# Bitcoin's Next Move Depends On One Fed Decision

https://www.youtube.com/watch?v=fEnq13uJBD0

[00:00] But the AI thematic side or the factor side, the V's up towards 100.
[00:04] Bitcoin V is still at 30.
[00:07] So if you're putting an asset in a portfolio right now, you can have three times as much uh Bitcoin on a V adjusted basis as you can AI.
[00:16] 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 uh get in once we get above the 200 day moving average.
[00:25] I believe we're at the start of something new.
[00:27] What's going on, guys?
[00:29] Today we got a great conversation with Jordy Visser.
[00:31] In this conversation, we talk about all the deleveraging happening in the stock market, why the midcycle slowdown in AI may be impacting your portfolio.
[00:39] We also get into what's going on with inflation and Kevin Worsh'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.
[00:49] Here's my latest conversation with Jordi Visser.
[00:51] All right, Jordy, I thought we could start the conversation.
[00:53] It seems like there's a big unwind happening in the public market, specifically around a lot of the AI names.
[00:57] You started talking quite a bit about uh this like summer slowdown and
[01:01] How that may affect things.
[01:03] What are you seeing?
[01:05] Yeah, it's, it's uh, this is probably going to be uh a fairly high level um discussion.
[01:13] I'm going to get a little wonky with the leverage side, but I think um people are going to have to get used to this.
[01:23] So, what's happening is the S&P is making new all-time highs or equal weight S&P's making new all-time highs.
[01:27] Breath is making new all-time highs.
[01:29] The AI names are going down.
[01:32] So, a lot of people are sitting there seeing their Micron go down and their Marll go down and they're go through the list of all of the names.
[01:42] Every single name, Caterpillar, modin, everyone that's been let's say going up fairly fast is giving back some of that now.
[01:50] Some of that is related to just what I talked about, which is the AI midcycle slowdown is the second derivative change and Nvidia went through this back in 2024 and I highly.
[02:02] Recommend everyone go back and look.
[02:04] Because from Chat GPT to about June of '24, Nvidia went up 12 times.
[02:13] So very similar to, let's say, Micron going from 100 to 1200.
[02:18] Since that period in June of '24, Nvidia's earnings have continued to grow.
[02:21] They've continued to dominate the AI trade, but in 2 years they've now gone up 48%.
[02:30] Good returns.
[02:32] I mean, you're getting 20-plus percent returns.
[02:33] You're outperforming the S&P, but it's not the 12 times that happened.
[02:38] And that's where we are in AI right now for all of these names.
[02:44] Um, meaning most of them had three to 10 times type moves, especially the semiconductor names, which mean they've built in a lot of the next two years.
[02:53] And I think what the market is going through is this second derivative, where when you look at the earnings of these companies, you're like, "Oh my god, they're up 400%, 500%."
[03:01] But then a year from now, they're only going to be...
[03:02] Up 30%, 40%.
[03:03] So you're decelerating.
[03:06] So that's the first part is I think the market is coming to term with the AI midcycle slowdown.
[03:11] And the other thing I wrote about which is the fireworks show.
[03:13] The under the hood story is that there is absolutely a deleveraging happening.
[03:21] And I want to use again a bunch of comparisons.
[03:25] So silver and gold were up massively last year.
[03:27] They had a drawdown, the biggest drawdowns they've ever seen in 30 years on different time horizons that were all within 20 days.
[03:36] The momentum factor for technology has seen an unprecedented move lower.
[03:42] I've posted an X about it.
[03:45] 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 multistrat market neutral hedge fund or it's a systematic quant strategy.
[04:01] And we've seen reports and numbers.
[04:04] Released from the prime brokers of just very large losses in a short amount of time.
[04:07] And because the volatility has gone higher, whether it's risk par, 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 V targeting, but it also means that that position when it starts to come back cannot be as big.
[04:25] 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 200 and back down to 800 as of early this morning.
[04:33] You've given back now depending on the name 30 to 50%.
[04:39] 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.
[04:46] But like silver, like gold and another one like Bitcoin after October 10th, these things have not come back yet.
[04:55] So their V may have come down, but those things have been on the downside and they haven't gone back.
[05:01] The difference is with the AI trade, they were significantly above their 200 day moving.
[05:05] Average.
[05:05] And so everyone hears this.
[05:07] Many of these names like Micron, they were unchanged for years.
[05:12] Micron was the same price at at liberation day lows that it was in 2017.
[05:17] So, a lot of these were breaking out of long-term ranges, they're way above their 200 day moving average.
[05:24] I think somewhere between this 30 and 60% retracement.
[05:27] They're going to hang in there and they'll start to move higher again, but I think the fireworks show is over.
[05:33] 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, but not quickly.
[05:40] Uh, and not something that's going to just turn into a, oh, that was no problem.
[05:43] It was something real, and it's about leverage.
[05:46] Do you have a framework for identifying which are the ones that will do well and which ones won't?
[05:50] Well, what I'm going through and I I wrote a paper um about memory.
[05:54] I think memory is the most important part of the AI trade.
[06:00] Uh I am focused on companies that are have not yet seen their step up function in earnings.
[06:02] So in the case of
[06:05] Nvidia, when it peaked in 2024 from a 12-bagger, one thing started to happen, which is they started to only beat earnings by a little bit.
[06:15] 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.
[06:23] Memory obviously blew away numbers.
[06:25] So far, we've seen Micron blow away numbers.
[06:27] We've seen Samsung blow away numbers.
[06:29] We've seen ASML blow away numbers, and all the stocks traded lower.
[06:34] Um, so the semiconductors are going to be fine, but memory is the place that I'm going to be focused on.
[06:39] And then I'm writing a very long piece, or I did write it, which I'll release on my paywall this weekend about Vera Rubin.
[06:46] And Vera Rubin is another area where there's certain names in there which haven't seen the step-up function in earnings yet.
[06:52] That is going to be the thing that drives it: you're going to need to beat earnings significantly.
[06:57] 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.
[07:04] So, I think.
[07:06] Everyone's going to have to now do some homework.
[07:07] Um, 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.
[07:15] 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.
[07:24] Maybe a third was trying to enter the fray in terms of Grock.
[07:28] Um, but we just got the Kimmy K3 release and this is a Chinese open-source model.
[07:34] Um, it seems to be performing as well, if not better than Fable or any of the latest closed source American models.
[07:41] 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?
[07:49] No.
[07:51] And this is a good time to bring this up.
[07:54] Um, so I wrote a paper this week on Brad Gersonner's interview.
[07:56] Uh, on well it wasn't an interview, he was a guest on the allimpod and on that every answer he gave on this to me was
[08:08] Very balanced.
[08:10] It kind of went through the pros and cons of all these stories,
[08:15] But the comment that I really focused on the most, which I think people have to understand,
[08:18] This is the largest TAM that will ever exist, at least on planet Earth.
[08:25] We'll see if the TAM in space will actually be something that happens.
[08:29] But that TAM is about intelligence, and intelligence will drive revenues.
[08:33] It will drive compute demand.
[08:35] So, here's the thing with open-source and with the Frontier models right now.
[08:43] If I wanted to use Kimmy K 3.0, I couldn't do it.
[08:46] Neither could you unless you had the hardware.
[08:48] There's no way to use it.
[08:50] Meaning, could an enterprise use it?
[08:52] Yeah.
[08:52] So, it's isolated right now to people that have enough hardware to use it.
[08:57] There's no way to even get the hardware.
[08:58] You have to have GPUs to be able to run it.
[09:00] Like, this is a big model.
[09:02] That's the only way it competes with the Frontier.
[09:04] If you want to use Anthropic, you just go onto the cloud and you go use it.
[09:07] So there is
[09:10] This element of well who's going to be the people that use it.
[09:12] Will developers use it?
[09:15] Yeah, they probably will.
[09:17] Um, they're trying to reduce cost.
[09:19] So AI native businesses are going to have a huge advantage.
[09:23] Will an enterprise company in the United States of America use a Chinese open source model?
[09:27] Maybe over time.
[09:30] Um, but they're trying to get adoption from the humans plus the agents.
[09:33] Humans need co-work.
[09:37] Humans need all of these things and they get used to using a model.
[09:41] So, you just can't keep swapping out every time there's a new model, it's not that easy.
[09:46] 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?
[09:57] I'm going to get rid of Fable 5 and anthropic and I'm going to move to this Chinese model.
[10:01] We're going to download it and we're going to teach our employees how to use something which doesn't have the tools.
[10:07] So the intelligence and the benchmarks may be there which is fine for someone who
[10:12] Knows how to code themselves and someone who's an engineer but it's not that easy for the employees to actually go through.
[10:19] So I think people have to be very careful about this.
[10:21] I hear this repeatedly and go back to Brad Gersonner's side.
[10:25] This is the largest individual TAM.
[10:27] Will people use open source?
[10:29] 100%.
[10:32] Will most of the token usage be open source?
[10:35] Yeah, it already is.
[10:37] But what we've seen so far over the last 6 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.
[10:49] And I think people who haven't worked for a Fortune 500 company, which I have done, [gasps] the bureaucracy of getting decisions made, how long it takes to decide on a model, how long it takes to decide on software, and then once you do, you have a long-term plan.
[11:04] I don't see the Fortune 500 companies in the United States switching to a Chinese model anytime soon.
[11:10] So, there's two parts of this that I think are interesting.
[11:13] These are just things that we're actively uh trying to figure out at Sylvia.
[11:18] And so I'm going to use that experience extrapolate where I think a lot of these companies are probably doing.
[11:24] The first is um we recently built and released uh in the product a model router.
[11:29] So the average consumer that's using Sylvia has no clue that this is happening but um they can think of uh 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 you know 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 query to whether it's open source or kind of you know lower cost lower compute uh intense uh models for simpler questions and what I find interesting about the model router is one we already are seeing a positive impact from it and it's you know putting some questions over to the to the less powerful model.
[12:14] What I don't know, and we're actively trying to figure out, how many models could you put into the model router?
[12:19] Does it make sense to do it with two or three, would you do 20 or 30?
[12:24] And I saw Sierra, um, Brett Taylor's uh company.
[12:27] I think that they have a blog post from their engineers where they have about 20 different models.
[12:32] That doesn't mean that's the right way to do it, but it does feel like, in a weird way, um, 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.
[12:45] 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.
[12:53] They just know that, hey, this is faster, is, you know, more accurate.
[12:56] What do you think about that?
[12:57] I think that's the way it'll go.
[13:00] Um, I don't think there's any question.
[13:01] I think the barriers to doing it right now are hard.
[13:06] Um, there will be companies that make it easier.
[13:08] So, you're getting to the point of let's think of the models as outsourced intelligence.
[13:13] So, let's just pretend like these are
[13:15] People and you're like, "Okay, so I have access to these 20 people."
[13:20] Well, you're going to pay the highest price for the most sophisticated things.
[13:23] Where this shows up is that we're in the early stages, the very early stages of the Jevans paradox situation.
[13:34] 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.
[13:44] I think when we get to that point, the downside to me, which I've always thought, is when people extrapolate anthropics arr 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.
[13:57] I believe AI will disrupt all businesses because intelligence will be commoditized.
[14:05] Now, that is not going to hurt Anthropic in terms of growing their ARR.
[14:10] But I have believed and I still believe that taking this pace and just because they did it the last 3 years 10
[14:16] Times 10 times and they're on pace for 10 times again to get to a 100 billion ARR.
[14:22] People are extrapolating saying, well, next year there'll be a trillion.
[14:25] And I do think there's an element of je 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.
[14:35] Do I think they could get to 200 next year?
[14:38] Yeah.
[14:38] Well, that's a doubling.
[14:41] That's not 10 times.
[14:41] 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.
[14:49] Eventually, you reach a point where this was a surge out of nowhere, but eventually competition shows up.
[14:55] 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.
[15:02] Deosabis wrote a piece on AGI.
[15:04] Demesis Sabis is the person that I think is the most levelheaded of the people who I also think wouldn't say anything unless he was confident that we were getting there.
[15:14] I think Dario Modai, I think Sam Alman, they run businesses.
[15:16] where they're talking about Sundar Pachai the Deisabas doesn't run Google
[15:22] he has talked about AGI since 2010 and forecasted that it would be around 2030.
[15:27] So he's right on the number.
[15:29] Well, he's now convinced and saying the world is going to change over the next three years.
[15:35] And what it means for public companies and private companies and 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.
[15:49] So, we've talked about terminal value.
[15:51] We've talked about how you can't view Adobe and Salesforce past the next 3 years.
[15:56] I think you're starting to get into that with all companies and especially with AGI.
[16:00] It even hits the physical companies, the energy companies, the microns, the stuff like that 3 years from now.
[16:05] So, I think that's all coming.
[16:06] 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.
[16:16] I think
[16:18] Every single asset is going to run through a problem where AI is going to run into its moat.
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[17:47] What I also find interesting about the open-source models versus uh 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 are the big model labs going to take your information and train their model or eventually compete with you.
[18:10] 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
[18:20] Values are incorporated into the weights.
[18:25] 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.
[18:32] So if you think of finance maybe as the best example, if you use the generalization of America in the west is capitalist and China in the 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.
[18:50] We just don't know, right?
[18:51] It's really hard and 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 Tik Tok algorithm feeding to people, this idea of like these cultural weights is going to become a huge part.
[19:04] 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.
[19:12] But then also, you know, if you're, I don't know, a customer service uh uh product and all of a sudden you start sharing, you know, kind of cultural values in response to
[19:22] Customers, companies are probably going to get pretty uncomfortable very quickly.
[19:25] And so it just feels like it's not only technical, there's also this other element that um is very uh not understood at the moment that we're going to have to do a lot of work on.
[19:35] Yeah.
[19:37] And this is why in the end I you you left one thing out uh or I don't know if it was 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.
[19:56] And let me let me let me let me make sure people understand why.
[20:00] Once you start going on the internet, you're exposed.
[20:03] 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 to get through.
[20:14] So I I've I've heard people talk about it.
[20:17] I I think the naive part is when people get into this, well, I'm not exposed.
[20:19] If I use ChemK 2.5, which I
[20:23] have on one of my hardware, I'm not
[20:25] worried about it in the same way only
[20:27] because I don't have any of my important
[20:30] information on my business in there. But
[20:33] on me going into the internet or
[20:35] anything like that, if I use agents and
[20:37] they've got credit card information or
[20:39] wallet information, I just don't think
[20:41] we're there. So I everything that you
[20:43] said I think it leads back to the fact
[20:46] that it is very difficult for a US
[20:49] fortune 500 company to not use US
[20:52] frontier models and probably Google,
[20:56] Amazon, Microsoft as the cloud provider
[21:00] in some kind of you know uh cyber
[21:04] related way that they can think about
[21:06] things along with their own cyber and
[21:08] that's why I think the adoption will
[21:10] continue to go. Um, the reason I said
[21:12] that on the AI side, I'm not worried
[21:15] about where we are and what stocks I
[21:16] want to I want to be involved in. I said
[21:18] it last week, I'll say it now, and I'm
[21:20] going to show it on the weekend video.
[21:22] We have barely entered the agentic
[21:25] world. Barely. Consumer agents are
[21:27] coming. Right now, we're at enterprise
[21:29] agents and they're barely being used.
[21:31] And that's why when you go back to Brad
[21:32] Gersonner's line, this is the largest
[21:35] TAM of intelligence that it could be. So
[21:39] if we knew that the number was $20
[21:42] trillion and that there were six model
[21:45] companies, they're all going to make
[21:47] money. That like in the end they're all
[21:50] going to make money. So getting worried
[21:51] about, you know, will they make any
[21:53] money? Will open source take everything?
[21:56] It's not going to work like that. It's
[21:57] going to be spread out. There'll be lots
[21:58] of different players. Jevans paradox is
[22:01] in play. Compute demands are everywhere.
[22:03] Everyone's going to get a little piece
[22:05] of the pie. The question is, if you're
[22:06] pricing this stuff really low, like the
[22:09] Chinese models are, like Meta is, do you
[22:12] have other ways to make money? Meta is
[22:14] trying to get it through the consumer
[22:15] agent side, through advertising, through
[22:17] a bunch of things with inside their
[22:18] world. Apple's trying to do this with
[22:21] the Gemini model to get Siri and to get
[22:23] volume going that way. On the hardware
[22:25] side, as well as dominating in in terms
[22:28] of the personal intelligence side,
[22:30] everyone's in a race to monetize this. I
[22:32] think it's a big pie. I just think the
[22:34] model providers are going to have an
[22:35] uphill battle from here compared to the
[22:36] last two years.
[22:38] Another thing that happened this week
[22:39] that I think is having a big impact on
[22:41] the market is obviously uh the inflation
[22:43] report. It came in much cooler than I
[22:45] think people were expecting. U we also
[22:47] got some comments from Worsh. What was
[22:49] your take on the data and then his
[22:50] commentary afterwards?
[22:53] Well, I I think the most important part
[22:55] um you know what you and I talked about
[22:57] the last couple weeks and I said
[22:59] probably about three weeks ago that one
[23:03] of the biggest surprises to me with this
[23:04] whole thing in the straight of horn
[23:06] moves is how people could literally be
[23:09] this wrong on something they had studied
[23:11] for I don't know 20 30 years. If this
[23:14] ever got shot down and we took down 20%
[23:17] of this what would happen? And the fact
[23:19] that not only did crude oil trade down
[23:21] and obviously we're trading back up now
[23:23] with rekindling and bombing and
[23:25] everything, but
[23:27] the second you stop bombing, we have the
[23:29] next ceasefire, what's going to happen
[23:30] to crude? I can't imagine it doesn't go
[23:32] straight back down. I mean, I I don't
[23:33] fall for the trap uh again, especially
[23:36] when inflation swaps this week actually
[23:39] went down. So 2-year inflation swaps as
[23:42] of yesterday were actually lower than
[23:44] where we started the week. So we're at
[23:46] the lows. So I think when you go through
[23:48] the inflation data, number one,
[23:51] there's just no way to read it. Unless
[23:52] this month was a fluke on the core
[23:55] services side,
[23:58] every single inflation data but one, PCE
[24:00] core is the only one that's pointing
[24:02] upward. everything else, whether it's
[24:04] median uh inflation, uh trimmed mean,
[24:09] whether it's the CPI core, whether it's
[24:12] sticky inflation, or whether it's true
[24:14] inflation, they've all come down while
[24:16] the PC core is at the highs of the year.
[24:19] And so, I'm leaning towards the fact
[24:21] that the inflation side is a non-story
[24:24] for the rest of the year. Now, that
[24:26] being said, with the change in
[24:28] inflation, we reduced the Fed rate hike
[24:30] significantly. And I've talked about how
[24:32] I think this is a very big positive for
[24:34] the debasement trade, a very big
[24:35] positive for crypto. We haven't seen it
[24:38] play out yet. We've seen Bitcoin act
[24:40] much better during a momentum unwind,
[24:42] which is not normal. But what Wars said,
[24:44] again, he's reiterated,
[24:46] he basically the headline for me is this
[24:48] is not a hawkish dovish thing. This is a
[24:51] reform thing. He is fixated on a point
[24:54] that you, you know, brought up at the
[24:56] beginning of the year repeatedly, which
[24:58] is we can't trust any data from the
[25:00] government. He believes that the Fed has
[25:03] been very backward-looking, which I know
[25:05] I agree with. I think looking at
[25:07] anything at a time of AI, you know, 6
[25:10] months later when the data gets revised
[25:12] for, you know, a long time, how can that
[25:15] be the types of things that you make
[25:17] decisions on? So, I think his message to
[25:20] everyone there is we're in a completely
[25:22] different time and I think that aligns
[25:23] with AI. He has talked about the fact
[25:25] that AI is very disruptive. He's a big
[25:27] believer in AI. He's also a big believer
[25:29] in digital assets. And I don't think
[25:31] people should forget that. So I think
[25:32] monetary policy the old traditional way
[25:35] is gone. And the most important thing
[25:37] for people is we've now taken the July
[25:39] rate hike to a 10% chance. So if you
[25:43] believe what the um where the
[25:46] expectations are, which is one rate hike
[25:48] before the end of the year, you're kind
[25:50] of saying he's going to raise rates
[25:52] before the midterm elections. And if he
[25:55] was going to do it, I think July would
[25:57] be the time. I don't see him doing it in
[25:58] September, October.
[26:00] One of the aspects to me that um feels
[26:05] uh like it has been exasperated in my
[26:08] understanding of all of this. Last
[26:10] Sunday I went to the Jay-Z concert and
[26:12] while we were there we walked around and
[26:14] I interviewed a bunch of people which
[26:15] basically just meant I put a microphone
[26:16] in their face and said, you know, why is
[26:18] everything so expensive?
[26:20] If you did knew nothing about economics,
[26:22] you had never seen a data point in your
[26:23] life, you would think that every single
[26:25] person is just completely unable to
[26:29] afford anything. Groceries are too
[26:31] expensive, gas is too expensive. We did
[26:32] it the day after the news came out that
[26:34] rent in New York City, uh, the median
[26:36] rents just hit a brand new all-time high
[26:38] of like 5,250
[26:40] bucks or whatever, right?
[26:43] At the same time, they're at a concert
[26:45] where the tickets are, you know, 500
[26:47] bucks, 700 bucks, whatever. So like
[26:48] there's a little bit of irony in people
[26:50] who were at this event where the ticket
[26:52] prices are really high talking about how
[26:53] everything's so unexpensive. So
[26:54] obviously they got money from somewhere
[26:55] or they know somebody who's got money.
[26:57] But the second aspect [clears throat] of
[26:59] it was almost nobody was actually
[27:01] referring to inflation. They were just
[27:04] referring to the aggregate increase in
[27:05] price over the last 5 or 6 years. And so
[27:08] what I do wonder is, you know, is there
[27:10] good news on the horizon? It's just
[27:13] going to take a couple of years. Well,
[27:14] that doesn't help politicians at the
[27:15] midterm. But it does feel like so much
[27:19] of the discontent, the the uh kind of
[27:21] issues in the actual economy in terms of
[27:24] people's perspective of their real life
[27:26] experience, it's all aggregate price
[27:28] increase. Almost none of it has to do
[27:30] with, you know, the inflation that you
[27:32] and I would think about in terms of the
[27:33] difference between 3.5 or 3.9%.
[27:37] Yeah. I So, I've thought a lot about
[27:39] this and and
[27:42] here here's my uh here's my take.
[27:46] If something bad happens to you, uh, you
[27:50] know, you have a ski accident, you hurt
[27:52] your knee, you get into a car accident,
[27:55] for the next 5 years,
[27:58] that thing is pretty front and center in
[28:00] your brain. [clears throat] Um, I
[28:03] believe what's happened is we can all
[28:05] remember what things cost before co like
[28:07] it's in our head. We remember what the
[28:11] car we bought cost. So, every day
[28:13] someone has to just make a decision
[28:15] because cars have a some type of
[28:17] lifespan. You're like, you know what?
[28:18] I'm going to go buy I'm I'm going to
[28:19] trade this one and go buy a new car. And
[28:22] I mean, I've run into this recently
[28:24] where I went to go see because I have a
[28:26] Model S that I bought in 2021. Well,
[28:28] they're they're stopping the Model S.
[28:31] I'm actually using the full self-driving
[28:32] now on my car and it's an old version. I
[28:35] want the newest version. The car the
[28:37] cost is up significantly from when I
[28:39] bought it in 2021. So my brain remembers
[28:42] what I paid on something. And I think
[28:44] this is one of the things with you with
[28:46] with us with COVID. Never does inflation
[28:49] go up that much in that short amount of
[28:51] time. Not in all of our lifetimes. So
[28:53] normally when inflation goes higher,
[28:55] it's this gradual process. When it
[28:57] happened in the 70s, it was driven by
[28:59] oil prices. And so oil went up, oil went
[29:02] down. This one wasn't that. This was
[29:04] here you go. Here's trillions of
[29:05] dollars. Everything went up in price.
[29:07] Every single thing went up in price. And
[29:09] so I think we all remember when eggs
[29:11] didn't cost $67 a carton. We all
[29:14] remember when XYZ didn't cost this. And
[29:17] I think it takes a long time for that to
[29:19] wear off. But I think when you add in
[29:21] the polarization and the fact that
[29:22] people need someone to blame for this
[29:24] and the fact that AI is standing in
[29:26] front of them where they don't feel like
[29:27] their job is ever safe the way it was, I
[29:30] really think I'm I'm getting to the
[29:32] point now I agree with you because
[29:34] I grew up in a house where my
[29:36] grandmother told me about the Great
[29:37] Depression all the time about not having
[29:38] money for food, being thrown out of her
[29:40] house in in her teens to basically they
[29:42] couldn't afford she had to go out and
[29:44] get a job. She had to go do something.
[29:46] Um and just remembering what the Great
[29:48] Depression was. This is not a we have
[29:50] the unemployment rate at near all-time
[29:52] lows. You can borrow money from anything
[29:54] right now. So I I agree with you that I
[29:57] think this is more of a psychological
[29:58] inflation thing and I think it has a lot
[30:00] to do with just what has happened the
[30:02] last 5 years.
[30:03] Given Worsh's comments, um you the first
[30:06] meeting that he really did a press
[30:07] conference, he didn't say much. Um this
[30:09] was a little bit more robust in in
[30:11] commentary. Uh, did you change your mind
[30:14] at all about how you're thinking about
[30:16] him as the leader of the central bank or
[30:17] actions he may take?
[30:19] No, I actually I think he's the right
[30:22] person for the job because I do think
[30:24] the most important thing for this
[30:25] current Fed chair to be is young enough
[30:30] to understand the importance of AI,
[30:33] which I don't think Jerome Pal had. They
[30:35] didn't even pay attention to AI honestly
[30:37] until like the fourth third fourth
[30:39] quarter of last year. um at least from
[30:42] what they said publicly. The second
[30:44] thing is I think it needs to be more of
[30:46] a market person and less of an academic
[30:49] and I think that's another important
[30:51] part that you know Worsh worked at
[30:53] Morgan Stan like Worsh has a background
[30:55] in capital markets in the same way that
[30:58] Bessant does. So you have Besson and him
[31:00] involved right now in the market at a
[31:03] very important time for people not
[31:05] focused on digital assets. And again,
[31:09] this is you're going to be hearing me
[31:10] talk about this a lot more. I mean, our
[31:11] our lives are crossing over to a very
[31:14] important point starting there because,
[31:16] you know, everything I'm starting to do
[31:17] in my video is related to what's going
[31:20] to happen for me in the second the final
[31:22] four months of the year when I get out
[31:24] of Maine. I mean, I'm very focused on
[31:26] the rise of agents and what Bessant and
[31:29] Walsh are talking about, which is the
[31:32] importance of the United States of
[31:33] America being the leaders of the
[31:36] financial guard rails, not losing the
[31:39] the benefit that they admit has been a
[31:42] huge benefit for the world, which is the
[31:44] reserve currency of the world, Swift,
[31:47] all of these different things. Digital
[31:49] assets are a major part of it. and the
[31:51] growth that's happening in prediction
[31:52] markets, the growth that's happening in
[31:54] real world assets and tokenization, the
[31:56] the news we saw this week on
[31:57] tokenization, all of this stuff is
[31:59] happening. And so I think Kevin Worsh is
[32:01] the right person at a major inflection
[32:04] point that very few people on Wall
[32:06] Street
[32:08] that are on the hedge fund world are
[32:10] fully embracing yet. I think they're
[32:12] realizing they have to. And with AI now
[32:15] being in a massive volatility spike, I
[32:19] think now we're going to start to see
[32:20] some money looking for new beta. And I
[32:22] think that's where Kevin Walsh is going
[32:23] to be a a big asset. So I'm very happy
[32:25] with the reform that's going to happen
[32:26] on all these fronts related to AI.
[32:29] The second that inflation starts to cool
[32:31] and interest rate hike odds start to
[32:33] come down, I think a lot of people look
[32:35] at something like Bitcoin and try to
[32:36] understand how is that reacting and and
[32:39] what is that telling us about the
[32:40] future. Seems like Bitcoin had a pretty
[32:42] strong bid this week. Um, what was your
[32:45] read on that?
[32:47] Yeah, I'm actually going to take it a
[32:48] different direction. I I don't I mean, I
[32:50] know Bitcoin is is is more of your focal
[32:53] point. Um, Ethereum's had the big move.
[32:56] Um, it's up as of yesterday's close or
[32:59] let's say since it doesn't close, as of
[33:01] yesterday's equity close, uh, it was up
[33:04] close to 20% monthto date. Um, and just
[33:06] so people understand that would be if we
[33:10] finish the month with 20% the largest
[33:12] month or the best month since August of
[33:14] last year. Um, Ethereum has outperformed
[33:17] Bitcoin. It's been the largest on a
[33:19] cross verse Bitcoin since then. The
[33:21] reason I care so much about Ethereum is
[33:22] because I do believe if AI agents are
[33:24] coming, if tokenization is coming, if
[33:26] all of these things are happening, this
[33:28] is an energy with inside the revenue
[33:30] side of crypto and we there's there's no
[33:33] there's no way to get around what's
[33:35] happening volume-wise. I think the
[33:36] Stripe
[33:38] bid for PayPal was a big deal, too. I
[33:42] have my crypto 40 name equal weight
[33:45] basket, similar to my AI thematic one
[33:47] meant to deal with the agentic world.
[33:50] and PayPal was one of the names in it.
[33:53] And so,
[33:55] number one, I was happy I've done my
[33:56] homework and figured out which public
[33:58] companies, because there's six of them
[33:59] that are in there, including Robin Hood,
[34:02] how they all fit in with this crossover
[34:03] with the AI agents. But I think Bitcoin
[34:06] is just hanging in there very well on a
[34:08] relative basis. It's obviously done well
[34:10] versus um AI, but the AI thematic side
[34:14] or the the factor side, the V's up
[34:16] towards 100. Bitcoin V is still at 30.
[34:19] So if you're putting an asset in a
[34:21] portfolio right now, you can have three
[34:22] times as much uh Bitcoin on a V adjusted
[34:25] basis as you can AI. And that means that
[34:28] we're at a point where I think you
[34:30] should start seeing more and more people
[34:32] as they get more focused on Ethereum. Uh
[34:35] get in once we get above the 200 day
[34:36] moving average. I believe we're at the
[34:39] start of something new. Until we are
[34:41] above there, I'm trading it actively.
[34:43] I'm trying to make sure that if a bottom
[34:44] is made here, it's there. I even put
[34:47] little started to buy a little bit of uh
[34:50] Micron this week in some of the semis.
[34:52] Uh Micron I have a position again. It's
[34:54] very small relative to what it was back
[34:56] then and I'm buying it at higher prices
[34:58] than where I ended up selling it on
[35:00] average. But that's because the new news
[35:03] that has come out over the course of the
[35:04] last 6 weeks and the consolidation and
[35:07] the the deleveraging that's happened. uh
[35:10] I feel more confident in terms of
[35:12] putting a little bit little bit of money
[35:13] in there, but I'm st still much more
[35:15] heavily weighted towards crypto.
[35:17] When you think of the crypto allocation,
[35:19] is it just Bitcoin and Ethereum?
[35:22] For me, at this point, it's Bitcoin,
[35:24] Ethereum, and and Micro Strategy. So,
[35:26] I'm not um I I'm I I don't think for I'm
[35:30] I'm sure this will change as I spend
[35:31] more time in the space. Uh
[35:36] I've never been a big stock person as a
[35:39] macro person. It's been thematic. So
[35:40] even though Micron is in the portfolio,
[35:42] if you ask me why, it's because of AI.
[35:44] Everything I have in the portfolio to me
[35:47] is either an AI trade or it's a crypto
[35:50] trade. And so that's it. I I really Eli
[35:54] Liy, it's an AI trade. Um silver, it's
[35:57] an AI trade. like anything I have in the
[36:00] portfolio is related to the stuff that I
[36:02] write about and I talk about. I believe
[36:04] we are at the convergence between AI and
[36:06] crypto and that all public companies
[36:09] will be disrupted the same way Adobe and
[36:12] Salesforce have been. Same way the
[36:14] hyperscalers had. They're they just
[36:16] rallied off the bottom. That's why the
[36:18] S&Ps hanging around the all-time highs
[36:20] while AI trades lower. But over the last
[36:22] nine months, they haven't done anything.
[36:24] So again, when you go through things,
[36:26] I'm just more focused on the AI
[36:28] infrastructure trade. Once the agentic
[36:30] side starts to accelerate, once AGI gets
[36:32] here, I believe the ROIC is headed
[36:35] towards private companies. I believe
[36:37] small private businesses are going to be
[36:40] the winners of this. The enterprises
[36:41] will find a way to reduce their expenses
[36:43] over the next two years. We are seeing
[36:45] that happen inside the public companies.
[36:47] If you haven't seen it so far, about 40
[36:49] of the S&P 500 companies have reported
[36:52] so far. And just like happened in Q1,
[36:54] the surprise ratio right now, we're
[36:56] we're outperforming earnings. It's been
[36:58] 16% in terms of the beat. Um, so we're
[37:03] again headed towards another big big
[37:06] month uh big big quarter for earnings
[37:09] and a lot of these have happened in the
[37:11] banks and in insurance companies.
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[39:24] for business today. What are the areas
[39:27] that uh you're actively avoiding? We
[39:29] talk a lot about where you're putting
[39:31] capital. Is there any areas that you see
[39:32] maybe people talking about that you're
[39:34] more nervous about? I I still have no
[39:37] interest in in SAS seatbased software.
[39:40] So, you know, a lot of people are trying
[39:42] to uh pick bottoms in in that. Um, aside
[39:46] from that, I
[39:49] I think you're going to get a lot of
[39:51] sectors that are S&P 500 related. The
[39:54] things that I mention, um, like I think
[39:57] between now and the end of the year at
[39:59] these levels, regardless of whether
[40:01] Micron sells off another 20%.
[40:05] I I don't see how the memory trade the
[40:08] earnings don't grow and how the S&P
[40:10] doesn't go higher. So that's one of the
[40:12] things when people get worried about
[40:14] things, they extrapolate a fall in a
[40:17] certain stock market to something else.
[40:19] So you've heard a lot of people talk
[40:20] about the debt side. Oh, this is
[40:22] unbelievable. The debt's going to go.
[40:24] And I want to make people feel very,
[40:25] very comfortable about this. Um, one of
[40:27] the reasons I care so much about crypto
[40:30] is because of the budget deficit. We
[40:33] still have a deficit of 5 to 6%. So
[40:36] again, the government is spending 5 to
[40:39] 6% a year more than they're getting in
[40:41] receipts. The printing press is still
[40:44] happening, meaning this is good for
[40:45] nominal GDP. At the same time, the
[40:48] government is in a race against China.
[40:51] So they're going to make sure this AI
[40:52] trade works. They're going to do
[40:53] whatever is necessary. If the funding
[40:56] markets, if we see long-term rates go
[40:59] higher, they got to do something because
[41:01] they can't lose to China on this. and
[41:03] China just gives money and opens up
[41:05] things in a very different way. So I'm
[41:07] very fixated on the capex is going to
[41:09] happen. AI is going to continue to
[41:12] accelerate the companies that people are
[41:14] worried about the hyperscalers their
[41:16] debt to equity is not it's nothing. Um
[41:19] so unless their stock price falls
[41:21] violently they have tons of ability to
[41:23] raise capital. They have $2 trillion of
[41:27] RPOS still sitting there. And again, so
[41:29] people understand, I've never understood
[41:31] over the next two years if they took
[41:33] debt for all of the capex. We're talking
[41:35] around $2 trillion.
[41:37] Well, there's $2 trillion between
[41:39] Amazon, Microsoft, Google, and Oracle
[41:42] contracted for the compute.
[41:45] So again, we already have demand for
[41:47] this stuff and these guys are going to
[41:49] have money to go through it. So I'm not
[41:50] worried about the debt. I'm not worried
[41:52] about that. So, I think people should be
[41:54] focused on the areas that are going to
[41:56] have a beta associated with them. And
[41:58] I'm going to stick with AI
[41:59] infrastructure,
[42:01] all the names that I've mentioned, plus
[42:02] the crypto side. So, I'm more focused on
[42:04] the beta. But, if you want to just go
[42:05] buy the S&P, I think you're going to get
[42:08] great returns in the S&P for at least
[42:09] the next couple years as well.
[42:11] What about the NASDAQ?
[42:15] The NASDAQ has um a beta side associated
[42:18] with it. I think is is is good. you can,
[42:21] you know, if you're going to buy S&P, I
[42:23] think you're generally going to get more
[42:24] on there. The area on on uh on the
[42:28] NASDAQ that I'm most interested in is is
[42:30] probably biotech at this point. Um the
[42:34] good thing about the NASDAQ, it is
[42:37] obviously heavily weighted towards the
[42:39] MAG 7, which is a negative, but the
[42:41] reason that it still has outperformed is
[42:44] because it's not a pure cap weighted
[42:45] side. So, you're not overly weighted
[42:48] towards it in there. And I think there
[42:50] are a lot of areas with inside the
[42:52] NASDAQ which will do well, but I I I'm
[42:54] not sure they're going to be able to
[42:55] outperform the S&P in in a in a big way.
[42:58] I got asked the question which I think
[43:01] was a good a good question. There's a
[43:03] lot of people have talked about the fact
[43:04] that this won't end until we have a true
[43:07] bubble. Um and they talk about it like
[43:10] the do-com bubble where Cisco is trading
[43:11] at 100p and that we're still in the
[43:14] early stages. And I want to I want to
[43:17] the people who are bullish, I want to
[43:19] take them a different direction on this
[43:20] because when I was asked the question,
[43:22] what do I think on it? And I said,
[43:24] number one, demographics are completely
[43:26] different than the dot bubble. Um the
[43:28] money being made, you know, with the
[43:31] baby boomers and this, they were still
[43:32] working. They were still taking risk.
[43:35] Now they're passive investments. They've
[43:37] got advisors. They're playing on the
[43:38] golf course. They're not sitting out
[43:39] there gambling. Plus, they've made so
[43:41] much money. They're not trying to make
[43:43] money the same way. There's obviously
[43:45] active traders that are doing it. That's
[43:46] fine. But then the other element that to
[43:48] me is very different and I think that's
[43:51] something people have to get involved
[43:52] in. It gets back to this concept that if
[43:55] in 3 years we have AGI at some point the
[43:57] stock market is going to start saying
[43:59] hey uh all businesses are going to be
[44:02] disrupted.
[44:05] I I don't think people realize what that
[44:07] means. One of the reasons that oil
[44:09] stocks basically really never go higher
[44:13] in a major way and see multiple
[44:14] expansion
[44:16] is because it's dependent on the price
[44:18] of oil. So if oil stays at $60 forever
[44:21] or if natural gas stays at $3 forever,
[44:25] how is an how's a company that generates
[44:27] their revenues based on the underlying
[44:29] asset moving actually going to get
[44:31] there? Well, I think if tokens are
[44:33] commoditized to zero, they don't hurt
[44:36] the model companies necessarily, but I
[44:37] think what they do do is they make it
[44:39] easier for AI native people to compete
[44:41] with all public companies because the
[44:44] inability for public companies to
[44:45] embrace AI and and and make it work is
[44:49] going to be much more challenging. So, I
[44:51] only bring that up. I think the market
[44:52] is going to go through multiple
[44:54] compression. So, I think earnings are
[44:55] going to be great. I think the S&P is
[44:57] going to grow less than earnings like
[45:00] we've seen so far this year and I think
[45:02] that's going to be a trend at some point
[45:03] in the next three years. I actually
[45:05] believe that multiple compression story
[45:07] will become a much bigger story.
[45:10] Yeah, it's um it's going to be
[45:12] fascinating I think to watch this play
[45:14] out because part of uh what you
[45:16] mentioned earlier I think is underrated.
[45:19] I see a lot of people trying to pick
[45:21] bottoms in SAS software and um I think
[45:24] that you have held steady on a view that
[45:27] AI is going to have a significant impact
[45:29] on those businesses and it's more of a
[45:31] structural change than a than kind of a
[45:33] sell-off that is somewhat temporary. Um
[45:38] and it does feel like AI now like I
[45:41] don't hear anyone saying AI is not going
[45:43] to be valuable or AI doesn't work right.
[45:46] You know, three years ago, I heard a lot
[45:48] of like, "Oh, I talked to the the
[45:49] chatbot and it was stupid. It you know,
[45:51] it lied to me." Type stuff, right? That
[45:53] that conversation's gone. Now, what I
[45:55] hear a lot is like, "Who are the winners
[45:57] going to be? How big can uh can the
[46:00] winners be? Um how profitable can they
[46:02] be? What's the impact of Chinese open
[46:04] source?" You know, we're in the nuance
[46:05] now. And so, I take that as everyone is
[46:08] convinced this is real. Um, but I think
[46:10] that the one area, [snorts] um, I still,
[46:13] and I did some of the math, uh, with
[46:15] Sylvia this week, um, a very large
[46:18] portion of my portfolio is exposed to
[46:20] physical AI and robotics. And it just
[46:22] feels like, you know, the software side
[46:25] of AI has now we've gotten so into the
[46:28] weeds because everyone is looking there
[46:30] that the next big, you know, kind of
[46:32] move um of capital in within the AI
[46:36] trade will be that uh that robotics
[46:37] hopefully, you know, at least that's
[46:39] what I'm betting on. Um do you have any
[46:41] exposure there? Are you thinking at all
[46:43] about that the robotic stuff?
[46:46] So, first of all, um, in this past
[46:49] weekend's video, uh, I I put up a chart
[46:53] and I got I got a lot of good responses
[46:55] from people on it, which was, and I
[46:58] don't think you and I have talked about
[46:59] this
[47:01] when people um, want to compare the AI
[47:04] situation.
[47:06] Yes, the.com bubble would come up a lot.
[47:08] But the other thing that comes up that I
[47:10] think it's both more recent, but I think
[47:13] people are thinking about it the right
[47:15] way is they bring up fracking and what
[47:17] happened to all of those companies. Now,
[47:19] the reason I bring it up here,
[47:23] oil demand at the end of the day is
[47:25] driven by people and that's why it grows
[47:28] with nominal GDP. So it's a function of
[47:31] how many more people are on the planet.
[47:32] How much money do those people have to
[47:33] spend? Are they using more energy? Like
[47:36] that's pretty much what drives the
[47:38] majority of energy price. And that's why
[47:40] if you ask any oil person, so how much
[47:42] does oil demand go up a year? Well,
[47:45] what's nominal GDP? Nominal GDP is the
[47:47] answer.
[47:49] The problem with that is eventually with
[47:51] fracking, technology made the supply
[47:55] side go exponential. it actually
[47:57] outpaced what happened with the demand
[47:59] side. So if the demand side stays linear
[48:01] and all of a sudden we get a technology
[48:03] that changes the supply side, well then
[48:05] we end up in a situation we're in, which
[48:07] is no matter what seems to happen with
[48:08] oil, it ends up going back down. And we
[48:11] probably don't know like with Hormuz how
[48:15] much was shifted to natural gas. We have
[48:17] endless natural gas. What what all of
[48:19] these different things have clearly
[48:21] changed. The problem in what you're
[48:23] bringing up and the reason I'm so
[48:24] focused on the infrastructure side, we
[48:27] haven't reached a point yet where we can
[48:29] change the supply side of what's
[48:31] necessary for this buildout because we
[48:34] haven't been focused on it. That's why I
[48:36] say Micron was the same price in 2017.
[48:39] You know what companies don't do when
[48:41] their stock price doesn't rise for 7
[48:43] years? They don't build new capacity.
[48:46] They don't have it. So that's why I'm
[48:48] convinced that on the memory side when
[48:49] you haven't built the capacity for any
[48:51] of this stuff, it's not there. For
[48:53] robotics, it's the same thing. So you
[48:55] have exponential demand for tokens.
[48:59] Tokens are driven by computers. They're
[49:02] driven by digital employees. They have
[49:04] nothing to do with human beings. The
[49:05] reason they're going parabolic is
[49:07] because you just put your computer on
[49:08] overnight and you say, "Okay, do this
[49:09] job for the rest of the day." what
[49:11] you're doing at Sylvia. If you go
[49:12] through your token usage, it's not just
[49:14] the cost that's going higher, your usage
[49:16] is going higher, too. As you grow more
[49:18] people, as you guys build more systems,
[49:20] as you have more agents, it'll just use
[49:22] more and more tokens. It never goes
[49:24] down. And so, until we get the supply
[49:26] side to move up on an exponential to
[49:29] match off the exponential demand, this
[49:31] is something we haven't seen before. And
[49:33] this is why whenever I say it, I'm like,
[49:35] guys, you're missing the point. Like,
[49:37] when consumer agents come, we're going
[49:38] to need a lot more tokens. When
[49:40] humanoids come, we need a lot more
[49:42] tokens. When FSD comes, we need a lot
[49:44] more tokens. So, the way I'm playing the
[49:45] robotic side right now is the structure
[49:48] trade, it's a semiconductor trade. What
[49:50] is Elon Musk doing for the robotics
[49:52] trade? He's building terraab because we
[49:54] don't have enough chips. So, eventually,
[49:56] and I'm sure I will start buying some of
[49:58] these robotics things because I do think
[50:00] the next trade is embodied AI because
[50:02] like you said with software, I don't
[50:04] want to fight this battle with software
[50:05] names. It's going to continually be an
[50:07] issue.
[50:09] I uh I completely agree. I appreciate
[50:11] your time today. The audience loves
[50:13] hearing from you. We'll do it again next
[50:15] week.
[50:15] All right, bud.