1 00:00:00,360 --> 00:00:02,880 Speaker 1: Is everything we've been told about the markets a flat 2 00:00:02,880 --> 00:00:05,440 Speaker 1: out lie. Well that's the question that deep Seek just 3 00:00:05,519 --> 00:00:08,079 Speaker 1: through at Wall Street, sending high flying stocks like in 4 00:00:08,200 --> 00:00:11,639 Speaker 1: Vidia into free fall. But more importantly, it shattered the 5 00:00:11,680 --> 00:00:15,840 Speaker 1: illusion of business as usual and enforced investors everywhere to 6 00:00:15,960 --> 00:00:19,440 Speaker 1: rethink some very important questions like what's going on under 7 00:00:19,480 --> 00:00:22,400 Speaker 1: the hood at these companies? Do we understand our assumptions? 8 00:00:22,680 --> 00:00:25,960 Speaker 1: What should real stock valuations be now that we know this, 9 00:00:26,400 --> 00:00:28,440 Speaker 1: what does this mean for tech stocks like in Vidia, 10 00:00:28,600 --> 00:00:32,199 Speaker 1: AI and the Nasdaq? And most importantly, what does this 11 00:00:32,280 --> 00:00:35,000 Speaker 1: new paradigm tell us about where we should be investing 12 00:00:35,240 --> 00:00:38,440 Speaker 1: and storing our wealth? And hint, it's not the old system. 13 00:00:38,560 --> 00:00:41,240 Speaker 1: Now this video is going to flip your entire understanding 14 00:00:41,280 --> 00:00:43,559 Speaker 1: of investing on its head. And by the end of 15 00:00:43,600 --> 00:00:45,760 Speaker 1: this video you're going to see why deep Seek isn't 16 00:00:45,880 --> 00:00:49,360 Speaker 1: just about AI, but it's something much, much bigger. Now 17 00:00:49,360 --> 00:00:51,360 Speaker 1: real quick, my name is Mark Moss. I've been a 18 00:00:51,400 --> 00:00:54,440 Speaker 1: tech focused investor since the early Internet days. I had 19 00:00:54,520 --> 00:00:57,120 Speaker 1: two big exits under my belt. I've got twelve years 20 00:00:57,360 --> 00:00:59,680 Speaker 1: in venture capital. I have a leadership role at a 21 00:00:59,680 --> 00:01:02,760 Speaker 1: bigcoin venture capital fund. And now I'm taking you behind 22 00:01:02,760 --> 00:01:05,399 Speaker 1: the scenes of the market shift that we see coming. 23 00:01:05,680 --> 00:01:08,520 Speaker 1: So if you're serious about not just surviving but thriving 24 00:01:08,640 --> 00:01:13,640 Speaker 1: in this new paradigm, let's go. All right, so we're 25 00:01:13,680 --> 00:01:16,319 Speaker 1: jumping right in. We're talking about deep seek, but really 26 00:01:16,480 --> 00:01:18,720 Speaker 1: this isn't about deep seak at all. All right, this 27 00:01:18,800 --> 00:01:22,240 Speaker 1: is what deep Seak just exposed in the markets, and 28 00:01:22,280 --> 00:01:24,000 Speaker 1: what I'm going to bring to you is again what 29 00:01:24,080 --> 00:01:26,800 Speaker 1: the information I use for my venture capital fund, how 30 00:01:26,800 --> 00:01:28,960 Speaker 1: we think about the markets. That's what I want to 31 00:01:28,959 --> 00:01:30,600 Speaker 1: give you. This is not about deep seek. If you 32 00:01:30,640 --> 00:01:33,200 Speaker 1: want the news, there's plenty of news sites out there. 33 00:01:33,240 --> 00:01:35,640 Speaker 1: There's plenty of people on YouTube just regurgitating the news 34 00:01:35,680 --> 00:01:37,480 Speaker 1: headlines and then give you all the details about that. 35 00:01:37,600 --> 00:01:39,080 Speaker 1: You can get it on your own. I want to 36 00:01:39,120 --> 00:01:42,039 Speaker 1: give you the insights that are actionable for us to use. Okay, 37 00:01:42,120 --> 00:01:45,080 Speaker 1: but let's understand what deep seak is for a minute 38 00:01:45,080 --> 00:01:46,880 Speaker 1: from a high level. So first of all, it's a 39 00:01:47,000 --> 00:01:51,320 Speaker 1: new Chinese LLM, a large language model and AI that 40 00:01:51,400 --> 00:01:55,120 Speaker 1: was just released. It's basically an open source AI version 41 00:01:55,160 --> 00:01:57,320 Speaker 1: that just came out. All right, this is what changed 42 00:01:57,320 --> 00:02:01,040 Speaker 1: the paradigm. Now. It took the top spot iTunes store, 43 00:02:01,080 --> 00:02:03,960 Speaker 1: So it's been one of the most downloaded apps out there. 44 00:02:04,120 --> 00:02:06,640 Speaker 1: It got so much usage that it kind of stopped working. 45 00:02:06,680 --> 00:02:08,600 Speaker 1: They said there was an attack against it. We don't 46 00:02:08,639 --> 00:02:10,720 Speaker 1: really know. It's kind of interesting that right when the 47 00:02:10,800 --> 00:02:15,240 Speaker 1: United States shut down TikTok and basically blocked Chinese access 48 00:02:15,280 --> 00:02:18,480 Speaker 1: to that, then China just opened up a large language model, 49 00:02:18,520 --> 00:02:21,360 Speaker 1: which now everybody will give their most sensitive and most 50 00:02:21,639 --> 00:02:24,280 Speaker 1: information to and they'll have that. That's all different conversation, 51 00:02:24,639 --> 00:02:27,760 Speaker 1: but really what Deepseek is is yes, an AI model, 52 00:02:27,800 --> 00:02:30,120 Speaker 1: but what it changed, the paradigm shift and what it 53 00:02:30,160 --> 00:02:33,480 Speaker 1: exposed is that they were able to achieve the same 54 00:02:33,480 --> 00:02:36,000 Speaker 1: thing that open ai and the other llms have done 55 00:02:36,080 --> 00:02:39,960 Speaker 1: Gemini and Cloud et cetera. Not the same thing. They've 56 00:02:40,280 --> 00:02:44,440 Speaker 1: achieved better things, but at a fraction of the cost, 57 00:02:44,280 --> 00:02:46,880 Speaker 1: at like a tenth of the cost. And they did 58 00:02:46,919 --> 00:02:50,000 Speaker 1: this by making their training way cheaper. And I want 59 00:02:50,000 --> 00:02:51,520 Speaker 1: to get into all the details of how they do this. 60 00:02:51,800 --> 00:02:53,840 Speaker 1: Rather than like a large LLM where it's had you 61 00:02:53,919 --> 00:02:56,440 Speaker 1: have to feed it all the data, what they did 62 00:02:56,520 --> 00:02:58,600 Speaker 1: is they created a way that it can learn on 63 00:02:58,680 --> 00:03:01,320 Speaker 1: its own information. I'm not going to get into that, 64 00:03:01,360 --> 00:03:03,560 Speaker 1: but it was a way cheaper way, so instead of 65 00:03:03,560 --> 00:03:06,520 Speaker 1: taking one hundred and fifty billion to train, they got 66 00:03:06,520 --> 00:03:10,120 Speaker 1: it done on just a couple And then the bigger 67 00:03:10,160 --> 00:03:13,760 Speaker 1: one that upset the market was the amount of processing 68 00:03:13,880 --> 00:03:16,359 Speaker 1: compute that was needed to do this, and they found 69 00:03:16,400 --> 00:03:18,760 Speaker 1: that they don't need all the chips like in video 70 00:03:18,800 --> 00:03:20,600 Speaker 1: makes all the GPU used to do this. They were 71 00:03:20,639 --> 00:03:23,400 Speaker 1: able to do it on just a fraction of the chips. 72 00:03:24,080 --> 00:03:26,520 Speaker 1: That's what changed everything. We'll get into that more. But 73 00:03:26,560 --> 00:03:28,519 Speaker 1: really there was a wake up call and so this 74 00:03:29,520 --> 00:03:31,120 Speaker 1: exposed a lot of things in the market. A couple 75 00:03:31,160 --> 00:03:35,040 Speaker 1: of things. Number One, it exposed again the US thinks 76 00:03:35,080 --> 00:03:37,600 Speaker 1: they're cracking down trying to be more secure, but it 77 00:03:37,640 --> 00:03:41,000 Speaker 1: opened up major security flaws. Number Two, even as Trump 78 00:03:41,160 --> 00:03:44,720 Speaker 1: himself tweeted out and talked about that, it really set 79 00:03:45,360 --> 00:03:48,320 Speaker 1: a fire under the US to be more competitive, like, oh, shoot, 80 00:03:48,360 --> 00:03:51,600 Speaker 1: we thought we were winning the race. We're not winning 81 00:03:51,600 --> 00:03:53,960 Speaker 1: the race. There's people that may way more advanced. We 82 00:03:54,040 --> 00:03:57,200 Speaker 1: better get with it. And then again, the wake up 83 00:03:57,200 --> 00:03:59,560 Speaker 1: call was everything we thought we knew about the financial 84 00:03:59,600 --> 00:04:02,440 Speaker 1: markets just changed. And that's exactly what we're going to 85 00:04:02,440 --> 00:04:04,840 Speaker 1: focus on for this video. Again, I'm not giving you 86 00:04:04,880 --> 00:04:08,160 Speaker 1: the news, I'm giving you the insights to make money. Okay, 87 00:04:08,320 --> 00:04:11,640 Speaker 1: so that is what deep seek is. Now what happened, 88 00:04:12,040 --> 00:04:15,120 Speaker 1: So basically, as it came out in video, one of 89 00:04:15,120 --> 00:04:18,400 Speaker 1: the best performing stocks or maybe actually the best performing 90 00:04:18,400 --> 00:04:23,599 Speaker 1: stock in the market plunged six hundred billion dollars now 91 00:04:23,680 --> 00:04:26,280 Speaker 1: was about seventeen percent of its value. It was the 92 00:04:26,400 --> 00:04:29,880 Speaker 1: single largest drop in a day in its history. It 93 00:04:29,920 --> 00:04:32,160 Speaker 1: was a big deal. We can see in this chart 94 00:04:32,240 --> 00:04:35,440 Speaker 1: right here to get like an illustration. Yes, all stocks 95 00:04:35,640 --> 00:04:38,040 Speaker 1: go up and down. There's never been one that go 96 00:04:38,400 --> 00:04:40,160 Speaker 1: up in a straight line or down a straight line. 97 00:04:40,200 --> 00:04:41,680 Speaker 1: So they go up and down. But what we can 98 00:04:41,720 --> 00:04:43,920 Speaker 1: see is this big gap right here. Look at that. 99 00:04:44,279 --> 00:04:47,200 Speaker 1: So this is important to understand about the markets because 100 00:04:47,200 --> 00:04:51,120 Speaker 1: this is a Chinese market that trades in a different 101 00:04:51,240 --> 00:04:54,000 Speaker 1: time frame than what the US does, and so this 102 00:04:54,160 --> 00:04:57,680 Speaker 1: affected things overnight. But then when the market opened, it 103 00:04:57,720 --> 00:05:00,560 Speaker 1: created this gap where it gap downs. You don't see 104 00:05:00,600 --> 00:05:02,920 Speaker 1: gaps on anywhere like this. There's the big piece. We're 105 00:05:02,920 --> 00:05:04,760 Speaker 1: going to come back to what this means in a minute, 106 00:05:04,839 --> 00:05:07,200 Speaker 1: but I want you to see that visually again, biggest 107 00:05:07,200 --> 00:05:09,360 Speaker 1: one day loss. And really what we saw is that 108 00:05:09,400 --> 00:05:13,560 Speaker 1: all AI models can be developed with now limited compute resources. 109 00:05:13,560 --> 00:05:16,040 Speaker 1: So why in video the most? There was other stocks, 110 00:05:16,080 --> 00:05:17,640 Speaker 1: we'll get into that. Why and video the most well, 111 00:05:17,680 --> 00:05:20,960 Speaker 1: because in Vidia makes the chips for the AI, right, 112 00:05:21,279 --> 00:05:24,520 Speaker 1: And so basically what the stock is, the PE ratio 113 00:05:24,600 --> 00:05:26,599 Speaker 1: is sort of like this forward looking ratio of what 114 00:05:26,640 --> 00:05:29,599 Speaker 1: they think sales and earnings and revenues will be. And 115 00:05:29,680 --> 00:05:32,880 Speaker 1: so as AI is projected to grow, they expected their 116 00:05:34,000 --> 00:05:36,560 Speaker 1: demand for their chips, their GPUs to continue to go 117 00:05:36,680 --> 00:05:41,719 Speaker 1: up linearly at least, if not exponentially like that. But 118 00:05:41,839 --> 00:05:45,080 Speaker 1: what we just found, how overnight all these assumptions are 119 00:05:45,120 --> 00:05:48,960 Speaker 1: wrong because now what Deepsek was able to do was 120 00:05:49,160 --> 00:05:52,320 Speaker 1: provide something better than what we had before with one 121 00:05:52,400 --> 00:05:55,520 Speaker 1: tenth of the resources. And so now everything that we thought, 122 00:05:55,560 --> 00:05:57,840 Speaker 1: like in Video's growth is going to be like this, 123 00:05:57,880 --> 00:05:59,800 Speaker 1: And we're like, well, wait a minute, no, it's not. 124 00:06:00,279 --> 00:06:02,960 Speaker 1: Because if Deepseak was able to do something like this, 125 00:06:03,240 --> 00:06:05,720 Speaker 1: that brings their growth down like this. But what if 126 00:06:06,920 --> 00:06:10,359 Speaker 1: what if deep Seak too, another competitor comes out and 127 00:06:10,400 --> 00:06:12,120 Speaker 1: finds a way to even do it for one tenth 128 00:06:12,200 --> 00:06:14,240 Speaker 1: of that, and now all of a sudden it goes 129 00:06:14,279 --> 00:06:17,799 Speaker 1: like this. And so what we're seeing is technology changing 130 00:06:17,960 --> 00:06:21,880 Speaker 1: so fast that it's challenging all the assumptions that we've 131 00:06:21,920 --> 00:06:26,480 Speaker 1: had because it moves so quickly. A small business owner, 132 00:06:26,600 --> 00:06:29,359 Speaker 1: are you buried in all types of work keeping you 133 00:06:29,400 --> 00:06:32,000 Speaker 1: from the real thing that makes you money. Well that's 134 00:06:32,040 --> 00:06:34,000 Speaker 1: where just Works comes in. They're the all in one 135 00:06:34,040 --> 00:06:37,360 Speaker 1: platform that supports small business growth. You can get all 136 00:06:37,440 --> 00:06:40,599 Speaker 1: their tools that help with benefits like payroll and HR 137 00:06:40,760 --> 00:06:44,799 Speaker 1: and compliance with transparent pricing. Now they help you hire 138 00:06:44,839 --> 00:06:49,520 Speaker 1: top talent internationally, internew markets, quickly scale international operations without 139 00:06:49,520 --> 00:06:52,599 Speaker 1: the workload, and for every how do I do it? Question? 140 00:06:52,760 --> 00:06:55,120 Speaker 1: You can reach out to their expert staff from sole 141 00:06:55,200 --> 00:06:59,080 Speaker 1: proprietor or a team of twenty. Just Works empowers all 142 00:06:59,160 --> 00:07:02,920 Speaker 1: kinds of small businesses with real human support. So visit 143 00:07:03,120 --> 00:07:06,680 Speaker 1: justworks dot com slash podcast to join the thousands of 144 00:07:06,680 --> 00:07:10,640 Speaker 1: small businesses that trust just Works to take care of payroll, benefits, 145 00:07:10,760 --> 00:07:15,560 Speaker 1: compliance and more. Again, that's Justworks dot com, slash podcasts. 146 00:07:17,000 --> 00:07:19,760 Speaker 1: And it's not just in Nvidia. This is really all 147 00:07:19,880 --> 00:07:23,040 Speaker 1: the tech stocks and really the AI shock that's happened. 148 00:07:23,280 --> 00:07:25,800 Speaker 1: And so we saw, like I said, one hundred and 149 00:07:25,840 --> 00:07:29,840 Speaker 1: fifty seven billion was spent for open Ai to train 150 00:07:29,960 --> 00:07:32,120 Speaker 1: their llms. That's how much we're spent. So then we 151 00:07:32,120 --> 00:07:34,000 Speaker 1: think about, okay, what does that mean for the amount 152 00:07:34,000 --> 00:07:36,240 Speaker 1: of capital that's going to flow into the markets, right, 153 00:07:36,240 --> 00:07:37,880 Speaker 1: because as an investor, we want to go, well, how 154 00:07:37,920 --> 00:07:41,000 Speaker 1: much capital will flow in? How much how much do 155 00:07:41,040 --> 00:07:43,320 Speaker 1: we think each company can capture from that will be 156 00:07:43,320 --> 00:07:46,440 Speaker 1: the future valuation so we can invest. Right, So we thought, well, 157 00:07:46,480 --> 00:07:48,480 Speaker 1: if they spend one hundred and fifty seven billion, then 158 00:07:48,520 --> 00:07:51,600 Speaker 1: other companies will need about that money. But now we 159 00:07:51,720 --> 00:07:54,440 Speaker 1: just found that they don't need that money. They need 160 00:07:54,440 --> 00:07:57,640 Speaker 1: about a tenth of that to provide something better. And again, 161 00:07:57,920 --> 00:08:00,360 Speaker 1: what if somebody else comes out next and does it 162 00:08:00,360 --> 00:08:03,000 Speaker 1: for a tenth of the cost as well? That caused 163 00:08:03,040 --> 00:08:06,360 Speaker 1: the entire Nasdaq to drop about three percent. Now, the 164 00:08:06,440 --> 00:08:08,800 Speaker 1: NASDAK is an index, right, so it represents sort of 165 00:08:08,880 --> 00:08:11,320 Speaker 1: all the tech stocks that are out there. So you 166 00:08:11,400 --> 00:08:14,600 Speaker 1: might go, well, you know, I mean, in VIDFL seventeen percent, 167 00:08:14,880 --> 00:08:18,160 Speaker 1: but the Nasdaq only fell three percent, So maybe y'all 168 00:08:18,280 --> 00:08:20,440 Speaker 1: make a strategy around that and don't worry. We're going 169 00:08:20,480 --> 00:08:22,440 Speaker 1: to come back to that in a second. But basically 170 00:08:22,480 --> 00:08:25,000 Speaker 1: we saw the chip makers and the data centers really 171 00:08:25,000 --> 00:08:27,280 Speaker 1: get hit the most, because of course the chip makers. 172 00:08:27,280 --> 00:08:28,680 Speaker 1: We thought their demand was going to go like this, 173 00:08:29,080 --> 00:08:31,080 Speaker 1: and now maybe it's not. And we saw the data 174 00:08:31,080 --> 00:08:33,880 Speaker 1: centers expanding because we need more compute space, and now 175 00:08:33,920 --> 00:08:37,240 Speaker 1: maybe we don't need that as well. Right, so again, 176 00:08:37,280 --> 00:08:39,240 Speaker 1: if they can make this for cheaper and we need 177 00:08:39,320 --> 00:08:42,760 Speaker 1: less investment. But even more importantly, we also saw that 178 00:08:42,920 --> 00:08:46,480 Speaker 1: maybe there's not really a moat. So we understand that 179 00:08:46,559 --> 00:08:51,679 Speaker 1: like open Ai and Claude and Lama and Xai and 180 00:08:51,720 --> 00:08:55,640 Speaker 1: now Deepseek, these are all like base layer applications and 181 00:08:55,720 --> 00:08:58,800 Speaker 1: we're finding like narrow use cases to be built on 182 00:08:58,880 --> 00:09:01,760 Speaker 1: top of them. And what we typically see is if 183 00:09:01,760 --> 00:09:04,040 Speaker 1: you think about like a base layer like the Internet, 184 00:09:04,400 --> 00:09:07,040 Speaker 1: the value doesn't accrue on the base layer, the value 185 00:09:07,040 --> 00:09:10,440 Speaker 1: actually accrues on the narrow applications on the brands on 186 00:09:10,520 --> 00:09:13,559 Speaker 1: top of it. And so I still think there's tremendous 187 00:09:14,360 --> 00:09:19,120 Speaker 1: growth potential being built all around here. But what we 188 00:09:19,160 --> 00:09:22,240 Speaker 1: think about the base layers down here, there really is 189 00:09:22,280 --> 00:09:24,480 Speaker 1: no mode. If deep Seak can just come out for 190 00:09:24,559 --> 00:09:26,440 Speaker 1: a tenth of the cost and the time and all 191 00:09:26,440 --> 00:09:29,280 Speaker 1: these things and be better, what does that mean for 192 00:09:29,320 --> 00:09:32,920 Speaker 1: everything else? And again that challenges everything that we know. Okay, 193 00:09:32,960 --> 00:09:35,439 Speaker 1: but here's the big paradigm shift that I want to 194 00:09:35,480 --> 00:09:38,800 Speaker 1: get through to today, and that is that equities being 195 00:09:38,920 --> 00:09:41,360 Speaker 1: used as a store of value. So we make money, 196 00:09:41,480 --> 00:09:43,640 Speaker 1: we hopefully don't spend it all, we have some leftover. 197 00:09:43,679 --> 00:09:45,960 Speaker 1: Where do we save that? That's our store, that's our value. 198 00:09:46,160 --> 00:09:47,960 Speaker 1: Where do we save that so we can put that 199 00:09:48,000 --> 00:09:50,440 Speaker 1: into goal We can put into bonds, real estate equities, 200 00:09:50,480 --> 00:09:52,600 Speaker 1: things like that, and typically we use equities for that. 201 00:09:53,240 --> 00:09:55,400 Speaker 1: We're storing our wealth for a long term. But what 202 00:09:55,440 --> 00:09:58,320 Speaker 1: we just found out, as deep Seek exposed, is that 203 00:09:58,440 --> 00:10:01,800 Speaker 1: is a very dangerous game. Why is that Because I'm 204 00:10:01,800 --> 00:10:05,280 Speaker 1: buying these companies like Nvidia, we don't really understand anything. 205 00:10:05,320 --> 00:10:08,000 Speaker 1: I don't understand the technology into the chip. I don't 206 00:10:08,040 --> 00:10:11,560 Speaker 1: understand the market dynamics of that. And even the people 207 00:10:11,600 --> 00:10:13,520 Speaker 1: that thought they did found out they didn't when deep 208 00:10:13,559 --> 00:10:16,840 Speaker 1: Seek was able to just change that overnight. And so 209 00:10:17,240 --> 00:10:21,520 Speaker 1: there's all these unknown disruptions if we buy these companies, 210 00:10:21,760 --> 00:10:24,040 Speaker 1: there's all these disruptions that could possibly come that we 211 00:10:24,080 --> 00:10:27,280 Speaker 1: don't know, we can't understand, we can't quantify. So back 212 00:10:27,320 --> 00:10:29,640 Speaker 1: to sort of the Nasdaq index, we might go, well, 213 00:10:29,720 --> 00:10:32,360 Speaker 1: instead of buying one company, I'll just buy the index, 214 00:10:32,600 --> 00:10:37,760 Speaker 1: right I'll buy the whole Nasdaq index, But what if 215 00:10:39,080 --> 00:10:42,480 Speaker 1: China releases something like d seek that's better. Would the 216 00:10:42,480 --> 00:10:46,240 Speaker 1: money flow from the nasdak over to the Chinese stock market? 217 00:10:47,200 --> 00:10:50,959 Speaker 1: Or what if the US This isn't really hypothetical. What 218 00:10:51,040 --> 00:10:54,760 Speaker 1: if what happens when I should say the US continues 219 00:10:54,800 --> 00:10:57,520 Speaker 1: to print more money and continue to devalue and debase 220 00:10:57,559 --> 00:11:00,800 Speaker 1: their currency. So you own the new index, but it's 221 00:11:00,840 --> 00:11:04,760 Speaker 1: denominated in the OS dollar. What happens then? Those are 222 00:11:04,800 --> 00:11:07,200 Speaker 1: big problems that all of a sudden has been brought 223 00:11:07,240 --> 00:11:09,880 Speaker 1: to the forefront of everybody with deep Seek exposed, that 224 00:11:09,960 --> 00:11:12,200 Speaker 1: we have to answer. So the question is where do 225 00:11:12,240 --> 00:11:14,000 Speaker 1: we go? And I think this is where the big 226 00:11:14,000 --> 00:11:16,800 Speaker 1: paradigm shift is going to go. That is that we 227 00:11:16,880 --> 00:11:20,920 Speaker 1: need a yard stick for a store value. How do 228 00:11:21,000 --> 00:11:23,400 Speaker 1: we measure it? Right? So, if I measure it in 229 00:11:23,520 --> 00:11:25,680 Speaker 1: US dollars, it shows me one thing. If I measure 230 00:11:25,679 --> 00:11:27,959 Speaker 1: it in Chinese you want it shows me another. If 231 00:11:28,000 --> 00:11:31,200 Speaker 1: I measured it in boulevard shows me something different. Or 232 00:11:31,200 --> 00:11:34,240 Speaker 1: if I measure it in oil or oranges or rice 233 00:11:35,280 --> 00:11:39,440 Speaker 1: or gold, and so it depends on what yardstick I'm using, 234 00:11:39,720 --> 00:11:42,520 Speaker 1: it shows me different things. How could you organize someone 235 00:11:42,520 --> 00:11:45,880 Speaker 1: to build a house if nobody had the same measuring tape, 236 00:11:45,880 --> 00:11:47,040 Speaker 1: as a matter of fact, that they didn't have a 237 00:11:47,080 --> 00:11:49,720 Speaker 1: measuring tape, they had bungee cords. How could you build 238 00:11:49,720 --> 00:11:51,600 Speaker 1: a house? How could you organize that? How can you 239 00:11:51,679 --> 00:11:54,360 Speaker 1: organize an economy in a market when everybody has different 240 00:11:54,400 --> 00:11:57,800 Speaker 1: measuring tapes. The supply of dollars changes every day, the 241 00:11:57,800 --> 00:12:00,240 Speaker 1: supply of oil changes every day, the supply of on 242 00:12:00,720 --> 00:12:03,720 Speaker 1: or whatever. You get that, So how do we measure 243 00:12:03,840 --> 00:12:06,400 Speaker 1: our wealth? I'm measuring in the Nasdaq and US dollars, 244 00:12:06,400 --> 00:12:09,280 Speaker 1: but the US dollars being debased, so we have a 245 00:12:09,320 --> 00:12:12,600 Speaker 1: problem now. Ludwig gun misis one of my favorite economists 246 00:12:12,600 --> 00:12:15,440 Speaker 1: from the Austrian school of economics. He said that in 247 00:12:15,480 --> 00:12:17,920 Speaker 1: the world of economics, there's no such thing as a constant. 248 00:12:18,320 --> 00:12:21,360 Speaker 1: So all throughout history commodities have been sort of money. 249 00:12:21,440 --> 00:12:23,960 Speaker 1: We needed a commodity money like gold, for example, or 250 00:12:23,960 --> 00:12:26,080 Speaker 1: oil or something like that. And they work good because 251 00:12:26,120 --> 00:12:28,760 Speaker 1: they fit some of the money attributes. They were scarce, right, 252 00:12:28,880 --> 00:12:31,840 Speaker 1: But the problem is, as I already said, the value 253 00:12:31,960 --> 00:12:33,959 Speaker 1: or not the value, but the supply the quantity of 254 00:12:34,000 --> 00:12:37,120 Speaker 1: those commodities was changing all the time. There's no sustaining 255 00:12:37,120 --> 00:12:41,200 Speaker 1: as a consistant, but there is today, and so I 256 00:12:41,280 --> 00:12:43,920 Speaker 1: believe that bitcoin is the first asset that we have 257 00:12:44,280 --> 00:12:46,959 Speaker 1: that has a constant There's twenty one million, there won't 258 00:12:46,960 --> 00:12:48,960 Speaker 1: be any more. And I believe this is the new 259 00:12:49,040 --> 00:12:51,959 Speaker 1: hurdle rate that all assets will be measured against. I've 260 00:12:51,960 --> 00:12:54,200 Speaker 1: been talking about this for a while. If you've been 261 00:12:54,200 --> 00:12:56,960 Speaker 1: watching my videos, you surety already understand this, and that 262 00:12:57,000 --> 00:12:59,120 Speaker 1: the hurdle rate is the rate that we have to beat. 263 00:12:59,160 --> 00:13:02,640 Speaker 1: So right now, the US monetary supply is expanding between 264 00:13:02,679 --> 00:13:04,760 Speaker 1: ten to sixteen percent a year, depending on what measurement 265 00:13:04,800 --> 00:13:07,560 Speaker 1: you're looking at. So, for example, the Fed balance sheet 266 00:13:07,800 --> 00:13:11,160 Speaker 1: has been averaging about a sixteen percent growth year over 267 00:13:11,280 --> 00:13:13,920 Speaker 1: year for the last four years. That's the hurdle rate. 268 00:13:13,960 --> 00:13:15,880 Speaker 1: That means I don't have to beat inflation at three 269 00:13:15,920 --> 00:13:19,040 Speaker 1: percent to keep ahead of inflation. The real number have 270 00:13:19,120 --> 00:13:21,760 Speaker 1: to beat is sixteen percent. Now, there's not a lot 271 00:13:21,800 --> 00:13:24,040 Speaker 1: of assets that do that. The S and P five 272 00:13:24,120 --> 00:13:26,120 Speaker 1: hundred hasn't been doing that over the four year period, 273 00:13:26,440 --> 00:13:29,600 Speaker 1: neither the NASDAK has barely been keeping up, whereas bitcoin's 274 00:13:29,600 --> 00:13:32,160 Speaker 1: been doing about fifty to sixty percent. And I believe 275 00:13:32,160 --> 00:13:35,360 Speaker 1: that's the new hurdle rate, the reason why one it's 276 00:13:35,400 --> 00:13:38,160 Speaker 1: beating it from return. But it's bigger than that. It's 277 00:13:38,200 --> 00:13:41,240 Speaker 1: what Deepseeak has showed us right here. It's that any 278 00:13:41,240 --> 00:13:43,720 Speaker 1: of these yardsticks can change, and any of these things 279 00:13:43,720 --> 00:13:46,840 Speaker 1: are susceptible to disruption. We see with bitcoin there is 280 00:13:46,880 --> 00:13:50,560 Speaker 1: no disruption that's there. There's no way to disrupt that technology. Sure, 281 00:13:50,559 --> 00:13:53,040 Speaker 1: you can talk about quantum computing in fifteen years from now. 282 00:13:53,200 --> 00:13:55,280 Speaker 1: That's already a known thing. There's already fixes being in 283 00:13:55,280 --> 00:13:59,000 Speaker 1: place for that. Two, it can't be changed. So like 284 00:13:59,040 --> 00:14:01,160 Speaker 1: all the other cryptocurrens, they have governance and they can 285 00:14:01,240 --> 00:14:04,079 Speaker 1: vote on things, and they can change things. Bitcoin doesn't change. 286 00:14:04,800 --> 00:14:07,360 Speaker 1: It can't be debased. You can't just print more currency 287 00:14:07,360 --> 00:14:09,520 Speaker 1: to debase it. And so I believe for all of 288 00:14:09,600 --> 00:14:12,800 Speaker 1: those reasons, what we're going to see is a massive 289 00:14:12,840 --> 00:14:14,720 Speaker 1: paradigm shift. And this is what the world's already seen. 290 00:14:15,040 --> 00:14:16,440 Speaker 1: As a matter of fact, at the time of this recording, 291 00:14:16,480 --> 00:14:20,760 Speaker 1: I saw today another major sovereign central bank saying they 292 00:14:20,800 --> 00:14:22,520 Speaker 1: want to add bitcoin to the balance sheet. The world 293 00:14:22,560 --> 00:14:24,640 Speaker 1: is seeing this right here, and there's going to be 294 00:14:24,640 --> 00:14:28,320 Speaker 1: a massive shift. And so really the trifecta. It's not 295 00:14:28,360 --> 00:14:31,720 Speaker 1: just bitcoin. The trifecta in this new paradigm, in this 296 00:14:31,760 --> 00:14:36,520 Speaker 1: new economy, this new money economy is AI. AI is 297 00:14:36,600 --> 00:14:40,520 Speaker 1: the disruptive engine of growth. AI is super important. It's 298 00:14:40,560 --> 00:14:43,400 Speaker 1: going to increase efficiency, it's going to lower cost, and 299 00:14:43,440 --> 00:14:45,920 Speaker 1: it's going to create a massive amount of growth and 300 00:14:45,960 --> 00:14:49,600 Speaker 1: abundance in AI. But that's going to push things cheaper 301 00:14:49,640 --> 00:14:54,280 Speaker 1: and cheaper and cheaper, so that disrupts the financial markets 302 00:14:54,280 --> 00:14:55,920 Speaker 1: that we're using to invest in because we want them 303 00:14:55,960 --> 00:14:59,080 Speaker 1: to go up in value. So we use AI, but 304 00:14:59,120 --> 00:15:02,560 Speaker 1: then we use bitcoin as a key financial hedge. So 305 00:15:02,600 --> 00:15:04,640 Speaker 1: the money that we put into here goes up and 306 00:15:04,720 --> 00:15:06,920 Speaker 1: up and up over time and holds that because it 307 00:15:06,920 --> 00:15:08,760 Speaker 1: can't be disrupted, it can't be debased like the US 308 00:15:08,800 --> 00:15:11,800 Speaker 1: dollar or the yuan or the ruin. Mby then, the 309 00:15:11,840 --> 00:15:16,160 Speaker 1: third part of the trifecta is energy, because the main 310 00:15:16,240 --> 00:15:19,280 Speaker 1: thing that both bitcoin and AI need is energy. It's 311 00:15:19,280 --> 00:15:23,520 Speaker 1: a crucial resource. We can't live without energy. I couldn't 312 00:15:23,520 --> 00:15:25,720 Speaker 1: be doing this, you couldn't be watching this video without energy. 313 00:15:25,840 --> 00:15:29,320 Speaker 1: And so this is the trifecta in the new paradigm. 314 00:15:29,400 --> 00:15:32,040 Speaker 1: And this is what Deepseat showed everybody. This is what 315 00:15:32,080 --> 00:15:34,200 Speaker 1: the world has seen, at least the smart people, and 316 00:15:34,280 --> 00:15:35,760 Speaker 1: I'm trying to give it to you again. This is 317 00:15:35,760 --> 00:15:37,160 Speaker 1: not the news. You can go read the news on 318 00:15:37,200 --> 00:15:38,920 Speaker 1: your own. Let me know what you think about the 319 00:15:38,960 --> 00:15:41,520 Speaker 1: new paradigm and the trifecta down the comments down below. 320 00:15:42,160 --> 00:15:44,480 Speaker 1: As always, give me likes if you like this video. 321 00:15:44,480 --> 00:15:46,040 Speaker 1: If you don't eat what something's down, that's okay. Tell 322 00:15:46,080 --> 00:15:47,720 Speaker 1: me either way. And that's what I got. All right, 323 00:15:47,720 --> 00:15:49,400 Speaker 1: to your success. I'm out.