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- [00:01]
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- [00:56]
Jordy Visser
But the AI thematic side or the the factor side, the volume's up towards 100. Bitcoin volume is still at 30. So if you're putting an asset in a portfolio right now you can have three times as much Bitcoin on a vol adjusted basis as you can AI. And that means that we're at a point where I think you should start seeing more and more people as they get more focused on Ethereum. Get in. Once we get above the 200 day moving average, I believe we're at the start of something new.
- [01:24]
Podcast Interviewer
What's going on guys? Today we got a great conversation with Jordy Visser. In this conversation we talk about all the deleveraging happening in the stock market, why the mid cycle slowdown in AI may be impacting your portfolio. We also get into what's going on with inflation and Kevin Warsh's recent comments. And then last but not least, we go and we cover what's happening with Bitcoin, Ethereum and the entire crypto industry. Here's my latest conversation with Jordy Visser. All right Jordy, I thought we could start the conversation. It seems like there's a big unwind happening in the public market specifically around a lot of the AI names. You started talking quite a bit about this like summer slowdown and how that may affect things. What are you seeing?
- [02:01]
Jordy Visser
Yeah, this is probably going to be a fairly high level discussion. I'm going to get a little wonky with the leverage side, but I think people are going to have to get used to this. So what's happening is the S and P is making new all time highs or equal weight S and P is making new all time highs. Breath is making new all time highs. The AI names are going down. So a lot of people are sitting there seeing their Micron go down and their marvell go down and go through the list of all of the names, every single name, Caterpillar, Modine, everyone that's been, let's say going up fairly fast is giving back. Some of that now some of that is related to just what I talked about, which is the AI mid cycle slowdown is the second derivative change. And Nvidia went through this back in 2024 and I highly recommend everyone go back and look because from ChatGPT to about June of 24, Nvidia went up 12 times. So very similar to let's say micron going from 100 to 1200. Since that period in June of 24, Nvidia's earnings have continued to grow. They've continued to dominate the AI trade but in two years they've now gone up 48% good returns. I mean you're getting 20 plus percent returns, you're outperforming the S and P. But it's not the 12 times that happened. And that's where we are in AI right now for all of these names, meaning most of them had 3 to 10 times type moves, especially the semiconductor names which mean they've built in a lot of the next two years. And I think what the market is going through is this second derivative where when you look at the earnings of these companies and you're like, oh my God, they're up 400%, 500%. But then a year from now they're only going to be up 30%, 40%. So you're decelerating. So that's the first part is I think the market is coming to term with the AI mid cycle slowdown. And the other thing I wrote about, which is the fireworks show, the, the under the hood story is that there is absolutely a deleveraging happening and I want to use again a bunch of comparisons. So Silver and Gold were up massively last year. They had a drawdown. The, the biggest drawdowns they've ever seen in 30 years on different time horizons that were all within 20. The momentum factor for technology has seen an unprecedented move lower. I've posted an X about it and what that does is the volatility rises and whether it's a single name retail person that is taking out leverage, whether it's Korean investors whose margins accounts have been closed or whether it's a long, short, multi strap market neutral hedge fund or it's a systematic quant strategy and we've seen reports and numbers released from the prime brokers of just very large losses in a short amount of time. And because the volatility has gone higher, whether it's risk parity, whether it's any kind of quant strategy, when the volatility goes higher, you not only have to reduce your risk at that point just from volume targeting, but it also means that that position when it starts to come back cannot be as big. So I think the best way for people to understand this, this was going to happen in a case like Micron by going from 100 to 1200 and back down to 800 as of early this morning, you've given back. Now, depending on the name, 30 to 50%. We've done enough based on what I think is there and I think we'll probably start to form some sort of a bottom here. But like silver, like gold and another one like Bitcoin after October 10th, these things have not come back yet. So their volume may have come down, but those things have been on the downside and they haven't gone back. The difference is with the AI trade they were significantly above their 200 day moving average. And so everyone hears this many of these names like Micron, they were unchanged for years. Micron was the same price at Liberation Day lows that it was in 2017. So a lot of these were breaking out of long term ranges. They're way above their 200 day moving average. I think somewhere between this 30 and 60% retracement, they're gonna hang in there and they'll start to move higher again. But I think the firework show is over and I think from this point on some names will do well, some names won't do well and you'll see volatility and gradually come down. Not quickly and not something that's going to just turn into a oh, that was no problem, it was something real and it's about leverage.
- [06:42]
Podcast Interviewer
Do you have a framework for identifying which are the ones that will do well and which ones won't?
- [06:46]
Jordy Visser
Well, what I'm going through and I, I wrote a paper about memory. I think memory is the most important part of the AI trade. I am focused on companies that have not yet see their step up function in earnings. So in the case of Nvidia, when it peaked in 2024 from a 12 bag thing started to happen, which is they started to only beat earnings by a little bit. So the Names that I'm focused on are the ones that I still think are going to beat earnings by a significant amount in the quarters to come, not just this quarter. Memory obviously blew away numbers. So far we've seen Micron blow away numbers, we've seen Samsung blow away numbers, we've seen ASML blow away numbers and all the stocks traded lower. So the semiconductors are going to be fine. But memory is the place that I'm going to be focused on. And then I'm writing a, a very long piece or I did write it, which I'll release on my paywall this weekend about Vera Rubin. And Vera Rubin is another area where there are certain names in there which haven't seen the step up function in earnings yet. That is going to be the things that drives it is you're going to need to beat earnings significantly. And if you're just beating them by a little bit, you can still produce 25% a year returns like Nvidia has. But you're not going to get back up into the 60 and 70. So I think everyone's going to have to now do some homework. That's the reason why I have my 100 name portfolio and I'll be spending the time on which names are better than others.
- [08:10]
Podcast Interviewer
Now a lot of what has been driving the AI trade has been all of these bottlenecks. And a huge piece of the bottleneck was that there was two major American companies, maybe a third was trying to enter the fray in terms of Grok. But we just got the Kimik 3 release and this is a Chinese open source model. It seems to be performing as well, if not better than Fable or any of the latest closed source American models. Does that change any of your analysis if all of a sudden the winning models or these open source models versus them being the American closed sourced?
- [08:45]
Jordy Visser
No. And this is, this is a good time to, to bring this up. So I, I wrote a paper this week on Brad Gerstner's interview on. Well, it wasn't an interview. He, he was a guest on the all in Pod and on that every answer he gave on this to me was very balanced. It kind of went through the pros and cons of all these stories but the comment that I really focused on the most, which I think people have to understand this is the largest TAM that will ever exist at least on planet Earth. We'll see if the, the TAM in space will actually be something that happens. But that TAM is about intelligence and intelligence will drive revenues, that will drive compute demand. So here's the thing with open source and with the Frontier models right now, if I wanted to use Kimike 3.0, I couldn't do it. Neither could you. Unless you had the hardware, there's no way to use it. Meaning could an enterprise use it? Yeah. So it's isolated right now to people that have enough hardware to use it. There's no way to even get the hardware. You have to have GPUs to be
- [09:56]
Podcast Host - Ad Read
able to run it.
- [09:56]
Jordy Visser
Like, this is a big model. That's the only way it competes with the Frontier. If you want to use Anthropic, you just go onto the cloud and you go use it. So there is this element of, well, who's going to be the people that use it? Will developers use it? Yeah, they probably will. They're trying to reduce costs. So AI native businesses are going to have a huge advantage. Will an enterprise company in the United States of America use a Chinese open source model? Maybe over time, but they're trying to get adoption from the humans plus the agents. Humans need, cowork, humans need all of these things and they get used to using a model. So you just can't keep swapping out every time there's a new model. It's not that easy. And so I think if they're, you know, if they're going to bet on something from an enterprise perspective, which is where the revenue is being driven, I don't buy into the fact that these Fortune 500 companies are going to all of a sudden go, you know what, I'm going to get rid of Fable 5 and Anthropic and I'm going to move this Chinese model, we're going to download it and we're going to teach our employees how to use something which doesn't have the tools. So the intelligence and the benchmarks may be there, which is fine for someone who knows how to code themselves and someone who's an engineer, but it's not that easy for the employees to actually go through. So I think people have to be very careful about this. I hear this repeatedly and go back to Brad Gerstner's side. This is the largest individual TAM. Will people use open source? 100%. Will most of the token usage be open open source? Yeah, it already is. But what we've seen so far over the last six months, and they talked about this on the all in, the actual enterprises are reducing their open source and going more towards this because that's the way their bureaucracy and everything works. And I think people have who haven't worked for a Fortune 500 company, which I have done, the bureaucracy of getting decisions made, how long it takes to decide on a model, how long it takes takes to decide on software, and then once you do, you have a long term plan. I don't see the Fortune 500 companies in the United States switching to a Chinese model anytime soon.
- [12:06]
Podcast Interviewer
So there's two parts of this that I think are, are interesting and these are just things that we're actively trying to figure out at Sylvia. And so I'm going to use that experience to extrapolate where I think a lot of these companies are probably doing. The first is we recently built and released in the product a model router. So the average consumer that's using Sylvia has no clue that this is happening. They can think of each query previously was going to kind of the highest intelligence, which also is the most expensive model to be able to go compute it. Which is great when you ask a really complex question, but if you ask what is the date? We probably don't need superhuman intelligence to be able to go and answer that question. And so the way the model router works is basically it can use the highest intelligence, most powerful model for really complex things, but it can direct queries to whether it's open source or kind of lower cost, lower compute, intense models for simpler questions. And what I find interesting about the model router is one we already are seeing a positive impact from it. It's, you know, putting some questions over to the, to the less powerful model. What I don't know. And we're actively trying to figure out how many models could you put into the model router? Does it make sense to do it with two or three? Would you do 20 or 30? And I saw Sierra, Brett Taylor's company, I think that they have a blog post from their engineers where they have about 20 different models. That doesn't mean that's the right way to do it, but it does feel like weird way. I agree that the open source model for the average employee is not going to be the thing that they're going to just, you know, put on their computer and all of a sudden start using. But I wonder if some of these companies start to create this, you know, harness and environment and the tools and then they basically just use the models on the back end and the end user doesn't even know what they're using. They just know that hey, this is faster, this is, you know, more accurate. What do you think about that?
- [13:54]
Jordy Visser
I think that's the way it'll go. I don't think there's any question. I think the barriers to doing it right now are hard. There will be companies that make it eas. So you're getting to the point of let's think of the models as outsourced intelligence. So let's just pretend like these are people and you're like, okay, so I have access to these 20 people. Well, you're going to pay the highest price for the most sophisticated things. Where this shows up is that we're in the early stages, the very early stages of the Jevons paradox situation. Adoption is still extremely low and we know that because there hasn't really been any job losses for any of the companies and so far they just haven't been hiring people. I think when we get to that point, the downside to me, which I've always thought is when people extrapolate anthropics ARR and they're like it'll be a trillion dollar. That what we're saying, which I agree with and I don't buy into they're going to be there. I believe AI will disrupt all businesses because intelligence will be commoditized. Now that is not going to hurt anthropic in terms of growing their ARR. But I have believed and I still believe that taking this pace and just because they did it the last three years 10 times, 10 times and they're on pace for 10 times again to get to 100 billion ARR. People are extrapolating and saying, well next year there'll be a trillion. And I do think there's an element of Jevin Paradox. But what you're talking about, and I think what people should see and get. I don't think they're going to get to those numbers. Do I think they could get to 200 next year? Yeah, well that's doubling. That's not 10 times. So with everything in AI, I think what people have to realize, what I said with Micron and with all these places, I think it goes with anthropic as well. Eventually you reach a point where this was a surge out of nowhere, but eventually competition shows up. And you and I have talked about this and I've said it before and I'm saying it more actively as time goes on. Demis Hassabis wrote a piece on AGI. Demis Hassabis is the person that I think is the most level headed of the people who I also think wouldn't say anything unless he was confident that we were getting there. I think Dario Modi, I think Sam Altman they run businesses where they're talking about Sundar Pichai, the Demis. Hassabas doesn't run Google. He has talked about AGI since 2010 and forecasted that it would be around 2030. So he's right on the number. Well, he's now convinced and saying the world is going to change over the next three years and what it means for public companies and private companies. In any company that exists, you don't know if your business will be disrupted by AI, but the probability of that happening rises every day that we get closer to AGI. So we've talked about terminal value, we've talked about how you can't view Adobe and Salesforce past the next three years. I think you're starting to get in debt with all companies and especially with AGI. It even hits the physical companies, the energy companies, the microns, the stuff like that three years from now. So I think that's all coming. And that gets us back to this is the reason why I say Bitcoin is the only thing that has a moat, which is what's an asset. That I don't have to worry about it being disrupted by AI, but I still have to invest. I think every single asset is going to run through a problem where AI is going to run into its mo.
- [17:21]
Podcast Host - Ad Read
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- [18:43]
Podcast Interviewer
What I also find interesting about the open source models versus the American closed source models is everyone is, I think excited about open source allowing you to self host and be able to actually use your data in your environment without having to worry about the zero data retention policies or you know, the big model labs going to take your information and, and train their model or eventually compete with you. The downside though is a lot of what we're seeing with Sylvia and the Chinese open source models is it is not well understood how some of the Eastern world values are incorporated into the weights. And so one aspect that I think is not a conversation really at all, but will become a conversation is this idea of like cultural weights. So if you think of finance maybe as the best example, if you use the generalization of America and the west as capitalist and China and the east, east is more socialist. Well, you obviously want the capitalist responses or that kind of capitalist weight into the model. If you're in the west, we just don't know. Right. It's really hard. I don't see a lot of research there yet. But I do think that just as much as people are worried about, you know, what is the Google algorithm or what is the tick tock algorithm feeding to people, this idea of like these cultural weights is going to become a huge part. And it goes back to your point about these large companies. There's like a technical and user experience barrier that they've got to overcome. But then also, you know, if you're, I don't know, a customer service product and all of a sudden you start sharing, you know, kind of cultural values in response to customers, companies are probably going to get pretty uncomfortable very quickly. And so it just feels like it's not only technical, there's also this other element that is very not understood at the moment that we're going to have to do a lot of work on.
- [20:32]
Jordy Visser
Yeah, and this is why in the end you left one thing out, or I don't know if it's intentional or you guys haven't thought about it with Sylvia, but there is no way that we know for sure that if you host your own model on your own computer that you're safe from people having information from you. And let me make sure people understand why once you start going on The Internet, you're exposed. So if you have this thing sitting someplace and it's contained but you're never accessing it to the Internet. We don't know what backdoor things could be in any of these models to get through. So I've heard people talk about it. I think the naive part is when people get into this, well, I'm not exposed if I use Chemike 2.5 which I have on one of my hardware, I'm not worried about it in the same way, only because I don't have any of my important information on my business in there, but on me going into the Internet or anything like that. If I use agents and they've got credit card information or wallet information, I just don't think we're there. So everything that you said, I think it leads back to the fact that it is very difficult for a U.S. fortune 500 company to not use U.S. frontier models and probably Google, Amazon, Microsoft as the cloud provider in some kind of, you know, cyber related way that they can think about things along with their own cyber. And that's why I think the adoption will continue to go. The reason I said that on the AI side, I'm not worried about where we are and what stocks I want to, I want to be involved in. I said it last week, I'll say it now and I'm going to show it on the weekend video. We have barely entered the agentic world. Barely. Consumer agents are coming. Right now we're at enterprise agents and they're barely being used. And that's why when you go back to Brad Gerstner's line, this is the largest TAM of intelligence that it could be. So if we knew that the number was $20 trillion and that there were six model companies, they're all going to make money. Like in the end they're all going to make money. So getting worried about, you know, will they make any money? Will open source take everything? It's not going to work like that. It's going to be spread out. There'll be lots of different players. Jevons Paradox is in play. Compute demands are everywhere. Everyone's going to get a little piece of the pie. The question is, if you're pricing this stuff really low, like the Chinese models are like Meta is, do you have other ways to make money? Meta is trying to get it through the consumer agent side, through advertising, through a bunch of things with inside their world. Apple's trying to do this with the Gemini model to get Siri in, to get volume going that way, on the hardware side, as well as dominating in, in terms of the personal intelligence side, everyone's in a race to monetize this. I think it's a big pie. I just think the model providers are going to have an uphill battle from here compared to the last two years.
- [23:34]
Podcast Interviewer
Another thing that happened this week that I think is having a big impact on the market is obviously the inflation report. It came in much cooler than I think people were expecting. We also got some comments from Warsh. What was your take on the data? And then his comment stores.
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Jordy Visser
Well, I, I think the most important part, you know, what you and I talked about the last couple weeks and I said probably about three weeks ago that one of the biggest surprises to me with this whole thing in the straight of Hormuz is how people could literally be this wrong on something they had studied for, I don't know, 20, 30 years. If this ever got shot down and we took down 20% of this, what would happen? And the fact that not only did crude oil trade down and obviously we're trading back up now with rekindling and bombing and everything, but the second you stop bombing, we have the next ceasefire. What's going to happen to crude, I can't imagine it doesn't go straight back down. I mean, I don't fall for the trap again, especially when inflation swaps this week actually went down. So two year inflation swaps as of yesterday were actually lower than where we started the week. So we're at the lows. So I think when you go through the inflation data, number one, there's just no way to read it. Unless this month was a fluke. On the core services side, every single inflation data but one PCE core is the only one that's pointing upward. Everything else, whether it's median inflation trimmed mean, whether it's the CPI core, whether it's sticky inflation or whether it's trueflation, they've all come down while the PCE core is at the highs of the year. And so I'm leaning towards the fact that the inflation side is a non story for the rest of the year. Now that being said, with the change in inflation, we reduced the Fed rate hike significantly and I've talked about how I think this is a very big positive for the debasement trade, a very big positive for crypto. We haven't seen it play out yet. We've seen bitcoin act much better during a momentum unwind, which is not normal. But what Warsh said again, he's reiterated he basically the headline for me is this is not a hawkish dovish thing, this is a reform thing. He is fixated on a point that you brought up at the beginning of the year repeatedly, which is we can't trust any data from the government. He believes that the Fed has been very backward looking, which I know, I agree with. I think looking at anything at a time of AI, you know, six months later, when the data gets revised for a long time, how can that be the types of things that you make make decisions on? So I think his message to everyone there is we're in a completely different time. And I think that aligns with AI. He has talked about the fact that AI is very disruptive. He's a big believer in AI. He's also a big believer in digital assets and I don't think people should forget that. So I think monetary policy, the old traditional way, is gone. And the most important thing for people is we've now taken the July rate hike to a 10% chance. So if you believe what the where the expectations are, which is one rate hike before the end of the year, you're kind of saying he's going to raise rates before the midterm elections. And if he was going to do it, I think July would be the time. I don't see him doing it in September. October.
- [26:57]
Podcast Interviewer
One of the aspects to me that feels like it has been exasperated is in my understanding of all of this. Last Sunday I went to the Jay Z concert and while we were there we walked around and I interviewed a bunch of people, which basically just meant I put a microphone in their face and said, you know, why is everything so expensive? If you didn't knew nothing about economics, you had never seen a data point in your life, you would think that every single person is just completely unable to afford anything. Groceries are too expensive, gas is too expensive. We did it the day after the news came out that rent in New York City, the median rents just hit a brand new all time high of like 5,002, 250 bucks or whatever, right at the same time they're at a concert where the tickets are, you know, 500 bucks, 700 bucks, whatever. So like there's a little bit of irony in people who were at this event where the ticket prices are really high, talking about everything so inexpensive. So obviously they got money from somewhere, they know somebody's got money. But the second aspect of it was almost nobody was actually referring to inflation. They were just referring to the aggregate increase in price over the last five or six years. And so what I do wonder is, you know, is there good news on the horizon? It's just going to take a couple of years. Well, that doesn't help politicians at the midterm, but it does feel like so much of the discontent, the, the kind of issues in the actual economy in terms of people's perspective of their real life experience, it's all aggregate price increase. Almost none of it has to do with, you know, the inflation that you and I would think about in terms of the difference between 3.5 or 3.9%.
- [28:33]
Jordy Visser
Yeah, I. So I've thought a lot about this. And, and here, here's my, here's my take. If something bad happens to you, you know, you have a ski accident, you hurt your knee, you get into a car accident for the next five years, that thing is pretty front and center in your brain. I believe what's happened is we can all remember what things cost before COVID Like it's in our head. We remember what the car we bought cost. So every day someone has to just make a decision because cars have some type of lifespan. You're like, you know what, I'm gonna go buy? I'm gonna trade this one and go buy a new car. And I mean, I've run into this recently where I went to go see because I have a model S that I bought in 2021. Well, they're stopping the model S. I'm actually using the full self driving now on my car. And it's an old version. I want the newest version, the car. The cost is up significantly from when I bought in 2021. So my brain remembers what I paid on something. And I think this is one of the things with you, with, with us with COVID Never does inflation go up that much in that short amount of time, not in all of our lifetimes. So normally when inflation goes higher, it's this gradual process. When it happened in the 70s, it was driven by oil prices. And so oil went up, oil went down. This one wasn't that. This was, here you go. Here's trillions of dollars. Everything went up in price. Every single thing went up in price. And so I think we all remember when eggs didn't cost 6$7 a carton. We all remember when XYZ didn't cost this. And I think it takes a long time for that to wear off. But I think when you add in the polarization and the fact that people need someone to blame for this and the fact that AI is standing in front of them, where they don't feel like their job is the way it was. I really think I'm getting to the point now. I agree with you because I grew up in a house where my grandmother told me about the Great Depression all the time about not having money for food being thrown out of her house in her teens to basically they couldn't afford. She had to go out and get a job. She had to go do something and just remembering what the Great Depression was. This is not a. We have the unemployment rate at near all time lows. You can borrow money from anything right now. So I agree with you that I think this is more of a psychological inflation thing. And I think it has a lot to do with just what has happened the last five years.
- [31:00]
Podcast Interviewer
Given Warsh's comments, you know, the first meeting that he really did, a press conference, he didn't say much. This was a little bit more robust in commentary. Did you change your mind at all about how you're thinking about him as the leader of the central bank or actions he may take?
- [31:16]
Jordy Visser
No, I actually, I think he's the right person for the job because I do think the most important thing for this current Fed chair to be is young enough to understand the importance of AI, which I don't think Jerome Powell had. They didn't even pay attention to AI, honestly until like the 4th, 3rd, 4th quarter of last year, at least from what they said publicly. The second thing is I think it needs to be more of a market person and less of an academic. And I think that's another important part that Warship worked at. Morgan Stan, like Warsh has a background in capital markets in the same way that Bessant does. So you have Besson and him involved right now in the market at a very important time for people not focused on digital assets. And again, this is. You're going to be hearing me talk about this a lot more. I mean, our, our lives are crossing over to a very important point starting there because you know, everything I'm starting to do in my video is related to what's going to happen for me in the second, the final four months of the year when I get out of Maine. I mean, I'm very focused on the rise of agents and what Bessant and Warsh are talking about, which is the importance of the United States of America being the leaders of the financial guardrails not losing the benefit that they admit has been a huge benefit for the world, which is the reserve currency of the world. Swift, all of these different things. Digital assets are a Major part of it. And the growth that's happening in prediction markets, the growth that's happening in real world assets and tokenization, the news we saw this week on tokenization, all of this stuff is happening. And so I think Kevin Warsh is the right person at a major inflection point that very few people on Wall street that are on the hedge fund world are fully embracing yet. I think they're realizing they have to. And with AI now being in a massive volatility spike, I think now we're going to start to see some money looking for new beta and I think that's where Kevin Warsh is going to be a big asset. So I'm very happy with the reform that's going to happen on all these fronts related to AI.
- [33:25]
Podcast Interviewer
The second that inflation starts to cool and interest rate hike odds start to come down, I think a lot of people look at something like Bitcoin and try to understand how is that reacting and what is that telling us about the future. Seems like Bitcoin had a pretty strong bid this week. What was your read on that?
- [33:44]
Jordy Visser
Yeah, I'm actually going to take it a different direction. I, I don't, I mean I know bitcoin is, is, is more of your focal point. Ethereum's had the big move. It's up as of yesterday's close or let's say, yeah, since it doesn't close as of yesterday's equity close, it was up close to 20% month to date. And just so people understand, that would be if we finish the month with 20%, the largest month or the best month. Since August of last year, Ethereum has outperformed Bitcoin. It's been the largest on a cross versus Bitcoin since then. The reason I care so much about Ethereum is because I do believe if AI agents are coming, if tokenization is coming, if all these things are happening, this is an energy with inside the revenue side of crypto and there's no way to get around what's happening volume wise. I think the stripe bid for PayPal was a big deal too. I have my crypto 40 name equal weight basket similar to my AI thematic one meant to deal with the agentic world and PayPal was one of the names in it. And so number one, I was happy. I've done my homework and figured out which public companies because there's six of them that are in there, including Robinhood, how they all fit in with this crossover with the AI agents. But I think bitcoin, Bitcoin is just Hanging in there very well. On a relative basis it's obviously done well versus AI. But the AI thematic side or the the factor side, the volume's up towards 100. Bitcoin volume is still at 30. So if you're putting an asset in a portfolio right now you can have three times as much Bitcoin on a volume adjusted basis as you can AI. And that means that we're at a point where I think you should start seeing more and more people as they get more focused on Ethereum. Get in. Once we get above the 200 day moving aver believe we are at the start of something new until we are above there. I'm trading it actively. I'm trying to make sure that if a bottom is made here, it's there. I even put little started to buy a little bit of Micron this week and some of the semis Micron I have a position again it's very small relative to what it was back then and I'm buying it at higher prices than where I ended up selling it on average. But that's because the new news that has come out over the course of the last six weeks and the consolidation and the deleveraging that's happen I feel more confident in terms of putting a little bit little bit of money in there. But I'm still much more heavily weighted towards crypto.
- [36:14]
Podcast Interviewer
When you think of the crypto allocation, is it just Bitcoin and Ethereum?
- [36:19]
Jordy Visser
For me at this point it's Bitcoin, Ethereum and Microstrategy. So I'm not, I don't think from. I'm sure this will change as I spend more time in the space. I've never been a big stock person as a macro person it's been thematic. So even though Micron is in the portfolio, if you ask me why it's because of AI. Everything I have in the portfolio to me is either an AI trade or it's a crypto trade. And so that's it. I really Eli Lilly it's an AI trade Silver, it's an AI trade. Anything I have in the portfolio is related to the stuff that I write about and I talk about. I believe we are at the convergence between AI and crypto and that all public companies will be disrupted the same way Adobe and Salesforce have been same way the hyperscalers had. They just rallied off the bottom. That's why the S and P's hanging around the all time highs while AI trades lower. But over the last nine months they haven't done anything so again, when you go through things, I'm just more focused on the AI infrastructure, trade. Once the agentic side starts to accelerate, once AGI gets here, I believe the ROIC is headed towards private companies. I believe small private businesses are going to be the winners of this. The enterprises will find a way to reduce their expenses over the next two years. We are seeing that happen inside the public companies. If you haven't seen it so far. About 40 of the S P 500 companies have reported so far and just like happened in Q1, the surprise ratio. Right now we're, we're outperforming earnings. It's been 16% in terms of the beat. So we're again headed towards another big, big, big month, big, big quarter for earnings. And a lot of these have happened in the banks and in insurance companies.
- [38:10]
Podcast Host - Ad Read
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- [40:23]
Podcast Interviewer
What are the areas that you're actively avoiding? We talk a lot about where you're putting capital. Is there any areas that you see maybe people talking about that you're more nervous about?
- [40:32]
Jordy Visser
I, I still have no interest in, in SaaS seat based software. So you know, a lot of people are trying to pick bottoms in, in that. Aside from that, I, I think you're going to get a lot of sectors that are S P500 related. The things that I mentioned like I think between now and the end of the year at these levels, regardless of whether Micron sells off another 20%, I don't see how the memory trade, the earnings don't grow and how the S and P doesn't go higher. So that's one of the things, when people get worried about things, they extrapolate a fall in a certain stock market to something else. So you've heard a lot of people talk about the debt side. Oh, this is unbelievable. The debt's going to go and I want to make people feel very, very comfortable about this. One of the reasons I care so much about crypto is because of the budget deficit. We still have a deficit of 5 to 6%. So again, the government is spending 5 to 6% a year more than they're getting in receipts. The printing press is still happening, meaning this is good for nominal gdp. At the same time, the government is in a race against China. So they're going to make sure this AI trade works. They're going to do whatever is necessary. If the funding markets, if we see long term rates go higher, they got to do something because they can't lose to China on this. And China just gives money and opens up things In a very different way. So I'm very fixated on the capex is going to happen. AI is going to continue to accelerate. The companies that people are worried about, the hyperscalers, their debt to equity, it's nothing. So unless their stock price falls violently, they have tons of ability to raise capital. They have $2 trillion of RPOs still sitting there. And again, so people understand, I've never understood over the next two years if they took debt for all of the capex we're talking around $2 trillion. Well there's $2 trillion between Amazon, Microsoft, Google and Oracle contracted for the compute. So again we already have demand for this stuff and these guys are going to have money to go through it. So I'm not worried about the debt, I'm not worried about that. So I think people should be focused on the areas that are going to have a beta associated with them and I'm going to stick with AI infrastructure, all the names that I've mentioned, plus the crypto side. So I'm more focused on the beta. But if you want to just go buy the S and P I think you're going to get great returns in the S and P for at least the next couple years as well.
- [43:08]
Podcast Interviewer
What about the Nasdaq?
- [43:11]
Jordy Visser
The Nasdaq has a beta side associated with I think is, is, is good. You can, you know, if you're going to buy S and P I think you're generally going to get more on there. The area on, on the Nasdaq that I'm most interested in is, is probably biotech at this point. The good thing about the Nasdaq it is obviously heavily weighted towards the Mag 7 which is a negative but the reason that it still has outperformed is because it's not a pure cap weighted side. So you're not overly weighted towards it in there and I think there are a lot of areas with inside the NASDAQ which will do well. But I, I, I'm not sure they're going to be able to outperform the S and P in a big way. I got asked the question which I think was a good question. There's a lot of people have talked about the fact that this won't end until we have a true bubble and they talk about it like the dot com bubble where Cisco is trading at 100 PE and that we're still in the early stages and the people who are bullish I want to take them a different direction on this because when I was asked the question what do I think on it. And I said, number one, demographics are completely different than the dot com bubble, the money being made. You know, with the baby boomers in this, they were still working, they were still taking risk. Now they're passive investments. They've got advisors, they're playing on the golf course, they're not sitting out there gambling. Plus they've made so much money, they're not trying to make money the same way. There's obviously active traders that are doing it. That's fine. But then the other element, that to me is very different and I think that's something people have to get involved in. It gets back to this concept that if in three years we have AGI, at some point the stock market is going to start saying, hey, all businesses are going to be disrupted. I don't think people realize what that means. One of the reasons that oil stocks basically really never go higher in a major way and see multiple expansion is because it's dependent on the price of oil. So if oil stays at $60 forever or if natural gas stays at $3 forever, how's a company that generates their revenues based on the underlying asset moving actually going to get there? Well, I think if tokens are commoditized to zero, they don't hurt the model companies necessarily. But I think what they do do is they make it easier for AI native people to compete with all public companies because the inability for public companies to embrace AI and make it work is going to be much more challenging. So I only bring that up. I think the market is going to go through multiple compression. So I think earnings are going to be great. I think the S and P is going to grow less than earnings like we've seen so far this year. And I think that's going to be a trend at some point in the next three years. I actually believe that multiple compression story will become a much bigger story.
- [46:07]
Podcast Interviewer
Yeah, it's, it's going to be fascinating, I think, to watch this play out because part of what you mentioned earlier I think is underrated. I see a lot of people trying to pick bottoms in SAS software. And I think that you have held steady on a view that AI is going to have a significant impact on those businesses. And it's more of a structural change than a, than kind of a sell off that is somewhat temporary
- [46:34]
Podcast Host - Ad Read
and it
- [46:35]
Podcast Interviewer
does feel like AI now. Like I don't hear anyone saying AI is not going to be valuable or AI doesn't work. Right. You know, three years ago I heard a lot of like, oh, I talked to the the chat bot. And it was stupid. It, you know, it lied to me type stuff, right? That, that conversation's gone now. What I hear a lot is like, who are the winners going to be? How big can can the winners be? How profitable can they be? What's the impact of Chinese Open? You know, we're in the nuance now. And so I take that as is, everyone is convinced this is real. But I think that the one area I still, and I did some of the math with Sylvia this week, a very large portion of my portfolio is exposed to physical AI and robotics. And it just feels like, you know, the software side of AI has now we've gotten so into the weeds because everyone is looking there, that the next big kind of move of capital within the AI trade will be that robotics hopefully. You know, at least that's what betting on. Do you have any exposure there? Are you thinking at all about the, the robotic stuff?
- [47:42]
Jordy Visser
So first of all, in this past weekend's video, I, I put up a chart and I got, I got a lot of good responses from people on it, which was, and I don't think you and I have talked about this. When people want to compare the AI situation, yes, the dot com bubble would come up a lot. But the other thing that comes up that I think it's both more recent, but I think people are thinking about it the right way is they bring up fracking and what happened to all of those companies. Now the reason I bring it up here, oil demand at the end of the day is driven by people. And that's why it grows with nominal gdp. So it's a function of how many more people are on the planet. How much money do those people have to spend? Are they using more energy? Like that's pretty much what drives the majority of energy price. And that's why if you ask any oil person, so how much does oil demand go up a year? Well, what's nominal gdp? Nominal GDP is the answer. The problem with that is eventually with fracking technology made the supply side go exponential. It actually outpaced what happened with the demand side. So if the demand side stays linear and all of a sudden we get a technology that changes the supply side, well, then we end up in a situation we're in which is no matter what seems to happen with oil, it ends up going back down. And we probably don't know, like with Hormuz, how much was shifted to natural gas. We have endless natural gas. All of these different things have clearly changed. The problem in what you're Bringing up. And the reason I'm so focused on the infrastructure side, we haven't reached a point yet where we can change the supply side of what's necessary for this build out out, because we haven't been focused on it. That's why I say Micron was the same price in 2017. You know what companies don't do when their stock price doesn't rise for seven years? They don't build new capacity. They don't have it. So that's why I'm convinced that on the memory side, when you haven't built the capacity for any of this stuff, it's not there for robotics. It's the same thing. So you have exponential demand for tokens. Tokens are driven by computers, they're driven by digital employees. They have nothing to do with human beings. The reason they're going parabolic is because you just put your computer on overnight and you say, okay, do this job for the rest of the day. What you're doing at Sylvia, if you go through your token usage, it's not just the cost that's going higher, your usage is going higher too. As you grow more people, as you guys build more systems, as you have more agents, it'll just use more and more tokens. It never goes down. And so until we get the supply side to move up on an exponential to match off the exponential, exponential demand. This is something we haven't seen before. And this is why whenever I say it, I'm like, guys, you're missing the point. Like, when consumer agents come, we're going to need a lot more tokens. When humanoids come, we need a lot more tokens. When FSD comes, we need a lot more tokens. So the way I'm playing the robotic side right now is the AI structure trade, it's a semiconductor trade. What is Elon Musk doing for the robotics trade? He's building Terrafab because we don't have enough chips. So eventually, and I'm sure I will start buying some of these robotics things because I do think the next trade is embodied AI. Because you said with software. I don't want to fight this battle with software names. It's going to continually be an issue.
- [51:05]
Podcast Interviewer
I. I completely agree. I appreciate your time today. The audience loves hearing from you. We'll do it again next week.
- [51:12]
Jordy Visser
All right, bud, have a good one.