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Linear vs. Exponential: AGI Has Arrived But Oil, Bonds and the Fed Oh My — Transcript

by Jordi Visser · 9,480 words · 1,347 segments · language en · Watch on YouTube

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0:00Let's get to work. Um, it's Friday,
0:02September 11th, 25 years ago.
0:06Uh,
0:08I lost my best friend and the best man
0:11at my wedding. Uh, tonight I am going to
0:14go out with some other friends. So, I'm
0:16going to talk about that briefly, but I
0:18just wanted to uh say I'm thinking for
0:20everyone that lost someone in in there
0:23or remembers that day as something as
0:26tragic as it was for me. Uh I uh thank
0:30everyone for reaching out after I kind
0:32of relayed that story a few weeks ago
0:35when I was still in Maine. So we're
0:37going to go through linear verse
0:38exponential thinking. Uh oil bonds and
0:41Fed. Oh my. I'll continue on this thing
0:43of if you're paying attention to oil
0:46bonds and the Fed, uh you're in a linear
0:49world and you need to focus on AGI has
0:53arrived. That should be the big news
0:54story of the week. It shouldn't be
0:55whether bond yields were up 10 basis
0:57points, whether oil was up $10, whether
0:59the Fed might goes from 65% to 85%. Uh,
1:03AGI has arrived. Uh, I'm going to go
1:05through Astra. I'm going to give you
1:07guys some podcast to get up to speed. I
1:09am going to show you how to build a
1:10trading system using it and especially
1:13for your kids. I created a subscriber
1:16video uh this week after I built one
1:19myself. I'm going to go through what I
1:21did, what you guys can do, uh, how you
1:23can attach an AI agent to it using Mumu,
1:27Robin Hood, Interactive Brokers, you
1:30three, reach out to me. I'm trying to
1:32help your people be able to do what I'm
1:36going to show and connect it in there so
1:38that they can start building systems,
1:40even if it's paper trading at this
1:41point. The amount of entrepreneurial
1:43success people will have by being able
1:45to do this will blow them away. It will
1:46empower them significantly. Of course,
1:48there's bad news. Robin Hood, we'll go
1:50through a question that I get asked all
1:52the time, which is hard to answer for
1:55people. How to value Ethereum and the
1:56crypto ecosystem. So, uh, Christopher
2:00Shawn Kaitton. Shawn Kaitton who worked
2:02at Caner. I'm sure there's people that
2:04over the years had, uh, met him. This is
2:06a photo of him on a July 4th. Uh, very
2:11big manquan person. And here is his name
2:15down here. Tonight I will be going out
2:17with these three guys. Um that's me.
2:20This is almost 40 years ago now. That is
2:22a photo of Shawn at my wedding.
2:26Uh so again for people who remember this
2:29day uh in the emotional way that I do I
2:33am thinking about you linear visser
2:36labs. Again you have to make a decision
2:39which side of this you want to be on. If
2:41you're worried about oil bonds and
2:43rates, again, I'm going to keep saying
2:45during these years, the economy cared
2:47about oil bonds and rates. That all
2:50changed beginning in 2008. That is when
2:53the exponential world took off because
2:55of the release of iPhone the year before
2:58and because transfer payments started to
2:59grow and the government really started
3:00to take up its debt. This is when we
3:03exited this point and this started and I
3:06went to Silicon Valley in 2013. I'll get
3:08through that again as I've talked about,
3:10but this is the world we're in and this
3:12is the world that has been making money
3:14since 2008. You wanted to be in the MAG
3:167. So, I figured by now people would
3:19have learned their lesson about caring
3:20about where oil was, where rates were,
3:22where all this stuff was, other than
3:24again, I get it traders. But on a day
3:26where we had higher than expected core
3:29inflation yesterday, we had higher than
3:31expected PPI, the probability the Fed
3:34went up, crude oil went through, the war
3:36is getting worse, and over the two days,
3:39as of when I started doing this, the S&P
3:41was up slightly. So, how do these things
3:44actually matter if they don't matter? So
3:47again, the news is focused on this. This
3:50is a linear world. These are things that
3:52mattered when housing and autos were
3:54driving the economy. AI capex is driving
3:56the economy. And as I showed last week,
3:59it is not at all rate sensitive. Uh the
4:01Fed rate hike odds surged to 90%.
4:07Jackson Hole from Timuros. I think this
4:10the reason I put this in there is the
4:11market is testing you, Warsh. This is a
4:14double dog daring you. This is straight
4:16schoolyard. The market is fighting with
4:19wars and bessent which I think is just
4:21great because more importantly I think
4:23people should be looking for ways to
4:24make money on the linear on the
4:26exponential side. But again that's just
4:28me. That's why I'm doing these videos
4:30because I think you guys are here either
4:32to at least know what's happening in
4:34that part of the world but also some of
4:36you want to make money on it. Uh the
4:38third mandate moderate long-term
4:40interest rates for the Fed. Just always
4:41keep this in mind that Trump clearly has
4:44got Bessant to be fighting the market in
4:46a way that Trump would fight the market
4:48participants and Worsh isn't fighting
4:51people but at the same time he was
4:53chosen by Bessant and Trump and they
4:57don't want rates higher. So we'll see
4:58what happens. Uh Besson's upsized
5:01buybacks get hit. So he goes to six
5:03billion and the market immediately sells
5:05off again. Good news hit with bad news.
5:10So that means the market's acting badly,
5:12but the S&P's up over the two days. Is
5:14it talk time to talk about plan B? If
5:17this doesn't work, they'll just cut
5:18long-term issuance outright.
5:22I mean, Besson is trying to be as
5:24obnoxious as possible. Um, I am the
5:26House now. Underscore his level of
5:28engagement on economic policymaking in
5:30Japan where he has coordinated with
5:32Japan finance minister again why
5:34fighting the government is the best
5:36trade. He's speaking out against the
5:39Bloomberg terminal bros. The arrogance
5:42stuff is coming out for the week. The
5:45S&P
5:47we're holding the 50-day for now.
5:49There's nothing much going on. Again,
5:51this looks more like a flag formation
5:53after a big high. We had this one here,
5:56then we went sideways, then we went up
5:57again. As I mentioned last week, we're
5:59barely up since June 2nd. So unless the
6:02economy is going to fall off and
6:04earnings are going to fall off, as far
6:06as I'm concerned, we can keep doing this
6:08for a while. But if you look, we did
6:10this rip and then pain here. We did this
6:14rip and then pain here. Guys, I showed
6:17this with Nvidia. Get used to the fact
6:19that when this just rips, it's going to
6:20rip for three days just when you're
6:23feeling like it has no chance of
6:24ripping.
6:26Here are the facts. Revisions this week
6:2932 up there. This is the 20week average
6:32of revisions.
6:34Here's PMI. The leading indicators are
6:36doing great. HYG relative to IEF, the
6:40proxy that I'll use real time and the
6:42one that I care the most about as an
6:44overlay rel instead of spreads. Two, the
6:48S&P had a huge ripper week. HYG up
6:52relative to EF, meaning as bonds are
6:54selling off, HY is not. Here it is
6:57overlaid with the S&P. If you go back
6:59and look at this in 2022 when the Fed
7:01was aggressively raising rate hikes as
7:02the S&P was going down, this was going
7:05down despite rates going higher. So
7:07again, the proxy for the equity market
7:09with credit completely fine. And as I
7:11said last week, bond va's not moving,
7:13junk spreads aren't moving. Uh any part
7:17the inflation expectations via tips not
7:20moving like the market is saying h we
7:22don't really care about what's going on.
7:24But the aida and the emotion in people
7:26is AI thematic portfolio. My portfolio
7:30uh breaking above the 50-day today.
7:32We'll see if it can get going. Um we're
7:35still doing the low V consolidation
7:38here, but we've already broken the
7:4050-day on what I consider the most
7:41important part, which is my 10 name
7:43concentrated one of the 10 names that I
7:45feel are the best by different
7:48groupings. So, if you guys haven't done
7:51it yet, I'd go look at it because it
7:53broke above the 50-day and it's getting
7:55close to the August highs.
7:57The names are all acting well. Bitcoin,
8:01well,
8:02flag
8:04range trading, Ethereum
8:08break, we'll see if it can continue.
8:09Broke broke back in before today's
8:11close. Uh, but again, I've said it
8:13before, I think Ethereum should be
8:14outperforming Bitcoin when we're
8:16actually in the bull market. uh because
8:17the ecosystem and the network effect
8:19should be the critical thing because the
8:20agentic side especially with Astra and a
8:24huge week for Ethereum over Bitcoin
8:27breaking out again to the highest level
8:29since January.
8:31Bessent warns nothing else would matter
8:33if China wins the AI race. There is no
8:35day after tomorrow if China wins this.
8:37Why would we fight the AI trade and why
8:40would you fight the bond side? Go with
8:43what he's saying. you don't have to go
8:45buy bonds because that to me is not a
8:47good idea. But I do believe fighting the
8:49AI trade is a bad idea. So again, do you
8:52want to be a linear side of my V or do
8:54you want to be the exponential side? You
8:56guys make the choice. But again, this is
8:59the big news of the week. We've talked
9:01about AGI. We've heard about AGI. Jensen
9:03Yuang, the godfather of AI, said AGI has
9:06arrived with Astra.
9:09The moonshot's portfolio covered it well
9:11and again 100,000k
9:15is what basically Astro was trained on.
9:17The next model is four times the size
9:20and behind that the Vera Rubins. Why
9:23fade this guys? Why? Why? The IQ is
9:27going through the roof and we're doing
9:28things unthinkable. So it was trained on
9:32100,000. They say research agents are
9:34now generating 3.1 workdays for every
9:36human workday. They hit the Navier
9:39Stokes
9:41challenge which mathematicians have been
9:44trying to do for a long time by using
9:4610,000 AI agents working in parallel for
9:4888 hours. So we hear about the agents
9:50working together on the negative side.
9:51This is then solving some of the world's
9:53greatest problems which have huge
9:55implications for physics and as I'll
9:58show huge implications for the PE of the
10:00S&P 500 going up five years. Compute can
10:02increasingly be converted into
10:04intelligence. Intelligence can be
10:05multiplied into thousands of agents. So
10:07again, more compute, higher
10:09intelligence, more intelligence, more
10:11agents. We're at the critical point
10:13where this is where we were in October
10:18of last year. We reached the point of
10:20high enough IQ to move into the second
10:22side. Those agents can be put at
10:25problems like the Navier Stokes which
10:27get us closer to curing drug disease at
10:29a mass scale solving problems for energy
10:32solving all physics pro like we start
10:35getting into the things that it's all
10:36built on and that's where we are now the
10:39agentic side means a big change and
10:42that's why I talk about crypto so much
10:44it's why I talk about other parts which
10:46we'll go through but we need more
10:48compute for that and we are nowhere in
10:51the compute side so we need a lot of
10:53GPUs and that's why GPU prices just
10:56refuse to go down.
10:58Now the way GDP changes more people plus
11:01more capital plus higher productivity.
11:03That's what the formula has always been
11:05on. But with AI a new possibility shows
11:08up. We have the human labor. Same thing
11:10up here. We don't need more people
11:11though because we now have digital labor
11:13and we actually have accelerating
11:14productivity because we not only have
11:16more of these to replace these but as I
11:17showed these work at three to five times
11:19this. This is my whole if you just take
11:22weekly hours, go through the economy for
11:24human beings, you add in the lunch
11:27breaks, the smoking breaks, the flirting
11:29breaks, and everything else that goes on
11:31and the daydreaming and not working.
11:33Just go back to um the office and go see
11:36how much time was wasted. Agents don't
11:38do that. They have no need for that.
11:40They also have no emotions from a
11:41trading side, which I'll get through.
11:42The old constraint on GDP was ultimately
11:44the number of humans and the
11:46productivity of their time. The new
11:48constraint may increasingly become
11:50compute, energy, and our ability to
11:51deploy intelligence. The reality is GDP
11:54productivity already is accelerating.
11:56It's seen through profit margins at this
11:57point. Forget the economist trying to
12:00figure this out. The model of GDP is
12:04wrong. You can't say that GDP, the index
12:07created in the 1930s to measure
12:09industrial production, is the right
12:12metric to be using to say productivity
12:14is not higher. Think about it.
12:15Productivity is an output of GDP. GDP
12:19doesn't count IP. G GDP doesn't count
12:21lots of things. That's why we change it
12:23all the time. It doesn't know what's
12:25happening. Navier Stokes importance. I'm
12:28not going to take you through all this.
12:29The reason I wanted to show this is
12:31because Navier Stokes, which I knew
12:34nothing about until two days ago, but I
12:36spent a lot of time, as I always do,
12:37when I hear something that they say is
12:39really important from a physics basis
12:41because it gets us closer to
12:44solving things in energy,
12:45transportation, compute, manufacturing,
12:47again, efficiency, medicine, climate,
12:49and more. But more importantly, I've
12:51talked about this, the PE of the market,
12:54which is is not here, but I want you to
12:56think about it. The economy gets bigger
12:58because of science break breakthroughs.
13:01So the total economic size gets bigger.
13:04More energy, more transportation, more
13:05compute, more manufacturing. Go spend
13:08time on why that's the case. Again, we
13:11get to a point where the TAM gets bigger
13:14at the same time that corporate duration
13:17gets shorter. This is terminal value. So
13:20we've already gone through this episode
13:21for
13:23software companies. We're kind of going
13:25through it already in hardware with
13:27Nvidia trading at such a cheap PE.
13:29Multiples are going to compress because
13:31terminal value, the ability to know when
13:33a company will have a cliff of their
13:36earnings no longer growing. And that's
13:38all it takes. Because once AI disrupts
13:41your business and your earnings are no
13:42longer growing, where should your
13:44multiple be? Should it be one? Where
13:47should it be if you're not growing
13:48anymore? That'll be a question that's
13:50going. And I know human beings won't
13:52want to buy anything that's not growing.
13:53So you're left in a situation that's
13:55there. Now if they're not growing, the
13:57only way they want it is the usefulness
13:58of the community and things like that.
14:00Again, it gets back into crypto. It gets
14:01into a mindset change which is happening
14:04with younger people. It's never going to
14:05happen with older people, but older
14:07people will get recycled with the newer
14:09people. So this is something important
14:11to think about because solving Navier
14:13Stokes leads to the ability of having
14:16and I'm just going to go through that.
14:17You can read all the different parts of
14:19what this means. I just want you to know
14:21it means better turbines, better
14:22aircraft, better cooling systems, better
14:25ships, better reactors, better
14:27batteries, industrial products, and
14:28more. Things just get more efficient. It
14:31changes everything. If you want to go
14:33read more about the people who know
14:36what's coming and then let their
14:38economist translate into what's coming,
14:40go to the economists who actually see
14:42the data. Most economists have no idea
14:45what models are coming up. The
14:46anthropicus economists do. So go read
14:49their economics team. I know everyone's
14:51going to read the Goldman Sachs one. I
14:53know everyone's going to read the Morgan
14:54and Stanley one. I know everyone's going
14:55to read all these different ones and
14:56they're going to listen to the rate
14:57forecast and they're going to go through
14:58this and I'm arguing that none of that
15:00matters because it's all linear thinking
15:02and that is the truth from my side. The
15:05truth Greg Brockman from OpenAI spoke.
15:08He's a boring guy but if you want to go
15:09listen to the interview it's only 20
15:10some odd minutes 24 minutes to be exact.
15:13On there he gives a description of what
15:16Astra is. So Astra AGI is here. He talks
15:20about it. I highlighted the different
15:22things you can go. He describes OpenAI's
15:24direction as merging chat. That is the
15:26one that almost everyone uses at this
15:27point with agents. Almost no one uses
15:29this with desktop. Almost no one uses
15:31this. Codeex, no tools, no applica. All
15:35of this in one place. So you can now use
15:37Astra in this way. So I've been talking
15:40about the fact that Grockbot allows you
15:41to use agents. Well, guess what?
15:44It's not the same user face. It doesn't
15:46look like a fun video game with your
15:48little agents running around, but you
15:52can use agents in this as they did. And
15:54that's where this all changes. And I
15:56will get into a little bit of this when
15:57we get into a trading system side. Uh
16:00image models, everything along those
16:02lines in one system. This is the
16:04critical point for you, for your
16:05children, for everyone who wants to get
16:07better, who wants to follow on the path
16:09of me spending all of my time on AI,
16:12wants to use it for work, wants to use
16:13it to build things, wants to have an
16:15entrepreneurial mindset, and wants to be
16:17empowered. So, if you don't like your
16:18job as an accountant, if you don't like
16:20your job in any kind of knowledge work,
16:22this is the point where you want to
16:23start paying attention.
16:25Greg Brockman, we're really trying to
16:27empower the individual to make it so
16:28that you can have superpowers, you can
16:30accomplish more. And I think that really
16:31trying to benefit people, empower
16:33people, build tools that can really help
16:34you in your daily life. That's what this
16:36thing does. So I did this on the video
16:40series. So for those of you who are
16:41subscribers who've never watched the
16:43video series, if you have access to it,
16:45um I did a five six-part video series
16:49which is all about develop developing an
16:51AI entrepreneurial mindset. For those of
16:53you who are not subscribers, this is
16:55where I would start is I would get these
16:58and basically be in the position and
17:00have your kids go through it. I think
17:02this is critical especially for 15 year
17:04olds and above. Let's say 15 to 24. I
17:08also think it's very important for
17:09people that don't like their jobs at
17:11this point. But anyone who wants to
17:13develop a new mindset to ask, to find,
17:16to build, to test, to fail, to learn, to
17:18adapt, to repeat. This is all what I'm
17:20going to show you in the new video,
17:22which is about how to build something
17:25from scratch and use the tools without
17:27needing any coding. I did 90% of the
17:31work for the first save, if not 100% of
17:33the work, but 90 plus% of the work and
17:36AI can do the rest. Um, and I talk about
17:38that in the video. It's an hour and a
17:39half video. It does a combination of
17:42walk you through slides to explain what
17:44I'm doing and then go to the place where
17:45the prompts all the prompts you're going
17:47to get all it's 14 different prompts you
17:51will have this thing and you're just
17:52opening something that I built that I
17:54saved on GitHub. So this will bring
17:57empowerment you will feel a sense the
17:59same way I did when I started to use AI
18:01in a really big way with code two years
18:03ago. I immediately felt like I had a
18:06superpower. It gave me agency to build
18:09my own business which is what I started
18:11guys. So the YouTube and all of that
18:12came after I took Python and after I was
18:14able to manipulate AI in a way through
18:17very basic stuff but know that the
18:19models were going to get better to where
18:21verbally I could just say this and I
18:22didn't need to speak as I like to say in
18:24the video. Coding to me was Chinese. I
18:28could not understand it and so I had to
18:30have other people translate for me. I
18:32don't need that anymore and it leads to
18:33entrepreneurship and you want to be an
18:35entrepreneur right now because of that
18:37duration of corporate moes that I
18:39mentioned. If you work for a company
18:41that company will be in trouble. So I
18:44would say the majority of you work for
18:46companies that need to fire people not
18:49because hey we're using AI and our
18:50business is thriving. They need to fire
18:53people because they're under pressure.
18:54And they're under pressure because AI
18:56can do these things all the time. And I
18:58know that because I'm doing it that way.
19:00Astra is the most dangerous AI model
19:02right now. I'm getting into something
19:03here. These came out and this is what
19:06triggered me on a journey on Monday,
19:08Labor Day of this week. Yes, Labor Day
19:09on a holiday. I was going through, I
19:13just worked out and I started on the way
19:14back, I saw all these things and I
19:16immediately went back and said, "Whoa, I
19:17want to build some alpha strategies.
19:19This is cool." Now, I've built alpha
19:21strategies before, but when I read
19:23through these, this was completely
19:25different. And so I uploaded these, got
19:28the explanation, I uploaded this, I
19:30uploaded this Jane Street intern openly
19:32shows on Reddit, but all of this stuff
19:35to me, got uploaded into chat GPT. And
19:39you'll be shocked if you just take my
19:41computer screen, take your snipping
19:42tool, if you're on a uh a ThinkPad or a
19:46Microsoft thing, you know that think
19:48that snipping tool. If you don't, just
19:50go in search snipping tool, take a a
19:53snapshot of it, and then go stick it
19:55into chat GPT and say, "Can you rebuild
19:57this?" Now, if you don't have Astra,
19:59it's not going to work the same way.
20:00Astra is part of the bigger package, but
20:03I think most people at this point have
20:05some access to it. If you don't, you can
20:07find out how to get access to it. Astra
20:09ran six AI agents on my trading account.
20:11Probe was one of them. Prism was one of
20:12them. Again, this is why I said this is
20:14basically the same thing as
20:17Grock. I put $500 in, $5,100 in the pot
20:20by the morning. Now, I could care less
20:23about these back tests and people making
20:25money. I don't care. And that's one of
20:26the things I go through. The great thing
20:28about a back test is it should fail most
20:31of the time. And to build an AI trading
20:33desk,
20:35the system is designed to reject almost
20:37everything. This is what I love most
20:38about this
20:40ideas
20:42found. So, thousands of ideas every day.
20:45This is the critical way to getting to
20:47something that works is the filtering
20:49process. Look at it. Many many ideas 99%
20:53rejected.
20:55The the balance of the 1% makes it
20:57there. Then it gets 90% of those get
20:59rejected. By the time you get to the
21:00end,
21:02you have models. Now again, if you're
21:04wondering how, let's say this here is
21:08Millennium
21:09deciding, and I saw this firsthand with
21:13my hedge fund or the hedge fund that I
21:15worked at that closed down. Okay, we
21:18like this, we don't like this, we want
21:19this, we don't want this. They go
21:21through and they're looking at ideas and
21:22they're looking at data to support it.
21:24It's some back test because they can't
21:26see the actual people and what went on
21:28on a daily basis. They can get daily
21:30returns, but they don't see what
21:31responded, what happened in their space,
21:32whatever the case. They're just trying
21:34to minimize the chance. So, they have
21:35their own process. Everyone who's
21:37figuring out who to hire people to get
21:39returns has it there. If you use AI and
21:42then you get one and you get two and you
21:44get three and you get four and you
21:46combine them all together and they're
21:47all uncorrelated, you're basically
21:49creating a mini multistrat. So, again,
21:51for anyone who wants to build not only a
21:53trading desk, but wants to build a
21:54system,
21:56you can do that. You really can because
21:58the agents can replace the humans on the
22:00trading side and I'm telling you the
22:01lack of emotion will be better. They
22:04will develop the skill set that's there.
22:06I believe for most human beings like I
22:09showed that V where everything changed
22:11as of the great financial crisis. We're
22:13at another kind of point of the
22:14exponential cycle. So what you learned
22:16over the past 10 years is not going to
22:18be as helpful as responding today.
22:20That's why I think momentum becomes a
22:22dominant factor and why I wanted to go
22:24do something my own. So one of the edges
22:27that I still think human beings have is
22:29on those ideas side
22:32what I did is wanted to build a
22:33technical system of when to buy things
22:34with inside the thematic portfolio. So
22:37for those of you who've asked for these
22:38things who've looked for trading signals
22:40who take the technical side with all of
22:42the data I give you and then want to
22:44look at the ratings and be like well
22:45this thing said buy. No thing doesn't
22:48tell you what to do. Yes, it'll give you
22:50some number of what it believes is a buy
22:53signal without any kind of a really deep
22:56algorithm. What I wanted to do is go
22:58back test things and just say okay based
23:00on what has happened over the past 5
23:03years, 10 years, nine years, what's in
23:06trend, what's resetting. So I created
23:08what is basically out of trend resetting
23:11coiled trending structural trend sign
23:14and this is all based on my belief of
23:16what's happening in the market. So, I've
23:17talked to you guys about market
23:18structure changing. I've had lots of
23:20conversations with the biggest mutual
23:21funds and hedge funds in the world about
23:23this. They seem very interested in how
23:25market structure is changing. They don't
23:27know why in their head, but they
23:30understand that it is changing because
23:32it's getting harder to make money in a
23:35consistent way without getting out of
23:39stuff ahead of time. So, it's making it
23:42more challenging because I believe
23:44what's going on is you're later to
23:46things then they get so far overbought
23:49they make perfect sense and like I did
23:51with the AI trade. I used what had
23:54happened because I believe the critical
23:56thing is select the hundred stock
23:57universe. So, take my hundred names. I
23:59believe those hundred names are going to
24:01benefit from the AI buildout over the
24:03next five years. The infrastructure
24:04needs, the compute needs, that is a
24:06capex trade. Those are the names that
24:08are going to benefit. Now, I think most
24:11of them will do what they've done. 80
24:13plus% are above the 200 day moving
24:14average with their 200 day moving
24:15average pointed upward. Great. I think
24:18overall that's going to create alpha.
24:20That's a structural bull market. I don't
24:22think you're going to get what you saw
24:23in the first quarter again. So, like
24:24I've said before, I don't think people
24:25should expect Micron to go back to to do
24:27a 5,000 from here over the next year,
24:29another five bagger. Do I think uh
24:312,000's possible, 1,800, 1,700? Let's
24:35say 1,600. We're at a,000 right now. you
24:38wouldn't take 60% on the name even
24:40though it was a 12 bagger before. Um, I
24:42think it's going to be really hard to
24:43find those names because like I said,
24:44multiple compressions coming. So, I
24:46think it's great that the multiples are
24:47compressing for Nvidia and Micron. I
24:49just don't think you're going to be able
24:50to make money on them the oldfashioned
24:51way of being in there and they go up all
24:53the time. I think most days they'll be
24:55either down or flat. Uh, and at the end
24:57of the year, maybe 5% of the rally, the
25:00days will be the rallies you need to
25:01miss. And if you miss those five days,
25:03you miss the whole move. So what I did
25:05is I said rate of change matters. What I
25:07care about is the structural uptrend and
25:09then I'm looking for a resetting. This
25:11is what the midcycle slowdown was. This
25:13is when I got out of micron way before
25:15the top. Then after that's happened I
25:18want to see coiled on deck. Now to do
25:20that I used ATR. That's what started
25:22this whole thing. Average true range
25:24which I've talked about. Um it's part
25:26it's a major part of the model. So's
25:28rate of change get coiled. Then there's
25:31an ignition. What's the initial point?
25:32what treats a breakout and then we're
25:34trending again. So, I'm looking for
25:36structural bull markets. When things get
25:38overdone, I want to basically be out
25:41based on rate of change and then I want
25:43to wait for them to reset. And I'm
25:44looking constantly for ideas within the
25:46space that way. I think you guys are
25:48going to enjoy it. This is the theory
25:50behind it. I'm not going to read you
25:51guys because it's just resetting some of
25:53the things I said,
25:55but the back test looks great. So, I'm
25:57I'm going to give you the end result
25:59signals on that. At the same time,
26:03I did a subscriber video. Like I said,
26:05it's basically on the theme of a
26:07treasure hunt. Uh, this is everything
26:09that comes in it. So, you know, you're
26:11going to get code, you're going to get
26:13prompts, you're going to get a research
26:14log, tools, this because it's all on
26:15GitHub. I put the whole thing in GitHub.
26:17Yes, you guys don't know what GitHub is.
26:19I'm going to show you in a second. I
26:21also built in Socrates mode for you. So,
26:24again, this is what you're going to be
26:26able to do. So, subscribers who are at
26:27this level, you're going to get access
26:28to it. use it. Here's what GitHub is. If
26:31you don't know, and I use that Chinese
26:33analogy for my life having data
26:36scientists, I needed them to basically
26:38be able to go into GitHub, which is a
26:40library of code. So, you don't have to
26:42reinvent the wheel. I go through this
26:45and show you how you can go in there and
26:47if you're an accountant, show me aic
26:50code accounting so I can be get
26:52superpowers in accounting so I can
26:54develop my own skill of knowing how to
26:56use a AI to be able to do more
26:59accounting work for my company without
27:03needing to lose my job. How do I use AI
27:05to do this? How do I help them? All of
27:07these things or how do I go set up my
27:09own business? Whatever. But this gives
27:11you coding in so many different things.
27:13It is not just the finance side, but I
27:15use the finance because back testing
27:17something I think everyone wants.
27:19Everyone wants a treasure hunt. They
27:21want to think that they've created
27:22renaissance. They've created all this
27:24stuff. And believe it or not, guys, you
27:26can have a trading system that can make
27:28you money going through the thing that
27:31you do. And you can keep coming up with
27:32new eyes, new ideas, new ideas, new
27:34ideas by listen to Stan Duck Miller. Go
27:37read a book on a chartered technic
27:39technical analysis. Use Demark. I don't
27:41really care. Whatever it is, go listen
27:43to someone who's made money over time
27:45and take the little parts they want and
27:47create your own strategy. You can make
27:49money in it. And again, it may not be
27:51scalable to run it at a multistrat in
27:53big size with a billion dollars, but
27:55there's plenty of strategies that you
27:57can do. And I believe AI can continue to
27:59find new strategies at small levels.
28:01This is one of the things with
28:02tokenization. You can do crypto as well.
28:05So, as long as you have good data, you
28:06can go through it. So, it starts with a
28:07question. We go to GitHub. We had our
28:11own idea. We test it, tried to break it.
28:14This is actually what happened in the
28:16video. And then we learned how to fail.
28:18And this is the golden side. You're
28:19basically learning how to fail and then
28:21restart and go through it again. When
28:24you find one that works, this shows you
28:26all the ways to kind of go through the
28:28promise, go through the progress using
28:30AI. It will take you through so many
28:33levels that are hard to do or hard to
28:36learn on your own. So, I think you guys
28:38will enjoy it. I uploaded it this week.
28:40Again, for people at Robin Hood, for
28:42people at Mumu, for people at
28:43Interactive Brokers, this will allow
28:46people to do what I have here, come up
28:48with their own trading system, and then
28:51they can upload it, and you guys can
28:52show them how it can be an agentic
28:54trading system on a paper trade. So,
28:56they can see if it works for whatever
28:57period they want. They can then upload
28:5910 more. And that way, they're
29:01increasing the probability. If you have
29:0210 different ones running at the same
29:04time with $100 in each or $50 in each,
29:07well, now you've got kind of a little
29:08mini multistrat of different strategies
29:10going on at the same time, you're
29:12starting to get empowered and you're
29:14starting to build something. And more
29:15importantly, your brain will start
29:16changing because you're developing an
29:18entrepreneurial mindset. So again,
29:21you'll see
29:23me as a pirate in the video. This is a
29:26different version. Um, but again, this
29:29is what it's going to take you through.
29:30This is where the Robin Hood Mumu, if
29:31you haven't seen it, again, these
29:33companies offer a Gentic side. So, I
29:36know the people at Mumu. I've already
29:37spoken to them. I want to find ways to
29:41get you guys to get empowered on this
29:42and do this stuff on your own. Here's
29:44the Aentic trading set from Robin Hood.
29:47Mumu launches Agentic Investing. They've
29:50been doing this really since April 23rd,
29:52but I had a meeting with them last week.
29:53continue to be more advanced on this in
29:55my opinion in terms of trying to do this
29:59allowing paper trading going through it
30:01giving you the API the data prices so as
30:04long as you go in and open an account
30:06with them you're going to have access to
30:08their data so you don't need to use
30:09Yahoo Finance and their data they're
30:11telling me is far better than Yahoo
30:12Finance you guys can go see on your own
30:14and of course Interactive Brokers has
30:16had this for some time too this is as of
30:18June of 2026 so you will learn you will
30:20build you advance and then you can plug
30:22it into a trading platform. It's pretty
30:24cool. I'm doing it with my stuff and
30:28hopefully I'll be able to give you guys
30:30a a look at this in the way that they
30:32have it from the paper trading side. So,
30:33I'm not going to end with this. I will
30:35show this for you guys. And again, find
30:37a GitHub code project that exists that
30:40could help an accountant begin to
30:41incorporate AI, how to do their job.
30:43First, let me know how many you find. I
30:45found at least 13 relevant GitHub
30:46projects that could help an accountant
30:48start incorporating AI into real-time
30:49accounting flows. A few of them are
30:51particularly strong for the message
30:52you're building. You don't have to wait
30:54for someone to build AI for accountants.
30:56It's already being built on a public
30:57GitHub. So again, don't be an AI victim.
31:01Find, build, experiment, learn. Everyone
31:03can do this. If you're young and you
31:05just started at an accounting firm, I'm
31:07telling you, spend the time on the
31:09weekend going through this and then see
31:11if they will let you use it. At a
31:13minimum, you will know where everything
31:15is going. Sundar Pachai, if you don't
31:18learn how to orchestrate agents now,
31:19you'll spend 2027 catching up to people
31:21who started today. That is the truth.
31:24Microsoft plans data center pushed
31:25triple its computing power. I remember
31:28people were saying the AI trade was the
31:30reason it petered out was because
31:31Microsoft's I mean this just never
31:33stops. Demand for Astra is really
31:35unprecedented. 6.2 million views.
31:39They're running out of space for it
31:41already. Now, this is an important one.
31:43These are the H100s.
31:46And I just want to take you back to the
31:48Michael Burries, the Jim Chanos's, and
31:50all the people that said on the
31:51accounting side, this is the thing
31:53you'll never get. So for all those guys
31:55that said this depreciation is a risk
31:59and the reason it's a risk is because
32:00there's no chance the those
32:03prices will go higher. You have to
32:05depreciate those. And saying this is
32:07going to last for more than three years
32:08is ridiculous, especially when the
32:10technology is getting so much better.
32:11The technology is getting better.
32:13Reubens are far better than the H100s.
32:16H100 rental prices are almost at the
32:18same level as they were three years ago.
32:20Think about that, guys. They're at the
32:22same price. We weren't talking about
32:24them making it for six years. We were
32:28talking about Yeah. How can you build in
32:30They're unchanged in three years. So,
32:33this again gets into the fact that the
32:35demand is insatiable. I'll say it every
32:37single time. By now, there's a normal
32:40aging process of chips. They should at
32:42least be down whatever say 10%. They're
32:46unchanged maybe 20%. The normal rate of
32:49what people would have thought is down I
32:51don't know 40% 50% by this time in three
32:53years and they're almost the same level
32:55and scarily they've actually gone
32:57higher. Every depreciation scale assume
32:59assumes a chip to sold lose only loses
33:01value. The market is playing paying up
33:03for it instead. So its rental price is
33:05up 22% on the month.
33:10I take you back to Gavin Baker one month
33:12ago.
33:14His core point was that the market was
33:16assuming GPU rental prices would
33:18steadily fall. Again, this was a month
33:19ago. You see what it's doing this month.
33:21Instead, older GPUs were holding their
33:23value far better than expected. In some
33:25cases, rental prices were actually
33:26rising. Exactly what we just saw. What
33:29he said was, and this is the critical
33:31point, this changes the financing
33:33debate. So this is about how much debt
33:38the hyperscalers will need. The cash
33:41flow estimates for the hyperscalers in
33:43cloud in his opinion are way too low
33:46because of this situation. If cloud
33:48providers generate much more cash from
33:50repricing their existing compute. So
33:52again, think of this side as you buy
33:56tomatoes at $2
33:59and the ability to sell tomatoes has now
34:02gone up to $20. That is the compute
34:05side. So the compute side is using these
34:09GPUs to what you can sell to people
34:11because the demand for the end compute
34:13is so large when it comes out of the
34:15data center that the chips that were
34:17bought to go in the data center have not
34:19had their prices fall yet. So the
34:21margins get really really high because
34:24what they get to do is repric the
34:25compute when the contracts end. So if
34:28they if they bought these at $2 and
34:31let's say the compute was at $3 and now
34:33compute prices are at $6, but they're
34:35still using and the demand for the $2
34:37ones is still there based on the fact
34:39that people were willing to pay $3 for
34:41them. So they get to reset their compute
34:43which was set at $3 to $6. This could
34:47remove hundreds of billions of dollars
34:49of expected credit needs. So again,
34:51whether or not you agree with it, the
34:53market is depreciating GPUs, the rental
34:55market is not, that's the issue. And so
34:58when you look at Nvidia and you look at
34:59the hyperscalers, there is a way that
35:01this can turn into not needing as much
35:03credit and free cash flow going up. And
35:05like I've said before, they have
35:07tremendous amounts of not only demand,
35:11they have cap they they have a capacity
35:12shortage and Microsoft just reiterated
35:14that this week. Now, Paul Tudtor Jones
35:17put out a, you know, a negative piece on
35:21AI. This is not the first time he's gone
35:23through it, and this is not a negative
35:24pace on the technology. He and I have
35:26exchanged emails, uh, over the past
35:28month. I think his, you know, he's
35:31legitimately
35:33engaged with people trying to figure out
35:34what's going on. And what's happening is
35:38shocking. And again, that's how fast
35:40things are moving. Greg Jensen warned AI
35:43may need to kill people before
35:45regulation is kickstarted. If you didn't
35:47see Iranian hackers shut down a UK power
35:50plant. Boston Scientific striker drop on
35:52fallout from cyber attacks. So the cyber
35:54attacks were so bad for Boston
35:56Scientific that they had to reduce their
35:58earnings forecast. Anthropic discloses
36:01the fourth AI hacking incident involving
36:03Opus 4.6.
36:06Anthropic says Iran used its American AI
36:09model to target US Navy warships. So,
36:11this is not all positive on AI and I
36:14believe that this hacking situation will
36:16continue. It's one of the reasons why
36:17I'm very positive on crypto as well
36:20because I think AI leads to not trusting
36:22anything and it will not stop the
36:24earnings. It will not stock
36:25productivity, but it will hurt smaller
36:28businesses and smaller companies that
36:30can't protect themselves. So, the cyber
36:34side is increasing dramatically. I've
36:36heard personally many many places uh
36:38through conversations about hit uh about
36:41hackings in bitcoin related wallets and
36:43all kinds of things uh not on the chain
36:46so the chain is safe but the apps that
36:49are on top for everything have become an
36:52issue now way put this out again we're
36:55starting to see the AI adopters again
36:58earnings grow so I think you're going to
37:00keep saying the profit margins go higher
37:03and again I showed this last week I'm
37:04going to say it Again, the market has
37:06never been cheaper or at least in the
37:09last 30 plus years with the PEG ratio
37:12down here. So, everyone who's negative
37:14goes, "Yeah, but this is peak uh
37:16earnings." Well, revisions are still
37:19going higher and we haven't even got to
37:22a point yet where this is falling and
37:23profit margins usually start to come
37:25over first. So, we're It's not like
37:27we're getting anywhere on this. If
37:29profit margins are going higher, guys, I
37:32don't know how if expenses don't need to
37:34go higher. I I like again we're at the
37:36productivity boom point. So I wrote this
37:39paper this week. We're going to move
37:40into the crypto section again very soon.
37:43You guys are seeing this now. About 30%
37:45is now crypto because this is in a bull
37:47market and this is where I want to focus
37:48my attention. So I wrote this on what I
37:50believe is the most important conversion
37:52in the world. The Robin Hood convergent.
37:54Robin Hood is basically the epicenter of
37:57AI
37:59crypto macro nexus. It is a trady
38:03company that has been somewhat involved
38:06in crypto but not making a ton of money
38:07on it relative to its other businesses.
38:10And it's an agentic company. So you guys
38:13should read this for the subscribers who
38:15got it. Uh and for the institutions that
38:18are getting this uh but won't be at some
38:22point soon unless you're subscribers.
38:24Um, again, I'm starting to go through
38:27this in in a very big way, and you
38:29should go read about Robin Hood because
38:30it is your entree into understanding how
38:33to start thinking about it from an
38:35earnings perspective. The chain is now
38:37earnings. Bernstein sees 31% upset for
38:39Robin Hood as fees top Salana.
38:43Robin Hood chain fees record 6 million
38:45in daily fees. Robin Hood chain has only
38:47been live for two months and it's
38:48already starting to rerate the onchain
38:50market. Arbitum, which is basically the
38:53app on top of it, surges 7.87% on Robin
38:56Hood chain. Boom. Uh, Arbitron. What are
39:00they? Oh, see, here's the news. You can
39:03go see it. Now, if you want to go see if
39:05Tradfi is covering it, Arbitron Wall
39:07Street Journal did not match any news
39:09results. Shocking. You're not going to
39:11learn anything from anyone unless you
39:13come to me uh from the Trady
39:16perspective. You can go to CoinDesk. You
39:18can go to crypto which are great places
39:19for this but I'm looking at it from the
39:21angle of merging the three of them tradi
39:24plus AI plus crypto which I think is
39:26critical especially for Robin Hood the
39:29AI agent site is the most important side
39:31uh if you didn't see they strike a deal
39:33with crypto.com the merge is continuing
39:37you want to be long stuff that looks
39:39like this is the pers like I said last
39:42week if you don't know what pers are
39:44please go pay attention tokenized stocks
39:47we continue to move forward on this.
39:51Robin Hood spoke at the Goldman Sachs
39:53technology conference
39:55and here's the five big takeaways.
39:57Aentic trading is going mainstream. This
39:59is from Robin Hood. So this is from
40:00Vlad, a hedge fund in your pocket. Well,
40:02I'm showing you guys how to do that.
40:04Robin Hood chain is about global
40:05financial infrastructure. Yes, it is
40:07tokenization.
40:08I believe if you have an advantage, if
40:10you get into tokenization ahead of
40:12everyone on the Trady side as they start
40:14to jump into this, which they will
40:16because they will need to make alpha,
40:18you're getting in front of the hordes of
40:20money if the Clarity Act goes through.
40:23And it's not a given that it won't go
40:25through and I'll be in DC in two weeks.
40:27I'm hopeful that by then they've already
40:28solved this, but
40:30the Clarity Act has huge implications
40:32from a spike perspective for this and
40:34from an institution of credibility with
40:36pension funds and things like that. So
40:38there's catalysts coming up. Robin Hood
40:40wants the entire financial relationship.
40:42Trading, crypto, retirement, banking.
40:44This is really critical, guys.
40:45Prediction markets are a gateway
40:46product. The bigger message. Robin Hood
40:48is evolving from a brokerage app to AI
40:51native tokenized financial platform
40:53bringing it sounds a lot like Apple to
40:56me. NASDAQ invests 100 million in
40:58Kraken, eyeing the 2027 launch of
41:01tokenized stock trading. Everyone's
41:03preparing. US Bank test stable coins.
41:07Visa stable coin card business is
41:08exploding. European banks plan to launch
41:11a euro stable coin on Ethereum. This is
41:12all this week, guys. Coinbase says clear
41:15US crypto rules are coming with or
41:16without Senate approval. Brian Armstrong
41:18said the Clarity Act is ready to get a
41:20yes vote. Patrick Wit said the same
41:22thing. The probabilities for this year
41:26of getting it through are still below
41:2820%. But that doesn't mean they can't
41:30get a yes vote. So, this is where I'm
41:32going to bring you to the final part.
41:33William
41:35Mogayier
41:36gave a TED talk. I think this was 2014,
41:392015, could be 2016.
41:43Um, no, no offense to William or Bill.
41:46He's very boring. I love finding boring,
41:48smart people. Um, because that means
41:50people don't listen to him. I highly
41:52recommend everyone goes listen this in
41:54TED talks. It's as usual 17 minutes.
41:57This is again a decade ago. him talking
41:59about Ethereum and the important of
42:01Ethereum and the importance of the
42:02blockchain.
42:06He did this a long time ago. Give me an
42:07assessment on how correct his vision was
42:09in what's happening today. He was 8 to
42:1110 on direction but closer to 510 on
42:13specific information which I think both
42:15of those is good to get something
42:16especially when when crypto has had so
42:18much regulatory problems to actually
42:20have an ability of guessing where things
42:21were going to be and to get an eight out
42:23of 10 on direction, five out of 10 on
42:25specific is still good. where he was too
42:27aggressive was removing the intermediary
42:29and this is Robin is a perfect example.
42:32I think this is the way to go through
42:34it. He didn't know about stable coins.
42:36The biggest thing he didn't see was AI
42:39agents and this ironically they may
42:42finally make his thesis work. That's the
42:44whole point. When you listen to this, I
42:46want you to connect AI agents to it.
42:48This is the way I bring you guys alpha.
42:50This is the way that you learn about
42:52this and you get the connection of AI
42:53agents because everything that he said
42:56was assuming humans would use this. It's
42:58not for humans.
43:02This is what his original vision was. He
43:04was a peer-to-peer guy. He was a Napster
43:05guy. He talks at item. I'm going to go
43:08through some other things because he
43:09gives the best talk on valuation for
43:11crypto. And I've been asked by so many
43:13people inside and outside of crypto how
43:15to value it. What happened instead? said
43:17the middleman stayed in but AI and
43:19crypto merge is changing it. So the AI
43:21side is different from this. It is
43:24critical for the success. It speeds
43:26things up. So here's the other one. This
43:28is now about 10 months ago. Ethereum's
43:31endgame.
43:33How to value Ethereum.
43:36He talks about his experience in the
43:381990s and that's critical to this. Now,
43:42I don't know a lot of tech people from
43:44the 1990s who are still involved in the
43:47market. They either made too much money,
43:49they blew up, and they moved to
43:50something else. It's been a young
43:51person's game since the iPhone came in
43:54for the most part. But there are people
43:55that were around. And his point is, we
43:58don't know how we we don't know how to
44:00value Ethereum. It's a new model the
44:03same way there was a new model when we
44:04had to figure out how to value the
44:06internet. And at first, it was eyeballs.
44:08Had nothing to do with earnings.
44:10This will get into my experience with
44:12Amazon as we go through. Then revenue
44:14finally started to matter in here. Then
44:16SAS metrics came, but that's a long
44:18time. That's 25 years before the metrics
44:21came up. There was no SAS metrics. And
44:23that's his point. So here they are.
44:27Now it's about other things. So with
44:29Ethereum and for all of crypto, there
44:32will be revenue. There are network
44:34effects. There's flow of money. And this
44:35is what I talk about all the time.
44:38There's ecosystem value, there's
44:39productive assets, there's so many
44:41things and it's programmable. You have
44:43to go listen to this both podcasts. Just
44:46listen to it. If you don't believe at
44:48that point, it's fine. But then I want
44:49you to go back to Amazon
44:52in 1997 when it was a lowly online
44:55bookstore to where it is now. Not now.
44:58This is 2013. The reason I'll tell you
45:00why I put this up there. So from here to
45:02here,
45:0427,000%
45:07Ethereum right now from its lows is up
45:10about 3,000%.
45:13I really do believe we're going to see a
45:15similar number at a similar time where
45:17someone who's in Tradfi is finally going
45:19to give up and say, "I don't understand
45:21how to value this thing." I didn't
45:22understand how to value Amazon at this
45:24point. I was a macro person focused on
45:26oil. I had made most of my money trading
45:29on being either bearish or bullish oil
45:32being bearish or bullish Brazil, China,
45:34whatever. That was the places that I
45:36made money. My best year was 2008 and
45:39that was being short the US financial
45:42system being what I was called as a
45:44perma bear and being along emerging
45:45markets and along commodities in a super
45:48cycle.
45:49I didn't understand this. And so when
45:52this went back during the great
45:53financial crisis, I figured for sure
45:54this would go to zero because it didn't
45:56make money. Well, it not only didn't,
45:58but it came back faster. And when it
46:00broke out, every single time it looked
46:02head and shoulders, I can remember this
46:04one. I showed it recently. It was
46:05breaking down during the EU crisis. Went
46:07right back up. Guys, its PE never ever
46:12was below 100. It didn't even have a PE
46:14for most of this. So, I went out to
46:16Silicon Valley and say, "How can this
46:17work?" I went to Singularity University.
46:19That's when exponential started for me.
46:21That's when my mind changed. That is 12
46:23years ago. That is why I can talk about
46:24crypto. That's why I'm using AI because
46:26I know you're fading the inevitable.
46:30When did Amazon finally reach a point of
46:32having a PE
46:34Tada. Below 100 for at least two
46:36quarters.
46:38Not till 2017, 2018. It wasn't until
46:422018 that it finally broke below for two
46:44quarters in a row. Again, most of the
46:46time before that, it didn't even have
46:48earnings. You had to measure it on
46:50eyeballs. Yes, truthful. So, when you're
46:52trying to figure out how to value crypto
46:54by the time it gets to the point where
46:56it's no longer a ridiculous price,
47:00you've already lost 27,000%
47:03in 2013. I never wanted to make that
47:05mistake again. For you mutual fund
47:07people, for you people on the hedge fund
47:09world, don't make the same mistake with
47:10crypto if you still want to be involved
47:13in markets from a bull market
47:15perspective. That's my take on the
47:18situation. He wrote a he has a new book
47:20coming out, Trust Shift. I believe trust
47:22is worth a significant amount of money
47:24and I believe Ethereum is the trust
47:26model. So you guys can just go through
47:28it if you listen to his two things. Love
47:30to hear from you, but I would do that.
47:33AI makes trust an economic asset. I'm
47:36100% sure that the blockchain needs
47:39every real world asset to go on there to
47:41keep its value. Trust is becoming an
47:42issue. It is absolutely something to
47:44measure things on. And anyone who wants
47:46trust, it's going to have to go on
47:47Ethereum. It has to final two slides. I
47:51will be in DC. This is the presentation
47:54I'm giving to a variety of people in DC,
47:57not just crypto people, congressmen, the
47:59whole thing. The time mismatch. So if
48:01you want to join me, Freedom Tech DC
48:032026, September 23rd, 22nd, and 23rd, I
48:07will be down there Monday night, Tuesday
48:08night, Wednesday night, coming back
48:10Thursday. Happy to meet up with people
48:13that are there in DC if I have the time.
48:16The Bitcoin Policy Institute's been
48:18great on this. I will be a pub key with
48:20them. This is one of the slides I will
48:22be showing which again this is
48:23tokenization. This is the bridge between
48:25the digital world over here and again
48:29the linear V, the exponential V, the
48:32linear V. If you want to stay over here,
48:34it's great. But this tokenized world is
48:36coming. You're going to cross the bridge
48:37at some point. Why not take a little
48:39mini jump over here and start spending
48:41your time here? And the Wall Street
48:43Journal had Bitcoin's overlooked
48:45promise, freedom. Again, for everyone
48:47who lost someone or was affected by 911.
48:51Uh, I'm thinking of you. It's a 24 25
48:54year anniversary
48:56of an emotional day for me. It tires me
48:58whenever this day comes up to think
49:00about. I am grateful for knowing Shawn
49:02and I'm grateful for you guys watching
49:04me every week. Uh, hit the subscribe
49:06button, reach out, do whatever, but most
49:08importantly, hug the ones you love today
49:10and I'll see you guys next week.

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