# The Biggest Pivot In AI History Is Happening Right Now

https://www.youtube.com/watch?v=qezOp08hwPQ

[00:00] When SpaceX happened this week, it
[00:02] became obvious. SpaceX and Bitcoin are
[00:04] basically to me the same thing. I love
[00:06] when people send me things and they're
[00:07] going, "You're wrong. SpaceX is
[00:09] overvalued." I'm like, "When something
[00:10] doesn't have a valuation, it can't be
[00:12] overvalued or undervalued. It has no
[00:14] valuation. It's a complete guess. We're
[00:16] talking about flying to Mars. We're
[00:18] talking about flying to the moon and
[00:19] building space stations." Like, this is
[00:21] a this is a dream. So, Bitcoin has no
[00:24] energy because it is a vehicle meant for
[00:27] two things. One is
[00:29] >> what's going on guys? Today we got a
[00:30] great conversation with Jordi Visser. In
[00:32] this conversation we talk about what's
[00:33] going on with the hyperscalers, why
[00:34] their stocks have been a little weak,
[00:36] what's going on with Fable 5 and many of
[00:38] the open source models, how the
[00:39] competition is heating up, what that
[00:40] means for you and for investors. We talk
[00:42] about Bitcoin trueflation, Kevin Worsh's
[00:44] first meeting, and what the Fed is
[00:46] likely to do going forward. Jordi is
[00:48] thinking a lot differently than he was
[00:50] maybe a couple of weeks ago, and he
[00:51] explains what's changed, what's stayed
[00:52] the same, and how his portfolio is
[00:54] adopting. Hope you enjoy my latest
[00:56] conversation with Jordi Visser. All
[00:58] right, Jordy, there's a big pivot going
[00:59] on in the AI world. It feels like the
[01:01] hyperscalers, there's a lot of weakness
[01:03] there, but there's a lot of technical
[01:05] innovation that's going on. How do you
[01:06] evaluate the current state of AI and why
[01:09] so much of a pivot is occurring?
[01:12] >> You know, a lot's happened in the last
[01:16] two weeks. That's probably more
[01:18] important than what um everyone
[01:21] realizes. And I think this is just a
[01:23] world where we sit here, we talk about
[01:24] AI every week. I think the reason we
[01:26] always have a new topic to talk about is
[01:28] because uh the changes happen so fast. I
[01:30] wrote a paper this week and
[01:33] so people know this because the the the
[01:36] number one story from let's say the end
[01:38] of February until now has been the
[01:40] straight of Hormuse
[01:42] >> Iran the US
[01:44] >> during that period where oil prices
[01:45] peaked in the first week
[01:48] literally the first week and then
[01:50] progressively have gone lower despite
[01:52] all of the doom and gloom forecast by um
[01:56] people who get paid to sell
[01:58] subscriptions on oil. Uh there's been
[02:02] over 20 model releases in AI, including
[02:06] Opus 4.7, 4.8, and Fable. So, uh the
[02:11] progress in AI last year, we had to wait
[02:14] a long time for Chat GPT5 to come out.
[02:17] Uh it was the most anticipated model
[02:21] release and the most nothing release of
[02:24] any model yet. And now we're releasing
[02:26] them so fast that they don't get any
[02:28] attention. So, in the last two weeks, we
[02:30] hit a point, and I think for everyone,
[02:33] um, they should go back to the the piece
[02:34] by Leopold, who's gotten all this
[02:37] attention now because of his hedge fund
[02:38] going up astronomically,
[02:40] >> situational awareness, and they should
[02:42] go back and read it. Um he highlighted
[02:44] in there that an important moment would
[02:47] occur in 2027 2028 when we would reach
[02:50] recursive self-improvement but also when
[02:53] the government would be forced to
[02:56] basically regulate AI and it would no
[02:58] longer be this everyone has this model
[03:01] and that happened in the last two weeks.
[03:03] >> Now recursive self-improvement is
[03:05] basically the idea that the model
[03:07] doesn't need feedback from humans. It is
[03:08] learning autonomously essentially and
[03:10] making improvements to itself.
[03:12] >> Yeah. Yeah. So we have to hit AI agents
[03:14] first and then the question is how long
[03:15] between AI agents growing in numbers. So
[03:18] think of it as digital employees just
[03:20] sprouting everywhere and the models
[03:22] getting so good that they can
[03:25] create new models on their own and all
[03:27] the algorithmic efficiencies and things
[03:29] that'll come with that. So he wrote that
[03:33] and we've got the government now getting
[03:35] involved and it's specifically involved
[03:38] because a third party researcher in this
[03:41] case it appears to be Amazon figured a
[03:44] way to get around the guardrails. So all
[03:46] that time we heard where mythos was
[03:48] released then it was pulled back during
[03:51] that time period they put up guard rails
[03:53] to make sure that they were preventing
[03:55] bad actors from being able to do bad
[03:56] things. Just so for people who aren't
[03:58] deep in the weeds, uh, Mythos was a new
[04:00] model from Anthropic. It was deemed
[04:02] incredibly powerful. People were using
[04:04] it internally in testing and they were
[04:06] finding a lot of cyber security uh, kind
[04:08] of vulnerabilities. And so the
[04:10] government and a couple of cyber
[04:11] security companies came together, said,
[04:12] "Hey, this may be too powerful to
[04:14] release in its current form." And so,
[04:16] Anthropic essentially took a watered
[04:18] down version. They were able to create
[04:20] these guardrails uh, around it. and they
[04:22] released it under the name Fable, but
[04:25] within I don't know what was it, three
[04:26] days. Yeah.
[04:27] >> Somebody at it appears Amazon was able
[04:29] to basically jailbreak it. So same way
[04:30] you could jailbreak a phone, you they
[04:31] jailbroke the model and then of course
[04:33] everyone freaked out cuz they're like,
[04:34] "Oh my god, this mythos thing is
[04:36] actually out in the wild in a jailbroken
[04:38] form."
[04:38] >> Yeah. So for those of you looking for an
[04:40] analogy who've played golf, if you take
[04:42] the governor off your golf cart, it goes
[04:43] a lot faster. So that's what they
[04:45] basically were able to do.
[04:46] >> No one would ever do that. Not not as a
[04:49] young kid playing golf. Um but what did
[04:52] end up what ends up happening is Leopold
[04:54] talked about the government getting
[04:56] involved which has happened and
[04:58] recursive self-improvement. Now he
[05:00] forecasted that that would happen in
[05:02] 2027 2028. So again I I want to make
[05:04] sure people understand that we've
[05:06] reached a point where the next step is
[05:08] AGI which is something we've all talked
[05:10] about. So you've got the government
[05:12] getting involved shutting it down in a
[05:14] way that makes it very very difficult.
[05:16] I'm sure it'll be re-released again
[05:18] after new guardrails are put in and they
[05:20] find some way to go through it. But you
[05:22] just opened up a can of worms and what
[05:24] he wrote about is once you get to this
[05:26] stage, everything changes. Now, at the
[05:27] same time,
[05:29] Z.AI, another one of these Chinese open
[05:32] source models, released GLM 5.2,
[05:36] which ended up basically getting close
[05:40] to Fable 5 Mythos. And so you've got
[05:44] you've lost sovereignty where you don't
[05:46] know if a model can be shut down. So if
[05:47] you built your entire business on Fable
[05:49] 5 now it only been quick. But let's
[05:51] assume you used it and you've already
[05:53] made upgrades and then all of a sudden
[05:54] they say it's shut down. Okay. But
[05:58] you've got an open source model which
[05:59] you can just download onto your
[06:01] hardware, run it, and it's almost as
[06:03] capable as that. Is this the point now
[06:06] where we start to see the drive to more
[06:07] open source? And that's become a story
[06:09] that's bigger and bigger. Now, at the
[06:11] same time with recursive
[06:13] self-improvement, you had OpenAI
[06:15] basically say maybe we're not going to
[06:17] do an IPO and the speculation on this
[06:21] point when they brought up codeex and
[06:22] all these points is are we reaching a
[06:25] point where capital is not going to
[06:26] become as important because these models
[06:28] have improved at this pace without the
[06:31] data centers being completed. So from my
[06:33] side the pivot point is we have a stock
[06:36] market which has just raced higher based
[06:38] on the capex buildup.
[06:41] every single part of its capex buildout.
[06:43] I think again we're at a point where in
[06:46] when the market shows the next sign of
[06:48] weakness in some of these semiconductor
[06:50] names and stuff, I think people should
[06:52] pay attention. What I just laid out is a
[06:54] narrative that will be a bigger
[06:55] narrative sometime. It might take 3
[06:57] months, it might take 6 months, it might
[06:58] take 12 months. But when you combine
[07:00] what you said, which is the hyperscalers
[07:03] are weak.
[07:05] The hyperscalers are weak because
[07:07] they're spending tons of money. And the
[07:09] question is, are they coming under
[07:10] pressure now to maybe cut their capex,
[07:15] especially a Microsoft and a Meta whose
[07:16] stocks are extremely weak.
[07:18] >> Now, as we watch this play out, there's
[07:20] a couple things that I think are
[07:21] happening. And I've talked in the past
[07:22] about, you know, the mandate from heaven
[07:24] 12 months ago was everyone go use AI.
[07:26] And every company went and ran crazy
[07:29] with it. We have now since seen uh a
[07:31] number of different companies come out
[07:33] and either say we blew through our
[07:34] budgets, we're spending too much. Hey,
[07:36] we're taking down the token leaderboards
[07:38] and we're saying it's not about
[07:39] consumption, it's about output and
[07:40] efficiency and effectiveness. Um we
[07:43] inside of Sylvia have seen this where we
[07:46] said hey look this user generated that
[07:48] means everyone can just go spend as much
[07:49] as they want of our money for
[07:50] subsidizing. Let's stop doing that.
[07:55] I see the per customer per query demand
[08:00] actually shrinking because everyone's
[08:02] becoming smarter about how efficiently
[08:03] do you use the model and the best way
[08:05] that I use this is like you know uh if
[08:07] you're using your regular computer and
[08:09] you type something in and you measured
[08:11] how much computational power is used for
[08:13] that query it is getting more and more
[08:15] efficient over time that's basically
[08:16] what's happening with the models
[08:18] >> but their revenue is skyrocketing still
[08:20] so each individual customer is becoming
[08:23] moreffic efficient which means it's
[08:24] actually less revenue for the company on
[08:26] a per query basis but the demand is not
[08:28] slowing in fact actually it may be
[08:30] accelerating because people are
[08:31] realizing wait I can do this more
[08:32] efficiently I get more productivity out
[08:34] of this and so I actually want to
[08:35] consume more overall it's just that I'm
[08:37] getting more productivity is that kind
[08:38] of how you see this playing out
[08:40] >> yeah so the whole point with Jevans
[08:43] paradox and this whole belief that if
[08:44] token prices start going lower because
[08:46] people get more efficient with going on
[08:47] the models get more efficient all this
[08:49] stuff happens you end up with place that
[08:51] you're just going to get more demand um
[08:53] which I agree with over the long term. I
[08:55] I I think in the Q1 of this year we had
[08:58] an explosion of people diving into
[09:02] anthropic partly to because they felt
[09:04] like they were falling behind. So one of
[09:06] the things that I think with Jeff
[09:07] German's paradox that people assume uh
[09:10] especially the people who say it on the
[09:12] AI side is that it's going to be a
[09:13] linear growth adoption and I don't think
[09:15] that's the case. I think now we're in a
[09:17] place where people are analyzing just
[09:19] like you just said with Sylvia, how much
[09:21] money am I spending and what ways can we
[09:23] get around that? Now it happens at a
[09:24] time when open source models are way
[09:26] ahead. And when I mentioned Leopold's
[09:29] situational awareness, if people go back
[09:30] and read it, he didn't expect open
[09:33] source models to be where they are. He
[09:35] literally in this piece he wrote about
[09:37] how important it is for the US
[09:39] government to take over these models if
[09:40] they get so good to pres to prevent
[09:43] China from the ability to catch up
[09:45] because it's a military dominance thing.
[09:47] Well, the Chinese have been able to keep
[09:49] up no more than 6 months behind
[09:54] without having our chips to the degree
[09:56] that is without having all of the things
[09:58] of the model. So, I think we've kind of
[10:01] reached a point in in AI where it's
[10:04] amazing how fast this moves. A year ago
[10:08] is when the GPT5 thing happened. It's
[10:10] it's we're we're moving so fast that I
[10:13] think people are getting caught up
[10:14] particularly people investing and this
[10:15] is a warning to everyone out there. Um
[10:18] this is why I do my weekly video. It's
[10:20] like anything can change during the
[10:22] week. And this narrative that I'm
[10:23] talking about and what you're saying we
[10:26] could see a period where token prices
[10:27] drop because the adoption side pulls
[10:30] back for a variety of reasons even
[10:31] though in the long term German paradox
[10:33] is going to work. So I think the cost of
[10:35] the data centers is becoming the bigger
[10:37] issue.
[10:37] >> There's two other aspects to this. um if
[10:39] the Chinese open source models are able
[10:41] to keep pace with the US models, I think
[10:44] the generalized uh view is that they
[10:47] don't have access to the chips, the
[10:48] power, you know, kind of all the the
[10:50] training ingredients, if you will, but
[10:52] they're keeping pace to a degree. Does
[10:54] that actually is that like indicative
[10:56] that the United States is not innovating
[10:58] fast enough? like we should the gap be
[11:00] bigger because of the advantages that we
[11:02] have in terms of chip access power uh
[11:04] and the computational um uh kind of
[11:07] aggregate size the training data all
[11:09] these things.
[11:10] >> So again this argument has been brought
[11:12] up now for since deepseek in January of
[11:15] last year which was okay when you take
[11:18] away something the the raw brute force
[11:21] of data centers and colossus and all of
[11:24] this stuff and you just say you're going
[11:25] to have to get smarter without it. The
[11:27] interesting thing about this week, there
[11:28] was another thing that Open Router came
[11:30] out with which was called Fusion.
[11:32] Now Fusion
[11:35] is somewhat similar to Z.AI
[11:40] GLM 5.2. GLM 5.2 is a mixture of
[11:45] experts. So with inside the model, it's
[11:49] kind of like having a judge and then a
[11:51] board that's giving things and then one
[11:54] person is, you know, one one part of it
[11:56] making the decision. On Fusion, it's
[11:59] taking all the best models and kind of
[12:02] taking all their opinions and going up.
[12:04] Now, when I originally showed people and
[12:06] gave prompts out on on on my payw wall,
[12:09] the thing that got the most attention
[12:11] was, "How did you come up with this
[12:12] concept of deep research?" So when I do
[12:14] deep research on Vera Rubin, which I
[12:16] just did one this week, I actually use
[12:19] all five models to do the deep research.
[12:21] So 30 pages each from five different
[12:23] models and then I consolidate them into
[12:25] one that is somewhat similar to what
[12:28] Fusion does, but it also has a similar
[12:29] construct to the way GL GLM 5.2. The
[12:32] reason I bring that up with the Chinese
[12:33] open source models, they're forced to
[12:35] take these other techniques using
[12:37] reasoning, using reinforcement,
[12:38] learning, human feedback, mixture of
[12:40] experts, all these different things and
[12:41] come up. And I just think that that has
[12:43] led to more innovation on them side on
[12:45] the algorithmic and the efficiency side
[12:47] while we've just focused our attention
[12:49] on all the spending on the data center
[12:51] side to getting bigger models and going
[12:53] through it. That's where I think it
[12:55] hasn't been that long. It takes a long
[12:57] time to get these data centers built
[12:58] except for Elon Musk. So I think maybe
[13:00] we're at that pivot point where people
[13:02] should start to pay attention that there
[13:03] will be another narrative at some point
[13:04] this year. There's no doubt in my mind.
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[14:22] right, now let's talk about the capex
[14:24] spending. Um, there has been a lot of
[14:27] debate as to are they spending too much?
[14:29] if they're not using free cash flow,
[14:31] they start to take a lot of debt, then
[14:32] there's the kind of leverage question.
[14:34] Um, but I think what you're really
[14:35] highlighting is maybe the amount of
[14:38] power and uh compute that we thought we
[14:41] needed, we may not actually end up
[14:43] needing if there's this recursive
[14:44] self-improvement, the software side is
[14:46] becoming so efficient. How do you
[14:48] analyze what the tipping point is when
[14:52] you would say, okay, all of this capex
[14:54] spending, maybe we only need 50% of what
[14:56] we thought we were going to need.
[14:58] So the tipping point from memory stocks
[15:03] is honestly going to be if someone says
[15:05] they're cutting capex. Uh the second
[15:08] derivative is a very powerful thing in
[15:10] investing. Um I say it all the time rate
[15:13] of change. And if you look at um
[15:16] semiconductor dollar growth for this
[15:19] year according to Gartner it's going to
[15:21] be close to 100% relative to last year.
[15:23] The forecast for 2027 is about 30%. So
[15:27] we went from 100% growth to 30. That's a
[15:30] problem. Um now again it's a good
[15:32] problem to be growing 30%. But if you
[15:34] question whether the capex is necessary,
[15:37] that is the point where I think people
[15:39] start to worry and I think it starts to
[15:40] become a bigger story. Now I I will say
[15:42] this to everyone out there. We have such
[15:44] a shortage of memory that it would be an
[15:47] air pocket. Uh and that's what I expect
[15:49] to happen at some point. I expect capex
[15:51] air pocket where everyone freaks out.
[15:53] >> Yeah. What does that mean air pocket?
[15:54] That means that if one person pulls back
[15:56] on their capex
[15:59] and again we have no signs of that right
[16:01] now. If anyone would be the likelihood
[16:03] it would be Microsoft is is my guess.
[16:05] Sacha Nadell has been very outspoken
[16:07] about things and even said in the last
[16:08] week
[16:10] they're moving to DeepSeek possibly as
[16:13] some for
[16:13] >> like a Microsoft hosted deepseek version
[16:15] or something right.
[16:16] >> Uh and again what that is basically
[16:18] saying is he made the decision a while
[16:21] ago to kind of break ties with open AI.
[16:23] He has said that the models will
[16:25] eventually be commoditized and getting
[16:26] involved in this. He said this not that
[16:28] long ago either. So when people go that
[16:30] was a long time ago. It was a long time
[16:31] ago in AI time. It was like a decade ago
[16:33] in AI time but it was about a year ago
[16:35] in in human time. Um
[16:37] >> mere mortal time.
[16:38] >> Exactly. If they and again they have a
[16:41] problem with pulling back on this not
[16:43] because they're a model company but
[16:45] because they have Azure and they need
[16:47] more and more stuff for to house this
[16:50] because they've got a lot of revenue to
[16:51] come in. But if capback starts to slow
[16:54] down, then all of a sudden you've got
[16:56] all these memory that's sitting there,
[16:58] it will not stop. Because what shutting
[17:00] down Fable 5 said to every country in
[17:03] the world who's way behind the US, you
[17:05] better go build your own thing. You
[17:07] better have open source. You better have
[17:08] whatever because you cannot depend on
[17:10] the United States to just give you
[17:11] models cuz we shut down the rest of the
[17:13] world. Non US people cannot use it. Um,
[17:16] the ironic thing is philanthropic and I
[17:18] think for all of the model companies
[17:20] like 70% of the people that work there
[17:22] are non US
[17:24] people from the moonshots uh episode
[17:27] this week. So I just think that we're
[17:29] going to hit a point where the risk
[17:31] finally and I didn't think this was
[17:33] going to happen is that there'd be an
[17:34] air pocket in capex because one of the
[17:36] companies would say we don't need it.
[17:38] You'd have all this memory. The stories
[17:39] would start going they have all this
[17:41] memory they're going to need to dump.
[17:43] But Apple said they're raising prices
[17:44] because memoryy's got it more expensive.
[17:46] At some point here, the price of all
[17:49] this stuff that's been hoarded could end
[17:51] up in an air pocket, but eventually
[17:53] everyone will build their own AI
[17:54] factories and every country will and
[17:55] there'll be demand for memory for the
[17:57] next 5 years. But I do expect an air
[17:58] pocket at some point.
[17:59] >> The open- source uh or open systems seem
[18:03] to win out over the long run. Um you
[18:05] know, AOL versus open uh systems. Um
[18:07] you've seen a lot of open source
[18:09] technology, Linux, etc. that that
[18:11] continue to dominate. is your belief
[18:13] that these closed AI models or the open
[18:16] source models end up winning over the
[18:18] long run?
[18:19] >> So I I do, but I think for scientific
[18:22] discoveries and stuff, they'll just
[18:24] continue to be there. I think anything
[18:26] that
[18:27] >> the closed sourced ones.
[18:28] >> Yeah. I I So I think um you have to
[18:31] break this down and say we need more
[18:34] Einsteins to solve living forever, to
[18:37] solve energy, to solve space, to solve
[18:40] having data centers on the moon. like
[18:42] Elon Musk is great, but it would be
[18:43] great to be able to do much better
[18:45] simulations and actually have scientists
[18:47] that are uh at 400 500 IQ. So, we're
[18:51] going to need those for scientific
[18:53] breakthroughs. But I think we're coming
[18:54] to the point of what do you actually
[18:56] need for all this other stuff. And I I
[18:58] think housing your own models, training
[19:00] your own models, which is different than
[19:02] what's happening. Um I do think we're
[19:04] getting to that point. I've always
[19:06] envisioned that there'd be more
[19:07] specialized models for particular things
[19:10] that each company that was big enough
[19:13] and was involved in something important
[19:15] would have their own factory just like
[19:17] Eli Liy does with Lily Pod. Uh I think
[19:19] we're going to get to that faster than
[19:21] we were. I never thought you could
[19:22] depend on the cloud for a variety of
[19:24] reasons. But now what's happened is it's
[19:26] not just security, it's not just
[19:28] latency, you're also dealing with the
[19:30] issue that you're at the mercy of a
[19:31] company that just says you can't use it
[19:33] anymore. Mhm. The thing that I kind of
[19:36] come back to is uh Revolute is a
[19:38] business that usually isn't talked about
[19:40] here in the United States. Uh Revolute
[19:41] is um maybe for the the most basic
[19:43] description for people to understand is
[19:45] the Robin Hood of Europe, right? So it's
[19:46] retail brokerage. They have a lot of
[19:48] banking services etc. Um they actually
[19:50] trained a foundation model and it seems
[19:53] like okay they've got their like retail
[19:55] offering and now they've got this model.
[19:57] We'll see what they do with it but that
[19:59] seemed like a very big breakthrough
[20:00] moment. Midjourney this week came out
[20:03] with uh hey we've been doing this image
[20:05] uh you know creation. It was this cute
[20:07] creative tool. Oh now we're going into
[20:09] hardware medical services and they seem
[20:12] to have a pretty big breakthrough in
[20:15] terms of the ability to scan your body.
[20:17] The way my I understand this works is
[20:19] like you stand on almost like a graded
[20:21] platform and then they submerge you in
[20:23] water and they're shooting light into
[20:26] your body. um and they're able to do
[20:28] some imaging and it's supposed to be,
[20:29] you know, faster, more accurate, etc.
[20:32] Forget whether it actually works or not.
[20:35] A retail brokerage creating a foundation
[20:37] model that is a cranking of the ambition
[20:40] dial from like 20 to 100.
[20:42] >> Mhm.
[20:43] >> Midjourney going from creative image
[20:45] generation to medical device cranking of
[20:48] the ambition dial to 100.
[20:51] I h I just don't see anything else other
[20:52] than like AI is now giving them the
[20:55] ability to do this stuff in a way that
[20:57] they couldn't have dreamed of trying to
[20:58] accomplish these way bigger more
[21:00] ambitious projects.
[21:03] Is that what we should expect now as the
[21:04] new normal is like people will just say
[21:06] what can I do that's bigger better you
[21:08] know go faster? Yes. Yes. Yes. I mean
[21:12] last week just as like a a jump off
[21:16] point here. So when you brought up Jeff
[21:19] Bezos and Bezos and Prometheus
[21:22] >> Mhm.
[21:23] >> crazy.
[21:24] >> Yeah. Crazy. And
[21:26] again
[21:28] intelligence is involved in all it
[21:30] crosses sectors. Creativity in my
[21:34] opinion crosses like you can have a
[21:36] person who's an engineer who is the
[21:39] greatest artist painting and cook and
[21:41] writer and all this stuff and you just
[21:43] would never know and you view them as
[21:45] being this math person that's good this
[21:48] what AI allows you to do is take
[21:49] intelligence and combine it with
[21:51] creativity and with that it's very
[21:52] powerful as someone who spends his time
[21:54] trying to think and I had to find a word
[21:57] for this because I've said it a lot on
[21:59] on on this show because I know we we
[22:01] reach a an audience based on the
[22:04] response that I'm getting that might be
[22:05] different than a lot of my my viewers,
[22:07] which is people that have children that
[22:10] care about their children that are not
[22:11] just in the financial world.
[22:13] >> And the issue with that is for all kids,
[22:16] they need agency. Um, and that word to
[22:20] me is very powerful and I think it fits
[22:21] into uh a degree what you're saying. If
[22:24] you're a person at home, agency to me
[22:26] fits directly with empowerment. How do
[22:29] you use the tool yourself to create a
[22:32] business, to create a life? And
[22:34] curiosity will lead you down rabbit
[22:36] holes that you never expected, but
[22:37] you've created the idea combined with
[22:40] the interaction with AI. It's the reason
[22:43] why the most powerful people in
[22:45] artificial intelligence that I listen
[22:46] to, and I've run into them at
[22:49] conferences, and they're at all ages,
[22:51] and you probably fit in with this to
[22:53] some degree, although your your your
[22:54] kids are younger.
[22:56] I don't have free time anymore.
[22:58] >> And the reason is because I can have a
[23:00] conversation with the smartest person
[23:02] I've ever met and any question that
[23:05] enters my mind, I'm in the habit of what
[23:08] do you think about this? And by the time
[23:10] we're done, if it's a great idea, it
[23:12] might be in my video over the weekend.
[23:14] I'm spending more time trying to help
[23:16] people with using artificial
[23:17] intelligence to get to your point
[23:19] because they can create ideas that will
[23:20] be better than the job they have. And
[23:23] the world needs people doing that
[23:25] because it speeds up innovation. It
[23:27] speeds up curing health. When I first
[23:29] talked about Eli Liy and I mentioned uh
[23:32] something on Nolan podcast that Gavin
[23:34] Baker talked about about a hedge fund
[23:35] manager that basically spent all of his
[23:37] time to figure out how to help his child
[23:41] that had a disease
[23:43] and he found a medicine that existed
[23:46] that came back and I don't remember I
[23:48] don't think he got into specifics but
[23:49] let's assume it was something that was
[23:51] being used for something else but AI
[23:54] said this will probably work for that
[23:55] and it ended up helping his kids and I
[23:57] mentioned other people that have had
[23:59] mold issues and all kinds of different
[24:00] things that have ended up there. You
[24:02] have to understand that if you're not
[24:04] using artificial intelligence, number
[24:06] one, you're falling behind on
[24:07] everything. And that's the reason why
[24:08] now I've broken my my weekly to there's
[24:11] a signal. How do I avoid the noise? This
[24:13] is a bubble. This is bad. Okay, let's
[24:14] get through it and show you the facts on
[24:16] this. The alpha, okay, if you're going
[24:18] to invest, what should you invest in?
[24:19] Why are the hyperscalers not working?
[24:21] And why are they an issue on the
[24:22] spending side? And why are all these
[24:24] memory? What's the risk that the memory
[24:25] names fall? And then you've got the
[24:27] agency side. Once you start with AI and
[24:29] you start using it, you get more
[24:31] powerful. And I think you can end up in
[24:32] the same situation as the story you
[24:33] described.
[24:34] >> Now, uh Torsten over at Apollo, uh he
[24:37] has uh sometimes charts heard around the
[24:39] world. You know, it's like a canon. He
[24:41] puts the he puts it in, he packs in all
[24:43] the uh uh the powder and then he says 3,
[24:46] two, one, fire. uh today he fired one
[24:50] which is uh if you take out AI and
[24:53] energy stocks from the S&P the S&P 500
[24:55] is down. Now I jokingly said earlier
[24:57] well if you take all the water out of
[24:58] the ocean then there's no ocean right
[25:00] obviously. Um but I do think that there
[25:04] was even a day this week Ryan Dietrich
[25:06] pointed this out that like 428 of the
[25:09] 500 stocks sold off in the same day. One
[25:12] of the biggest sell-offs where you know
[25:14] majority sold off. And so we've been
[25:17] talking about this for a long time now,
[25:18] how there's weakness in a lot of other
[25:20] industries. Do you get worried that it's
[25:23] only AI and energy or are you like, no,
[25:26] this is what happens. There's sectors
[25:27] that get hot, everything else kind of
[25:29] cools as capital rotates and you know,
[25:31] this is more normal than people would
[25:32] think.
[25:34] >> Um, I mean, we watched this the prior 15
[25:38] years.
[25:39] The S&P 500 was driven by the Mag 7. So
[25:42] this is not something new. And this is
[25:44] what happens when innovation reaches the
[25:45] point where it's very concentrated. Um
[25:49] the the the funny thing is the Russell
[25:50] >> indexes work.
[25:52] >> So in mentioning the S&P a lot of times
[25:55] what I'll I'll look at is a combination
[25:57] of equal weight or the Russell 2000. I
[26:01] mean these are small cap stocks. The
[26:04] Russell 2000 made an all-time high this
[26:05] week. The S&P 500 did not. So the
[26:08] problem is for people with statistics,
[26:11] you can always find statistics that
[26:13] support your case. You can always find
[26:15] things that show up. Here's the reality.
[26:17] AI has exploded higher in a pace that no
[26:21] industry has ever seen. I believe it is
[26:23] incredibly disruptive. I believe it has
[26:27] been a problem for a lot of things, but
[26:28] I also believe that a lot of the S&P 500
[26:32] are companies that are based on the
[26:33] industrial revolution. And now we've got
[26:35] companies that are based on AI. The
[26:38] industrial revolution companies which
[26:40] make up the majority of the names. I I
[26:42] don't see how they're going to compete.
[26:44] It'll really get bad when crypto is
[26:46] working too because then crypto will
[26:48] have the same impact. So I have said
[26:49] before, I will continue to say it at the
[26:52] pace that we are going and the fact that
[26:53] we are closer to we are at RSI now. AGI
[26:57] is behind it. Super intelligence behind
[26:58] that. We will have missed the forecast.
[27:00] Everyone's moving their forecasts up on
[27:02] AGI. everyone including Deis Sabis who
[27:04] was the most skeptical
[27:06] I'd say realistic person someone who I
[27:09] actually believed the most he is not
[27:10] hyperbolic in any way so when he goes
[27:12] from I think it's in the early 2030s to
[27:14] I'm now thinking 2029 that's a big deal
[27:17] to move up the timeline that far for it
[27:20] to to shatter Liupold I have said 20 by
[27:24] 2030
[27:26] all companies that exist all large
[27:28] companies will have an issue with AI
[27:31] they will be disrupted in some way. If
[27:34] we don't need as much capex,
[27:37] well, then there's nothing left in the
[27:38] stock market. I I mean, you're
[27:40] commoditizing AI, which is the model
[27:42] companies are having trouble with that.
[27:45] If we don't need the capex, but AI is
[27:47] accelerating without the capex, what's
[27:49] going to happen to all the capex stocks?
[27:50] So, my belief has been for all investors
[27:53] that at some point here, it becomes an
[27:55] issue. We're not there yet. Earnings are
[27:58] growing, the stock market's up. I
[28:00] learned a long time ago as my first rule
[28:02] before I ever put a dollar into the
[28:04] market and I ever traded. I studied the
[28:07] Elliot wave theory for a reason. As long
[28:10] as the market is trending a certain
[28:11] direction, everything's fine.
[28:13] >> If the market has issues like breath and
[28:16] all this stuff, the S&P 500 will start
[28:18] to go down. But the S&P 500 is like
[28:20] Bitcoin is completely amorphous. It gets
[28:24] rid of the weak and it keeps the money
[28:26] with the strong. right now. AI are the
[28:29] strong at some point. I'm not sure all
[28:30] the AI companies are going to win.
[28:32] >> All right. Kevin Wars had his first big
[28:34] day in front of the bright lights. Uh
[28:37] started off hot. Didn't say good
[28:38] afternoon. Said good day. Everyone was
[28:40] freaking out about that. Um I don't
[28:43] know. I thought he did a pretty good
[28:44] job. Uh he didn't say a lot, which maybe
[28:46] was why he did a good job because he
[28:48] didn't have a big attack surface. What
[28:50] was your take on his press conference,
[28:51] some of the decisions they made, uh
[28:53] their focus on, you know, this task
[28:55] force? I think what we learned is he's
[28:57] going to be very different than Jerome
[28:59] Pal and he has said that um he has very
[29:02] different views. Uh I think the reaction
[29:06] by the media was just like the oil
[29:09] doomers and just like every other issue
[29:12] that has popped up. Tariffs are going to
[29:13] take down the country. Oh, he was
[29:15] hawkish. He wasn't hawkish. Um it's
[29:18] ridiculous. Uh tenure rates have been
[29:20] stuck in a range now since 2022. And in
[29:24] this weekend, I'm going to highlight to
[29:25] people the only reason rates went higher
[29:28] over the course of the last since 2021
[29:31] is because the Fed raised rates.
[29:34] Yes. We
[29:35] >> Funny how that works.
[29:36] >> Yeah. But that's it. Like everyone is
[29:38] worried about the debt. Everyone is
[29:40] worried they're going to go higher.
[29:41] Every time it ticks higher for a week,
[29:42] then everyone comes out and says the
[29:43] world's going to end. Then it ticks
[29:44] right back down. Two things that
[29:47] happened. Uh number one, he's a believer
[29:50] in productivity. He announced task
[29:52] forces. Now my kind of thought on the
[29:56] task force is he believes which I do as
[29:58] well and I think a lot of I think a lot
[30:01] of younger people non-academic and I
[30:04] consider myself non-academic because of
[30:05] much how much I hated school but I've I
[30:07] I I understand macroeconomics extremely
[30:10] well.
[30:11] I think the Fed has been in in the habit
[30:14] since 2009 of micromanaging everything
[30:17] >> every word every speech. It's
[30:19] ridiculous. At the end of the day, they
[30:22] do very little unless they have to come
[30:24] in and save something. That's it. Like,
[30:26] they're not moving rates much at all.
[30:29] They're going to cut 25. Nope. Now
[30:30] they're going to raise 25. Who cares?
[30:32] It's not going to change anything. It's
[30:33] a function where the market gets overly
[30:35] dramatic with it. So, the task force to
[30:37] me is, are we looking at this the right
[30:39] way? And I have said repeatedly GDP by
[30:42] itself is a horrible measure of an AI
[30:44] world. But let's use inflation. He has
[30:47] been very outspoken that he thinks the
[30:48] way we think of inflation and goes
[30:50] through it is wrong. He did not change
[30:53] and he won't change the target inflation
[30:56] rate. And the reason is cuz we're kind
[30:58] of trapped into that. If he came out and
[30:59] said, "I don't actually think the 2%
[31:01] means anything. We're going to go back
[31:02] to something else." But what he did say
[31:04] with inflation and what he said publicly
[31:06] is, I think the trimmed mean is a much
[31:10] better measure. And I completely agree.
[31:14] I believe in getting rid of these things
[31:16] that are way on the bottom, way on the
[31:18] top, and just kind of sticking with
[31:19] where the bulk of things are, using the
[31:22] median, and every single part of the
[31:24] median and trimmed mean, it's been it's
[31:27] been getting in a tighter range, meaning
[31:28] most things are kind of in this point of
[31:31] like 3%.
[31:33] And the extremes with oil and with all
[31:35] this stuff, it blew out. I think one of
[31:36] the most important things that's
[31:38] happened in the last
[31:40] month is as the news got worse on the
[31:43] straight of Hormuz, oil prices continued
[31:46] to move lower. We've seen no ships go
[31:49] through. Yet the ura price in New
[31:51] Orleans has collapsed back to lower than
[31:53] it was, meaning fertilizer.
[31:56] Somehow or another, the world had the
[31:59] most important thing shut down and
[32:01] nothing changed. How is oil ever going
[32:04] to sustain an up move at this point if
[32:06] it didn't just do it now? Now, maybe
[32:07] that'll change over the summer as we hit
[32:09] rock bottom, but I learned with prices,
[32:11] that's a warning sign. And the reason
[32:13] that matters is one-year inflation
[32:16] swaps, which are the only thing that has
[32:18] led the rise up in 2022 from the Fed. It
[32:22] led the entire time said, "Okay,
[32:24] inflation's going higher." It collapsed
[32:27] over the course of the last two weeks.
[32:29] So all the crap I gave to true
[32:31] inflation, even though we did get above
[32:32] 4% and they broke away from their CPI
[32:36] kind of guide, it stayed near what the
[32:40] median did and what the mean did. And
[32:41] now we have a Fed chair that's trying to
[32:43] create a task force to agree that okay,
[32:45] we shouldn't be watching this thing. I
[32:48] think that means actually at the end of
[32:49] the day when they focus on inflation
[32:50] that they're going to realize that it's
[32:52] actually lower than what we thought it
[32:54] would be. And if it couldn't go higher
[32:56] with that, how is it actually going to
[32:58] go higher when you strip out memory
[32:59] prices and you strip out all these
[33:01] one-off things?
[33:03] >> Are you saying that you think true is
[33:04] more accurate now
[33:06] >> or no?
[33:07] >> Well, again, when you say more accurate,
[33:10] >> let me rephrase. Are you using
[33:12] trueflation as a data point in anything
[33:14] you do or not really?
[33:16] >> This weekend, I'm going to show it
[33:17] overlaid with
[33:18] >> Oh, that's that's big.
[33:20] >> Yes. I don't think I've ever shown it in
[33:22] there. Um, but I'm also going to show
[33:23] how it deviate deviated from CPI. So, if
[33:27] if you were using it to forecast what
[33:29] would happen with inflation, it didn't
[33:31] work.
[33:32] >> If you were using it to say what the
[33:34] true level of inflation is that you
[33:37] should be using for where things will
[33:39] settle once you get rid of a disruption,
[33:41] it was far better than the headline CPI.
[33:44] >> But core CPI did the same thing. And I
[33:46] didn't think core CPI would go higher.
[33:47] The question is on this whole thing is
[33:49] CPI went up to 4.2. too. The next
[33:52] reading, which will come out in early
[33:55] July,
[33:55] >> you think up or down?
[33:57] >> It's going to be around zero.
[33:58] >> Yeah. Like zero 0% month- over-month
[34:00] >> growth. And that'll make the
[34:02] year-over-year down if that happens down
[34:04] to like four from 4.2. So, you'll have a
[34:07] peak in inflation, which will come back
[34:09] down. And and that was not not only not
[34:12] that, there were there were shows saying
[34:13] we're going to see double digit
[34:14] inflation. Double digit. I remember
[34:16] sitting on
[34:17] >> when listen on the the next CPI report.
[34:20] If that happens, everyone should just
[34:21] stay off the internet for the day. I'm
[34:24] going be uh you know what what's the
[34:26] saying? Uh uh trigger fingers turn to
[34:28] Twitter fingers.
[34:29] >> I I would be surprised
[34:32] if it doesn't come out close to zero
[34:34] just because gas at the pump has gone
[34:36] from 455 to below four now.
[34:38] >> Yeah.
[34:39] >> And that's one of the major drivers.
[34:41] >> All right, guys. Let's talk about
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[37:01] we talked about this last week or not.
[37:03] Uh I think two things are true.
[37:04] Everything you're saying about
[37:05] inflation, I think, is right. There's
[37:06] kind of been this peak. I think the end
[37:08] of the war, I early on was like, hey, I
[37:11] don't think the war is going to be that
[37:13] long. I think that we probably hit a
[37:16] point where I could say I was wrong
[37:17] about that, right? Like it was longer
[37:18] than I thought it was going to be, but
[37:19] it's still not like it's like a
[37:20] three-year thing, but I was like, hey,
[37:22] if we're going to do this, let's do it
[37:23] in like 90 days and be out. So, it's I
[37:26] don't know how long it's been now. Maybe
[37:27] it's 150 days or or whatever, but it's
[37:28] longer than I I thought it was going to
[37:30] be. And so there's been a little bit
[37:31] more persistent uh pressure, but the
[37:33] fact that we're now kind of near the end
[37:35] and it's now rolling back over feels
[37:38] pretty good. And it wasn't that crazy
[37:39] inflation. Very similar to the tariff
[37:41] thing, right? Some areas you saw spikes,
[37:42] whatever.
[37:44] >> At the exact same time, what is also
[37:46] true, if you go on the streets of New
[37:48] York and you talk to people about
[37:49] grocery prices, gas prices, all this
[37:52] stuff,
[37:52] >> they are in pain. If you go to any city
[37:55] in America, everything is way too
[37:56] expensive. They still can't afford a
[37:58] home. they still can't, you know, uh,
[37:59] buy all the things they want, all the
[38:01] stuff. And so,
[38:03] I've actually maybe changed my mind a
[38:05] little bit on when I talk to people in
[38:08] the finance world, it's all about the 2,
[38:10] you know, up or down or this or
[38:12] whatever. The numbers don't matter.
[38:14] >> Mhm.
[38:15] >> People psychologically think everything
[38:16] is too expensive. And it goes back to
[38:19] the Bessant, you know, do you believe
[38:20] the economic data or not? What he said
[38:22] is, no, I believe the people over the
[38:23] data. What I think he really was saying,
[38:26] you know, in hindsight was the data
[38:28] doesn't matter because ultimately people
[38:30] are going to act the way they feel. And
[38:33] so the uh the data point now that I've
[38:37] been using for the last week in
[38:38] conversation, I've got young kids. My
[38:41] wife went on Amazon recently. She bought
[38:43] two boxes of diapers. For those of you
[38:47] young men and women who don't have kids,
[38:49] you could do a lot of diapers with kids.
[38:52] >> I don't know. when I should ask her,
[38:53] were they like superized boxes or some
[38:55] whatever, right? But she bought two
[38:56] boxes of diapers. $150.
[38:59] >> Yep.
[39:01] >> I don't care how many diapers are in the
[39:02] two boxes. If you're going through 8 to
[39:04] 10 diapers a day, right? That's
[39:07] unsustainable.
[39:08] >> And so you look and you say, like, by
[39:10] the way, like I don't think he's buying,
[39:11] you know, super organic, non-GMO,
[39:13] whatever crazy diapers. That is one tiny
[39:16] anecdote across an entire economy where
[39:18] people are saying to themselves, "This
[39:20] is nuts." And World Cup ticket prices,
[39:23] Knicks, you know, NBA Finals tickets,
[39:25] all of that stuff, I think, is the
[39:27] extreme end
[39:28] >> where you just have this massive
[39:30] divergence of the K-shaped economy.
[39:34] But you know, the crazy data point in
[39:37] 2006, 20 years ago, guess how many
[39:40] Americans were considered under the
[39:41] poverty line? 36.5 million.
[39:45] 20 years later, guess how many Americans
[39:48] are considered under the poverty line?
[39:50] 35.9.
[39:51] It's basically the exact same number.
[39:53] >> Mhm.
[39:54] >> 20 years later, now people celebrate
[39:56] because the poverty percentage has
[39:58] dropped because the overall population
[40:00] has grown, but it's only dropped by 2%.
[40:03] >> And so, you look at that and you say,
[40:04] there's 35 million Americans who live
[40:07] below the poverty line. the poverty line
[40:09] for those that don't know $15,000 a year
[40:11] in income. A family is $33,000.
[40:16] >> 35 million Americans. And so when Kevin
[40:18] Worse gets up and starts talking about
[40:19] inflation and all this stuff, it's like,
[40:21] dude, we Yes. As an investor, you got to
[40:23] pay attention, the average American,
[40:25] Kevin Worsh, Kevin, right? They're just
[40:27] like, "Look, man, groceries are
[40:28] expensive, diapers are expensive." And I
[40:30] think that's ultimately where you get so
[40:32] much uh debate in uh in society now.
[40:36] So, I I have a uh
[40:38] >> I hope you disagree.
[40:39] >> No, no, no. I I think I have a different
[40:41] um
[40:43] a different take. And
[40:44] >> well, that's called a disagreement,
[40:46] Jordy.
[40:46] >> No, no, no, no. Um so, I I think
[40:50] inflation is um is an excuse for for
[40:54] people at this point. Uh it's not that
[40:57] it's not real, but it's always real. So,
[40:59] let's go through it this way. Wages are
[41:00] growing right now at 3.6% and inflation
[41:03] is four.
[41:04] >> So, not good. That's not good. That
[41:06] means you can't keep up with what's
[41:07] going on. Uh I think the bigger issue
[41:10] and the biggest issue and I hear this
[41:12] repeatedly from young people. So when I
[41:14] say young, because I live in
[41:16] Williamsburg, so I knew who was going to
[41:17] win the mayor the the election in in New
[41:20] York.
[41:20] >> I know you
[41:21] >> as opposed to being in Manhattan. Um uh
[41:26] that group of people.
[41:27] >> I'm going to be walking the streets of
[41:28] the Bronx this weekend, Jordy.
[41:31] Um, I've never seen young people more
[41:34] dissatisfied with the work environment
[41:35] than now.
[41:36] >> And here's what I think it's feeling.
[41:38] And this is a word that everyone hate
[41:40] hates. Um, Bruce Springsteen sang about
[41:44] this, trapped. There's no worse feeling
[41:46] for a human being than feeling trapped.
[41:49] >> If they're trapped at a job they can't
[41:50] get out of, you used to be able to go
[41:52] interview. And sometimes what would
[41:54] satisfy people enough is knowing they
[41:56] could get a job with a raise.
[41:57] >> Yeah. But if nobody is going to hire you
[41:59] for more money or the probability of
[42:01] finding it, you're trapped. If you're
[42:03] trapped in a bad relationship and you're
[42:05] trapped, if you're trapped in a city
[42:07] that you can't get out, if you're a
[42:10] Democrat and you're trapped in a
[42:12] Republican world, if you're a Republican
[42:13] and you're trapped in a Democrat world,
[42:15] I just think these have been amplified
[42:17] because of technology
[42:19] >> and it has coincided with the post
[42:22] period of the great financial crisis. So
[42:23] the great financial crisis took the
[42:25] unemployment rate up to 10. The iPhone
[42:28] comes out. So there's a grace period. We
[42:30] went from 10% all the way down to three
[42:32] and change. It took a decade. I don't
[42:34] think people realize that. If people are
[42:36] listening, we were at 10% unemployment.
[42:38] It took us literally a decade to get
[42:41] back down there. Now during that time,
[42:43] you could become a Door Dash driver. You
[42:45] could become an Uber driver. Like none
[42:46] of that stuff existed before the great
[42:47] financial crisis because we didn't have
[42:49] the iPhone. So I think there was a grace
[42:51] period for people. Then COVID happens
[42:53] and the reality sits in. We dump a ton
[42:56] of money on people. They yolo it for a
[42:58] little while. But then 2022 happens. We
[43:00] move rates higher. Insurance goes
[43:02] higher. And all of the money that we
[43:04] gave to people that they spent on cruise
[43:06] lines and traveling through Europe,
[43:08] well, they didn't work. That was meant
[43:10] to offset the inflation that comes.
[43:12] There's a direct relationship between
[43:14] this is money because we're shutting
[43:16] down the economy. We know it's going to
[43:17] create inflation. So don't spend it all
[43:20] now because you're going to need it. and
[43:21] then we reset the bar and then the job
[43:23] situation was worse. That is what I
[43:25] think happened and AI happened. When did
[43:26] it happen? 2022,
[43:29] right? When rates went higher. So, I
[43:31] just think there's a chain of events
[43:32] here that have left people um angry and
[43:35] they're blaming inflation. They're
[43:36] blaming politics. They're blaming a
[43:38] bunch of stuff. The reality is uh I
[43:40] believe in empowerment and that gets
[43:42] back to that agency side. You have a
[43:43] chance to make more money. you have a
[43:45] chance to not have to work for someone
[43:47] or make money on your own, just like you
[43:48] did as an Uber driver, but you have to
[43:50] use AI and you have to embrace it. And
[43:52] if you keep saying AI is a bubble and I
[43:54] don't want to use it,
[43:55] >> good luck.
[43:55] >> You're just being a victim then.
[43:56] >> Yeah. All right. So, we got two things
[43:58] real quick before uh uh we got to go.
[44:00] But uh first is Nick's parade happened
[44:01] this uh uh this week. Um my number one
[44:05] takeaway was New York forever. I mean
[44:08] that this is the most New York thing of
[44:10] all time. My second takeaway, do these
[44:12] people not have jobs? There's two
[44:14] million people in lower Manhattan right
[44:17] now. We gave our entire office the day
[44:19] off. And I said, "You want to go to the
[44:20] parade? Knock yourself out. You don't
[44:21] want to go to the parade, that's fine.
[44:22] You get the day off." Very unlike me to
[44:24] normally do this. But I said, "Okay, I
[44:26] at least know our people have the
[44:28] opportunity to go because we're giving
[44:29] them the day off."
[44:31] >> 50% of the people there, they playing
[44:32] hookie. Like I there's two million
[44:34] people, right? I was like, "What the
[44:36] hell is going on here?" Um, I saw one uh
[44:38] one image was a big picture of a huge
[44:40] crowd and it said uh for those of you
[44:42] watching this from your office on
[44:44] Instagram right now, just know your tax
[44:45] dollars are supporting these people. I
[44:48] don't think that's actually true, but
[44:49] that was the sentiment. That's first.
[44:50] Second, Bitcoin uh has actually been
[44:53] somewhat weak in the last two or three
[44:55] uh weeks. What's your take as to what's
[44:57] going on with Bitcoin?
[44:58] >> Um, so
[45:00] first of all, it's in a bare market. I'm
[45:02] going to say it every single day until
[45:03] it's not in a bare market. When we break
[45:04] above the 200 day moving average, it
[45:06] will change. Until that happens, it is a
[45:08] bare market. Every single time it runs
[45:10] into any moving average, the most recent
[45:12] one was the 20 moving average, it falls
[45:14] back down. Uh you mentioned the money
[45:18] going into AI
[45:20] when SpaceX happened this week and it
[45:24] became obvious.
[45:26] SpaceX and Bitcoin are basically to me
[45:29] the same thing. Like SpaceX is a future.
[45:32] >> They're both going to the moon. Well,
[45:34] they're both based on a belief that
[45:36] people have in the future. They're
[45:38] they're not about anything fundamental
[45:40] right now. Like, it's very hard to make
[45:42] an argument as to the fundamentals
[45:44] behind this. I love when people send me
[45:46] things and they're going, "You're wrong.
[45:47] Space S is overvalued." I'm like, "No."
[45:49] When something doesn't have a valuation,
[45:51] it can't be overvalued or undervalued.
[45:53] It has no valuation. It's a complete
[45:55] guess. We're talking about flying to the
[45:57] Mars. We're talking about flying to the
[45:59] moon and building space stations. Like,
[46:00] this is a this is a dream. So, Bitcoin
[46:03] has no energy because it is a vehicle
[46:07] meant for two things. One is for people
[46:09] to hide their money from the government,
[46:11] but that is always going to be a small
[46:12] portion of it because the wealthiest
[46:14] people on the planet, which is where it
[46:15] draws its money from, aren't hiding
[46:17] their money from anyone at this point
[46:19] because they're not taking it. On the
[46:20] other side is the energy that comes from
[46:22] retail and the energy that comes from
[46:24] momentum. It has no momentum last right
[46:27] now. It every week there's more people
[46:29] now. You've got uh strategy has brought
[46:32] people's attention. They're looking at
[46:33] the way STRC is trading and it's down to
[46:37] every everybody has a viewpoint on it.
[46:40] I'm going to keep saying the same thing.
[46:43] It is very difficult for Bitcoin to be
[46:45] traveling higher if all the money is
[46:48] going into stuff that is based on
[46:49] earnings.
[46:50] >> Mhm.
[46:50] >> We need and we're running into the
[46:52] second quarter. I believe the second
[46:54] quarter will be more of a disappointment
[46:56] for earnings than the first quarter. Not
[46:58] that it won't grow, but now the
[47:00] expectations are so high.
[47:02] >> 22% earnings.
[47:03] >> Exactly. So if if the stock market is
[47:05] unchanged from now until September,
[47:08] well, that's a better environment for
[47:09] Bitcoin than one where AI continues to
[47:11] go at 50% a month or 50% a quarter
[47:14] because if it keeps doing that, I do
[47:17] believe like you said six weeks ago,
[47:19] you're talking to people in Korea. It's
[47:21] like they used to be a big player in
[47:22] Bitcoin. Not there. Retail will migrate
[47:25] to what's working. And right now,
[47:26] Bitcoin is in a bare market. We need to
[47:28] see it change. And I'm gonna emphasize
[47:29] this point again and again.
[47:32] Never believe you're smarter than the
[47:33] market. Ever. The market knows. I had a
[47:36] day on Friday in my own or Thursday on
[47:39] my own portfolio. I finished up on the
[47:42] day.
[47:43] I have 20 stocks that I own including
[47:46] Bitcoin. 18 of the 20 were down. Two
[47:49] were up. Those two, Marll and
[47:52] Entrogress, they made up for everything
[47:55] of the other ones. But I silver was
[47:57] down, Bitcoin was down, Eli Liy was
[48:00] down. All of these things that we've
[48:01] talked about over the time, they were
[48:02] all down. When I'm hoping Bitcoin and
[48:06] these other things are working, it's
[48:08] when there's a pause in all of the AI
[48:10] stuff, but we're not there yet.
[48:12] >> I don't think that uh anything you're
[48:13] saying is crazy. I actually agree. I
[48:16] like Bitcoin here. We'll see what
[48:17] happens. um your video this weekend. If
[48:21] you get any value whatsoever out of
[48:22] Jordy, go to Jordy Visser YouTube on
[48:25] your little Google machine, AI machine,
[48:27] whatever. Go hit the subscribe button.
[48:28] It's a digital thank you, a little
[48:30] handshake. Dap them up, tell them I
[48:32] appreciate all the information. And uh
[48:33] we'll do this again next week. See you
[48:35] next week.