# Why Is Bitcoin CRASHING?!

https://www.youtube.com/watch?v=5TTtJBwmmnM

[00:00] There are more AI agents on HTML sites than humans.
[00:03] This is where we're headed.
[00:05] So if you think the world of human beings is going to dominate commerce, it's not.
[00:09] It's AI agents.
[00:11] So if you ask me what is a direct play on that, I believe Bitcoin is a direct play on agents dominating humans going forward.
[00:18] What's going on guys?
[00:19] Today we got a great conversation with Jordy Visser.
[00:21] In this conversation, we talk about what's going on with Bitcoin.
[00:22] Why is it selling off?
[00:23] Is Jordy worried?
[00:25] And is he going to sell his Bitcoin?
[00:27] On top of that, we talk about what's going on with Eli Liy, why he is so convicted that it could be the best AI name for the AI trade.
[00:32] And then we get into a bunch of other second and third order effects of what's going on with the infrastructure buildout, artificial intelligence, so much tokens being consumed, and then how does Bitcoin fit into all this?
[00:42] All that much more in this conversation with Jordy Visser.
[00:45] All right, Jordy, Bitcoin is down 50% from its all-time high.
[00:47] People are freaking out.
[00:49] Michael Sailor sold 32 Bitcoin this week, and people think that maybe he doesn't believe anymore.
[00:54] What's your take as to why Bitcoin has fallen so much and is it over or will Bitcoin recover?
[01:00] So, I learned my lesson that last year
[01:02] not to predict levels on the upside.
[01:04] I'm also not going to predict levels on the downside.
[01:09] Um, last week in my weekend video, I highlighted the difference between a bull market and a bare market.
[01:14] And that's what charts are good for.
[01:17] um we're still in a bare market until that changes and until we start seeing some moving averages start to either point higher, but more importantly, we failed at the 200 day moving average a few weeks ago.
[01:26] We started to go down again all while the stock market was going up nine weeks in a row.
[01:30] So, the good news is Bitcoin's not correlated to the stock market anymore.
[01:35] The bad news is uh it's down 50% off the highs.
[01:41] I wrote a paper last week to yeah last week um in Substack about taking a stoic approach to everything in life.
[01:47] But it's really important with with markets and I think for people that are either a frustrated or b people that are really happy and pounding on X and the bearish thing, this bubble's going to unwind, strategy is going to go bust.
[02:01] This is the way it all ends.
[02:01] None of that's true.
[02:05] opinion uh I also don't believe that Micron can continue to go up every single week.
[02:10] So on one side we have this whole recognition of hardware everything should be bought.
[02:16] We had software go down.
[02:19] Now you've had some of the software names go up.
[02:22] Most of them so people realize are not true software names.
[02:24] They are AI software names.
[02:26] So cyber names and the Bitcoin uh miners and things like that.
[02:30] So I think Bitcoin's been lumped in.
[02:33] Um, I'm starting to write about this more.
[02:35] Uh, you're going to see a lot more from me.
[02:36] I believe we're at a rotation point that's going to last for at least the next 3 to 6 months.
[02:40] And that rotation is we're kind of at a I don't want to say a market stock market bubble.
[02:45] What I'll say is a rotation bubble.
[02:47] We've had one group winning and most groups have been losing.
[02:54] Starting to see a rotation.
[02:56] And I think software is going to have a bid.
[02:58] But I don't think when people recognize what I'm going to say with software, it's going to resonate with them.
[03:03] But the software is not going to be the traditional SAS software.
[03:05] So I think
[03:06] people are going to have to think outside the box on human software and also the financial guardrails with tokenization and everything.
[03:12] And that's where my attention is focused.
[03:14] So I think Bitcoin's fine.
[03:15] Let it break through the 60,000 level.
[03:17] Maybe it goes down even below that.
[03:19] I don't really care.
[03:22] You told me months ago four-year cycle basically was like uh male astrology, right?
[03:28] You're just like, why why does this four-year cycle exist?
[03:30] Who made this up?
[03:32] Why does this thing uh anyone pay attention to it?
[03:33] Are you a believer yet?
[03:36] No.
[03:37] Why not?
[03:38] Again, um first of all, I don't do the same thing with the stock market.
[03:41] One thing I will say is this is the first time in that quote unquote four-year cycle that stocks are going higher at the same time that Bitcoin's going down.
[03:48] And I don't know whether that's good or bad.
[03:50] My whole belief has been that the only time that crypto can go through the growth that I believe it will go through which is the transfer of wealth from the fiat system into the crypto side or at least a merging of the two.
[04:02] That was the whole reason why I focused on AI and focused on crypto for
[04:08] that to occur you need to run to a point.
[04:10] where believe it or not they have to be uncorrelated to some degree.
[04:12] And I think we're at that phase now.
[04:14] So that's the positive side.
[04:16] The negative side is and again the thing that has always protected me in life.
[04:17] We all have views on assets.
[04:18] We all have views and we're all wrong at some period of time.
[04:25] I don't want to get heavily involved with playing Bitcoin or any crypto stuff on the upside until someone else is doing it.
[04:32] I'm not a momentum investor, but at this point, we're not talking about momentum.
[04:35] It's down 50%.
[04:36] So, let it start to base.
[04:39] Let it look like supply and demand have met a place where it's positive and then let it break a long-term moving average.
[04:46] There was something um this week about Charlie Mer uh talking about if I could just have one thing in hindsight, it was the fact that find good companies that you believe in long-term that get back to their 200E moving average.
[04:59] That's the way I'm focused on Bitcoin.
[05:02] I don't remember where the 200WE moving average is, but the 200WE moving average is a
[05:08] really important thing.
[05:09] And again, if you lock it in to what you said, what is the 200WE moving average?
[05:13] Well, that's kind of a 4-year moving average.
[05:15] So, if the four-year cycle is this, it's fine.
[05:17] I've done a couple interviews in the past week, and I just want to say this to everyone.
[05:20] Um, I believe that the IPOs that are coming, what Google did this past week, which I'm sure we'll talk about all of these, but I think these are a sign of something important.
[05:33] It's not a stock market bubble to me, but it is a sign that people need a lot of capital right now for what is happening with inside the AI world.
[05:38] And that's an important story.
[05:40] On the flip side with what's going on with crypto,
[05:45] I think if you would have looked in hindsight for a what would be a sell the news event, very similar to what I think might be happening in the hardware side for the time being, an ETF launch, we're still above where we were trading at the ETF launch.
[05:58] Number two, the US government basically decides that crypto is good and the president of the United States says okay and he launches a memecoin.
[06:07] If you would have taken those
[06:08] events which basically occurred in 24 and 25 and said what would that be?
[06:13] Well, that will be a sell the news event and yet Bitcoin went higher into those.
[06:18] But I think if you look at it and you go back to how many OGs have been selling and what's been going on, I do think there's been churn that's been happening now since 2024.
[06:25] So, for people that are looking for hope, until the charts start giving you hope and you get a it going higher on bad news type thing, I'm not going to get too into it.
[06:35] I'll still stick with the the the the main thing I said, which is we right now have three-month rates that are below inflation.
[06:44] Just wait for the next trend higher in Bitcoin.
[06:45] And I think this will be the one that gets very important.
[06:48] What could convince you to sell your Bitcoin?
[06:53] I I know this is going to um not be the answer people want want to hear, but um there's a reason why all of my eggs are not in one basket.
[07:03] I have plenty of things.
[07:05] So does everyone who's investing own things that are probably going to zero.
[07:09] might sit there and say, "No, that's not true.
[07:11] If you own the S&P 500, trust me, you own some things that are going to zero.
[07:18] Bitcoin is not everything in my life.
[07:21] So, I believe on where crypto is going to go.
[07:22] I have plenty things in my portfolio that I'm going to own forever.
[07:25] I really do.
[07:28] Uh, do I think Bitcoin might go to zero?
[07:30] Sure.
[07:30] It's part of the distribution of outcomes.
[07:32] Do I think quantum is going to do it?
[07:34] Do I think it I think it's a very low probability.
[07:36] So, again, everything in my mind is always based on what my father taught me, which is what do I think the upside is versus what do I think the downside is?
[07:42] And then what percentage of the bets do I want it to be?
[07:45] It's not everything for me.
[07:46] So, if people are sitting there and they have 100% of their wealth in Bitcoin, I think that's very stupid.
[07:50] If they have less than 1%, I think that's very stupid.
[07:52] I believe that it should be at this point in everyone's portfolio at least 2 to 3% regardless of what they believe in.
[07:59] So, that's the way I'm going to answer the question.
[08:01] It could go to zero.
[08:02] I'm not selling any because it's not that important in my lifetime.
[08:06] If it was, I'd probably be going through it.
[08:08] One thing I have said, I've never sold a
[08:10] single one in it, single Bitcoin.
[08:14] I have traded Micro Strategy many many times.
[08:16] Got in, got out, got in, got out.
[08:19] I will trade, but I trade more in uh in Micro Strategy and I really didn't own much Ethereum at all.
[08:24] I've been buying Ethereum during this whole drop.
[08:26] So, I'm happy it's going down because I'm putting bits and pieces in.
[08:29] If we start to trend higher, I'm going to treat this like I did Micron last year.
[08:33] I bought Micron from 105 down to 60 all beginning part of last year and look where it is today.
[08:41] That's the way I view Bitcoin for next year.
[08:43] Jordy, you can't come into the church of a podcast and talk about Ethereum.
[08:45] Why are you buying Ethereum if Bitcoin is so cheap?
[08:50] Well, I'm buying Bitcoin as well.
[08:53] Um, the Ethereum thing again is more of a uh an ecosystem thing at this point.
[08:56] I I really am betting that the network effects are going to be the big story for next year, for the next 12 months.
[09:01] I think Bitcoin is going to be a participant in this whole situation.
[09:05] I don't know if you saw I sent you something.
[09:08] So I am working on
[09:13] having a weekly YouTube that is specifically geared towards crypto.
[09:17] Now to do that I want to convert for the traditional finance crowd how they can look at the crypto ecosystem in the same way they look at the S&P 500 which means some sort of sectors or themes with inside.
[09:29] And so for me Ethereum is a better proxy for that in terms of I want to bet on the ecosystem.
[09:35] I'm not going to bet solely on Bitcoin.
[09:38] But the reality is when I create an equal weight of 40 separate companies, 34 of them being cryptocurrencies or tokens, six of them being public stocks, all as one index, very similar to my uh agentic thematic portfolio, magically it's extremely correlated to Bitcoin, even when you don't include Bitcoin in it.
[09:58] So for me, that means that the ecosystem is acting the way I think it should.
[10:02] It also means that Bitcoin is what I think it is, which is the S&P 500 of the crypto world.
[10:07] So, at some point, the king, it's it's the S&P 500.
[10:10] It's the only thing that lasts at the end of time.
[10:12] And I don't know if we've talked about it.
[10:14] don't believe any idea or innovation in the history of mankind has ever lasted.
[10:18] There's always a new thing that's better.
[10:19] There's always a new way of doing something that's different.
[10:22] Well, that is what stocks are.
[10:23] That is what tokens are.
[10:25] They're ideas.
[10:25] They're innovations by human beings.
[10:27] And if AI is now going to be creating all of the ideas, that means they're not going to be around that long.
[10:30] There'll be something better that comes up.
[10:31] You're going to start seeing this far more rapidly.
[10:34] That's why when people say well what's the bare case on memory I went very easily you think human beings are going to solve the memory side I don't I think algorithms are going to solve the memory side when is that going to happen I don't know but within 5 years I know it will in my head so when Goldman Sachs says 5 years from now we'll be at this I'm like I don't really care that's why I stick myself in the AI world so I I just think for this whole thing when people really think about crypto and they really think about this you have to make a decision on whether you believe still in the long-term story and if you don't you should be out if you still believe in the long-term story, then it's a gift that you're getting to put things down here.
[11:07] I'm not only buying for me.
[11:09] I mentioned to you early on when we started doing this that I have strategic Bitcoin reserves for my kids.
[11:14] This is a blessing to me.
[11:14] My business is
[11:16] growing and I'm able to put more of the profits that I have back into Bitcoin for my kids.
[11:20] So, if it doesn't work out, sorry guys, you guys lost out.
[11:22] If it does work out the way I think it will, they're going to be very, very happy in few years.
[11:27] It's always um I like old school ads because I think that the ad creative used to be very uh thoughtful, very uh kind of bold, right?
[11:33] Um and one of them I think it's uh Philippe PC uh has this entire ad campaign that talks about it's not your watch, you're merely taking care of it for the next generation.
[11:45] And this idea that when you buy this, it is not only one going to last, but two is you were going to pass it down.
[11:51] And so now all of a sudden emotion, family, and all this stuff gets attached to it.
[11:54] very powerful ad campaign for obvious reasons.
[11:56] Um, it's very luxury positioning.
[11:58] But the more that I've thought about that campaign in an investment portfolio, especially when you have kids, you start to think about, well, what if I don't think of this portfolio as mine?
[12:06] I think about it as theirs and what do I want to allocate to resilience and the ability to have durability from a a time horizon really
[12:18] becomes interesting.
[12:20] Now the reason I think of that is because probably the smartest investor that I know who who I don't want to name uh said to me one time that the hardest problem in finance is the intertemporal transfer of wealth.
[12:31] And I was like yeah that's too smart for me.
[12:33] What does that mean?
[12:34] He basically say how do you give yourself money 20 years from now?
[12:36] So this idea again of resilience of durability and historically I think a lot of families real estate has been a great asset for them to do but there are cases where you know Detroit used to be really popular and now all of a sudden maybe the real estate prices aren't what they were at one point.
[12:51] Obviously CO I think really scared the heck out of a lot of um you know corporate building owners in New York City for example right and it's come back but there was a period there where people were were questioning it.
[13:02] I don't know of an asset more than Bitcoin that people have confidence in over some very long period of time, 50 years, 60 years, is going to continue to do that.
[13:11] And so that's what I think I hear you saying as well is like, look, this is such like a long-term thing that there's almost nothing that can convince you to sell it, but you understand that doesn't
[13:19] mean it's going to be successful.
[13:21] It's just the thing that you are playing or
[13:23] the exposure you're buying is almost
[13:25] this like durability in the portfolio
[13:26] over a long period.
[13:28] Is that like a fair way to categorize it?
[13:30] Yeah, but
[13:32] So over the course of the last year,
[13:34] you've gotten to know me and and the viewers and listeners have.
[13:38] You weren't wearing these nice shirts back then, you know.
[13:40] Now all a sudden we got a fashion icon.
[13:44] So I I haven't um this is a Hawaiian shirt and because I'm in this now library.
[13:49] I think we're going to call it the podcast cathedral.
[13:50] That's what I've been thinking.
[13:52] Okay.
[13:55] So I've decided that it needs a little Hawaiian shirt every day until I head to Maine in 3 weeks.
[13:58] though.
[13:58] Um, here's here's the thing I'm going to say.
[14:01] I I spend a lot of time thinking about what the future's going to look like and I take bits and pieces from a lot of futurists.
[14:07] So, I mentioned yesterday that I met Keith Keith Gman and we talked about Kevin Kelly from Wired magazine.
[14:17] Kevin Kelly had a huge influence in me during the 2014 to 2020 period.
[14:19] I read a
[14:22] lot of his books.
[14:24] He's a futurist that called a lot of things directly right.
[14:26] his angle on this and my belief in Moore's law, Ray Kerszswwell, singularity, all of that stuff is why I believe in Bitcoin.
[14:31] I think it's ironic that Bitcoin is as of today, it's a trillion half dollar asset.
[14:37] Isn't it ironic that we have SpaceX coming and it's about a trillion and a half asset?
[14:47] How can people justify buying a company that not only is not making money right now?
[14:53] And forget Elon, let's leave it alone.
[14:55] He's great.
[14:58] But to make the comparison between Bitcoin and space, you're still buying something based on your future thought.
[15:02] And when I talk to people who love rocket investments and I go, "How is that any different than Bitcoin?
[15:09] How do you have any idea on something that is more than 3 years out?
[15:14] How do you know the government won't take over SpaceX?
[15:15] How do you know?
[15:17] There's there's no way to know what the future's going to look like when you're dealing with something that's based on
[15:22] going to Mars, which has never been done before.
[15:24] So, when I think of investments and I think of the future, I have a belief on what I think will happen.
[15:30] I don't think investing in the S&P 500 is safe past 2030.
[15:32] I've said that repeatedly because I think AI will disrupt all companies.
[15:35] So, for me, I don't think Apple's safe.
[15:39] I don't think Google's safe.
[15:41] I don't think Amazon's safe.
[15:43] So when people look at Bitcoin and they don't think it's safe, I understand that that's their belief.
[15:47] The question is, have they thought a lot about the future?
[15:50] Because one of the reasons that I think Bitcoin is safe is because the consumer, human beings will not be consuming more than AI agents in a short amount of time.
[16:03] Now, one of the great things about I know you you know him and you go through, but one of the great things about Moonpay is the agentic side and being able to talk to someone who knows what's happening with AI agents and involved.
[16:12] It came out on X this week that there are more AI agents on HTML sites than humans.
[16:17] Like this is where we're headed.
[16:20] So if you think the world of human beings is going to dominate
[16:24] commerce, it's not.
[16:24] It's AI agents.
[16:26] So if you ask me what is a direct play on that, I believe Bitcoin is a direct play on agents dominating humans going forward.
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[17:46] I agree with you that Bitcoin is a safer bet than any company just given all of the complexities, all the changes, etc. over let's say 20 years.
[17:55] Does that then mean if you get paid for the risk that you take that companies should be more asymmetric and actually Bitcoin should not be asymmetric because it is quote unquote safer and therefore the return profile should be lower?
[18:07] Now here here's what I'll say is happening in the world today and here's where I say Bitcoin actually set the framework for this.
[18:10] So what's another positive thing in Bitcoin?
[18:12] Well, this 50% crash has occurred with volatility collapsing.
[18:18] It's not been because of FTX.
[18:19] It's not been like the volatility is going down.
[18:24] So, Bitcoin's bleeding like 2% a week.
[18:28] It's not going down 15% in one day anymore,
[18:31] but every day we're watching the leading stocks in the stock market move 8 to 10% a day.
[18:36] Every single one of them.
[18:38] We're seeing individual stocks trading at the highest volatility relative to index vault that we've ever seen.
[18:45] And so this is a representation to me that the traders of the world which are very zero date to expiration option related.
[18:51] They're very retail related.
[18:53] It's training people to get re to get ready more for parabas and bubbles and speed crashes as I've written about.
[19:00] That is what I think we're in now.
[19:01] That means that Bitcoin is acceptable as an asset because one of the big negatives was it was too volatile.
[19:07] It's not too volatile anymore relative to the things that are making alpha in the market.
[19:11] So what I see happening is this exponential move.
[19:13] The agentic move is compressing time.
[19:16] And one of the things when I spoke at the New York Stock Exchange this week that I highlighted to people, you have to understand that the MAG7 went from 1 trillion to 20 plus trillion in basically a decade.
[19:29] Isn't that a bubble?
[19:31] It's a bubble except for one thing.
[19:33] It just happened over a longer time period.
[19:36] So if Micron can go from 60 to,00 and then it goes back to 600 and I'm not saying it's going to but if it does was it a bull market was it a bare market or was it both and that's what Bitcoin then all of a sudden maybe these aren't four-year cycles maybe these are now 9mon cycles and we've compress the time and that's what a bubble is.
[19:54] It's price versus time and I'll say it again and again.
[19:57] AI is speeding up time.
[19:59] The exponential age is speeding up time at a pace we've never seen before.
[20:02] So there's a couple pieces of this.
[20:04] Uh first of all, we need more bubbles and we need more billionaires, which I think is uh two ideas that you're getting both of those.
[20:10] Yeah.
[20:10] Both of those ideas, I think, are very uh counterintuitive to people.
[20:14] But the bubbles bring capital and you've mentioned that these companies need the capital to build out the infrastructure for what is going to be the future.
[20:19] Now, with Bitcoin, and I think that Micron and some of these other companies are now experiencing the same thing.
[20:27] And so, uh I actually think that there's a very interesting historical analysis of
[20:30] crypto over the last 15 years or so. It
[20:33] may have been the best training ground
[20:35] to be an investor in any asset class
[20:37] because what you essentially did is you
[20:39] compressed all these market cycles into
[20:40] a very short period of time. Volatility
[20:42] was magnified in in a way that um you
[20:46] know the the stat that I always tell
[20:47] people is uh 50% draw down in public
[20:50] equities in the global financial crisis.
[20:52] >> Bitcoin has gone through that every 18
[20:54] months for a decade. Yep.
[20:55] >> Right. So you just see this stuff over
[20:57] and over. Now, the framework that I've
[20:59] used for Bitcoin, why does it go up and
[21:01] then crash, then go up and crash? It's
[21:03] very similar to like a mobile app. So,
[21:05] if I created a mobile app with you, we
[21:06] want to go get users. We'd run a
[21:07] marketing campaign. 100 people come in
[21:09] and sign up. Well, some portion of those
[21:11] people are not going to stay. They're
[21:13] going to churn. So, let's say that 30
[21:14] turn out. We're left with a net gain of
[21:16] 70 people. We run another marketing
[21:18] campaign. Another 100 people come in,
[21:20] but 30 of those people turn out. Well,
[21:21] now we have 140 people who are left,
[21:23] right? And you keep doing this. And
[21:25] that's basically what we've seen in
[21:26] Bitcoin is you get these big run-ups in
[21:28] price, a bunch of people pile in, you
[21:30] get it kind of bleeds out, some people
[21:31] leave, but you've converted new people.
[21:34] AI is starting to do this now. And I
[21:36] think that's where you see even when you
[21:37] get these big moves and there's some
[21:39] draw down, some portion of those people
[21:41] are not leaving, whether it's passive
[21:42] indexing, whether it's just, you know,
[21:44] longerterm believers, etc. We are almost
[21:47] driving more capital into these
[21:49] businesses and they're setting new
[21:51] floors even if there's volatility in it.
[21:53] And to me that becomes really
[21:54] interesting because as the companies get
[21:56] bigger and bigger, the dollars being
[21:58] invested are getting bigger, but also
[22:00] the productivity is accelerating. Right?
[22:01] You've talked about Eli Liy and a number
[22:03] of these companies where they're just
[22:04] they're good capital allocators and
[22:06] they're able to accelerate.
[22:08] >> And so actually in a weird way, the
[22:10] bubbles are necessary in order for us
[22:13] not only to build out the
[22:14] infrastructure, but it's also necessary
[22:16] to get capital to appreciate for the
[22:20] investor as well. Right.
[22:22] >> Yeah. And and
[22:24] so the the worst part about this, we
[22:26] we're now at a point where when we say
[22:29] AI, let's let's use forever Jensen
[22:32] Snuang's five layer cake. And let's just
[22:34] say that okay, you got the chips, the
[22:35] energy, the infrastructure, the models,
[22:37] and the applications.
[22:40] The only thing that's been monetized or
[22:42] the only thing making money are the
[22:44] chips, the energy, and the
[22:46] infrastructure.
[22:48] There's a problem with that eventually.
[22:50] um this is all about the buildout in
[22:52] preparation for it and like I said you
[22:55] eventually do have to get the revenues.
[22:57] There was an interesting interview with
[22:59] um the head of the Norwegian um
[23:02] sovereign wealth fund and he interviewed
[23:04] I don't know the name of the CEO of IBM
[23:06] but the IBM CEO and the IBM CEO who's
[23:10] obviously
[23:12] been involved with AI as long as anyone.
[23:13] I mean Watson was before Google was even
[23:16] a company. Um he basically said when you
[23:20] do the math and he and he went through
[23:22] it logically he's like a data center now
[23:25] costs and so people hear this in the
[23:27] course of basically 9 months a data
[23:30] center for 1 gawatt has gone from 50
[23:32] billion he was saying it's 60 to 80 and
[23:35] Jensen Yuang said in Computex this
[23:37] weekend it'll very quickly be 80 to 100
[23:41] billion. So you're talking about massive
[23:43] inflation in building this stuff. That's
[23:45] how bad the bottleneck situation is. And
[23:47] it just shows that okay, how are we
[23:49] going to keep building this smart people
[23:51] are going to solve this. But what the
[23:52] guy said is at these costs for the
[23:54] gigawatts for they're not going to be
[23:57] able to make the revenues. Now I have
[24:00] said repeatedly this is not a bubble.
[24:02] But what I do agree with is that DeepS
[24:06] is in direct competition with the model
[24:08] component of this. I'm not sure a
[24:10] generalist model anymore you're going to
[24:12] be able to make the money. I don't think
[24:13] the adoption is going to happen on the
[24:14] enterprise side. You brought up Eli Liy.
[24:17] The reason I believe Eli Liy, and you
[24:20] can mark this down, we can go back to
[24:21] see it has a chance to be the largest
[24:24] company in the world and the number one
[24:27] AI company in the world within 5 years
[24:30] is because they're building a
[24:33] specialized model. And I think
[24:35] eventually people have to realize that
[24:36] they have their own data center with a
[24:38] thousand GPUs with all of the data that
[24:40] Eli Liy has had. There's a hundred and
[24:43] what is it 150 year old company all the
[24:46] failures all the successes all of that
[24:48] data actually matters I've joked before
[24:49] that I don't know if an asset management
[24:51] company's data is as valuable as they
[24:52] think it is but I know that all of these
[24:55] trials and things they started from some
[24:57] intelligence place and if you combine
[24:58] all this stuff and you combine it with
[24:59] Alphafold where they have a partnership
[25:01] with Isomorph if you combine it with
[25:02] their Nvidia co-inovation lab if you
[25:05] combine it with toune lab which is their
[25:08] Google X which means they allow people
[25:10] to use their data center effectively and
[25:13] the only thing they get is the data like
[25:16] they get the access to what's going on.
[25:18] They are creating an innovation hub of
[25:20] using data all for human software. So if
[25:22] I think about who's going to get the
[25:24] revenues well if a drug company can make
[25:26] their entire process of getting the FDA
[25:29] approval efficient and at the same time
[25:31] they can benefit by selling better drugs
[25:33] well they're getting revenue directly.
[25:35] That's an easy one for me to understand.
[25:37] The other ones I don't understand. So, I
[25:39] think people have to realize that in
[25:40] this five layer cake, we're kind of at
[25:43] the point where every dollar that's
[25:44] generating margins in the S&P 500 is
[25:47] commodity related that has inflation.
[25:49] Until we start seeing the application, I
[25:51] think what the IBM CEO said on this,
[25:53] people should go listen to. I don't know
[25:55] if they're going to be able to get the
[25:56] revenues in as quickly as they need it.
[25:58] And that's the issue is if you have
[26:00] bottlenecks and you're spending all this
[26:01] money, you eventually need to get the
[26:03] revenues. And we've seen what Anthropics
[26:05] ARR looks like. The question is if that
[26:07] slows for even a month, what are people
[26:11] going to do? You've been involved in
[26:12] this a long time. If a company is
[26:13] growing rapidly and it's parabolic, if
[26:15] they tweak a little bit, think about
[26:17] what happened to OpenAI over the course
[26:19] of the last year.
[26:19] >> Oh, I was going to say OpenAI showed us
[26:21] what what happens there. So, I want to
[26:23] talk about Eli Lilly a little bit more
[26:24] in a second, but um on this general
[26:25] versus specialized workflow, um we have
[26:27] direct experience with this, right?
[26:28] We're building CFO Sylvia. see the
[26:30] actual specialized workflows and I'll
[26:32] tell you that there are um and I've been
[26:34] talking about this for a couple months
[26:35] now and I think finally it is cracking
[26:36] into the mainstream conversation the
[26:38] single most important thing that I see
[26:40] happening in the AI industry is that the
[26:42] general purpose models were the default
[26:44] no one knew how to build specialized
[26:45] workflows or any of this stuff and so
[26:47] open AI came out anthropic started to
[26:49] push claw everyone basically kind of
[26:51] mandate from heaven to their teams go
[26:53] use AI and people listened and they went
[26:56] and we're now seeing reports of whether
[26:57] it's Amazon or JP Morgan or Uber They're
[27:00] all reporting that they blew through
[27:01] their token budgets, you know, in a
[27:02] single quarter for the entire year,
[27:04] stuff like that.
[27:05] >> But people are starting to question, are
[27:07] we getting the value for what we're
[27:09] spending?
[27:10] >> And they are as AI pilled as they come,
[27:13] but what they're trying to connect it
[27:14] back to is the ROI. And so what we saw
[27:17] at CFO Sylvia is that we actually gave
[27:21] token consumption to the user. So the
[27:23] user was in charge of how much times
[27:25] they queried, etc. So you essentially
[27:27] could think of that as you have uncapped
[27:28] upside for usage of the tokens but we as
[27:32] a company had uncapped expenses because
[27:34] as much as the users want to use it. So
[27:36] then that forced us if we want to keep
[27:37] cost under control to go look at how do
[27:39] you efficiently consume tokens.
[27:41] >> Yep.
[27:42] >> We have seen a significant reduction in
[27:44] the number of tokens that are used on a
[27:46] per query basis for certain things in
[27:47] the back end. All this kind of stuff
[27:49] >> as we went through that process I
[27:51] started talking to many of my friends
[27:52] who run companies or have implemented
[27:54] some of this stuff. They're all going
[27:56] through the exact same thing. Y they're
[27:57] all trying to figure out if I'm spending
[27:59] hundreds of thousands or millions of
[28:01] dollars per year using some sort of AI
[28:04] system, how do I get the same output but
[28:06] get a cheaper bill? It's human nature.
[28:08] It's corporate incentive. And so now
[28:10] what I'm starting to see is all of these
[28:12] companies are becoming successful at
[28:14] doing it and they're all sharing some of
[28:15] the best practices and and the engineers
[28:17] are all talking to each other. So in a
[28:19] weird way it makes Anthropic's revenue
[28:21] growth even more impressive that they
[28:23] are growing at the rate that they're
[28:24] going at the same time that every single
[28:25] one of their customers is trying to
[28:26] become more efficient using their
[28:28] service right so you have like a per
[28:29] customer per token revenue basis is
[28:32] coming down but your overall revenue is
[28:34] growing so rapidly because the demand is
[28:36] just you know insatiable so when I look
[28:38] at that it does split the world into
[28:41] general purpose versus specialized
[28:42] workflow I think that finance I think
[28:45] that healthcare I think there's very
[28:47] specific areas where it's going to be
[28:48] incredibly difficult. And I think that
[28:50] the general purpose models have waved
[28:52] the white flag. They're admitting it
[28:54] because what are they doing? They're
[28:55] creating JVS. They're creating internal
[28:57] teams. And they're basically saying, "We
[28:59] need a biotech team. We need a team
[29:01] that's going to go and we're going to
[29:02] partner with a bunch of PE firms and go
[29:04] do accounting rollups or whatever. And
[29:06] they're essentially saying that their
[29:08] general purpose models are not going to
[29:09] be able to compete on a specialized
[29:11] basis. And so a company like Eli Liy
[29:13] that has a data advantage, has technical
[29:14] capabilities, they've got the
[29:16] infrastructure, it's not hard to see
[29:17] them beating whatever general purpose
[29:20] models are out there for their specific
[29:21] use case, right?
[29:23] >> Yes. And everything you said gets tied
[29:25] up into the same thing. So
[29:26] philanthropic, the cost of building the
[29:28] ability of providing the tokens is going
[29:30] up dramatically. So they have to raise
[29:31] the cost. So users who are very smart
[29:34] are like, "Wait, wait, wait, wait. I I
[29:36] I'm not paying for this." So then you
[29:38] start figuring out ways to not pay for
[29:39] it. So Davin Baker on an interview about
[29:42] a year ago, sorry, about six months ago,
[29:46] it's amazing how fast this is. He
[29:47] literally said the bearish argument for
[29:51] all of the model providers is eventually
[29:53] going to be the edge.
[29:56] So the problem with the edge is the edge
[29:58] is coming sooner than what people think.
[30:00] The data center buildout and the the
[30:02] borrowing of money and the building of
[30:04] this stuff. This is why I keep saying
[30:06] there is risk for every one of them.
[30:08] when you when we talk about enthropic
[30:10] and we're like it's 44 it's not 44
[30:12] billion that's the ARR so like I want to
[30:15] make sure people realize going like this
[30:19] for 3 months does not ensure you'll be
[30:21] doing that for another 3 years and
[30:23] there's a lot of factors and you're
[30:24] naming if you go through all the factors
[30:25] you're saying so let me get their cost
[30:27] of providing that's going higher the the
[30:31] clients using it are like wait my
[30:33] budgets are too high this is too
[30:35] expensive I got to figure ways to do it
[30:36] oh magically I don't need as any tokens.
[30:39] Anthropic doesn't care cuz they have a
[30:40] wait list for tokens. So, they're still
[30:42] growing. But the issue is you're still
[30:44] playing with this game of like, well, we
[30:46] need more compute and they're out there
[30:48] racing to Colossus and to Google and
[30:50] trying to get all this stuff. It just
[30:52] seems I very clear to me that there's a
[30:55] problem with bottlenecks and shortages
[30:57] and oh by the way, the straight of
[30:58] Hormuz is still shut. And I can't say
[31:00] this loud enough. The one thing about
[31:02] prediction markets that people need to
[31:03] pay attention to when you hear all these
[31:05] things of like the straight will be
[31:07] reopened by whatever. If you believe
[31:08] that then go bet on couch sheet because
[31:11] right now for the straight to completely
[31:13] reopen to normal by right before the
[31:17] midterms is less than 50%. So we're
[31:20] getting to the point where all of these
[31:22] bottlenecks are building. And as someone
[31:24] who's a macro person who's focused on
[31:26] the situation of bottlenecks, I want to
[31:29] focus on what Eli Liy is doing because
[31:31] you know what? They don't depend on
[31:33] tokens. They spent the money on a
[31:36] thousand black wells to build a data
[31:40] center to be able to take their data.
[31:43] And so you have to think real hard about
[31:45] why do they have an advantage? Because
[31:47] they are printing money and they can
[31:50] build their own. And so for companies
[31:51] like Morgan Stanley and Goldman Sachs,
[31:53] they're going to have to make a choice
[31:54] at some point. Do I want to pay
[31:56] anthropic or is this a way to get
[31:58] started on this because they were
[31:59] nowhere seven months ago? And that's
[32:01] what I think is happening. There's a
[32:02] combination of hoarding on the hardware
[32:04] side. There's FOMO on both the model
[32:07] side, but also on the enterprise side
[32:10] because Goldman doesn't want to fall
[32:11] behind Morgan, doesn't want to fall
[32:12] behind Bank of America or JP Morgan. So
[32:14] they all have to start spending money
[32:16] because they're like, "We have to do
[32:17] something on this. Oh my gosh, Opus and
[32:19] Claude make it easier than OpenAI. Let's
[32:21] get rid of ChatgBT. But chat GPT
[32:23] enterprise was the biggest thing a year
[32:25] ago. So I think people are
[32:27] overestimating this and that's why the
[32:28] IBM interview is so important to me.
[32:30] >> I recently saw uh one person uh online
[32:34] say that they have completely uh
[32:36] eradicated the use of cloud internally
[32:38] and they've gone to Deep Seek V4.
[32:40] >> Yep. and they believe that not only is
[32:42] it saving them a lot of money, but they
[32:44] also think that it is a better
[32:45] performance in terms of accuracy,
[32:47] latency, etc. Now, it will be very
[32:50] interesting to watch over the next 30 to
[32:51] 60 days if more people do not start
[32:54] saying as part of this, hey, what are we
[32:56] getting for the token, you know, bill
[32:57] that we're receiving? Can I get away
[33:00] with using an open source model that
[33:01] maybe we fine-tune a little bit
[33:03] >> and get 90% maybe even better
[33:05] performance than what I'm getting here
[33:07] with Claude? Now, I actually think that
[33:10] this is a PI expanding exercise and so
[33:14] Anthropic is going to continue to do
[33:15] well. OpenAI will continue to do well. I
[33:17] think XAI is very underrated in terms of
[33:20] their ability to kind of come out of
[33:21] nowhere and and start to get adoption.
[33:23] Um, I also think that whether it's Eli
[33:26] Liy, Revolute is a business that here in
[33:28] the United States people don't really
[33:29] talk about a lot, but it is kind of the
[33:31] Robin Hood of Europe. They probably
[33:32] wouldn't like that term, but but just
[33:34] think of them that way. Is a retail
[33:35] brokerage. they've built their own model
[33:37] and they've used their own data to be
[33:39] able to do it. And so you go and you
[33:40] look at this and you say at the end of
[33:42] the day what people are always going to
[33:43] be incentivized to do is control as much
[33:45] of the stack as possible.
[33:46] >> Mh.
[33:46] >> And if you have a model whether it
[33:49] started as open source that you
[33:50] fine-tuned and you trained or you were
[33:53] able to actually go and do it probably
[33:54] similar to what Eli Liy did, you are
[33:56] going to have such a competitive
[33:58] advantage. It's no different than why
[34:00] are you spending so much money going to
[34:01] every college campus trying to find the
[34:03] smartest new people. you're looking for
[34:04] intelligence, right? Well, what if there
[34:06] is synthetic intelligence that is better
[34:08] than anybody at any college?
[34:10] When I started to think about that, I
[34:12] said, "No wonder young people are having
[34:15] a hard time trying to find a job."
[34:16] >> Mhm.
[34:17] >> Because people are saying, "I can go and
[34:18] I can get this same intelligence in a
[34:20] different way. I don't have to do
[34:21] recruiting. I don't have to do all this
[34:22] stuff." Now, with that said, the young
[34:24] people are getting smart and what are
[34:26] they doing? They're learning how to use
[34:27] the tools. Mhm.
[34:28] >> And so you get this ever moving dynamic
[34:30] environment where everyone is trying to
[34:32] like take a snapshot of the market and
[34:34] they want everything to be black and
[34:35] white. Anthropic is winning, open eye is
[34:38] losing. Closed source versus open
[34:40] source. Young people can't find a job.
[34:42] Eli Liy is screwed, right? Like whatever
[34:44] the snapshot in time is, people start to
[34:46] extrapolate these kind of hardened
[34:48] thoughts. And my conclusion over the
[34:50] last couple weeks is the single most
[34:51] important thing you can do right now is
[34:53] to remain with incredible flexibility
[34:55] mentally because it is changing very
[34:58] quickly and if you try to take that
[35:00] static snapshot you are going to be
[35:01] wrong 3 weeks later and so you've got to
[35:04] stay informed. You've got to continue to
[35:05] update kind of your mental models here
[35:06] and if you do that that's the best way
[35:08] to kind of navigate all this.
[35:09] >> Yeah. The only thing I would add and and
[35:11] I don't know if you felt this and we
[35:12] didn't talk about it but um
[35:16] the LLMs are now commoditized and what I
[35:19] mean by commoditized the price is not
[35:20] zero but the difference between
[35:24] and I won't say all of them but I will
[35:26] say Claude and Chat GPT
[35:31] they're indistinguishable to me in terms
[35:33] of now being able to use them. And I got
[35:35] into a conversation with someone we both
[35:37] know this week who had just gotten off a
[35:39] plane and mentioned something they did
[35:42] and I said, "Oh, I I don't really use
[35:45] Claude as much." And I was the person
[35:47] that said, "You really have to use
[35:48] Claude, not ChatgPT." So people are
[35:50] starting to ask me like, "Are you using
[35:52] Codeex and Chat GPT?" And I'm like,
[35:54] "Yeah, that's my model. That's it now."
[35:56] Now I'm using both of them. But the
[35:59] reason I say they're commoditized is
[36:01] when you interview someone and this is
[36:03] the easiest way for for we've both been
[36:05] in the seat. Let's assume that you had
[36:08] four piece two pieces of information for
[36:10] each of them. Their grades in school,
[36:11] they both went to the exact same
[36:12] college. They both finished with perfect
[36:14] scores. Their SATs exactly the same and
[36:18] their IQ exactly the same. Now, you're
[36:21] going to pick the person not based on
[36:23] that. then you're going to pick it based
[36:25] on the nuances that match with you, what
[36:28] you're looking for, cuz they're not
[36:29] going to be the same person. They might
[36:31] have exactly the same scores on
[36:33] everything, which is where I believe the
[36:34] LLMs are now, at least for Chat GBT and
[36:37] Claude. Now, maybe Claude is slightly
[36:39] better at coding, but I'm not really
[36:41] sure about that anymore either. I'm
[36:42] building stuff in codeex every day. And
[36:44] I'm working on a very long project, the
[36:46] longest one I've ever worked on, and I'm
[36:48] doing it in cursor and codecs.
[36:51] I I'm I'm just going back and forth
[36:53] between the two and it's I'm doing
[36:55] because this one is something for the
[36:57] subscribers that to me is really cool
[36:59] and it it it's breaking it's creating a
[37:01] new structure in terms of in terms of
[37:02] the way I look at the market but I it's
[37:05] indistinguishable. So the reason I've
[37:06] chose chatbt 5.5 is because it is the
[37:10] better brainstorming partner for me and
[37:12] when I meet intelligent people and I
[37:15] love to meet someone who can always puts
[37:19] things in my head that I hadn't thought
[37:20] about. They could speak for an hour and
[37:23] only two things enter but those two
[37:24] jewels are worth so much to me. Chad GBT
[37:27] does it all the time. Claude almost
[37:29] never does it for me anymore. And when I
[37:31] say never it may sound like an
[37:32] exaggeration but for me it's not. I just
[37:35] believe that the the critical things
[37:38] that make my brain go, "Oh my gosh,"
[37:40] happen more in GPT 5.5 and it's not a
[37:44] reflection of the model's abilities.
[37:46] It's a reflection of how it responds to
[37:48] me and can almost feel what I'm looking
[37:50] for better than Claude. It said better
[37:52] at anticipating what Jordy wants and I
[37:54] that's why I've migrated back towards
[37:56] it. All right, guys. Let's talk about
[37:58] something that's actually moving the
[37:59] needle in crypto right now and that's my
[38:00] guys over at Arch Public. These guys are
[38:03] killing it. They continue to lead the
[38:05] way in everything that's got to do with
[38:06] agentic trading. And everyone knows
[38:07] this. Nothing else is being talked about
[38:09] in the market other than let your AI
[38:11] agents trade whatever asset you want.
[38:13] Now, with the addition of Arch AI, the
[38:15] market wave algorithm, and their tax
[38:17] harvest tool, they have turned this into
[38:19] a true one-stop shop for automated
[38:20] trading. They have now over 25,000
[38:23] users. That includes several corporate
[38:25] treasuries, asset managers, and
[38:26] businesses. And so, the testing phase
[38:28] for Arch Public, that is over. They have
[38:30] perfected how to automate advanced
[38:32] trading strategies without ever taking
[38:34] custody or asking you for your private
[38:36] keys. It's a big deal obviously. So,
[38:38] Arch Public is an action speak louder
[38:40] than words type company. That's what I
[38:42] like to see. They give every user access
[38:44] to their platform absolutely free. You
[38:46] get to test it. You run the strategies.
[38:48] You watch the performance in real time.
[38:50] And then only after all of that do you
[38:52] put real money in to go put it to work
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[40:23] That's simple.io.
[40:25] io/p. Go check it out today and see if
[40:28] you should get into the mining game.
[40:30] Usually people see us come on here and
[40:32] talk. They don't get to see the uh time
[40:34] before. That's the most fun that we
[40:36] have. We get to joke around, you know,
[40:38] we talk about what we're going to uh to
[40:40] discuss. Um and today you said something
[40:43] to me that was very interesting. I'd
[40:44] love for you to elaborate, which is
[40:46] peptides are the API key for the human
[40:50] body. Now I have learned throughout my
[40:53] life that there are two types of experts
[40:55] in the world. There are medical doctors.
[40:57] >> Yes.
[40:58] >> And then there are the bros scientists.
[41:00] The bros scientists have been very right
[41:03] for a long time. They are the ones who
[41:06] were talking about everyone should be
[41:07] taking creatine. They were the ones who
[41:09] were talking about you know saunas and
[41:11] cold plunges and you know all of that
[41:13] type of stuff. They have been on the
[41:15] peptide train for a while now and it
[41:18] feels like the rest of the world is now
[41:21] saying, "Oh, peptides, that's
[41:23] interesting." And the bro scientists are
[41:24] saying, you know, "Come into the warm
[41:26] water. We've been here a while."
[41:27] >> Y
[41:28] >> what is a peptide? Why is it the API key
[41:31] for the human body?
[41:33] >> So to I I want to take a step back from
[41:36] just answering this for people at this
[41:38] point. Um
[41:41] you made a comment which I agree with
[41:43] and this is the way Wall Street has been
[41:45] separated. Um people who are not
[41:46] scientists never enter the biotech and
[41:50] pharma world as an investor. Uh and
[41:52] because you can't understand the science
[41:55] but for some reason we all became
[41:57] experts at technology
[41:59] and we think like we know exactly what
[42:02] goes on in a computer and Moore's law
[42:04] and everything else. And the reason we
[42:06] became experts at it is because that was
[42:08] the way we all made money. So we all own
[42:10] Nvidia. We all go through this. So what
[42:12] I know I know what a GPU is.
[42:15] >> I I I the funny thing is why would
[42:18] people know what an API key is? So an
[42:22] API key and a peptide are basically ways
[42:25] to enter into something with a receptor.
[42:29] Meaning I want to do this. I want to
[42:31] take my data from this software that I
[42:34] pay for. I use my a API key. So, it's a
[42:37] door into something. So, the easiest way
[42:40] to do this is for people to learn that
[42:42] GLP1s
[42:44] are peptides. Peptides are growing
[42:47] exponentially. So, if you had Chris
[42:49] Camilo sitting across from you and he
[42:50] was doing all his Tik Tok analysis at
[42:52] nighttime and we said, "Are peptides
[42:54] big?" He'd be like, "Peptides are huge.
[42:56] How do I make money on peptides?" Like,
[42:58] it was a lot of private companies. But
[43:00] the reality is when you start spending
[43:02] time well GLP1 is the king of peptides
[43:05] and its growth is enormous but it's only
[43:08] serving a very small portion. I can't
[43:12] think of a scenario where whatever your
[43:14] view is of GLP1s.
[43:16] Peptides is now kind of what they've
[43:18] been replaced with. GLP1s are a little
[43:20] scary to people but peptides everyone
[43:22] seems to be migrating towards because
[43:24] now they're on every podcast. Now
[43:25] everyone's talking about Google Trends.
[43:27] It's going through the roof. I can't go
[43:28] in any kind of um setting without
[43:31] hearing it. I worked out today. The
[43:33] person at the desk, I know what her job
[43:35] is and she's a health coach. She deals
[43:38] with nutrition.
[43:40] Before I could finish saying peptide and
[43:42] I said, "What percentage of the people
[43:44] that you have as clients every single
[43:46] day come into you and talk about PEP?"
[43:48] And she went, "Everybody." And she said,
[43:50] "This is never ending." And she went,
[43:52] "If you're talking about GLP1s, more
[43:54] than 50% of my clients are on GLP1." Now
[43:57] again, this is Manhattan.
[43:58] >> Are they doing it for weight loss or are
[44:01] they doing it for other non-weight loss
[44:03] reasons?
[44:04] >> At this point, the majority of them are
[44:06] for weight loss. They're not. But she
[44:08] does have a lot of diabetic clients and
[44:10] she does have a lot of pre-diabetic
[44:11] clients. So I don't want to be it's
[44:12] people have money that can afford to pay
[44:14] for these things cuz they're there, but
[44:16] they're growing rapidly. The thing is
[44:19] what Eli Lily and the reason this is so
[44:21] important. So if the decade of 2009 to
[44:25] 2020 was about the app store and API
[44:29] keys, you could argue that API keys were
[44:31] the key to all of the money made by the
[44:33] Mag 7. I believe the pharma industry
[44:36] with peptides has locked into something
[44:39] where again whether it's gene editing,
[44:42] any way you want to go, we're getting to
[44:43] the software side of the body. We're
[44:46] actually getting to the point of
[44:47] understanding this does this to to
[44:49] someone. So Eli Liy has data that is
[44:52] unexplained for them. And if you listen
[44:53] to David Ricks, he'll say, "We knew it
[44:57] was losing weight. We knew it was
[44:58] helping with diabetes. What we didn't
[45:00] understand is why is addiction going
[45:02] down? Why is this going down? They're
[45:04] getting to the part and they've been
[45:05] doing metabolic metabolic disease
[45:08] focused for 100 years. So now we're
[45:11] getting to the point of actually getting
[45:13] to the root cause of problems as opposed
[45:15] to the treatment of problems. And if you
[45:16] get to the root cause of problems
[45:18] through peptides and through receptors,
[45:20] you're now getting into the point where
[45:21] you're putting an API key into the human
[45:23] body to deal with something. This is the
[45:26] beginning of a massive trend because if
[45:28] it wasn't for AI, in my opinion, we're
[45:31] still kind of guessing and going through
[45:33] a long process, but AI helps speed up
[45:35] the process. I'll give you something we
[45:37] didn't talk about. So, you know, there's
[45:39] different phases of trials. So very
[45:42] recently, I think in the last month,
[45:44] maybe it was two months, Eli Lilly
[45:45] stopped
[45:47] disclosing phase one trials they're
[45:49] working on, which is when they're
[45:50] actually using human beings for this.
[45:52] They won't disclose it anymore. Why
[45:54] wouldn't you disclose it anymore? Well,
[45:56] because it's much easier to catch up to
[45:58] IP if you have AI. If you're doing this
[46:02] and disclosing it, it was for investors
[46:03] because they want investors to be
[46:05] focused on it. Well, now what they're
[46:06] worried about is competition.
[46:07] Competition is about AI. So what we're
[46:09] watching in front of our face is human
[46:11] software. The TAM market for obesity in
[46:15] the in the world is between 200 and $300
[46:18] billion.
[46:20] That's a big TAM and it's very little of
[46:23] it right now is being accessed because
[46:25] of the cost of this and the fact that
[46:26] you can't get insurance. But if you find
[46:28] ways to make them and what they're
[46:30] working on is one treatment as opposed
[46:31] to every single month pill not shot.
[46:35] like we watch all this stuff and that's
[46:36] what they're focused on and they are
[46:38] buying companies almost every single
[46:40] week and in some weeks they're buying
[46:41] multiple companies but if you go through
[46:43] they're all connected to the parts of
[46:47] the diabetes side that GLP1s that
[46:50] they've seen some kind of impact whether
[46:51] it's kidneys whether it's cancers
[46:53] whether it's all this you're talking to
[46:54] someone who didn't know any of this 6
[46:56] months ago but I wrote a paper in
[46:58] October when I get fixated on something
[47:00] I keep going and the reason I'm talking
[47:02] about it today people is because I
[47:04] believe we are seeing signs of a top in
[47:07] hardware. Not that they're going to go
[47:09] down and not that this is a crash, but
[47:10] you look for rotations to where the
[47:12] market narrative shifts. And I think the
[47:14] market narrative is shifting from the
[47:16] chips, infrastructure, energy side of
[47:19] the cake and it's moving up to the
[47:21] application side and I think the best
[47:23] application for this is going to be on
[47:25] the human software side. So, one of the
[47:26] aspects that uh I became very interested
[47:28] in is the second I heard the GLP1s could
[47:31] help with addiction. And the data point
[47:34] that really hammered it home was that
[47:36] some of the hedge funds on Wall Street
[47:38] were requiring people to not take GOP1
[47:41] >> because it took away some of the
[47:42] risk-taking genes, you know, the
[47:43] risk-taking uh component
[47:45] >> was everyone is looking at GOPs as a
[47:49] physical body weight loss, you know,
[47:52] etc. impact.
[47:54] What happens when this hits the drug and
[47:56] alcohol addiction market?
[47:58] >> I don't know where people are yet in
[48:00] terms of actually being able to do that
[48:01] from a a pure medical standpoint. Will
[48:03] insurance dollars be able to be used,
[48:05] etc. But if you're telling me that there
[48:08] is now something that can be injected
[48:10] that will help solve that problem and it
[48:13] maybe is matched with recovery centers
[48:16] or rehab or whatever, that is a very big
[48:20] market. That is a market that not only
[48:22] would have a profound positive impact on
[48:24] society, but there will be very big
[48:26] businesses built there. And so I think
[48:28] that to me is what's interesting here is
[48:29] you're talking about this like API key
[48:31] for the human body, but it seems like a
[48:34] lot of these peptides, they're not just
[48:36] single application. We're starting to
[48:39] see, okay, it can do weight loss, it can
[48:40] do addiction, it can do what it's one
[48:43] single drug, right, or peptide. Mhm.
[48:46] >> When we look at the cholesterol shot, my
[48:49] guess is it does other things as well,
[48:51] right? And has certain impacts on
[48:52] people's body. And so as you see this
[48:55] kind of roll out here, it feels like we
[48:58] understand maybe the first order impact,
[49:00] but we yet do not understand what else
[49:03] can these things do. And so it's a
[49:05] perfect example of a market that
[49:07] continues to expand as we better
[49:09] understand the technology. As an
[49:11] investor, what else do you want? It's
[49:12] already a big TAM. And oh by the way,
[49:14] you know, it's kind of like the SpaceX
[49:16] uh TAM slide, you know, we have rocket
[49:19] launch, we have Starlink, enterprise AI.
[49:23] >> Yeah.
[49:23] >> Right. Same thing's going to happen here
[49:25] in healthcare, right?
[49:27] >> Yeah. And for people, I mean, we're
[49:28] we're we're almost at 20% of uh personal
[49:32] expenditures in the country each year
[49:34] are healthcare. We're getting close to
[49:36] that. Um it grows every single year
[49:38] because of demographics and because of
[49:39] the health of the country. So we all
[49:41] realize it's a huge market. Um, I don't
[49:43] think people fully grasp how big the
[49:45] market is, but forget housing, forget
[49:47] all this stuff like health expenditures
[49:49] are what you want to focus your
[49:50] attention on. So, if you can get a piece
[49:51] of that pie, it's great. Second thing,
[49:53] when when you talked about addiction, I
[49:56] people hear the word side effect and
[49:59] they think it's something negative.
[50:01] Well, these side effects of addictions
[50:04] going down, all these are just one of
[50:06] the things that are coming that they can
[50:08] now go study. So I believe what Eli Liy
[50:11] has figured out is side effects now
[50:13] become something very useful to go
[50:14] investigate as to why this is having an
[50:16] impact. This is different than spending
[50:18] an enormous amount of years to get a
[50:20] drug that treats something as opposed to
[50:22] a peptide which is there to make the
[50:25] body act differently. And that's the
[50:27] thing people have to realize is if they
[50:28] go spend the time and for everyone
[50:30] listening I I did this on my weekly
[50:32] video. I highly recommend listening to
[50:34] an interview on YouTube with David
[50:36] Ricks, the CEO of Eli Liy and Jensen
[50:39] Yuang. They're partners.
[50:42] Eli Liy is partners with Nvidia. That
[50:44] should be enough for people to be
[50:45] interested because he's had a pretty
[50:46] high hit ratio. But if you listen to the
[50:48] interview, you'll learn more about why
[50:50] GLP1s are so important and why peptides
[50:52] are so important and you'll get a sense
[50:54] as to where Eli Liy is going with this.
[50:57] So I think as everyone thinks about this
[50:58] more and they get through how big the
[51:00] market can be, how it'll go, they're
[51:01] going to get back to one other important
[51:02] issue. I've never worried about the debt
[51:04] of the country despite all the doom and
[51:06] gloom that's out there because the
[51:07] household net worth of the country is
[51:09] five times the size of the debt of the
[51:11] country. So yes, the government has a
[51:13] bad balance sheet, but the household
[51:15] balance sheet is phenomenal. But
[51:17] entitlements are a major issue that are
[51:19] going to be an issue. But what makes up
[51:20] the bulk of entitlements when you get
[51:22] through Medicare and Medicaid and you're
[51:24] dealing again with the health of the
[51:25] country? If we're going to get to the
[51:27] point with peptides, but also with gene
[51:29] editing, with uh mRNA, e every single
[51:32] thing, if we're going to get to the
[51:34] point where people are going to die
[51:36] healthy as opposed to die sick, that has
[51:40] a huge impact on the entitlement issue.
[51:42] And that's where again, I don't think
[51:43] looking out 5 years, people should think
[51:45] that any business that they've invested
[51:47] in is safe. I don't think they should
[51:48] think that they're going to die. The
[51:50] reason I spend so much time trying to be
[51:52] healthy today is because I'm not sure
[51:54] they're going to be able to reverse my
[51:55] age. So, I want to stay the same age for
[51:56] as long as I can or at least have the
[51:58] delta be be shrinking. So, I think the
[52:00] healthc care side is something people
[52:01] need to think more about. Watch Eli Liy
[52:04] stock just because number one, it is a
[52:06] trillion dollar company. Number two,
[52:08] believe it or not, it's been kind of
[52:09] consolidating to a very high degree for
[52:11] the last 18 months. So, you have no clue
[52:15] as to what the impact of GLP1s are. And
[52:17] neither did I until this past week.
[52:20] Victoria Secret
[52:22] put their earnings out there. Yep. The
[52:24] stock was up 47%
[52:26] earlier this week. They reported 15%
[52:29] sales growth in uh I think Q1
[52:34] directly attributable or in a large part
[52:37] to GLP1's people are losing weight.
[52:40] Bedroom fashion is back I guess.
[52:42] >> Yeah.
[52:43] >> The second order effects here on some of
[52:45] these businesses. Everyone was talking
[52:47] about our fast food company's going to
[52:48] come under pressure
[52:50] >> but there's the positive stories as
[52:51] well. And so it does feel like this is
[52:53] going to kind of infiltrate out into the
[52:56] US economy in a bunch of ways that maybe
[52:58] we didn't predict before.
[53:00] >> Yeah. And and I think again the main
[53:01] point here for people to think about is
[53:03] this is what limited access. So I
[53:06] remember when I first wrote something
[53:07] about GLP1s which was probably four
[53:09] years ago now and it was when originally
[53:13] it was becoming kind of a big theme
[53:15] where everyone was talking about but it
[53:16] was when it was starting to impact the
[53:17] consumer staples companies. And I
[53:19] remember people asked me the question
[53:21] because people will say what do you
[53:22] think and doctors were already telling
[53:24] me this is like a miracle drug and most
[53:27] people thought it was bad and the
[53:30] doctors some of which were family
[53:32] members were like Jordy you have to
[53:34] understand for every 10 people that I
[53:37] take care of seven of them can't go on
[53:39] trips to Disney they can't do things
[53:41] with their family this is changing their
[53:43] ability to live their life and are there
[53:45] side effects yes but they're going to
[53:48] live a healthier life going forward. So,
[53:50] what you're talking about now is four
[53:51] years later, the technologies have
[53:53] gotten better. They're still getting
[53:55] better. The weight loss percentage is
[53:57] getting higher. The muscle mass loss is
[53:59] going down. The ability for people to
[54:01] take these less often and not in shot
[54:04] form is increasing. And it's only going
[54:06] to get better. So, a lot of the things,
[54:08] and again, I'm writing a paper on this
[54:10] on Eli Liy. I can't possibly describe to
[54:12] you all of the strategic purchases
[54:15] they've made of other companies. So if
[54:17] you go back to what was happening with
[54:20] the Mag 7, what were they doing? Buying
[54:22] Instagram, buy like they were buying
[54:26] companies. They were buying API keys. So
[54:28] what's Eli Lily doing? They're making so
[54:31] much money from this one drug that
[54:33] they're taking the cash to build a data
[54:36] center to like this is the greatest
[54:39] story you could ever want to hear. And
[54:41] like I said, Toune Lab is basically
[54:43] Google X. Their co-inovation lab out in
[54:46] Silicon Valley with Nvidia. Co-inovation
[54:49] lab with Nvidia is to speed up health
[54:52] and it's to attract talent from Stanford
[54:54] and the people that are graduating out
[54:56] there to make sure that when they have a
[54:57] choice and they're like, "Do I want to
[54:58] go work for a software company or do I
[55:00] want to work for a human software
[55:02] company?" All of this stuff is happening
[55:04] and I can already see the supersonic
[55:06] tsunami of healthcare is approaching and
[55:08] so I think there's going to be more and
[55:10] more Victoria Secret stories going
[55:12] forward. What are you going to put in
[55:13] your video this week?
[55:15] >> Uh, there's obviously going to be a lot
[55:17] of uh Eli Lillian teasing out some of
[55:19] the things that I said here. There's
[55:21] going to be a lot on my belief that the
[55:23] IPOs that are coming to the market that
[55:25] people are underestimating what they
[55:27] signal the Google what the 85 billion
[55:31] why Berkshire buying it why that says
[55:33] something too that a company that's been
[55:35] raising cash decides oh we'll take 10
[55:37] billion of a company that's up 120%
[55:39] year-over-year. a lot of stuff going on
[55:42] in the market that I think people need
[55:43] to be paying attention to. And again,
[55:45] I'm going to say that this is not a
[55:46] bubble. The title of my video last week
[55:48] is we will crash, which was a play on
[55:50] Andrew Ross Sorcin. Um, but the rotation
[55:53] to me is going to happen, and I'd be
[55:54] focused on companies there. And I I will
[55:56] emphasize one other point, too. We
[55:58] talked about the human software side.
[56:00] I'm not going to emphasize the
[56:02] importance of crypto and tokenization on
[56:04] the financial guardrails, but that is
[56:05] the other software side that if I'm
[56:07] right for the second half of the year,
[56:10] when if and when Bitcoin breaks through
[56:13] the 200 day moving average, if and when,
[56:14] maybe it's two years from now, maybe
[56:16] it's three years from now, maybe it goes
[56:17] to zero before then, I don't know. But
[56:19] once it does, I believe we're entering a
[56:22] new phase where the software that people
[56:24] are choosing is for the human body and
[56:26] for the financial guardrails because AI
[56:28] agents are both that part of software.
[56:32] >> I love it. We have three asks of the
[56:34] audience today. Three. I mean, look, you
[56:36] know, it's getting to be summertime. We
[56:38] got three of them. The first is go
[56:40] search on YouTube for Jordy Visser and
[56:43] subscribe to his channel so you can
[56:44] watch his weekly video. Every Sunday it
[56:46] comes out. It's amazing. He has more
[56:49] charts than you can ever imagine. It's
[56:50] very in uh informative and I think
[56:53] you'll learn a lot. The second thing is
[56:54] that we want you to go to uh Jordiv
[56:56] Visser 22V research. And how many pieces
[56:59] are you putting out a week right now?
[57:01] >> Uh I'm putting out two pieces a week,
[57:05] but then I'm also putting in a bunch of
[57:06] models for trading and stuff like that.
[57:08] >> This guy writes so much I can't read it
[57:09] all. He's getting out of hand here.
[57:11] You're going to have to put a speed
[57:12] limit on them. Um, so 22V research Jordi
[57:15] Visser or if you want to use AI to
[57:18] better manage your portfolio, you can go
[57:19] to cfosylvia.com.
[57:21] You can sign up there for free. So go
[57:23] subscribe to Jordy on YouTube. Go listen
[57:25] to or uh subscribe to uh 22V research or
[57:28] go sign up for cfosilia.com. If you do
[57:31] those three things, we'll be happy guys.
[57:32] You know, we we don't ask for much
[57:34] around here, but those three things will
[57:35] be very helpful. And uh we'll see you
[57:37] guys next week. See you.