1 00:00:00,240 --> 00:00:03,880 Speaker 1: AI stocks have been on fire, but most investors don't 2 00:00:03,920 --> 00:00:07,160 Speaker 1: realize they're walking into a trap. Now, the entire market 3 00:00:07,160 --> 00:00:09,720 Speaker 1: got a wake up call when China's deep Seek released 4 00:00:09,760 --> 00:00:13,640 Speaker 1: an open source AI model that's shocked everyone overnight. The 5 00:00:13,680 --> 00:00:17,880 Speaker 1: way that investors value stocks, AI stocks, and even indexes 6 00:00:18,000 --> 00:00:20,959 Speaker 1: has completely changed. So if you're holding AI stocks, you 7 00:00:21,040 --> 00:00:23,319 Speaker 1: need to hear this before it's too late. But of 8 00:00:23,360 --> 00:00:26,360 Speaker 1: course don't panic. Look this isn't the end of AI investing. 9 00:00:26,400 --> 00:00:29,920 Speaker 1: In fact, there's a massive opportunity if you know where 10 00:00:29,960 --> 00:00:31,720 Speaker 1: to look. So in this video, I'm going to break 11 00:00:31,760 --> 00:00:35,000 Speaker 1: down why the AI market is breaking down right now, 12 00:00:35,400 --> 00:00:38,760 Speaker 1: how open source models light deep Seek is forcing a 13 00:00:38,880 --> 00:00:42,879 Speaker 1: total rethink of AI stocks and just stocks overall on 14 00:00:42,920 --> 00:00:45,440 Speaker 1: the valuations, and we're going to talk about where the 15 00:00:45,479 --> 00:00:48,280 Speaker 1: smart money is moving next and how to position yourself 16 00:00:48,320 --> 00:00:51,920 Speaker 1: for the biggest gains in the AI next wave real quick. 17 00:00:51,960 --> 00:00:54,880 Speaker 1: I'm Mark Moss. I've built and exited multiple tech companies. 18 00:00:54,880 --> 00:00:57,640 Speaker 1: I've invested through several boom and bus cycles. Today I'm 19 00:00:57,680 --> 00:01:00,440 Speaker 1: a partner at a leading bitcoin venture capital fund called 20 00:01:00,480 --> 00:01:03,240 Speaker 1: the Bitcoin Opportunity Fund. I also write the Quantum Wave 21 00:01:03,320 --> 00:01:06,720 Speaker 1: Investment Report or help investors navigate the biggest shifts in 22 00:01:06,800 --> 00:01:09,160 Speaker 1: tech and money, and I make these videos to give 23 00:01:09,200 --> 00:01:11,760 Speaker 1: you the insights that we're using so you can navigate 24 00:01:11,760 --> 00:01:14,160 Speaker 1: and profit from these shifts as well. So let's go 25 00:01:16,200 --> 00:01:18,200 Speaker 1: all right, we're jumping right into it. We're talking about 26 00:01:18,200 --> 00:01:21,399 Speaker 1: how AI investing is breaking down. Now listen, Look, this 27 00:01:21,440 --> 00:01:25,240 Speaker 1: is not a doom in gloom video. AI is massively transformative. 28 00:01:25,319 --> 00:01:27,720 Speaker 1: It is going to create massive efficiencies, and it is 29 00:01:27,840 --> 00:01:30,280 Speaker 1: changing the world. I use it every day. I'm making 30 00:01:30,319 --> 00:01:33,000 Speaker 1: money invest in it. But if you don't understand the 31 00:01:33,120 --> 00:01:36,560 Speaker 1: nuances of how this shifts, you could lose money. So 32 00:01:36,600 --> 00:01:40,520 Speaker 1: let's break this down. Okay, we know if you living 33 00:01:40,600 --> 00:01:43,839 Speaker 1: under rock that AI has completely skyrocketed really from about 34 00:01:43,840 --> 00:01:46,039 Speaker 1: twenty twenty two to twenty twenty three. It's not that old, 35 00:01:46,319 --> 00:01:49,200 Speaker 1: right open AI storm. The scene was that November of 36 00:01:49,240 --> 00:01:52,200 Speaker 1: twenty twenty two, So all twenty twenty three and twenty 37 00:01:52,200 --> 00:01:54,800 Speaker 1: twenty four, it has been blowing up. It's the darling. 38 00:01:55,280 --> 00:01:57,840 Speaker 1: Wall Street loves that. Every investment newsletter's talking about it, 39 00:01:58,040 --> 00:02:01,680 Speaker 1: and it's like all in right, except for the problem 40 00:02:01,760 --> 00:02:05,559 Speaker 1: is that the way technology works is it moves through 41 00:02:05,600 --> 00:02:08,639 Speaker 1: different cycles, and so what we're seeing is the AI 42 00:02:09,000 --> 00:02:12,799 Speaker 1: business model is changing really rapidly. Right, This technology is 43 00:02:12,800 --> 00:02:15,639 Speaker 1: moving so much faster than previous technology cycles in the past. 44 00:02:16,040 --> 00:02:18,519 Speaker 1: But if you understand that, which I'm going to break 45 00:02:18,520 --> 00:02:20,600 Speaker 1: down for you, you can see that the models shifting. 46 00:02:20,680 --> 00:02:22,760 Speaker 1: So if you're still investing like you were in twenty two, 47 00:02:22,800 --> 00:02:25,760 Speaker 1: twenty three, and twenty four, you're gonna be losing money. 48 00:02:25,960 --> 00:02:27,600 Speaker 1: And now that we'd be losing money, you'll be missing 49 00:02:27,680 --> 00:02:29,800 Speaker 1: out on the massive gains that we have. Now we 50 00:02:29,840 --> 00:02:33,960 Speaker 1: can look at historical parallels the dot com boom and bust, 51 00:02:34,240 --> 00:02:36,320 Speaker 1: we can look at the crypto sort of boom and bust, 52 00:02:36,360 --> 00:02:38,960 Speaker 1: and we can understand the fractals. We can understand how 53 00:02:39,040 --> 00:02:42,359 Speaker 1: those markets evolved. We'll compare it to history and technology 54 00:02:42,480 --> 00:02:46,240 Speaker 1: to understand that, and we can understand that the AI 55 00:02:46,360 --> 00:02:50,000 Speaker 1: stocks that most people think about today open AI being 56 00:02:50,000 --> 00:02:52,919 Speaker 1: the leader, of course Google with their Gemini and so forth, 57 00:02:53,440 --> 00:02:57,239 Speaker 1: they're not really monopolies. And really what it's highlighting is 58 00:02:57,280 --> 00:03:00,320 Speaker 1: that valuation is only a concern when the underl buying 59 00:03:00,560 --> 00:03:05,600 Speaker 1: fundamentals change, and that's the problem. Those fundamentals are changing. Okay, 60 00:03:05,600 --> 00:03:08,480 Speaker 1: so let's understand this so you know how to navigate 61 00:03:08,520 --> 00:03:11,079 Speaker 1: the cycles. Okay, first of all, we do want to 62 00:03:11,160 --> 00:03:14,000 Speaker 1: understand that this is not just about AI or tech 63 00:03:14,240 --> 00:03:17,320 Speaker 1: or stock. It's all the markets as we know them. 64 00:03:17,360 --> 00:03:19,280 Speaker 1: I'm talking about the S and P five hundred specifically, 65 00:03:19,280 --> 00:03:21,880 Speaker 1: I'm talking about the NASDAC. All right, So, right now, 66 00:03:21,880 --> 00:03:23,440 Speaker 1: a lot of people are with your four oh and k, 67 00:03:23,560 --> 00:03:25,960 Speaker 1: your mutual funds or financial advisors. Maybe you're just like 68 00:03:26,000 --> 00:03:28,800 Speaker 1: every two weeks investing and you're allocating to the Nasdaq. 69 00:03:28,840 --> 00:03:31,680 Speaker 1: You're passively investing. That's going to be super dangerous. I'll 70 00:03:31,680 --> 00:03:34,920 Speaker 1: show you why. So the market is highly concentrated. As 71 00:03:34,920 --> 00:03:37,880 Speaker 1: a matter of fact, concentration in the market is at 72 00:03:37,920 --> 00:03:40,920 Speaker 1: an all time high. If to sort of take a 73 00:03:40,960 --> 00:03:43,960 Speaker 1: look at this, looking at the Nasdaq again, the Nasdaq 74 00:03:44,000 --> 00:03:46,640 Speaker 1: one hundred here is this again represents the tech stocks, 75 00:03:46,640 --> 00:03:48,360 Speaker 1: which is where all the growth is. You've heard me 76 00:03:48,360 --> 00:03:51,480 Speaker 1: talk about the investing black hole and how basically only 77 00:03:51,520 --> 00:03:53,920 Speaker 1: bitcoin and the Nasdaq have been keeping up with the 78 00:03:53,960 --> 00:03:56,920 Speaker 1: real rate of inflation of debasement. And so we can 79 00:03:56,960 --> 00:03:59,960 Speaker 1: see the NASDAC right here. This goes back. This is 80 00:04:00,040 --> 00:04:02,520 Speaker 1: the two thousand dot com boom and bust right here, 81 00:04:02,720 --> 00:04:04,960 Speaker 1: and of course here we are today. Now this looks 82 00:04:04,960 --> 00:04:07,680 Speaker 1: pretty good if you would have just bought here and 83 00:04:08,200 --> 00:04:10,120 Speaker 1: held tell here he did pretty good. Of course, in 84 00:04:10,560 --> 00:04:12,960 Speaker 1: the dot com boom, we had an eighty one percent 85 00:04:13,040 --> 00:04:16,120 Speaker 1: draw down, pretty massive eighty one. Now, the one thing 86 00:04:16,160 --> 00:04:17,960 Speaker 1: to keep in mind about that eighty one percent draw 87 00:04:18,000 --> 00:04:21,000 Speaker 1: down is it took a decade or more just to 88 00:04:21,000 --> 00:04:23,440 Speaker 1: get back to even In the year two thousand and eight, 89 00:04:23,520 --> 00:04:26,160 Speaker 1: the Great Financial Crash, we had a fifty percent draw 90 00:04:26,200 --> 00:04:29,520 Speaker 1: down in the Nasdaq. In twenty twenty, during the pandemic, 91 00:04:29,560 --> 00:04:32,839 Speaker 1: we had a thirty six percent draw down. Now, one 92 00:04:32,839 --> 00:04:35,120 Speaker 1: thing you might notice is that these draw downs are 93 00:04:35,120 --> 00:04:40,400 Speaker 1: getting less and less, from eighty one to fifty to thirty. 94 00:04:40,600 --> 00:04:43,440 Speaker 1: You notice that. So this fits into why I continually 95 00:04:43,440 --> 00:04:45,760 Speaker 1: tell you that what we're seeing as a crash up, 96 00:04:46,200 --> 00:04:48,560 Speaker 1: not a crash down. The way that the government has 97 00:04:48,680 --> 00:04:52,320 Speaker 1: used debt, especially around this period right here, fiscal spending 98 00:04:52,400 --> 00:04:55,320 Speaker 1: has changed these markets. Anyway, we're not talking about that 99 00:04:55,320 --> 00:04:57,360 Speaker 1: in this video. But you can see that the Nasdaq 100 00:04:57,400 --> 00:04:58,840 Speaker 1: has gone up. But the thing that I want to 101 00:04:58,920 --> 00:05:02,920 Speaker 1: draw your attention to is the concentration that's happening in 102 00:05:02,960 --> 00:05:06,000 Speaker 1: the Nasdaq. So what this shows is the largest ten 103 00:05:06,080 --> 00:05:10,440 Speaker 1: percent of stocks as a percent of the total value 104 00:05:10,440 --> 00:05:13,080 Speaker 1: of stocks. And what this shows us is that over 105 00:05:13,120 --> 00:05:15,960 Speaker 1: the past five and a half decades there's only been 106 00:05:16,080 --> 00:05:20,640 Speaker 1: two previous peaks in market concentration. So we saw that 107 00:05:20,760 --> 00:05:23,839 Speaker 1: right here in the seventies, we saw it again in 108 00:05:23,880 --> 00:05:26,560 Speaker 1: the two thousand dot Com boom and bust, and now 109 00:05:26,560 --> 00:05:29,680 Speaker 1: we see it again here today. Now I've put this 110 00:05:29,880 --> 00:05:31,719 Speaker 1: red line on there, so again I like to show 111 00:05:31,720 --> 00:05:33,880 Speaker 1: you the charts. You can see the direction, the size 112 00:05:33,880 --> 00:05:35,880 Speaker 1: of the speed of the moves, and you can see 113 00:05:35,880 --> 00:05:39,960 Speaker 1: that the concentration keeps getting bigger and bigger and bigger. 114 00:05:40,080 --> 00:05:42,800 Speaker 1: Now why is this important, Well, if you're buying the 115 00:05:42,920 --> 00:05:45,240 Speaker 1: Nasdaq index or the S and P five hundred index 116 00:05:45,360 --> 00:05:47,360 Speaker 1: for that matter, you're buying the S and P five 117 00:05:47,400 --> 00:05:50,599 Speaker 1: hundred because of the mag seven. Right, there's seven stocks 118 00:05:50,600 --> 00:05:53,640 Speaker 1: that are driving most of that entire index. In the Nasdaq, 119 00:05:53,680 --> 00:05:56,000 Speaker 1: you're seeing about the same thing. The concentration of the 120 00:05:56,040 --> 00:05:58,359 Speaker 1: top ten is getting bigger. Now. The reason why this 121 00:05:58,440 --> 00:06:01,200 Speaker 1: is the problem is if you're passively invested into the 122 00:06:01,279 --> 00:06:04,360 Speaker 1: index and one or two of these companies, there's only seven, 123 00:06:04,400 --> 00:06:06,320 Speaker 1: and they have to be five hundred back seven. If 124 00:06:06,360 --> 00:06:10,039 Speaker 1: they drop, they bring the entire index down with them. 125 00:06:10,279 --> 00:06:13,800 Speaker 1: Super important to understand. Okay, so we can see that 126 00:06:13,839 --> 00:06:17,120 Speaker 1: concentration is at an all time high. Now what does 127 00:06:17,120 --> 00:06:20,159 Speaker 1: that mean? What are the historical parallels to this? Well, 128 00:06:20,320 --> 00:06:25,839 Speaker 1: we can see that historically speaking, high concentration equals high danger. 129 00:06:26,080 --> 00:06:28,920 Speaker 1: We can see that historically speaking, whenever we've reached these 130 00:06:29,000 --> 00:06:33,080 Speaker 1: levels of concentration, we've seen big crashes happen off the 131 00:06:33,080 --> 00:06:35,680 Speaker 1: back of that. Now we also have historical parallels to 132 00:06:35,720 --> 00:06:38,480 Speaker 1: where those happened, like the dot com boom, for example, 133 00:06:38,839 --> 00:06:42,720 Speaker 1: was when we had extreme tech optimism. Now I'm optimistic 134 00:06:42,720 --> 00:06:45,800 Speaker 1: about tech, but we had extreme tech optimism in the seventies. 135 00:06:45,880 --> 00:06:48,240 Speaker 1: Same thing that was when the microprocessor came out. You 136 00:06:48,320 --> 00:06:51,360 Speaker 1: might know from my quantum wave thesis the last one 137 00:06:51,360 --> 00:06:54,120 Speaker 1: started in nineteen seventy one, right at that peak. I'll 138 00:06:54,120 --> 00:06:56,159 Speaker 1: show you more than that in a second. We also 139 00:06:56,240 --> 00:06:58,960 Speaker 1: had a sudden change in the models. I'm going to 140 00:06:59,000 --> 00:07:02,480 Speaker 1: talk about that in a second. But this is pricing 141 00:07:02,560 --> 00:07:05,320 Speaker 1: the nasdak in gold. This is from my friend Luke 142 00:07:05,360 --> 00:07:08,520 Speaker 1: Grammanov at FFTT. Check him out. He's worth a follow. 143 00:07:08,760 --> 00:07:10,320 Speaker 1: But what we want to do is we want to 144 00:07:10,320 --> 00:07:13,120 Speaker 1: look at things if they're expensive or cheap priced in 145 00:07:13,200 --> 00:07:15,000 Speaker 1: other things, not just US dollars, because if we look 146 00:07:15,040 --> 00:07:17,680 Speaker 1: at US dollars, it's always manipulated. So here's the Nasdaq 147 00:07:17,760 --> 00:07:20,680 Speaker 1: priced in gold. Again, during the dot com boom got 148 00:07:20,680 --> 00:07:23,040 Speaker 1: really expensive, but we can see that it's basically been 149 00:07:23,040 --> 00:07:26,000 Speaker 1: breaking down ever since, and it's been in this range 150 00:07:26,080 --> 00:07:28,800 Speaker 1: right here, and so again if you're passively invested in 151 00:07:28,920 --> 00:07:32,000 Speaker 1: index and to be wary of that, and especially when 152 00:07:32,000 --> 00:07:35,640 Speaker 1: they're sudden changes in the technology, which is what happened 153 00:07:35,720 --> 00:07:38,800 Speaker 1: in nineteen seventy. In the year two thousand, all right, 154 00:07:38,840 --> 00:07:41,360 Speaker 1: so what are we talking about? How is AI changing 155 00:07:41,400 --> 00:07:43,040 Speaker 1: and what do we need to be aware of? Well, 156 00:07:43,520 --> 00:07:46,080 Speaker 1: what really happened. I made a video a few weeks ago. 157 00:07:46,120 --> 00:07:48,840 Speaker 1: I think it was talking about deep Seat. Deep Seat 158 00:07:49,040 --> 00:07:52,080 Speaker 1: was a new open source LLM, a new AI model 159 00:07:52,240 --> 00:07:54,680 Speaker 1: that was released from a company in China. But what 160 00:07:54,800 --> 00:07:57,200 Speaker 1: happened is when that was released, we saw the entire 161 00:07:57,240 --> 00:08:00,480 Speaker 1: market plunge. In video, Everyone's Darling plunged time, but the 162 00:08:00,560 --> 00:08:03,200 Speaker 1: entire market plunged, And I made a video. I'll link 163 00:08:03,240 --> 00:08:05,160 Speaker 1: to it down below. You should watch that to really understand. 164 00:08:05,200 --> 00:08:08,119 Speaker 1: But basically what it did is exposed that all our 165 00:08:08,160 --> 00:08:11,840 Speaker 1: models for evaluating these companies, the growth of these companies 166 00:08:12,520 --> 00:08:14,960 Speaker 1: and even the way that money goes into the index 167 00:08:15,000 --> 00:08:18,160 Speaker 1: of the NASDAC has completely changed. And so it highlighted 168 00:08:18,200 --> 00:08:21,680 Speaker 1: that everything that we thought we knew we don't know anymore. Now. 169 00:08:21,680 --> 00:08:23,640 Speaker 1: One of the things that we saw is that because 170 00:08:23,680 --> 00:08:27,120 Speaker 1: deep seek was an open source LLM, then what it 171 00:08:27,160 --> 00:08:29,640 Speaker 1: did is it's shone a light on all the AI 172 00:08:29,840 --> 00:08:34,320 Speaker 1: monopolies that we saw again Open Ai, Google, those types 173 00:08:34,320 --> 00:08:38,160 Speaker 1: of companies, Cloud, etc. It showed that their pricing is over. 174 00:08:38,440 --> 00:08:41,240 Speaker 1: How can any of those open AI or gym and 175 00:08:41,240 --> 00:08:43,920 Speaker 1: how could they be charging when we have open source 176 00:08:44,000 --> 00:08:47,160 Speaker 1: models that are better. And so that changed all that 177 00:08:47,200 --> 00:08:51,040 Speaker 1: we saw that AI's paywall is losing pricing power eventually 178 00:08:51,240 --> 00:08:54,600 Speaker 1: be priced out completely. And what that's showing is that 179 00:08:54,640 --> 00:08:58,960 Speaker 1: the entire AI stock market needs to be reevaluated. Now 180 00:08:59,040 --> 00:09:02,920 Speaker 1: It's not just this, there's all types of now AI gateways, 181 00:09:02,960 --> 00:09:06,720 Speaker 1: AI agents that are now bridging all of the aillms together. 182 00:09:06,800 --> 00:09:09,520 Speaker 1: So for example, now for like five bucks a month, 183 00:09:09,600 --> 00:09:11,640 Speaker 1: I could get access to all of them without having 184 00:09:11,679 --> 00:09:14,320 Speaker 1: to pay for them individually. So we're seeing this but 185 00:09:14,360 --> 00:09:16,920 Speaker 1: now again like these open source models are completely changing this. 186 00:09:17,200 --> 00:09:19,480 Speaker 1: So then the question is again is if lllms are free, 187 00:09:19,920 --> 00:09:23,520 Speaker 1: where does the value go? Well, good thing, I have 188 00:09:23,520 --> 00:09:26,160 Speaker 1: an answer for you, because history tells us that. And 189 00:09:26,200 --> 00:09:28,600 Speaker 1: of course I've been investing in technology for decades. So 190 00:09:28,640 --> 00:09:30,440 Speaker 1: let me show you how we look at this. So 191 00:09:30,559 --> 00:09:34,000 Speaker 1: open source shift. So it started where I think, right 192 00:09:34,040 --> 00:09:36,400 Speaker 1: where open ai hit the scene and they raised a 193 00:09:36,440 --> 00:09:38,959 Speaker 1: ton of money. Right they're the Wall Street Darland, They're 194 00:09:38,960 --> 00:09:41,680 Speaker 1: gaining all this momentum. And where I've really first started 195 00:09:41,720 --> 00:09:45,600 Speaker 1: noticing it is Meta. Facebook Meta launched Lama, which is 196 00:09:45,640 --> 00:09:49,120 Speaker 1: an open source LLM, a large language model an AI. 197 00:09:49,679 --> 00:09:51,640 Speaker 1: And when I saw that happen, it made me stop 198 00:09:51,679 --> 00:09:55,280 Speaker 1: and think, why would Facebook, who's changed their name to Meta, 199 00:09:55,320 --> 00:09:57,520 Speaker 1: who's rushing into the space, Why would they open up 200 00:09:57,559 --> 00:10:02,360 Speaker 1: a free, open source model when the apparent model seems 201 00:10:02,400 --> 00:10:03,839 Speaker 1: to be like open AI and try to raise a 202 00:10:03,840 --> 00:10:05,240 Speaker 1: bunch of money and be worth a lot of money. 203 00:10:05,640 --> 00:10:08,440 Speaker 1: Why would Facebook do that? And one of my thoughts was, well, 204 00:10:08,679 --> 00:10:12,400 Speaker 1: Facebook is worth i don't know, ten times twenty times 205 00:10:12,400 --> 00:10:15,000 Speaker 1: more than open AI. Open AA is not really a 206 00:10:15,000 --> 00:10:19,480 Speaker 1: threat to them today, there's really small. If Facebook opens 207 00:10:19,559 --> 00:10:24,959 Speaker 1: up a open source LLM, they neutralize opening I how 208 00:10:24,960 --> 00:10:27,160 Speaker 1: can opening I be worth any money if now there's 209 00:10:27,200 --> 00:10:29,840 Speaker 1: all the free ones that are even better, And so 210 00:10:29,880 --> 00:10:32,319 Speaker 1: it seemed like it was like maybe Zuckerberg playing forty 211 00:10:32,480 --> 00:10:36,080 Speaker 1: chess when open AI and he's trying to kind of 212 00:10:36,080 --> 00:10:38,400 Speaker 1: play the old playbook. That was what I thought at first. 213 00:10:38,840 --> 00:10:40,559 Speaker 1: But it's changed a little bit, and I'm going to 214 00:10:40,600 --> 00:10:42,520 Speaker 1: show you where the real value is accruing. Now we 215 00:10:42,520 --> 00:10:45,360 Speaker 1: can see this other open source models, code gen, which 216 00:10:45,400 --> 00:10:48,640 Speaker 1: is Salesforce CRM, so the giant the CRM space. So 217 00:10:48,640 --> 00:10:51,760 Speaker 1: we're seeing like SaaS companies jumping into the space. Goose 218 00:10:51,800 --> 00:10:55,040 Speaker 1: which is an open it's an open source AI agent 219 00:10:55,080 --> 00:10:57,720 Speaker 1: project from Jack Dorsey, the founder of Twitter. Now he's 220 00:10:57,920 --> 00:11:00,959 Speaker 1: head a block deep Seek. Of course, since deep Sea 221 00:11:01,000 --> 00:11:02,840 Speaker 1: came how just a few weeks ago, we've seen like 222 00:11:02,840 --> 00:11:04,880 Speaker 1: half a dozen more come out of China. They're coming 223 00:11:04,920 --> 00:11:08,520 Speaker 1: out in mass A small business owner, are you buried 224 00:11:08,640 --> 00:11:11,040 Speaker 1: in all types of work keeping you from the real 225 00:11:11,120 --> 00:11:13,720 Speaker 1: thing that makes you money? Well that's where just Works 226 00:11:13,760 --> 00:11:15,960 Speaker 1: comes in. They're the all in one platform that supports 227 00:11:16,040 --> 00:11:19,000 Speaker 1: small business growth. You can get all their tools that 228 00:11:19,040 --> 00:11:22,760 Speaker 1: help with benefits like payroll and HR and compliance with 229 00:11:22,920 --> 00:11:26,880 Speaker 1: transparent pricing. Now they help you hire top talent internationally, 230 00:11:26,920 --> 00:11:31,200 Speaker 1: internew markets, quickly scale international operations without the workload, and 231 00:11:31,280 --> 00:11:34,160 Speaker 1: forevery how do I do it? Question? You can reach 232 00:11:34,160 --> 00:11:37,360 Speaker 1: out to their expert staff from sole proprietor or a 233 00:11:37,400 --> 00:11:40,800 Speaker 1: team of twenty. Just Works empowers all kinds of small 234 00:11:40,840 --> 00:11:45,040 Speaker 1: businesses with real human support. So visit Justworks dot com 235 00:11:45,080 --> 00:11:48,440 Speaker 1: slash podcast to join the thousands of small businesses that 236 00:11:48,480 --> 00:11:52,199 Speaker 1: trust just Works to take care of payroll, benefits, compliance 237 00:11:52,320 --> 00:11:58,040 Speaker 1: and more. Again that's Justworks dot com slash podcasts. But 238 00:11:58,120 --> 00:11:59,240 Speaker 1: really what we want to do is we want to 239 00:11:59,240 --> 00:12:02,200 Speaker 1: look back to the dot and even crypto models to 240 00:12:02,240 --> 00:12:06,559 Speaker 1: really understand how this works. Where does the value accrue? Now, 241 00:12:06,600 --> 00:12:08,880 Speaker 1: you might have seen me use this chart. If you 242 00:12:08,960 --> 00:12:10,679 Speaker 1: watch my content, you see me use this chart all 243 00:12:10,720 --> 00:12:13,960 Speaker 1: the time. And you understand that in these quantum wave cycles, 244 00:12:14,160 --> 00:12:16,320 Speaker 1: we have about a fifty year cycle and they happen 245 00:12:16,480 --> 00:12:19,480 Speaker 1: in these four phases, and we need to understand that 246 00:12:19,480 --> 00:12:23,480 Speaker 1: the way that we invest through each phase changes. So 247 00:12:23,520 --> 00:12:25,800 Speaker 1: the way that I invested here is going to be 248 00:12:25,840 --> 00:12:27,800 Speaker 1: different than the way and the companies I invest in 249 00:12:27,840 --> 00:12:31,080 Speaker 1: here different here and so forth. All right, So right 250 00:12:31,120 --> 00:12:35,080 Speaker 1: now we are right here starting this second phase, and 251 00:12:35,120 --> 00:12:37,800 Speaker 1: so the old way of investing no longer works. So 252 00:12:38,200 --> 00:12:40,640 Speaker 1: let me break it down with some parallels. We think 253 00:12:40,679 --> 00:12:44,559 Speaker 1: about technology in layers, all right, Technology scales and layers 254 00:12:44,600 --> 00:12:47,319 Speaker 1: is what most people misunderstand, and so they think the 255 00:12:47,320 --> 00:12:49,400 Speaker 1: Internet was too slow, can't scale. Let's go spend a 256 00:12:49,440 --> 00:12:52,600 Speaker 1: billion dollars in intranets. Bitcoin is too slow, can't scale. 257 00:12:52,640 --> 00:12:55,720 Speaker 1: Let's go try all these crypto projects without understanding that 258 00:12:55,720 --> 00:12:59,040 Speaker 1: technology scales and layers, but also the way value accruise 259 00:12:59,080 --> 00:13:01,080 Speaker 1: happens in layers. So what do I mean by that? 260 00:13:01,240 --> 00:13:03,319 Speaker 1: If you think about the Internet, we have a base 261 00:13:03,440 --> 00:13:05,280 Speaker 1: layer of the Internet, right, so this would be like 262 00:13:05,400 --> 00:13:09,800 Speaker 1: TCP and IP, right, and then we want email, so 263 00:13:09,840 --> 00:13:13,840 Speaker 1: then we have like SMTP, and then we want security, 264 00:13:13,920 --> 00:13:17,280 Speaker 1: so we have like https. Right. You know what those 265 00:13:17,280 --> 00:13:20,600 Speaker 1: things are all right, but no value as a crude 266 00:13:20,800 --> 00:13:26,200 Speaker 1: at this base layer TCP, IP protocol, SMTPA, CTPS protocols, 267 00:13:25,960 --> 00:13:30,080 Speaker 1: they're not worth anything. They're just open source protocols. Where 268 00:13:30,120 --> 00:13:33,760 Speaker 1: all the value has accrued is on higher levels, so 269 00:13:34,000 --> 00:13:38,760 Speaker 1: on the applications. So for example, you have Google. Google 270 00:13:38,800 --> 00:13:41,960 Speaker 1: created Chrome and now you have all these Chrome plugins 271 00:13:42,040 --> 00:13:44,520 Speaker 1: right here that are worth a lot of money. You 272 00:13:44,520 --> 00:13:46,200 Speaker 1: can think about this like with the iPhone. You have 273 00:13:46,240 --> 00:13:48,320 Speaker 1: the iPhone, which obviously you create a lot of value, 274 00:13:48,440 --> 00:13:50,080 Speaker 1: but then think about the app store and think about 275 00:13:50,080 --> 00:13:53,400 Speaker 1: all the apps inside of that, all right, So this 276 00:13:53,440 --> 00:13:56,440 Speaker 1: is where the value is accrued, not on the base layer, 277 00:13:56,679 --> 00:13:59,080 Speaker 1: but on the stack, all right. We can think about 278 00:13:59,120 --> 00:14:03,000 Speaker 1: the same thing with bigcoin. Now, we had Bitcoin, which 279 00:14:03,040 --> 00:14:07,160 Speaker 1: is a protocol, It's a protocol that transfers data, right, 280 00:14:08,200 --> 00:14:10,800 Speaker 1: and obviously value is accruing there, but not so much 281 00:14:10,800 --> 00:14:13,080 Speaker 1: on the protocol, but the asset Bitcoin, the asset, not 282 00:14:13,120 --> 00:14:17,120 Speaker 1: the network. Now we have companies that are building layers 283 00:14:17,640 --> 00:14:20,720 Speaker 1: on top of the Bitcoin stack, and so certainly the 284 00:14:20,720 --> 00:14:22,800 Speaker 1: Bitcoin network has a crude value, but then we have 285 00:14:22,880 --> 00:14:25,080 Speaker 1: even more value being accrued up peer. That's what my 286 00:14:25,200 --> 00:14:28,360 Speaker 1: fund investment we invest into these. But back to the 287 00:14:28,800 --> 00:14:31,160 Speaker 1: topic that we're talking about right now, which is AI, 288 00:14:31,360 --> 00:14:33,560 Speaker 1: we're seeing the same thing. So what I would say 289 00:14:33,680 --> 00:14:37,320 Speaker 1: is these lms are like a base layer. So the 290 00:14:37,440 --> 00:14:40,000 Speaker 1: lms are now open source, the deep seek, the LAMA, 291 00:14:40,160 --> 00:14:43,800 Speaker 1: all those things, and there's no value accruing there. They're 292 00:14:43,840 --> 00:14:45,880 Speaker 1: all racing down to the bottom. They're all for free. 293 00:14:46,040 --> 00:14:50,360 Speaker 1: Where the value gets accrued is on higher levels. So 294 00:14:50,400 --> 00:14:53,520 Speaker 1: it's on the applications, the narrow specific use cases that 295 00:14:53,560 --> 00:14:56,280 Speaker 1: are being built on top of the open source model. 296 00:14:56,600 --> 00:14:58,400 Speaker 1: And so we can see right now today the smart 297 00:14:58,400 --> 00:15:01,760 Speaker 1: money isn't just betting on AI. That was the old way, 298 00:15:01,800 --> 00:15:04,040 Speaker 1: that was twenty three, twenty four. Now it's betting on 299 00:15:04,080 --> 00:15:07,080 Speaker 1: the right layer of AI. Which layer do we want 300 00:15:07,080 --> 00:15:08,600 Speaker 1: to invest and do the same way might fund investing 301 00:15:08,560 --> 00:15:10,920 Speaker 1: in to bitcoin? Which layer do we want to invest into? 302 00:15:11,360 --> 00:15:14,000 Speaker 1: Now I'll show you that. Don't worry. Now, I am 303 00:15:14,080 --> 00:15:16,560 Speaker 1: gonna break this down in greater detail and show you 304 00:15:16,600 --> 00:15:19,080 Speaker 1: what different types of projects and companies are being built there. 305 00:15:19,440 --> 00:15:21,120 Speaker 1: If you want to join me next week, we're gonna 306 00:15:21,160 --> 00:15:23,280 Speaker 1: go live deep into this. I got I don't know, 307 00:15:23,320 --> 00:15:25,760 Speaker 1: thirty forty charts or I'll break all of this down 308 00:15:25,920 --> 00:15:27,560 Speaker 1: and then I'll take questions, so we'll talk about it. 309 00:15:27,560 --> 00:15:29,320 Speaker 1: We'll discuss it, figure out the best way to find 310 00:15:29,320 --> 00:15:31,120 Speaker 1: these companies invest into them. I'll throw you a couple 311 00:15:31,120 --> 00:15:32,560 Speaker 1: of names that I like. If you want to come 312 00:15:32,640 --> 00:15:34,480 Speaker 1: join me, it's all for free. I'll put a link 313 00:15:34,520 --> 00:15:37,480 Speaker 1: down there down below. Come hang out. Let's have fun 314 00:15:37,520 --> 00:15:39,800 Speaker 1: talking about this. Let's discuss it all. Like I said, live, 315 00:15:39,880 --> 00:15:41,520 Speaker 1: Q and A and so much more. Join me for 316 00:15:41,520 --> 00:15:45,400 Speaker 1: free and the link down below. Okay, now, what we're 317 00:15:45,440 --> 00:15:48,440 Speaker 1: seeing because of this is a massive shift of capital. 318 00:15:48,720 --> 00:15:51,200 Speaker 1: And it's not just from AI based layer to a 319 00:15:51,680 --> 00:15:55,120 Speaker 1: higher level. Like I said, it's an entire index. It's 320 00:15:55,200 --> 00:15:58,440 Speaker 1: even an entire continent. So what I'm talking about, Well, 321 00:15:58,480 --> 00:16:02,600 Speaker 1: if China is now pushing these open source models, what 322 00:16:02,640 --> 00:16:04,680 Speaker 1: we're seeing is that the US has sort of been 323 00:16:04,800 --> 00:16:07,160 Speaker 1: competing more of a scarcity, right, we got to compete. 324 00:16:07,280 --> 00:16:10,200 Speaker 1: Let's keep China out of the game. But China is 325 00:16:10,240 --> 00:16:12,800 Speaker 1: trying to compete. Now it's not an even playing field. 326 00:16:13,080 --> 00:16:15,320 Speaker 1: This is the whole conversation about tariffs and so forth, 327 00:16:15,360 --> 00:16:18,080 Speaker 1: and you have a country that's subsidizing things, and that's 328 00:16:18,120 --> 00:16:19,960 Speaker 1: a whole other topic. We can make a video if 329 00:16:19,960 --> 00:16:21,960 Speaker 1: you want, drop me a comment down below. But what 330 00:16:22,000 --> 00:16:25,440 Speaker 1: we've seen is that China has been trying to outcompete us. 331 00:16:25,560 --> 00:16:28,120 Speaker 1: The US has been trying to protect but it's basically 332 00:16:28,280 --> 00:16:31,280 Speaker 1: forced the shift in the market where now open source 333 00:16:31,360 --> 00:16:35,480 Speaker 1: projects are now superior to companies that are trying to 334 00:16:35,560 --> 00:16:37,880 Speaker 1: protect the mote. If you're trying to protect the mote, 335 00:16:37,880 --> 00:16:39,200 Speaker 1: you're just not going to make it the world is 336 00:16:39,280 --> 00:16:41,480 Speaker 1: open source. Jack Dorsy tweeted this so much the other 337 00:16:41,560 --> 00:16:44,800 Speaker 1: day on Twitter saying or on x saying that the 338 00:16:44,800 --> 00:16:47,280 Speaker 1: world is open source and that is the future. It's 339 00:16:47,320 --> 00:16:50,000 Speaker 1: why I talk about decentralization all the time. But the 340 00:16:50,080 --> 00:16:53,000 Speaker 1: question is if this is happening. We know that the 341 00:16:53,160 --> 00:16:55,680 Speaker 1: US has been the financial hub of the world. We 342 00:16:55,760 --> 00:16:58,240 Speaker 1: know that the US stock markets S and P five 343 00:16:58,320 --> 00:17:01,040 Speaker 1: hundred and the Nasdaq are the great investment markets in 344 00:17:01,080 --> 00:17:02,960 Speaker 1: the world. We know all that money is accrueing there, 345 00:17:02,960 --> 00:17:06,720 Speaker 1: all the businesses are listed there. But if China is 346 00:17:06,760 --> 00:17:10,080 Speaker 1: out competing US, does some of that money start leaving 347 00:17:10,119 --> 00:17:12,560 Speaker 1: the US and going to China. Well, I have a 348 00:17:12,640 --> 00:17:16,240 Speaker 1: chart to answer that question. What we can see right here, 349 00:17:16,800 --> 00:17:18,359 Speaker 1: as you know again if you watch my videos on 350 00:17:18,400 --> 00:17:21,280 Speaker 1: a regular basis the reason why, and I hinted too earlier, 351 00:17:21,320 --> 00:17:23,000 Speaker 1: the reason why we see the stock markets going up 352 00:17:23,040 --> 00:17:24,959 Speaker 1: so high is because the amount of money that they 353 00:17:24,960 --> 00:17:27,600 Speaker 1: continue to print right through the debasement. And what we 354 00:17:27,640 --> 00:17:29,840 Speaker 1: can see here is that. So what we have here 355 00:17:30,000 --> 00:17:33,159 Speaker 1: is on the red line, we have the Nasdaq one 356 00:17:33,320 --> 00:17:36,199 Speaker 1: hundred going up, that's right here. But what we have 357 00:17:36,400 --> 00:17:41,600 Speaker 1: on the green line is the US net investment position. 358 00:17:42,080 --> 00:17:43,800 Speaker 1: So this is the amount of money that went in, 359 00:17:44,000 --> 00:17:47,000 Speaker 1: which you can see is higher than the amount of 360 00:17:47,080 --> 00:17:49,520 Speaker 1: the Nasdaq itself. And what we have in the blue 361 00:17:49,560 --> 00:17:53,639 Speaker 1: line down here is the foreign direct investment in US equities, 362 00:17:54,119 --> 00:17:57,560 Speaker 1: mainly coming from China. So what happens is, just like you, 363 00:17:58,080 --> 00:18:01,200 Speaker 1: a country has surpluses, so they have trades, exports, they 364 00:18:01,200 --> 00:18:03,720 Speaker 1: have imports, they have surpluses, they have savings. What do 365 00:18:03,760 --> 00:18:06,240 Speaker 1: they do with that, Well, they put it somewhere and 366 00:18:06,320 --> 00:18:08,879 Speaker 1: in this case, a lot of that has been being recycled, 367 00:18:08,960 --> 00:18:12,240 Speaker 1: used to be recycled into US treasuries, still is a 368 00:18:12,240 --> 00:18:14,840 Speaker 1: lot of it is has been recycled into the NASDAK 369 00:18:14,880 --> 00:18:17,320 Speaker 1: and that's exactly what we've seen. So China has been 370 00:18:17,359 --> 00:18:21,600 Speaker 1: recycling a substantial portion of its surpluses into these US equities, 371 00:18:21,800 --> 00:18:25,000 Speaker 1: which is pushed the entire index up. But back to 372 00:18:25,040 --> 00:18:28,480 Speaker 1: the competing angle. Now, if China now is moving ahead 373 00:18:28,480 --> 00:18:31,040 Speaker 1: in tech, which they've already sort of outpaced the US 374 00:18:31,040 --> 00:18:33,480 Speaker 1: with evs and batteries and lots of things like that, 375 00:18:34,080 --> 00:18:36,280 Speaker 1: will a lot of that Chinese money, instead of going 376 00:18:36,320 --> 00:18:39,600 Speaker 1: to the Nasdaq start going to their own indexes. So 377 00:18:39,640 --> 00:18:42,800 Speaker 1: we're seeing a massive disruption here all over the place. 378 00:18:43,000 --> 00:18:44,800 Speaker 1: So the question or the thing we need to ponder 379 00:18:44,880 --> 00:18:48,160 Speaker 1: is not only is AI itself changing, but the global 380 00:18:48,240 --> 00:18:51,399 Speaker 1: flow of capital is shifting as well. If you have 381 00:18:51,440 --> 00:18:53,880 Speaker 1: to understand these things if you want to have success 382 00:18:54,160 --> 00:18:57,040 Speaker 1: with your portfolio, because the world is changing rapidly. It's 383 00:18:57,040 --> 00:18:59,760 Speaker 1: always technology that changes the world, and in these quantum 384 00:18:59,760 --> 00:19:01,720 Speaker 1: wave cycles like we're in right now, it's where all 385 00:19:01,760 --> 00:19:04,919 Speaker 1: the change happens. Okay, so what is this next phase 386 00:19:04,960 --> 00:19:08,240 Speaker 1: for AI? Well, the losers, the ones that are getting 387 00:19:08,280 --> 00:19:13,240 Speaker 1: left behind are the AI monopolies, the open ais, the Googles, right, 388 00:19:13,320 --> 00:19:14,919 Speaker 1: those are the ones that are trying to kind of 389 00:19:15,119 --> 00:19:17,359 Speaker 1: hold their LLM behind a paywall. They're going to be 390 00:19:17,400 --> 00:19:23,440 Speaker 1: the losers. Chip stocks Nvidia AMD why because they were 391 00:19:23,480 --> 00:19:27,159 Speaker 1: pricing in unlimited demand. But what Deepseak showed us is 392 00:19:27,160 --> 00:19:29,840 Speaker 1: that they're able to train these AIM models for way 393 00:19:29,920 --> 00:19:33,359 Speaker 1: cheaper with way less GPUs than we thought. So instead 394 00:19:33,400 --> 00:19:35,520 Speaker 1: of the demand for chips being like this, we find 395 00:19:35,560 --> 00:19:38,080 Speaker 1: out it's probably more like this, and as technology continues 396 00:19:38,119 --> 00:19:41,200 Speaker 1: to accelerate, it might even be more like this. So 397 00:19:41,359 --> 00:19:43,479 Speaker 1: those are ones we want to watch out for. We 398 00:19:43,520 --> 00:19:46,359 Speaker 1: also want to watch out for all the hype driven narratives. Right, 399 00:19:46,400 --> 00:19:48,240 Speaker 1: So all these companies that are trying to ride this 400 00:19:48,320 --> 00:19:51,320 Speaker 1: hype train we're talking about, like AI SaaS companies think 401 00:19:51,359 --> 00:19:55,000 Speaker 1: about Salesforce launching their open AM model or their LM model. 402 00:19:55,200 --> 00:19:58,920 Speaker 1: So hype driven AI SaaS companies with no moat again, right, 403 00:19:59,119 --> 00:20:01,720 Speaker 1: there is no mot This is all going down. It's 404 00:20:01,760 --> 00:20:03,199 Speaker 1: going to be a base layer and they're all going 405 00:20:03,280 --> 00:20:05,680 Speaker 1: to be basically competing as commodities. So who will the 406 00:20:05,720 --> 00:20:08,120 Speaker 1: winners be? Where will the real money go? Where will 407 00:20:08,160 --> 00:20:12,600 Speaker 1: the real money be made? Well, AI high value applications, 408 00:20:12,960 --> 00:20:17,120 Speaker 1: narrow niche use cases, high value applications on top of 409 00:20:17,160 --> 00:20:19,800 Speaker 1: the open source llms. Let me give you an example. 410 00:20:20,640 --> 00:20:23,760 Speaker 1: In twenty twenty two, when open ai released, you had 411 00:20:23,800 --> 00:20:27,040 Speaker 1: all the open APIs you could use. You could do anything. 412 00:20:27,119 --> 00:20:30,560 Speaker 1: You can create images, you could to create text, right, code, whatever. Well, 413 00:20:30,600 --> 00:20:32,879 Speaker 1: when people are faced with I could do anything, they 414 00:20:32,880 --> 00:20:34,639 Speaker 1: don't know what to do. So there was an app 415 00:20:34,640 --> 00:20:38,000 Speaker 1: you might remember created called lensa AI and all it 416 00:20:38,000 --> 00:20:41,240 Speaker 1: did was just use the APIs that open i had produced. 417 00:20:41,400 --> 00:20:43,160 Speaker 1: But with LENDSAI, I could take a picture of myself 418 00:20:43,200 --> 00:20:46,120 Speaker 1: and it would give me back ten avatars. A very 419 00:20:46,200 --> 00:20:47,919 Speaker 1: narrow use case of what the whole thing could do. 420 00:20:48,600 --> 00:20:50,879 Speaker 1: But it got so popular so fast. I believe in 421 00:20:50,920 --> 00:20:53,679 Speaker 1: like ninety days it was worth like a billion dollars 422 00:20:54,240 --> 00:20:55,800 Speaker 1: because it was a very narrow use case. And that's 423 00:20:55,840 --> 00:20:58,840 Speaker 1: what we're talking about, high value applications on top of 424 00:20:59,359 --> 00:21:02,720 Speaker 1: the base layer, the open source lms. Specifically, I'm looking 425 00:21:02,760 --> 00:21:08,400 Speaker 1: for where bitcoin, AI, and open source decentralization, where all 426 00:21:08,440 --> 00:21:11,240 Speaker 1: those things converge so we have a new set of 427 00:21:11,280 --> 00:21:15,800 Speaker 1: building blocks. What happens when we use these three together, 428 00:21:15,840 --> 00:21:17,880 Speaker 1: where they converge and build things that we can't even 429 00:21:17,920 --> 00:21:22,320 Speaker 1: imagine today. And AI infrastructure provides that it doesn't really 430 00:21:22,400 --> 00:21:26,080 Speaker 1: high on close sourced models. Again, it's all moving to 431 00:21:26,160 --> 00:21:28,920 Speaker 1: open source. That's the big theme. Hopefully you're catching onto that. 432 00:21:28,960 --> 00:21:31,640 Speaker 1: I've been talking about what I call the decentralized revolution 433 00:21:31,920 --> 00:21:34,159 Speaker 1: for about five years now. Okay, now, how do we 434 00:21:34,200 --> 00:21:36,800 Speaker 1: play this? What does this mean to us? Well, one, 435 00:21:36,840 --> 00:21:38,960 Speaker 1: we have to understand the game is changing, right and 436 00:21:39,040 --> 00:21:42,800 Speaker 1: we understand through historical parallels exactly how that changes. Number Two, 437 00:21:43,040 --> 00:21:45,800 Speaker 1: we have to understand that passive investing is super dangerous 438 00:21:45,880 --> 00:21:47,919 Speaker 1: right now, because, as I said, if we have this 439 00:21:48,080 --> 00:21:51,159 Speaker 1: over concentration, if one or two of these companies that 440 00:21:51,200 --> 00:21:53,840 Speaker 1: are at risk right now. If they drop, the entire 441 00:21:53,920 --> 00:21:56,919 Speaker 1: index can drop. On top of that, we realize that 442 00:21:57,200 --> 00:21:59,600 Speaker 1: maybe China could steal some of that capital, take their 443 00:21:59,640 --> 00:22:02,000 Speaker 1: capital back even to their own markets. We also know 444 00:22:02,080 --> 00:22:04,880 Speaker 1: that most likely there's this next four or five year 445 00:22:04,920 --> 00:22:07,920 Speaker 1: cycle we're going to see a massive amount of monetary debasement, 446 00:22:08,160 --> 00:22:10,159 Speaker 1: and so that also manipulates what we see in the 447 00:22:10,240 --> 00:22:13,200 Speaker 1: Nasdaq or the indexes. So I think in order to survive, 448 00:22:13,240 --> 00:22:16,000 Speaker 1: we need to be much more selective in the companies, 449 00:22:16,200 --> 00:22:19,280 Speaker 1: specifically looking for the ones that are in that convergence. 450 00:22:19,400 --> 00:22:21,720 Speaker 1: Right in those three those are the ones that's going 451 00:22:21,800 --> 00:22:23,720 Speaker 1: to be where the biggest gains, and they're going to 452 00:22:23,720 --> 00:22:27,119 Speaker 1: come again from the convergence of bitcoin, AI and open 453 00:22:27,119 --> 00:22:31,280 Speaker 1: source where those three things work together. Individually, yeah sure great, 454 00:22:31,359 --> 00:22:34,760 Speaker 1: but together is where the magic made. Where that convergence is. Now, 455 00:22:34,800 --> 00:22:37,400 Speaker 1: if you want to know more about these cycles and 456 00:22:37,440 --> 00:22:39,879 Speaker 1: these three things converging again, come hang out with me 457 00:22:39,960 --> 00:22:42,159 Speaker 1: next week. It's all live, it's all free. There's a 458 00:22:42,200 --> 00:22:44,200 Speaker 1: link down below. I'll break out, like I said, thirty 459 00:22:44,240 --> 00:22:46,880 Speaker 1: forty charts. We'll dig through this in great detail. Tell 460 00:22:46,880 --> 00:22:49,280 Speaker 1: you where I'm focusing where my fund's focusing, and then 461 00:22:49,280 --> 00:22:51,560 Speaker 1: we'll discuss it. It's all open life, Juneing so much. 462 00:22:51,720 --> 00:22:53,680 Speaker 1: Come hang out with me, but that's what I got. 463 00:22:53,840 --> 00:22:55,919 Speaker 1: Let me know what you think about this. Hopefully you're 464 00:22:55,920 --> 00:22:58,600 Speaker 1: shifting your portfolio, and of course that's always give me 465 00:22:58,640 --> 00:22:59,800 Speaker 1: thumbs up if you like it. If you don't give 466 00:22:59,800 --> 00:23:01,560 Speaker 1: me the was down that it's okay. At least tell 467 00:23:01,560 --> 00:23:03,080 Speaker 1: me why. And that's what I got. All right, to 468 00:23:03,119 --> 00:23:04,760 Speaker 1: your success, I'm out,