WEBVTT 00:00:00.000 --> 00:00:02.339 Welcome back to the Deep Dive. If you've been 00:00:02.339 --> 00:00:04.559 watching the headlines at all, you know the biggest 00:00:04.559 --> 00:00:06.599 story right now. I mean, maybe the biggest story 00:00:06.599 --> 00:00:11.140 of 2025 is the sheer, just breathtaking flow 00:00:11.140 --> 00:00:14.019 of capital into artificial intelligence. It's 00:00:14.019 --> 00:00:15.960 everywhere. Everywhere. We're talking trillions 00:00:15.960 --> 00:00:19.519 of dollars being funneled into a really concentrated 00:00:19.519 --> 00:00:23.519 group of tech firms all building this infrastructure 00:00:23.519 --> 00:00:28.039 for our AI future. The momentum, it just feels 00:00:28.039 --> 00:00:30.660 unstoppable. It does. And that momentum is precisely 00:00:30.660 --> 00:00:32.960 where our deep dive has to begin. The sources 00:00:32.960 --> 00:00:35.899 you sent over really highlight this powerful 00:00:35.899 --> 00:00:38.240 central paradox. OK. On the one hand, you have 00:00:38.240 --> 00:00:40.859 this rapid growth, this unprecedented investment 00:00:40.859 --> 00:00:43.640 sparking just mass optimism. But on the other, 00:00:44.000 --> 00:00:46.259 a lot of established financial experts are Well, 00:00:46.399 --> 00:00:48.340 they're sounding an alarm. Alarm about what exactly? 00:00:48.500 --> 00:00:50.399 They're warning that all this growth is masking 00:00:50.399 --> 00:00:53.340 some pretty significant systemic risks, hidden 00:00:53.340 --> 00:00:55.280 vulnerabilities that could challenge the stability 00:00:55.280 --> 00:00:57.340 of the whole market. That's fascinating. So the 00:00:57.340 --> 00:00:59.240 risk isn't just about whether the tech itself 00:00:59.240 --> 00:01:01.840 works, but how the financial system is, you know, 00:01:02.100 --> 00:01:04.870 handling all this money. Our mission today is 00:01:04.870 --> 00:01:08.390 to take a really detailed look at the AI market 00:01:08.390 --> 00:01:11.730 landscape, maybe identify some historical parallels 00:01:11.730 --> 00:01:13.930 that tell us where we might be in the cycle, 00:01:14.030 --> 00:01:16.709 and most importantly, pull back the curtain on 00:01:16.709 --> 00:01:19.510 the fragility behind all the hype. And we'll 00:01:19.510 --> 00:01:21.709 be using your research as our map. Let's do it. 00:01:21.750 --> 00:01:23.909 I think we have to unpack the scale first, because 00:01:23.909 --> 00:01:27.510 the numbers themselves are just... They're staggering. 00:01:27.750 --> 00:01:30.170 And they really lay the groundwork for understanding 00:01:30.170 --> 00:01:32.329 the risk. Absolutely. When we talk about financial 00:01:32.329 --> 00:01:35.969 commitment, we are way past the point of casual 00:01:35.969 --> 00:01:38.769 investing. Oh, yeah. The projection is that US 00:01:38.769 --> 00:01:41.469 AI -related investment is set to exceed $100 00:01:41.469 --> 00:01:44.709 billion this year alone. And that's just the 00:01:44.709 --> 00:01:47.269 US. If you look globally, some estimates are 00:01:47.269 --> 00:01:50.010 suggesting we could be approaching $200 billion 00:01:50.010 --> 00:01:52.129 by the end of the year. That kind of concentrated 00:01:52.129 --> 00:01:55.900 capital is. It's just so rare. It is rare, but, 00:01:55.900 --> 00:01:58.219 you know, the total dollar amount, while it's 00:01:58.219 --> 00:02:00.159 eye -catching, it's actually secondary to how 00:02:00.159 --> 00:02:01.780 that money is circulating. OK, what do you mean? 00:02:02.060 --> 00:02:05.000 This colossal investment isn't discussed widely. 00:02:05.540 --> 00:02:08.080 It's flowing through a small, really tightly 00:02:08.080 --> 00:02:11.539 controlled ecosystem. And that introduces what 00:02:11.539 --> 00:02:15.620 our sources are calling concentration risk. Concentration 00:02:15.620 --> 00:02:17.360 risk. And that's the foundational problem. It 00:02:17.360 --> 00:02:19.740 leads us directly to this concept of closed loop 00:02:19.740 --> 00:02:22.319 spending. Closed loop spending. When you hear 00:02:22.319 --> 00:02:24.860 a term like that in finance, you instinctively 00:02:24.860 --> 00:02:27.539 know it's probably not a good thing. How does 00:02:27.539 --> 00:02:30.039 that loop actually operate? Think of it as a 00:02:30.039 --> 00:02:32.889 really specific interconnected network. a club, 00:02:33.289 --> 00:02:35.650 basically, where money is only exchanged between 00:02:35.650 --> 00:02:37.530 the members. Okay. Give me an example. Sure. 00:02:37.969 --> 00:02:41.189 A major venture capital arm of, say, a big AI 00:02:41.189 --> 00:02:44.270 software firm gives financing to a specialized 00:02:44.270 --> 00:02:47.669 chip startup. That startup then uses that funding 00:02:47.669 --> 00:02:51.229 to buy advanced chips exclusively from the original 00:02:51.229 --> 00:02:53.889 parent company. Ah, so the money never actually 00:02:53.889 --> 00:02:56.030 leaves the orbit of this small group of firms. 00:02:56.449 --> 00:02:58.789 Exactly. Company A gives capital to Company B, 00:02:58.949 --> 00:03:00.849 and Company B turns right around and uses it 00:03:00.849 --> 00:03:02.969 to buy Company A's products. It's a circular 00:03:02.969 --> 00:03:05.650 mechanism. And that artificially inflates asset 00:03:05.650 --> 00:03:08.949 valuations. It has to, because the spending isn't 00:03:08.949 --> 00:03:12.909 being validated by organic third -party demand 00:03:12.909 --> 00:03:16.050 from the real economy. It's internal capital 00:03:16.050 --> 00:03:18.789 driving the recorded price and what looks like 00:03:18.789 --> 00:03:20.699 revenue growth. Which makes it almost impossible 00:03:20.699 --> 00:03:22.719 to figure out the true value of the technology 00:03:22.719 --> 00:03:25.300 if and when that cycle eventually breaks. It 00:03:25.300 --> 00:03:28.419 does. And the consequence of this closed loop 00:03:28.419 --> 00:03:32.240 is this rapid, extreme concentration of risk 00:03:32.240 --> 00:03:34.719 across the whole industry. These firms aren't 00:03:34.719 --> 00:03:37.199 just partners. They're financially interwoven. 00:03:37.360 --> 00:03:40.080 So if one of them gets into trouble, if sentiment 00:03:40.080 --> 00:03:42.520 shifts or if regulators land heavily on just 00:03:42.520 --> 00:03:45.699 one major player, the dependency in that loop 00:03:45.699 --> 00:03:48.699 means the contagion will be swift and frankly 00:03:48.699 --> 00:03:51.159 pretty painful for the entire sector. And we 00:03:51.159 --> 00:03:53.180 know regulators are watching this like a hawk. 00:03:53.300 --> 00:03:55.520 The Financial Stability Oversight Council, they've 00:03:55.520 --> 00:03:57.620 explicitly flagged vulnerabilities tied to this 00:03:57.620 --> 00:04:00.360 exact boom. But what really stood out to me was 00:04:00.360 --> 00:04:02.819 the observation that markets are showing markedly 00:04:02.819 --> 00:04:05.860 increased correlations. That phrase is a five 00:04:05.860 --> 00:04:08.139 alarm fire bell for systemic risk. It sounds 00:04:08.139 --> 00:04:10.680 like it. I mean, historically, you mitigated 00:04:10.680 --> 00:04:13.900 risk with diversification. Yeah. Right. You held 00:04:13.900 --> 00:04:16.939 stocks in different sectors, energy, health care, 00:04:17.000 --> 00:04:19.300 tech. And if one went down, the others might 00:04:19.300 --> 00:04:21.819 be stable or even go up because they had different 00:04:21.819 --> 00:04:25.040 risk drivers. Precisely. But when correlations 00:04:25.040 --> 00:04:28.620 become markedly increased, it means assets that 00:04:28.620 --> 00:04:30.560 should move independently are now all moving 00:04:30.560 --> 00:04:33.040 in lockstep. It's a direct result of this closed 00:04:33.040 --> 00:04:35.660 loop financing. So diversification isn't really 00:04:35.660 --> 00:04:38.759 a safety net anymore? The refuge is dramatically 00:04:38.759 --> 00:04:41.639 shrinking, especially if your portfolio is heavy 00:04:41.639 --> 00:04:44.579 in these AI exposed sectors. The factors driving 00:04:44.579 --> 00:04:46.779 one company's price are the same factors driving 00:04:46.779 --> 00:04:49.379 all of them. This level of financial fervor, 00:04:49.560 --> 00:04:51.839 it just naturally makes you think about financial 00:04:51.839 --> 00:04:53.620 history. I mean, have we seen this kind of setup 00:04:53.620 --> 00:04:56.720 before? Oh, we absolutely have. And to analyze 00:04:56.720 --> 00:04:59.420 it... We really need the framework from the economist 00:04:59.420 --> 00:05:02.240 Charles Kindleberger. He outlined the classic 00:05:02.240 --> 00:05:04.620 sequence of a financial mania. The five phases. 00:05:04.920 --> 00:05:07.279 Right. Displacement, euphoria, mania, distress, 00:05:07.620 --> 00:05:10.180 and finally, revulsion. And if we're looking 00:05:10.180 --> 00:05:13.079 at the current AI moment through that lens, where 00:05:13.079 --> 00:05:15.560 do we land? Well, the displacement was the breakthrough 00:05:15.560 --> 00:05:18.660 of large language models, of generative AI itself. 00:05:19.379 --> 00:05:21.699 The euphoria was that first burst of capital 00:05:21.699 --> 00:05:24.660 back in 2023. But according to historians like 00:05:24.660 --> 00:05:27.519 Neil Ferguson, the current AI market is now, 00:05:27.519 --> 00:05:30.019 and I'm quoting, firmly within the media phase. 00:05:30.259 --> 00:05:33.620 That is a critical label. But wait, I have to 00:05:33.620 --> 00:05:35.939 push back just a little on that. Unlike, say, 00:05:36.040 --> 00:05:38.620 the Dutch tulip mania or even the dot com era. 00:05:38.920 --> 00:05:42.699 AI produces real, tangible efficiency gains for 00:05:42.699 --> 00:05:45.399 businesses right now. It's transforming processes 00:05:45.399 --> 00:05:48.279 today. Doesn't that genuine tech displacement 00:05:48.279 --> 00:05:51.339 justify some of this valuation? Does the mania 00:05:51.339 --> 00:05:54.000 comparison really hold up? That's the essential 00:05:54.000 --> 00:05:56.120 difficult question, isn't it? Yeah. Separating 00:05:56.120 --> 00:05:58.699 genuine innovation from financial excess. And 00:05:58.699 --> 00:06:01.160 you're right, the technology is undeniably transformative. 00:06:01.839 --> 00:06:04.240 But mania isn't defined by the technology's quality. 00:06:04.360 --> 00:06:06.759 It's defined by investor behavior. Exactly. In 00:06:06.759 --> 00:06:09.240 the mania phase, you see this excessive optimism 00:06:09.240 --> 00:06:11.519 where spectacular future revenues are treated 00:06:11.519 --> 00:06:14.459 as near certainties today. It results in valuations 00:06:14.459 --> 00:06:17.040 that demand decades of absolutely perfect execution. 00:06:17.319 --> 00:06:19.139 So the behavior is just outrunning the balance 00:06:19.139 --> 00:06:22.220 sheet. It is. The investment enthusiasm consistently 00:06:22.220 --> 00:06:24.800 outstrips the underlying measurable fundamentals. 00:06:25.579 --> 00:06:28.500 It's investment based on the dream, not the current 00:06:28.500 --> 00:06:30.860 proven earnings. We saw the same psychology in 00:06:30.860 --> 00:06:33.480 the 1920s stock bubble and the 90s tech surge, 00:06:34.040 --> 00:06:36.040 that feeling that the rules have changed forever. 00:06:36.199 --> 00:06:39.079 That this time is different. That belief is the 00:06:39.079 --> 00:06:41.500 defining psychological trap of the mania phase. 00:06:41.620 --> 00:06:44.459 And we're seeing specific vivid markers of it 00:06:44.459 --> 00:06:47.509 today. We are. The source material points to 00:06:47.509 --> 00:06:49.689 things like advanced chip orders being placed 00:06:49.689 --> 00:06:52.050 years ahead of when a customer could possibly 00:06:52.050 --> 00:06:54.949 use them, or near -weekly partnership announcements 00:06:54.949 --> 00:06:57.350 that seem designed more for market headlines 00:06:57.350 --> 00:07:00.329 than for immediate functional value. And you 00:07:00.329 --> 00:07:03.550 see entire legacy sectors being forced to realign 00:07:03.550 --> 00:07:05.089 just so they can tell investors they're part 00:07:05.089 --> 00:07:07.250 of the AI theme. It's that pressure to just be 00:07:07.250 --> 00:07:09.790 seen as participating that defines it. Yes. And 00:07:09.790 --> 00:07:12.550 here's where the paradox gets so dangerous. History 00:07:12.550 --> 00:07:15.509 shows the mania phase feels the safest while 00:07:15.509 --> 00:07:18.329 you're in it because the market's rising. Everyone 00:07:18.329 --> 00:07:20.269 else is getting rich. The riskiest choice feels 00:07:20.269 --> 00:07:23.230 like stepping away. And that illusion of safety. 00:07:23.600 --> 00:07:26.240 is the core of the fragility we have to recognize. 00:07:26.800 --> 00:07:29.879 The sheer narrow concentration, everyone piling 00:07:29.879 --> 00:07:33.500 into the same few stocks, it just. mathematically 00:07:33.500 --> 00:07:35.740 increases the systemic fragility of the markets. 00:07:36.079 --> 00:07:37.980 It's like everyone building their house on the 00:07:37.980 --> 00:07:40.839 same increasingly narrow foundation. The whole 00:07:40.839 --> 00:07:43.060 neighborhood is vulnerable to the same earthquake. 00:07:43.240 --> 00:07:45.420 That's a perfect analogy. And when you combine 00:07:45.420 --> 00:07:47.240 that with the closed -loop financing we talked 00:07:47.240 --> 00:07:49.579 about, where firms are tethered together, you 00:07:49.579 --> 00:07:52.160 create these powerful feedback loops. So one 00:07:52.160 --> 00:07:54.600 bad announcement from one company. And the entire 00:07:54.600 --> 00:07:57.079 intertwined sector immediately feels distress. 00:07:57.420 --> 00:08:00.399 This is why these soaring AI indices, while they 00:08:00.399 --> 00:08:02.560 give off this sense of you know, seeming stability, 00:08:02.959 --> 00:08:05.379 are actually masking vulnerabilities that could 00:08:05.379 --> 00:08:08.500 trigger rapid violent adjustments if that investor 00:08:08.500 --> 00:08:10.839 sentiment subtly changes. Which brings us from 00:08:10.839 --> 00:08:13.720 structural risk to behavioral risk. You call 00:08:13.720 --> 00:08:16.379 this action bias. And this affects everyone, 00:08:16.459 --> 00:08:19.279 from a CEO deciding on R &D spending to an individual 00:08:19.279 --> 00:08:21.680 investor trying to manage their savings. Action 00:08:21.680 --> 00:08:25.279 bias is that powerful compulsion to act, even 00:08:25.279 --> 00:08:27.680 when the rational choice might be to wait or 00:08:27.680 --> 00:08:31.089 diversify or even retreat. In this context, it 00:08:31.089 --> 00:08:34.009 means corporate execs and retail investors feel 00:08:34.009 --> 00:08:37.250 this intense pressure social competitive to maintain 00:08:37.250 --> 00:08:39.730 maximum exposure to the winning theme, which 00:08:39.730 --> 00:08:42.889 right now is AI. Even when the risks are becoming 00:08:42.889 --> 00:08:45.769 pretty obvious. Even then. The fear of missing 00:08:45.769 --> 00:08:48.830 out, you know, it just overrides basic risk management. 00:08:48.970 --> 00:08:50.769 Which is what makes the inevitable correction 00:08:50.769 --> 00:08:54.970 so much worse. That behavioral pressure intensifies 00:08:54.970 --> 00:08:58.190 the volatility. When market reality finally hits 00:08:58.190 --> 00:09:00.070 disappointing earnings or regulatory action, 00:09:00.250 --> 00:09:02.850 whatever it is, the adjustment is amplified because 00:09:02.850 --> 00:09:04.789 so many people felt they had to be in this one 00:09:04.789 --> 00:09:07.889 single theme. The rush for the exit is just incredibly 00:09:07.889 --> 00:09:10.090 crowded. It's a really compelling case for the 00:09:10.090 --> 00:09:12.730 fragility of it all. So against this backdrop 00:09:12.730 --> 00:09:15.490 of concentration and behavioral pressure, prudent 00:09:15.490 --> 00:09:17.649 planning means you have to look outside the dominant 00:09:17.649 --> 00:09:20.700 tech cycle for some stability. That forces us 00:09:20.700 --> 00:09:23.320 to shift focus dramatically. We have to move 00:09:23.320 --> 00:09:26.559 away from these high beta tech assets to assets 00:09:26.559 --> 00:09:29.039 the sources site as potentially providing that 00:09:29.039 --> 00:09:33.100 stability. Specifically, long -standing monetary 00:09:33.100 --> 00:09:37.240 metals. Gold and silver. Contrasting assets in 00:09:37.240 --> 00:09:39.519 almost every way. On every functional way. Yeah. 00:09:39.799 --> 00:09:42.120 And that contrast matters so much right now. 00:09:42.320 --> 00:09:44.360 Why specifically? What makes them so different 00:09:44.360 --> 00:09:46.830 in this context? Because they operate completely 00:09:46.830 --> 00:09:49.289 independently of the current tech cycles and 00:09:49.289 --> 00:09:51.350 those circular financing schemes we talked about. 00:09:51.850 --> 00:09:54.149 Their value is driven by things like monetary 00:09:54.149 --> 00:09:57.049 policy, inflation, geopolitical stability, not 00:09:57.049 --> 00:09:59.090 the quarterly earnings of a chip maker. They're 00:09:59.090 --> 00:10:01.750 non -correlated. Genuinely non -correlated. And 00:10:01.750 --> 00:10:04.190 critically, they carry virtually no counterparty 00:10:04.190 --> 00:10:06.889 risk, which is a key requirement for safety when 00:10:06.889 --> 00:10:08.710 you think the system itself might be fragile. 00:10:08.929 --> 00:10:11.950 And the data suggests this isn't just... a hypothetical 00:10:11.950 --> 00:10:14.149 flight to safety, there are structural trends 00:10:14.149 --> 00:10:16.929 in these assets that started even before the 00:10:16.929 --> 00:10:19.409 current AIP. Absolutely. The research highlights 00:10:19.409 --> 00:10:21.149 some specific data here. Gold, for instance, 00:10:21.169 --> 00:10:23.450 has broken out of what was an 11 -year relative 00:10:23.450 --> 00:10:25.850 performance base against equities. OK, let's 00:10:25.850 --> 00:10:27.809 just clarify that term for everyone listening. 00:10:28.169 --> 00:10:31.330 An 11 -year relative performance base breakout. 00:10:32.009 --> 00:10:34.649 That sounds technical, but what does it actually 00:10:34.649 --> 00:10:37.549 mean for investor confidence? It means that for 00:10:37.549 --> 00:10:40.370 over a decade, gold's performance compared to, 00:10:40.370 --> 00:10:43.750 say, the S &P 500 was stuck in a defined range. 00:10:44.669 --> 00:10:46.909 Breaking out of that range suggests the market's 00:10:46.909 --> 00:10:49.990 long -term calculus of risk and reward has fundamentally 00:10:49.990 --> 00:10:52.840 changed. So investors are basically saying that 00:10:52.840 --> 00:10:55.240 gold stability is more valuable today than it 00:10:55.240 --> 00:10:57.399 has been for the last 10 years. Exactly. It indicates 00:10:57.399 --> 00:11:00.320 a deep -seated loss of confidence in the sustained 00:11:00.320 --> 00:11:03.039 stability of these high -growth, concentrated 00:11:03.039 --> 00:11:06.120 equity markets. And what about silver? It's always 00:11:06.120 --> 00:11:08.460 a bit trickier with its dual role as a monetary 00:11:08.460 --> 00:11:11.700 metal but also with huge industrial demand. Well, 00:11:11.820 --> 00:11:13.740 silver is poised for some more momentum gains. 00:11:14.120 --> 00:11:16.519 And that dual nature actually makes it more resilient. 00:11:16.679 --> 00:11:19.120 It gets the safety hedge benefit like gold. But 00:11:19.120 --> 00:11:21.279 it's huge industrial demand for solar panels, 00:11:21.519 --> 00:11:24.399 electronics. It supports its value, even if financial 00:11:24.399 --> 00:11:26.919 markets get volatile. It has a diversified demand 00:11:26.919 --> 00:11:30.120 base, which makes it a powerful anchor. So we've 00:11:30.120 --> 00:11:32.659 mapped the concentration. We've seen the historical 00:11:32.659 --> 00:11:35.539 parallels. We've identified some stability anchors. 00:11:36.019 --> 00:11:37.600 What does this all mean for the big picture? 00:11:37.919 --> 00:11:40.120 Let's start with policymakers. What a challenge 00:11:40.120 --> 00:11:42.360 they must be facing. It's monumental. For them, 00:11:42.480 --> 00:11:45.559 the rapid spread of AI demands refined governance, 00:11:46.220 --> 00:11:50.980 regulatory transparency, and just more robust 00:11:50.980 --> 00:11:53.909 risk management. The challenge is mitigating 00:11:53.909 --> 00:11:56.990 this systemic risk, avoiding a collapse rooted 00:11:56.990 --> 00:11:59.789 in one sector without stifling the incredible 00:11:59.789 --> 00:12:02.429 innovation AI promises. A tough balancing act. 00:12:02.590 --> 00:12:04.309 It's historically very difficult to achieve. 00:12:04.529 --> 00:12:06.610 And for you, for the individual learner trying 00:12:06.610 --> 00:12:09.190 to navigate this landscape day to day. The main 00:12:09.190 --> 00:12:11.909 takeaway is just the absolute importance of enhancing 00:12:11.909 --> 00:12:14.929 your financial literacy around this. This dissonance 00:12:14.929 --> 00:12:17.629 between market narrative and economic reality. 00:12:17.690 --> 00:12:20.590 The story versus the numbers. Right. The narrative 00:12:20.590 --> 00:12:22.860 is exhilarating. The reality is that the underlying 00:12:22.860 --> 00:12:25.519 fundamentals are strained by closed -loop financing 00:12:25.519 --> 00:12:27.860 and concentration. You have to maintain critical 00:12:27.860 --> 00:12:30.120 awareness of these themes and understand financial 00:12:30.120 --> 00:12:33.019 cycles, recognizing the behaviors of a mania 00:12:33.019 --> 00:12:34.980 phase as it's happening. So here's the final 00:12:34.980 --> 00:12:38.620 synthesis from your sources. The AI boom is a 00:12:38.620 --> 00:12:40.860 watershed moment. It's extraordinary capital 00:12:40.860 --> 00:12:43.379 flow. It's transformative technology. But, and 00:12:43.379 --> 00:12:46.450 this is the critical part, This momentum conceals 00:12:46.450 --> 00:12:49.549 a significant fragility steeped in narrow concentration 00:12:49.549 --> 00:12:53.669 and exuberant, often irrational, sentiment. And 00:12:53.669 --> 00:12:57.210 the need to value differentiated assets that 00:12:57.210 --> 00:12:59.870 can provide stability against corrections has, 00:12:59.870 --> 00:13:02.049 I think, rarely been higher. The traditional 00:13:02.049 --> 00:13:04.840 anchors, gold and silver, They stand out because 00:13:04.840 --> 00:13:07.480 they reflect these enduring qualities of diversification 00:13:07.480 --> 00:13:09.759 and safety that the current tech market just 00:13:09.759 --> 00:13:12.480 cannot offer. This deep dive has laid bare the 00:13:12.480 --> 00:13:14.600 historical precedence and the structural risks 00:13:14.600 --> 00:13:16.220 we're facing. But I want to leave you with one 00:13:16.220 --> 00:13:18.460 final thought. It ties the history to the behavioral 00:13:18.460 --> 00:13:20.779 challenge right now. If history consistently 00:13:20.779 --> 00:13:23.639 shows that the mania phase feels the least risky 00:13:23.639 --> 00:13:26.500 while you are fully immersed in it, how do you 00:13:26.500 --> 00:13:28.940 personally distinguish between genuine technological 00:13:28.940 --> 00:13:32.059 displacement that justifies massive valuations 00:13:32.059 --> 00:13:34.379 and the sheer beha - behavioral pressure of action 00:13:34.379 --> 00:13:36.639 bias compelling you to follow the crowd right 00:13:36.639 --> 00:13:39.379 up to the cliff's edge. That's the essential 00:13:39.379 --> 00:13:41.580 self -reflective question every investor has 00:13:41.580 --> 00:13:43.759 to answer right now. That is a profound thought 00:13:43.759 --> 00:13:45.759 to end on. Thank you for sharing your sources 00:13:45.759 --> 00:13:48.080 and letting us dive deep into the risks behind 00:13:48.080 --> 00:13:50.799 the AI boom. We'll see you next time on the Deep 00:13:50.799 --> 00:13:51.080 Dive.