about it and that it's meaningful. If they're not, then they're also making the decision right. And so it's like solar panels when is the right time to add a solar panel? Is it now? Is the technology going to transform in the next six months to a solar panel? Is it, you know? Is it now? Is the technology going to transform in the next six months to a year? And you should wait? The same thing seems to be true of AI. Are we just going to keep waiting or are we going to say now it's open and now it's the time to jump in?
Clem Miller:This is a very, very fast-moving technology. So if you want to be able to use it now, go ahead and use it now, but be prepared to be able to upgrade as time goes on. That's what's going to happen is the need to upgrade, and certainly OpenAI is doing this now. Uh, $20 a month, I think it's $20 a month. Now, uh, you always have access to their uh, their newest uh model. Always, right, they'll, they'll always upgrade you to their newest model. So that's the. That's basically the commercialized model uh that they use.
Clem Miller:Now, you were talking about, you know, the implications for us companies, um, companies, as well as the issue of sort of benchmarking, right? So the issue Let me start with the issue of benchmarking. You know, there, you know, I think you know, as you sort of were implying, the only true benchmark for which models are better than others is dollars, right? How much are these companies actually earning from these models? And I would say not just in terms of revenue, but also in terms of profitability as well. How much in the way of operating profits are they getting from these models? So, you know, take into account capital costs. You know, on into account capital costs. You know, model development costs, semiconductor purchases and so on. That's the. That's really the measure of the cost of, or the measure of the strength of, individual AI models.
Clem Miller:I wouldn't trust what comes out of a research institute, you know, a university, I mean. Think about it this way. Think about all those different companies that come out with ESG ratings. You know they're all over the place with regard to the kinds of information they use in developing these ESG ratings. And I would say the same thing here. If you see somebody who rates models, ai models, you know what are they rating it on. Are they rating it on energy costs? Are they rating it on? You know how many GPUs were necessary? Are they rating it on speed? Are they rating it on? You know volume of information. I mean what are they rating it on? Speed? Are they rating it on? You know volume of information? I mean, what are they rating it on? You can't trust that right as a, as a metal.
Steve Davenport:I think that you got to ask is what's you know, what's their, what's their investment or what's their VIG right? How do they? How do they get paid? And if they improve the demand for software aid, do they, you know? Are they an underlying investor in some of these things? So I find the whole thing to be a reporting question.
Steve Davenport:Are we sure that some of these statements and forward statements about their models being better I mean, are those investment comments that some regulator is going to say you can't say that you have no proof of that and therefore you're misleading shareholders? I mean, I hate to think that anybody would mislead shareholders, but I'm going to go out on a limb here and say that perhaps some of these comments were just a result of so much demand for US technology in the last 24 months that the people in China are sitting there saying, well, this isn't right, we should have more of this, we should have a piece of this pie and our pie, our pie, should, you know, our piece should be bigger. And if it is that case and we are in a technology, you know, a race for space and AI then maybe we, you know, maybe we need to take a lot more of these things seriously, and I was reading about how they the Chinese government loves the fact that this was developed with Chinese nationals, that these are people who grew up in China and educated in China and they came up with the Chinese software, and I find this kind of nationalism and feelings of superiority that we get from who has the best AI a little bit like you know who has the nicest waterfall. I mean, I think it's a great discussion and it leads to a lot, but is it really defining the beauty of AI or is it just people getting on the soapbox and making statements that have no material impact on investing?
Steve Davenport:I find that, comparing this guy as the Sam Altman of China and some of the comments about Liang, the CEO of High Flyer and also the CEO of DeepSeek, I mean it's interesting that when somebody disappears, we don't talk much about them, but when they're competing with US technology companies and they have a better mousetrap, china is more than willing to talk about the individual and not necessarily the whole culture. And so if I were him, I would be wondering you know what is? You know deep seek 2.0? Is there a 2.0 or is this just a? You know, a one-off?
Clem Miller:uh, I think, uh, I think, uh, wang fang, I think he's got to be worried that if he, uh, if he becomes too popular, uh, he may end up like jack ma did at alibaba a few, that's what I was I'm trying to put this together that alibaba sticking their neck in, kind of, is a question about.
Steve Davenport:Well, gee, is that because he had some bad experiences recently and he suddenly wants to, you know, tell everyone that they're.
Steve Davenport:They're not to be forgotten well, jack ma is out of the picture at alibaba but I'm just saying that the company obviously knows how Amal was treated, and so do they want to be. You know, it's interesting how the politics of China are not too different than the politics of the United States. Right, we got the Bezos and Zuckerberg sitting on the stage at the inauguration, wanting to be close to what's happening at the top of the government, wanting to be close to what's happening at the top of the government, and obviously you know, first two days of this week it was deep seek, deep seek, and now Alibaba raises their hand.
Steve Davenport:So you know, I've never heard of Alibaba being the AI model developer, so I'm a little bit like Well, alibaba.
Clem Miller:I'm not surprised about Alibaba because Alibaba, even in cloud services, has been becoming a greater and greater proportion of a cloud services provider, largely because of requirements for data localization in China. So Alibaba has become bigger and bigger on that, so you can look at Alibaba as being obviously it's always been the Amazon of China, and just like Amazon has Amazon Web Services, which is their cloud services, so does Alibaba and it shouldn't be any surprise. I think that Alibaba is getting into AI. So I think everybody is getting into. You know all the big companies are getting into AI. You know even you know sometime last year, salesforce got into AI, started developing their own AI, so we're going to see a continued proliferation of AI for people to invest in companies simply because you know AI is in their title or AI is, you know, in the one sentence description of the company Press release.
Clem Miller:Yeah, in a press release, I think it's. I think it's. You know, ai is a is a tool, it's not an, it's not an end in itself. I mean, I mean I'll make the. I'll make the mistake of saying AI-related company. That's kind of a mistake, I would say. Probably the better description would be industries that are making increased use of AI as a tool. Maybe is a better way to do it If more awkward statement. But we're going to see AI used more and more and I think the focus will turn on companies that are able to use AI in their existing business models more efficiently in their existing business models more efficiently.
Steve Davenport:Okay, I think we have to get it back to our investors and the people who listen. So my question from our mailbag would be investor A wants to know what companies and how did you change your perspective on investing after Monday's correction? Did you make any changes or should there be something that we think about in the future, in the near term, that this is going to change? You got any changes or things you're going to do differently now that you've experienced Deep Seek?
Clem Miller:Well, I had a. It was a shocking experience on Monday, no question about it, but I was able to resist my urge to sell some of these, or to sell down some of these, because I don't believe that this is a fundamental change, a fundamentally negative change let's put it that way in how companies are going to be using AI going forward and its ability to generate future profit growth. So, no, I did not sell anything on Monday, I did not sell anything yesterday and so far, during the course of this call, our prior call I haven't sold anything either, so I'm still holding on.
Steve Davenport:And I don't think your perspective at all.
Clem Miller:Has it changed my perspective? You know it really. It really has not. It just it's. If anything, it's told me that you know, maybe the market was a little overdone on the AI sector and there needed to be a little bit of air let out of the sector. But that's actually good.
Steve Davenport:That's not bad, that's good, I mean my take from this is and you don't sell.
Clem Miller:You don't sell just because the market has done a little bit of a correction. If I had seen three or four days of declining stock prices for some of these stocks, then I would have sort of put them more on a watch list. These are my AI-related stocks, but I saw one day of downturn and then I saw recovery yesterday and I've seen recovery today. So I'm not really that concerned about the sort of AI-related stocks in my portfolio.
Steve Davenport:Yeah, I mean, I agree with you. I didn't do anything, but I think my perspective has changed, in that we need to be more global when we look at who's in this space and what's going on in this space and who are the players who are the players in the EU, who are the players in Asia, who are the players in? Who are the players in the EU, who are the players in Asia, who are the players in North and South America, the Americas and when we look at things in that perspective, I think we become better investors, because I think that focusing on seven names was a folly. I think that thinking that these seven names are the only names you needed to use and seeing CNBC give you a graph of how those seven names have done in the last two years is just imprudent advice for the general public. I don't think anybody would ever expect you to have seven investments, all similar, all in the same space and all based on demand for one new idea.
Steve Davenport:So I think what this does is and I hate to say this, but China's deep seek is democratizing the idea of other players and other people in the space outside of the US, and I think the competition is good, and if the competition comes from a small Chinese hedge fund, it comes from a small Chinese hedge fund.
Steve Davenport:Now that I see Alibaba entering the fray see Alibaba entering the fray I think that what we really have is a much more global and a much more competitive space than anybody was really realizing.
Steve Davenport:I think there are a lot of companies that are going to report in the next week or so, who are going to talk about savings from AI, and I think we're starting to move down this curve a lot faster. And so I would say, if anything, we should be looking, as we talked about in our podcast at the beginning of the year, a little outside the normal characters, the regular suspects of the top 10 names in technology, and start thinking about are there some startups, are there some people who are doing some things that may not be in the space right now, but they could be significant players in the space going forward? I always like to have a balance between those mega caps, the large caps, the mid caps and even some small cap ideas, the mid caps and even some small cap ideas, and then, if you want to get even more carried away, down to the venture and private equities.
Clem Miller:Let's not go too far, steve. So let me just I mean, I'm looking at my portfolio here and just looking at where we are today as of right now. Some of the larger names aren't doing so well, but some of the smaller names or less well-known names in my portfolio are doing quite well today. So you know, I've got you know as of uh, as of our recording right now. I've got Power Solutions International, psix, up 6.8%. I've got Celestica up 5.84%. I've got Vistra up 4.13%. I've got Primorus up 2.17%. I got Comfort Systems up 1.95%.
Steve Davenport:Right, but.
Clem Miller:Vistra was down. What on Monday 30? Yeah, it was down a lot. I'm just saying it's bounced back a lot, I know.
Steve Davenport:I'm just saying that I think what you're seeing in the market is what we should be thinking about, which is there will be some shredding of some of the larger players that have had more of the investor mindshare, and now my thing is let's try to think about outside that mindshare of the largest and biggest to some of these other names.
Clem Miller:So let's talk. I mean, if you look at the other side of this, you'll see NVIDIA today is down 4.54. 0.54. You've got some of the users like database services, data centers, cloud Oracle down 1.7, salesforce down 1.8, ServiceNow down 2.4. So Microsoft down one, so Microsoft down one, broadcom down 0.8, meta down 0.4. So all those aren't doing so well. So some of these other ones that are bouncing back are doing a lot better and I think that's good. It just showed that the smart thing to do was basically, as the market was dropping on monday, was to basically put your put your computers aside and go for a walk.
Steve Davenport:I mean, I was surprised about this story and my main comment would be it's an overreaction.
Steve Davenport:Because of the size of the company and the fact that it's a Chinese company, there's too much unknown if it's short-term gains is just not a good idea.
Steve Davenport:So I think that we have to expect some downturn in these names and we have to accept competitors, and my comment would be this competitor isn't going to probably take market share from other software people in this space, because I think it's too small and I think it's too specific.
Steve Davenport:Their experience in trades for a hedge fund are going to be a different logic than some of the applications that people are pursuing in this space. So I'm going to wrap with that comment, which is stay true to your school, be aware of what this company is and what it's trying to do, but also be aware that you own high quality names, and those high quality names, while they may get overpriced, they still represent what I think is going to be the future. But I think there is a call for or an idea here that we should pursue, which is are there mid cap and small cap names that we need to be more aware of, because we don't want to be blindsided by one of these companies that we should have paid attention to when we didn't. What do you think the summary is Okay.
Clem Miller:So, steve, I'm going to take us back to what I consider. You know the basics that I look at, the quant measures. Basic quant measures I look at to basically screen out stocks. They're not necessarily to screen in stocks, but they're certainly there to screen out stocks. And one is the short interest is short interest, that is, the percentage of outstanding free float against which there are shorts, and I like to see a relatively small number on that, certainly under 2 percent and usually under 1.5 and in some cases under 1. So I like to see that. I mean probably the median short interest for my portfolio is somewhere around 1.3, 1.4%. So that's quite low. A lot of the more. A lot of companies have like 3%, 4%, especially the more.
Steve Davenport:I like that as a measure.
Clem Miller:I think it's a good choice. And then the second indicator I look at, major indicator I look at these days, is the PEG ratio. I know you look at PEG too forward PEG, and I like to keep that again, just like with short interest. I like to keep that under two and preferably down around 1.5, 1.6. I think trying to go down to 1 or below 1 or 1.2, I think that's too much to ask for. But around 1.5, 1.6, I think is good. And keep in mind everybody that the forward peg ratio already takes into account growth because it takes into account long-term growth expectations in the denominator. Now, for sure, those are analyst expectations and so they could be wrong, analysts could be over-optimistic, but it's a lot better than using trailing PEG because the future is different than the past.
Steve Davenport:No, I agree. I think that we're getting back to what really investors should think about, which, in my mind, is what are the company's prospects, how are they going to grow and how much are you paying for that growth rate? And I think that you're right on, and I think we can start to think about the deep, dark world of AI and using GPUs and energy. You know, and get down this rabbit hole, but in reality, we still need companies to make sales and revenue and then bring that profit to the bottom line. That, we think, is they're doing a better job than others, and so um, I think also, steve.
Clem Miller:I think it's. While it's not as important as the first two indicators forward peg and short interest I think also on a portfolio level, it's important to have beta that's not too high. I think that it's useful to have, on a portfolio level, to have beta of around one, or maybe a little less than one, given the fact that the market might be a little overblown. So you have to really be careful about some of these stocks that have betas above two and because you're going to see those react the most negatively in a situation like this. So, unfortunately, I had three stocks in the portfolio that had betas above two going into this Marvel Technology, Broadcom and Nvidia, and all three of them had betas above two. So they reacted the most negatively. But I would say that beta is a complicated measure and I certainly wouldn't put it on the same level as short interest or the forward peg. It's complicated because there are betas for different time periods. You don't know what the frequencies are.
Steve Davenport:You also don't know if a company's earnings or revenue mix has changed. That's why I have the problem with beta is that when a company like Meta has decided to go into one area, like they were into the metaverse, and everybody was like, oh, this is, you know well, this is a different area for them. Their profitability, revenues are going to be different. So how do you you know, how do you look at the past and say I think this is the right beta we should apply?
Clem Miller:Now you could do as I know you do, steve is have some, you know, be very, very mindful of sector balance. So you've got your cyclical sectors and your defensive sectors and I've been less sensitive towards that. But you know, I wonder whether I should be, you know, more sensitive to that issue.
Steve Davenport:Yeah, I just think that when you're making, when you're talking about taxable assets, it's easy to get overweight in one particular area and just not sell because you've got the friction of paying taxes. And so when you're in an IRA or a 401k and you can get out of a name without any impact and into another name, you know your characteristics can be improved in my mind by a better, you know, downside capture. And that's the thing I looked at on Monday Our portfolio of equal weighting. You know, equal weighting performed great on Monday and guess what, it hadn't performed well for the year and a half, two years. So do I then say, okay, you, ok, we were thinking about whether we get away from equal weighting because it's just hurting us, these top seven names with most of these weights, we're never going to be those weights. But then you have a correction, like Monday, and we outperform and you sit there and say this is why we stay balanced and we stay spread evenly. So I think that Monday was healthy for the market.
Steve Davenport:I think Monday was a reaction that we should you know, should we have been better prepared? Absolutely. What do we do differently? We got to work on it. So I think that you know, what I would say is there are always competitors out there, whether we know about them or not, and so we should be aware and be sensitive and be on alert. And so I guess I would say 2025 is going to be an interesting year, but it's going to be a year full of deep seeks and other various deep fakes. Um, so let's try to keep uh, keep that in our mind and not get too complacent.
Clem Miller:So, steve, just right before we close off, um, I'm just looking at a uh, a note here that I got uh indicating that uh, pursuant to the Italian investigation, deepseek has been dropped from the Apple Store in Italy. I think that's an interesting development. Dropped globally Yep from the App Store in Italy.
Steve Davenport:From the App.
Clem Miller:Store in Italy, currently not available in the country or area where you are in, and Google Apps said the download was not supported in Italy.
Clem Miller:So Google, google too, and so I think, I think, given that one can expect that to spread throughout the, throughout the EU, and or might be able to, might, might spread throughout the EU, this unavailability and I also see another, another note that News Guard, which is an organization that takes a look at the accuracy of reporting, has indicated that it's much less has indicated that it's much less. Uh, they ranked deep seek 10 out of 11 in a comparison with uh, chat GPT, uh, google's Gemini, um and uh and other, uh other chat bots, saying that it repeated false claims 30% of the time and provided vague or not useful answers 53% of the time in responding to news, not useful answers 53 percent of the time in responding to news related prompts, leading to an 83 percent fail rate. So it's so. I mean, to the extent that chat at deep seek is sort of a chatbot light. Uh, you know clearly, uh, uh, clearly, a chatbot light doesn't give you the kind of accuracy that maybe a more sophisticated model might give you.
Steve Davenport:Yeah, I mean, I look at, you know, the marine model, semper Paratus, the Marine motto, semper paratus. I mean, I think, clem, I would love to say that US has come out ahead and we, you know, this is meaningless. And this is, no, in no way affects our. You know, technology decisions going forward. But I'd take a more cautious approach and say it could be a wake up call. And that could be a good call, because I think that we always need to be aware of who our competitors are and try and make sure we differentiate and continue to be value-add in any company that we invest. Do you have any?
Clem Miller:final comment no, no, that's it.
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