Speaker 1: AI stocks have been on fire, but most investors don't
Speaker 1: realize they're walking into a trap. Now, the entire market
Speaker 1: got a wake up call when China's deep Seek released
Speaker 1: an open source AI model that's shocked everyone overnight. The
Speaker 1: way that investors value stocks, AI stocks, and even indexes
Speaker 1: has completely changed. So if you're holding AI stocks, you
Speaker 1: need to hear this before it's too late. But of
Speaker 1: course don't panic. Look this isn't the end of AI investing.
Speaker 1: In fact, there's a massive opportunity if you know where
Speaker 1: to look. So in this video, I'm going to break
Speaker 1: down why the AI market is breaking down right now,
Speaker 1: how open source models light deep Seek is forcing a
Speaker 1: total rethink of AI stocks and just stocks overall on
Speaker 1: the valuations, and we're going to talk about where the
Speaker 1: smart money is moving next and how to position yourself
Speaker 1: for the biggest gains in the AI next wave real quick.
Speaker 1: I'm Mark Moss. I've built and exited multiple tech companies.
Speaker 1: I've invested through several boom and bus cycles. Today I'm
Speaker 1: a partner at a leading bitcoin venture capital fund called
Speaker 1: the Bitcoin Opportunity Fund. I also write the Quantum Wave
Speaker 1: Investment Report or help investors navigate the biggest shifts in
Speaker 1: tech and money, and I make these videos to give
Speaker 1: you the insights that we're using so you can navigate
Speaker 1: and profit from these shifts as well. So let's go
Speaker 1: all right, we're jumping right into it. We're talking about
Speaker 1: how AI investing is breaking down. Now listen, Look, this
Speaker 1: is not a doom in gloom video. AI is massively transformative.
Speaker 1: It is going to create massive efficiencies, and it is
Speaker 1: changing the world. I use it every day. I'm making
Speaker 1: money invest in it. But if you don't understand the
Speaker 1: nuances of how this shifts, you could lose money. So
Speaker 1: let's break this down. Okay, we know if you living
Speaker 1: under rock that AI has completely skyrocketed really from about
Speaker 1: twenty twenty two to twenty twenty three. It's not that old,
Speaker 1: right open AI storm. The scene was that November of
Speaker 1: twenty twenty two, So all twenty twenty three and twenty
Speaker 1: twenty four, it has been blowing up. It's the darling.
Speaker 1: Wall Street loves that. Every investment newsletter's talking about it,
Speaker 1: and it's like all in right, except for the problem
Speaker 1: is that the way technology works is it moves through
Speaker 1: different cycles, and so what we're seeing is the AI
Speaker 1: business model is changing really rapidly. Right, This technology is
Speaker 1: moving so much faster than previous technology cycles in the past.
Speaker 1: But if you understand that, which I'm going to break
Speaker 1: down for you, you can see that the models shifting.
Speaker 1: So if you're still investing like you were in twenty two,
Speaker 1: twenty three, and twenty four, you're gonna be losing money.
Speaker 1: And now that we'd be losing money, you'll be missing
Speaker 1: out on the massive gains that we have. Now we
Speaker 1: can look at historical parallels the dot com boom and bust,
Speaker 1: we can look at the crypto sort of boom and bust,
Speaker 1: and we can understand the fractals. We can understand how
Speaker 1: those markets evolved. We'll compare it to history and technology
Speaker 1: to understand that, and we can understand that the AI
Speaker 1: stocks that most people think about today open AI being
Speaker 1: the leader, of course Google with their Gemini and so forth,
Speaker 1: they're not really monopolies. And really what it's highlighting is
Speaker 1: that valuation is only a concern when the underl buying
Speaker 1: fundamentals change, and that's the problem. Those fundamentals are changing. Okay,
Speaker 1: so let's understand this so you know how to navigate
Speaker 1: the cycles. Okay, first of all, we do want to
Speaker 1: understand that this is not just about AI or tech
Speaker 1: or stock. It's all the markets as we know them.
Speaker 1: I'm talking about the S and P five hundred specifically,
Speaker 1: I'm talking about the NASDAC. All right, So, right now,
Speaker 1: a lot of people are with your four oh and k,
Speaker 1: your mutual funds or financial advisors. Maybe you're just like
Speaker 1: every two weeks investing and you're allocating to the Nasdaq.
Speaker 1: You're passively investing. That's going to be super dangerous. I'll
Speaker 1: show you why. So the market is highly concentrated. As
Speaker 1: a matter of fact, concentration in the market is at
Speaker 1: an all time high. If to sort of take a
Speaker 1: look at this, looking at the Nasdaq again, the Nasdaq
Speaker 1: one hundred here is this again represents the tech stocks,
Speaker 1: which is where all the growth is. You've heard me
Speaker 1: talk about the investing black hole and how basically only
Speaker 1: bitcoin and the Nasdaq have been keeping up with the
Speaker 1: real rate of inflation of debasement. And so we can
Speaker 1: see the NASDAC right here. This goes back. This is
Speaker 1: the two thousand dot com boom and bust right here,
Speaker 1: and of course here we are today. Now this looks
Speaker 1: pretty good if you would have just bought here and
Speaker 1: held tell here he did pretty good. Of course, in
Speaker 1: the dot com boom, we had an eighty one percent
Speaker 1: draw down, pretty massive eighty one. Now, the one thing
Speaker 1: to keep in mind about that eighty one percent draw
Speaker 1: down is it took a decade or more just to
Speaker 1: get back to even In the year two thousand and eight,
Speaker 1: the Great Financial Crash, we had a fifty percent draw
Speaker 1: down in the Nasdaq. In twenty twenty, during the pandemic,
Speaker 1: we had a thirty six percent draw down. Now, one
Speaker 1: thing you might notice is that these draw downs are
Speaker 1: getting less and less, from eighty one to fifty to thirty.
Speaker 1: You notice that. So this fits into why I continually
Speaker 1: tell you that what we're seeing as a crash up,
Speaker 1: not a crash down. The way that the government has
Speaker 1: used debt, especially around this period right here, fiscal spending
Speaker 1: has changed these markets. Anyway, we're not talking about that
Speaker 1: in this video. But you can see that the Nasdaq
Speaker 1: has gone up. But the thing that I want to
Speaker 1: draw your attention to is the concentration that's happening in
Speaker 1: the Nasdaq. So what this shows is the largest ten
Speaker 1: percent of stocks as a percent of the total value
Speaker 1: of stocks. And what this shows us is that over
Speaker 1: the past five and a half decades there's only been
Speaker 1: two previous peaks in market concentration. So we saw that
Speaker 1: right here in the seventies, we saw it again in
Speaker 1: the two thousand dot Com boom and bust, and now
Speaker 1: we see it again here today. Now I've put this
Speaker 1: red line on there, so again I like to show
Speaker 1: you the charts. You can see the direction, the size
Speaker 1: of the speed of the moves, and you can see
Speaker 1: that the concentration keeps getting bigger and bigger and bigger.
Speaker 1: Now why is this important, Well, if you're buying the
Speaker 1: Nasdaq index or the S and P five hundred index
Speaker 1: for that matter, you're buying the S and P five
Speaker 1: hundred because of the mag seven. Right, there's seven stocks
Speaker 1: that are driving most of that entire index. In the Nasdaq,
Speaker 1: you're seeing about the same thing. The concentration of the
Speaker 1: top ten is getting bigger. Now. The reason why this
Speaker 1: is the problem is if you're passively invested into the
Speaker 1: index and one or two of these companies, there's only seven,
Speaker 1: and they have to be five hundred back seven. If
Speaker 1: they drop, they bring the entire index down with them.
Speaker 1: Super important to understand. Okay, so we can see that
Speaker 1: concentration is at an all time high. Now what does
Speaker 1: that mean? What are the historical parallels to this? Well,
Speaker 1: we can see that historically speaking, high concentration equals high danger.
Speaker 1: We can see that historically speaking, whenever we've reached these
Speaker 1: levels of concentration, we've seen big crashes happen off the
Speaker 1: back of that. Now we also have historical parallels to
Speaker 1: where those happened, like the dot com boom, for example,
Speaker 1: was when we had extreme tech optimism. Now I'm optimistic
Speaker 1: about tech, but we had extreme tech optimism in the seventies.
Speaker 1: Same thing that was when the microprocessor came out. You
Speaker 1: might know from my quantum wave thesis the last one
Speaker 1: started in nineteen seventy one, right at that peak. I'll
Speaker 1: show you more than that in a second. We also
Speaker 1: had a sudden change in the models. I'm going to
Speaker 1: talk about that in a second. But this is pricing
Speaker 1: the nasdak in gold. This is from my friend Luke
Speaker 1: Grammanov at FFTT. Check him out. He's worth a follow.
Speaker 1: But what we want to do is we want to
Speaker 1: look at things if they're expensive or cheap priced in
Speaker 1: other things, not just US dollars, because if we look
Speaker 1: at US dollars, it's always manipulated. So here's the Nasdaq
Speaker 1: priced in gold. Again, during the dot com boom got
Speaker 1: really expensive, but we can see that it's basically been
Speaker 1: breaking down ever since, and it's been in this range
Speaker 1: right here, and so again if you're passively invested in
Speaker 1: index and to be wary of that, and especially when
Speaker 1: they're sudden changes in the technology, which is what happened
Speaker 1: in nineteen seventy. In the year two thousand, all right,
Speaker 1: so what are we talking about? How is AI changing
Speaker 1: and what do we need to be aware of? Well,
Speaker 1: what really happened. I made a video a few weeks ago.
Speaker 1: I think it was talking about deep Seat. Deep Seat
Speaker 1: was a new open source LLM, a new AI model
Speaker 1: that was released from a company in China. But what
Speaker 1: happened is when that was released, we saw the entire
Speaker 1: market plunge. In video, Everyone's Darling plunged time, but the
Speaker 1: entire market plunged, And I made a video. I'll link
Speaker 1: to it down below. You should watch that to really understand.
Speaker 1: But basically what it did is exposed that all our
Speaker 1: models for evaluating these companies, the growth of these companies
Speaker 1: and even the way that money goes into the index
Speaker 1: of the NASDAC has completely changed. And so it highlighted
Speaker 1: that everything that we thought we knew we don't know anymore. Now.
Speaker 1: One of the things that we saw is that because
Speaker 1: deep seek was an open source LLM, then what it
Speaker 1: did is it's shone a light on all the AI
Speaker 1: monopolies that we saw again Open Ai, Google, those types
Speaker 1: of companies, Cloud, etc. It showed that their pricing is over.
Speaker 1: How can any of those open AI or gym and
Speaker 1: how could they be charging when we have open source
Speaker 1: models that are better. And so that changed all that
Speaker 1: we saw that AI's paywall is losing pricing power eventually
Speaker 1: be priced out completely. And what that's showing is that
Speaker 1: the entire AI stock market needs to be reevaluated. Now
Speaker 1: It's not just this, there's all types of now AI gateways,
Speaker 1: AI agents that are now bridging all of the aillms together.
Speaker 1: So for example, now for like five bucks a month,
Speaker 1: I could get access to all of them without having
Speaker 1: to pay for them individually. So we're seeing this but
Speaker 1: now again like these open source models are completely changing this.
Speaker 1: So then the question is again is if lllms are free,
Speaker 1: where does the value go? Well, good thing, I have
Speaker 1: an answer for you, because history tells us that. And
Speaker 1: of course I've been investing in technology for decades. So
Speaker 1: let me show you how we look at this. So
Speaker 1: open source shift. So it started where I think, right
Speaker 1: where open ai hit the scene and they raised a
Speaker 1: ton of money. Right they're the Wall Street Darland, They're
Speaker 1: gaining all this momentum. And where I've really first started
Speaker 1: noticing it is Meta. Facebook Meta launched Lama, which is
Speaker 1: an open source LLM, a large language model an AI.
Speaker 1: And when I saw that happen, it made me stop
Speaker 1: and think, why would Facebook, who's changed their name to Meta,
Speaker 1: who's rushing into the space, Why would they open up
Speaker 1: a free, open source model when the apparent model seems
Speaker 1: to be like open AI and try to raise a
Speaker 1: bunch of money and be worth a lot of money.
Speaker 1: Why would Facebook do that? And one of my thoughts was, well,
Speaker 1: Facebook is worth i don't know, ten times twenty times
Speaker 1: more than open AI. Open AA is not really a
Speaker 1: threat to them today, there's really small. If Facebook opens
Speaker 1: up a open source LLM, they neutralize opening I how
Speaker 1: can opening I be worth any money if now there's
Speaker 1: all the free ones that are even better, And so
Speaker 1: it seemed like it was like maybe Zuckerberg playing forty
Speaker 1: chess when open AI and he's trying to kind of
Speaker 1: play the old playbook. That was what I thought at first.
Speaker 1: But it's changed a little bit, and I'm going to
Speaker 1: show you where the real value is accruing. Now we
Speaker 1: can see this other open source models, code gen, which
Speaker 1: is Salesforce CRM, so the giant the CRM space. So
Speaker 1: we're seeing like SaaS companies jumping into the space. Goose
Speaker 1: which is an open it's an open source AI agent
Speaker 1: project from Jack Dorsey, the founder of Twitter. Now he's
Speaker 1: head a block deep Seek. Of course, since deep Sea
Speaker 1: came how just a few weeks ago, we've seen like
Speaker 1: half a dozen more come out of China. They're coming
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Speaker 1: really what we want to do is we want to
Speaker 1: look back to the dot and even crypto models to
Speaker 1: really understand how this works. Where does the value accrue? Now,
Speaker 1: you might have seen me use this chart. If you
Speaker 1: watch my content, you see me use this chart all
Speaker 1: the time. And you understand that in these quantum wave cycles,
Speaker 1: we have about a fifty year cycle and they happen
Speaker 1: in these four phases, and we need to understand that
Speaker 1: the way that we invest through each phase changes. So
Speaker 1: the way that I invested here is going to be
Speaker 1: different than the way and the companies I invest in
Speaker 1: here different here and so forth. All right, So right
Speaker 1: now we are right here starting this second phase, and
Speaker 1: so the old way of investing no longer works. So
Speaker 1: let me break it down with some parallels. We think
Speaker 1: about technology in layers, all right, Technology scales and layers
Speaker 1: is what most people misunderstand, and so they think the
Speaker 1: Internet was too slow, can't scale. Let's go spend a
Speaker 1: billion dollars in intranets. Bitcoin is too slow, can't scale.
Speaker 1: Let's go try all these crypto projects without understanding that
Speaker 1: technology scales and layers, but also the way value accruise
Speaker 1: happens in layers. So what do I mean by that?
Speaker 1: If you think about the Internet, we have a base
Speaker 1: layer of the Internet, right, so this would be like
Speaker 1: TCP and IP, right, and then we want email, so
Speaker 1: then we have like SMTP, and then we want security,
Speaker 1: so we have like https. Right. You know what those
Speaker 1: things are all right, but no value as a crude
Speaker 1: at this base layer TCP, IP protocol, SMTPA, CTPS protocols,
Speaker 1: they're not worth anything. They're just open source protocols. Where
Speaker 1: all the value has accrued is on higher levels, so
Speaker 1: on the applications. So for example, you have Google. Google
Speaker 1: created Chrome and now you have all these Chrome plugins
Speaker 1: right here that are worth a lot of money. You
Speaker 1: can think about this like with the iPhone. You have
Speaker 1: the iPhone, which obviously you create a lot of value,
Speaker 1: but then think about the app store and think about
Speaker 1: all the apps inside of that, all right, So this
Speaker 1: is where the value is accrued, not on the base layer,
Speaker 1: but on the stack, all right. We can think about
Speaker 1: the same thing with bigcoin. Now, we had Bitcoin, which
Speaker 1: is a protocol, It's a protocol that transfers data, right,
Speaker 1: and obviously value is accruing there, but not so much
Speaker 1: on the protocol, but the asset Bitcoin, the asset, not
Speaker 1: the network. Now we have companies that are building layers
Speaker 1: on top of the Bitcoin stack, and so certainly the
Speaker 1: Bitcoin network has a crude value, but then we have
Speaker 1: even more value being accrued up peer. That's what my
Speaker 1: fund investment we invest into these. But back to the
Speaker 1: topic that we're talking about right now, which is AI,
Speaker 1: we're seeing the same thing. So what I would say
Speaker 1: is these lms are like a base layer. So the
Speaker 1: lms are now open source, the deep seek, the LAMA,
Speaker 1: all those things, and there's no value accruing there. They're
Speaker 1: all racing down to the bottom. They're all for free.
Speaker 1: Where the value gets accrued is on higher levels. So
Speaker 1: it's on the applications, the narrow specific use cases that
Speaker 1: are being built on top of the open source model.
Speaker 1: And so we can see right now today the smart
Speaker 1: money isn't just betting on AI. That was the old way,
Speaker 1: that was twenty three, twenty four. Now it's betting on
Speaker 1: the right layer of AI. Which layer do we want
Speaker 1: to invest and do the same way might fund investing
Speaker 1: in to bitcoin? Which layer do we want to invest into?
Speaker 1: Now I'll show you that. Don't worry. Now, I am
Speaker 1: gonna break this down in greater detail and show you
Speaker 1: what different types of projects and companies are being built there.
Speaker 1: If you want to join me next week, we're gonna
Speaker 1: go live deep into this. I got I don't know,
Speaker 1: thirty forty charts or I'll break all of this down
Speaker 1: and then I'll take questions, so we'll talk about it.
Speaker 1: We'll discuss it, figure out the best way to find
Speaker 1: these companies invest into them. I'll throw you a couple
Speaker 1: of names that I like. If you want to come
Speaker 1: join me, it's all for free. I'll put a link
Speaker 1: down there down below. Come hang out. Let's have fun
Speaker 1: talking about this. Let's discuss it all. Like I said, live,
Speaker 1: Q and A and so much more. Join me for
Speaker 1: free and the link down below. Okay, now, what we're
Speaker 1: seeing because of this is a massive shift of capital.
Speaker 1: And it's not just from AI based layer to a
Speaker 1: higher level. Like I said, it's an entire index. It's
Speaker 1: even an entire continent. So what I'm talking about, Well,
Speaker 1: if China is now pushing these open source models, what
Speaker 1: we're seeing is that the US has sort of been
Speaker 1: competing more of a scarcity, right, we got to compete.
Speaker 1: Let's keep China out of the game. But China is
Speaker 1: trying to compete. Now it's not an even playing field.
Speaker 1: This is the whole conversation about tariffs and so forth,
Speaker 1: and you have a country that's subsidizing things, and that's
Speaker 1: a whole other topic. We can make a video if
Speaker 1: you want, drop me a comment down below. But what
Speaker 1: we've seen is that China has been trying to outcompete us.
Speaker 1: The US has been trying to protect but it's basically
Speaker 1: forced the shift in the market where now open source
Speaker 1: projects are now superior to companies that are trying to
Speaker 1: protect the mote. If you're trying to protect the mote,
Speaker 1: you're just not going to make it the world is
Speaker 1: open source. Jack Dorsy tweeted this so much the other
Speaker 1: day on Twitter saying or on x saying that the
Speaker 1: world is open source and that is the future. It's
Speaker 1: why I talk about decentralization all the time. But the
Speaker 1: question is if this is happening. We know that the
Speaker 1: US has been the financial hub of the world. We
Speaker 1: know that the US stock markets S and P five
Speaker 1: hundred and the Nasdaq are the great investment markets in
Speaker 1: the world. We know all that money is accrueing there,
Speaker 1: all the businesses are listed there. But if China is
Speaker 1: out competing US, does some of that money start leaving
Speaker 1: the US and going to China. Well, I have a
Speaker 1: chart to answer that question. What we can see right here,
Speaker 1: as you know again if you watch my videos on
Speaker 1: a regular basis the reason why, and I hinted too earlier,
Speaker 1: the reason why we see the stock markets going up
Speaker 1: so high is because the amount of money that they
Speaker 1: continue to print right through the debasement. And what we
Speaker 1: can see here is that. So what we have here
Speaker 1: is on the red line, we have the Nasdaq one
Speaker 1: hundred going up, that's right here. But what we have
Speaker 1: on the green line is the US net investment position.
Speaker 1: So this is the amount of money that went in,
Speaker 1: which you can see is higher than the amount of
Speaker 1: the Nasdaq itself. And what we have in the blue
Speaker 1: line down here is the foreign direct investment in US equities,
Speaker 1: mainly coming from China. So what happens is, just like you,
Speaker 1: a country has surpluses, so they have trades, exports, they
Speaker 1: have imports, they have surpluses, they have savings. What do
Speaker 1: they do with that, Well, they put it somewhere and
Speaker 1: in this case, a lot of that has been being recycled,
Speaker 1: used to be recycled into US treasuries, still is a
Speaker 1: lot of it is has been recycled into the NASDAK
Speaker 1: and that's exactly what we've seen. So China has been
Speaker 1: recycling a substantial portion of its surpluses into these US equities,
Speaker 1: which is pushed the entire index up. But back to
Speaker 1: the competing angle. Now, if China now is moving ahead
Speaker 1: in tech, which they've already sort of outpaced the US
Speaker 1: with evs and batteries and lots of things like that,
Speaker 1: will a lot of that Chinese money, instead of going
Speaker 1: to the Nasdaq start going to their own indexes. So
Speaker 1: we're seeing a massive disruption here all over the place.
Speaker 1: So the question or the thing we need to ponder
Speaker 1: is not only is AI itself changing, but the global
Speaker 1: flow of capital is shifting as well. If you have
Speaker 1: to understand these things if you want to have success
Speaker 1: with your portfolio, because the world is changing rapidly. It's
Speaker 1: always technology that changes the world, and in these quantum
Speaker 1: wave cycles like we're in right now, it's where all
Speaker 1: the change happens. Okay, so what is this next phase
Speaker 1: for AI? Well, the losers, the ones that are getting
Speaker 1: left behind are the AI monopolies, the open ais, the Googles, right,
Speaker 1: those are the ones that are trying to kind of
Speaker 1: hold their LLM behind a paywall. They're going to be
Speaker 1: the losers. Chip stocks Nvidia AMD why because they were
Speaker 1: pricing in unlimited demand. But what Deepseak showed us is
Speaker 1: that they're able to train these AIM models for way
Speaker 1: cheaper with way less GPUs than we thought. So instead
Speaker 1: of the demand for chips being like this, we find
Speaker 1: out it's probably more like this, and as technology continues
Speaker 1: to accelerate, it might even be more like this. So
Speaker 1: those are ones we want to watch out for. We
Speaker 1: also want to watch out for all the hype driven narratives. Right,
Speaker 1: So all these companies that are trying to ride this
Speaker 1: hype train we're talking about, like AI SaaS companies think
Speaker 1: about Salesforce launching their open AM model or their LM model.
Speaker 1: So hype driven AI SaaS companies with no moat again, right,
Speaker 1: there is no mot This is all going down. It's
Speaker 1: going to be a base layer and they're all going
Speaker 1: to be basically competing as commodities. So who will the
Speaker 1: winners be? Where will the real money go? Where will
Speaker 1: the real money be made? Well, AI high value applications,
Speaker 1: narrow niche use cases, high value applications on top of
Speaker 1: the open source llms. Let me give you an example.
Speaker 1: In twenty twenty two, when open ai released, you had
Speaker 1: all the open APIs you could use. You could do anything.
Speaker 1: You can create images, you could to create text, right, code, whatever. Well,
Speaker 1: when people are faced with I could do anything, they
Speaker 1: don't know what to do. So there was an app
Speaker 1: you might remember created called lensa AI and all it
Speaker 1: did was just use the APIs that open i had produced.
Speaker 1: But with LENDSAI, I could take a picture of myself
Speaker 1: and it would give me back ten avatars. A very
Speaker 1: narrow use case of what the whole thing could do.
Speaker 1: But it got so popular so fast. I believe in
Speaker 1: like ninety days it was worth like a billion dollars
Speaker 1: because it was a very narrow use case. And that's
Speaker 1: what we're talking about, high value applications on top of
Speaker 1: the base layer, the open source lms. Specifically, I'm looking
Speaker 1: for where bitcoin, AI, and open source decentralization, where all
Speaker 1: those things converge so we have a new set of
Speaker 1: building blocks. What happens when we use these three together,
Speaker 1: where they converge and build things that we can't even
Speaker 1: imagine today. And AI infrastructure provides that it doesn't really
Speaker 1: high on close sourced models. Again, it's all moving to
Speaker 1: open source. That's the big theme. Hopefully you're catching onto that.
Speaker 1: I've been talking about what I call the decentralized revolution
Speaker 1: for about five years now. Okay, now, how do we
Speaker 1: play this? What does this mean to us? Well, one,
Speaker 1: we have to understand the game is changing, right and
Speaker 1: we understand through historical parallels exactly how that changes. Number Two,
Speaker 1: we have to understand that passive investing is super dangerous
Speaker 1: right now, because, as I said, if we have this
Speaker 1: over concentration, if one or two of these companies that
Speaker 1: are at risk right now. If they drop, the entire
Speaker 1: index can drop. On top of that, we realize that
Speaker 1: maybe China could steal some of that capital, take their
Speaker 1: capital back even to their own markets. We also know
Speaker 1: that most likely there's this next four or five year
Speaker 1: cycle we're going to see a massive amount of monetary debasement,
Speaker 1: and so that also manipulates what we see in the
Speaker 1: Nasdaq or the indexes. So I think in order to survive,
Speaker 1: we need to be much more selective in the companies,
Speaker 1: specifically looking for the ones that are in that convergence.
Speaker 1: Right in those three those are the ones that's going
Speaker 1: to be where the biggest gains, and they're going to
Speaker 1: come again from the convergence of bitcoin, AI and open
Speaker 1: source where those three things work together. Individually, yeah sure great,
Speaker 1: but together is where the magic made. Where that convergence is. Now,
Speaker 1: if you want to know more about these cycles and
Speaker 1: these three things converging again, come hang out with me
Speaker 1: next week. It's all live, it's all free. There's a
Speaker 1: link down below. I'll break out, like I said, thirty
Speaker 1: forty charts. We'll dig through this in great detail. Tell
Speaker 1: you where I'm focusing where my fund's focusing, and then
Speaker 1: we'll discuss it. It's all open life, Juneing so much.
Speaker 1: Come hang out with me, but that's what I got.
Speaker 1: Let me know what you think about this. Hopefully you're
Speaker 1: shifting your portfolio, and of course that's always give me
Speaker 1: thumbs up if you like it. If you don't give
Speaker 1: me the was down that it's okay. At least tell
Speaker 1: me why. And that's what I got. All right, to
Speaker 1: your success, I'm out,