1 00:00:00,280 --> 00:00:04,080 I think like it's tempting to say like AI is going to automate everything. 2 00:00:04,080 --> 00:00:08,480 I think you really have to still have a view and have a driving bisis 3 00:00:08,519 --> 00:00:12,759 and then understand basically how that AI is going to hold your hand through those 4 00:00:12,839 --> 00:00:17,079 ups and downs and wherever it's going, so you know first first kind of 5 00:00:17,160 --> 00:00:20,960 concept I would say is like for markets, the biggest risk I find is 6 00:00:21,000 --> 00:00:24,359 when all markets are being driven by a single factor. You are listening to 7 00:00:24,480 --> 00:00:30,000 Carrie Letz's Financial Survival Network, where you get valuable information you just can't find 8 00:00:30,079 --> 00:00:36,159 anywhere else to thrive in today's trying times. You need the Financial Survival Network 9 00:00:36,439 --> 00:00:41,679 now more than ever. Go to Financial Survivalnetwork dot com and get your free 10 00:00:41,759 --> 00:00:51,960 newsletter and gift. Financial Survival Network now more than ever. And welcome you 11 00:00:52,079 --> 00:00:56,840 are listening to and watching the Financial Survival Network. I'm your host, and 12 00:00:57,359 --> 00:01:02,479 right now we've got Max Osmond with us. And Max you are a eventure 13 00:01:02,560 --> 00:01:07,599 capitalist, fintech guy, crypto guy, and big tech trend follower. We 14 00:01:07,680 --> 00:01:14,000 love tech on this show. I couldn't be doing this show without tech. 15 00:01:14,439 --> 00:01:17,680 That right now, we just take it for granted, Max, But you 16 00:01:17,680 --> 00:01:22,920 know, ten years ago Zoom was a real pain to use. Oh yeah, 17 00:01:23,560 --> 00:01:26,159 you know ten years ago to do a podcast, really you had to 18 00:01:26,280 --> 00:01:30,959 really jump through hoops. Now it's all commonplace and we just take it for 19 00:01:32,040 --> 00:01:36,760 granted. But one day, at one time, this was somebody's vision. 20 00:01:37,280 --> 00:01:42,599 So you specialize in working with people who have vision, right, a vision 21 00:01:42,200 --> 00:01:48,719 of creating a product or service based on tech that's going to have an effect 22 00:01:49,040 --> 00:01:55,000 in the future once their vision is realized. How how do you separate people's 23 00:01:55,120 --> 00:01:59,959 visions from pie in the sky to hey, this guy really is onto something. 24 00:02:00,680 --> 00:02:05,719 Well, so my primary framework on anything is that there are no companies 25 00:02:05,879 --> 00:02:09,439 or tradings to strategies or anything that are run autonomously. It's all run by 26 00:02:09,439 --> 00:02:14,080 people. So at the end of the day, the companies any company, 27 00:02:14,280 --> 00:02:16,319 but it's Apple, Google, Amazon, It's run by people. So the 28 00:02:17,120 --> 00:02:22,199 primary filter, beginning, middle, and end of a zero to one kind 29 00:02:22,240 --> 00:02:24,599 of decision making process, it comes back to the person. So do you 30 00:02:24,639 --> 00:02:28,800 believe in this person, their vision, their capability, and really, more 31 00:02:28,840 --> 00:02:31,479 importantly than that, the context. So how do they arrive at this? 32 00:02:32,159 --> 00:02:36,599 Why? Now did they fail at a whole bunch of other stuff? And 33 00:02:36,599 --> 00:02:39,280 this is what they're like kind of last shot is it desperation or is it 34 00:02:39,319 --> 00:02:45,319 something that lined up perfectly for them because of their career history, their opportunity. 35 00:02:45,479 --> 00:02:46,800 You can look at public markets, you can look at private markets. 36 00:02:46,840 --> 00:02:51,159 I think all in the same way. Why is this person doing what they're 37 00:02:51,199 --> 00:02:53,719 doing? Is this something that I'm willing to get on board with right now? 38 00:02:54,080 --> 00:02:57,759 I think it's a great framework for evaluating public stocks too, and that's 39 00:02:57,759 --> 00:03:01,280 why people like founder led companies in public markets. Okay, so as far 40 00:03:01,360 --> 00:03:07,319 as when you you know, because mostly these people are considered somewhat eccentric, 41 00:03:07,439 --> 00:03:13,240 They certainly don't fit the moldy because they wouldn't be doing what they're doing. 42 00:03:14,120 --> 00:03:19,120 If they did right, they'd be working, you know, coding and makeing 43 00:03:19,280 --> 00:03:23,759 nice living. But that's not enough. So what is it about a particular 44 00:03:23,840 --> 00:03:28,719 founder where you will look at him and say, Wow, this guy is 45 00:03:28,879 --> 00:03:35,800 really onto something. It's who they're connected to and what they'd done previously. 46 00:03:35,879 --> 00:03:40,039 So you know, we do we do some direct investing at an early stage, 47 00:03:40,080 --> 00:03:45,039 and you know, I won't go in like to too many specifics because 48 00:03:45,039 --> 00:03:47,199 they're not like publicly trade not available wouldn't be helpful in this case. But 49 00:03:47,599 --> 00:03:52,000 you know, in the last investment we made was a guy who'd been in 50 00:03:52,000 --> 00:03:57,080 the hedge fund industry for twenty years in the utilities sector and retired and put 51 00:03:57,159 --> 00:04:02,879 you know, a bunch of money into utility startup that decentralizes ammonia and and 52 00:04:02,919 --> 00:04:06,879 then started the company and has all the connections and is a unique CEO, 53 00:04:08,039 --> 00:04:11,919 founder and h and it's the kind of person that you'd want to follow into 54 00:04:11,960 --> 00:04:15,000 battle, right this is this is a is a good fight, and these 55 00:04:15,039 --> 00:04:18,160 are talented people. As a talented person, so the previous company before that, 56 00:04:18,279 --> 00:04:24,399 you know, it's like in the regulation fintech regulation space, same same 57 00:04:24,439 --> 00:04:30,360 story. Someone who worked at levels of government, connected affected well within government 58 00:04:30,480 --> 00:04:34,600 and has a technology background. And then the problem with starting companies that have 59 00:04:34,639 --> 00:04:39,959 to interact with the government is that so many people come in too hot with 60 00:04:40,040 --> 00:04:42,759 the government. You know, they'll be kind of insulting, and you got 61 00:04:42,759 --> 00:04:44,800 to realize there are people on the other side too. They don't like to 62 00:04:44,839 --> 00:04:47,519 be insulted, even though they know that their regulations are frustrating. And so 63 00:04:47,560 --> 00:04:50,920 if you come in from both angles. I think the reason why they've been 64 00:04:50,959 --> 00:04:55,279 successful is because too many people came in and insulted the government and they work 65 00:04:55,360 --> 00:04:58,720 collaboratively. You know. This is when they started. It was around the 66 00:04:58,720 --> 00:05:01,319 time when Uber was still getting and kind of shut down, you know, 67 00:05:01,399 --> 00:05:04,839 locally because in favor of the taxi drivers because they're being too aggressive. Same 68 00:05:04,839 --> 00:05:11,920 with airbnbing. Yeah, like that was a fascinating story, and they came 69 00:05:12,000 --> 00:05:17,079 to the conclusion it's better to ask forgiveness, better to seek fitness that it 70 00:05:17,160 --> 00:05:20,959 is ask permission. Uh, you know, and that works in some cases, 71 00:05:21,240 --> 00:05:26,959 maybe not. This one that really annoyed me about that was the scooter 72 00:05:27,079 --> 00:05:32,600 companies that just dumped their scooters and like the Middle Texas, right, Yeah, 73 00:05:33,040 --> 00:05:38,639 not a good model in my opinion. No, that was an interesting, 74 00:05:38,759 --> 00:05:42,079 like terrible, terrible execution. Maybe would never have worked, but like 75 00:05:42,480 --> 00:05:46,279 the financial model was always interesting online scooters because you know, you're basically buying 76 00:05:46,360 --> 00:05:49,560 them cheap and then you're trying to rent them out for like a dollar a 77 00:05:49,680 --> 00:05:53,240 day or a dollar an hour or whatever it is, and so the financial 78 00:05:53,240 --> 00:05:57,120 model may be made sense, but ultimately, yeah, you'd ended up just 79 00:05:57,199 --> 00:06:00,800 creating a ton of trash. I don't I don't focus a ton on the 80 00:06:00,000 --> 00:06:05,040 on the line story or that, but but I am I am focused you 81 00:06:05,040 --> 00:06:10,519 know, a lot right now on like you know AI, AI's impact, 82 00:06:12,399 --> 00:06:15,000 whether it's as impact on a portfolio or AI is impact on how you spend 83 00:06:15,000 --> 00:06:21,000 your time efficiently to be productive. So let's talk about that. So AI, 84 00:06:21,600 --> 00:06:28,680 you know, I don't know certainly it can identify trends. It kind 85 00:06:28,680 --> 00:06:38,399 of is a a progression from neural networks and quantum computing right well, the 86 00:06:38,639 --> 00:06:42,079 way I look at it is like zeros and ones for classical computering. That's 87 00:06:42,199 --> 00:06:46,240 just like it's binary, it's if then statements. It's like if I go 88 00:06:46,279 --> 00:06:48,759 over here, if it's Tuesday, or if it's raining outside, if it's 89 00:06:48,839 --> 00:06:51,680 raining outside, bringing umbrella. If it's not, you don't need it, 90 00:06:53,360 --> 00:06:57,079 And it's just statements. What a AI has done in machine learning is has 91 00:06:57,160 --> 00:07:00,800 just made it probabilistic. So if you add up enough of the zero ones, 92 00:07:00,839 --> 00:07:06,319 you can do an insane amount of probability calculations and instead of getting you 93 00:07:06,319 --> 00:07:09,319 know, should I bring the umbrella or not if it's raining, it's like, 94 00:07:09,319 --> 00:07:12,240 well maybe sixty percent chance you should bring it, you know, And 95 00:07:12,279 --> 00:07:15,160 then you add those things up enough, and then you end up replicating language. 96 00:07:15,199 --> 00:07:20,040 You end up bropricating analysis where it becomes really interesting for financial markets is 97 00:07:20,199 --> 00:07:25,759 I would say I now basically have a team of about twelve different analysts AI 98 00:07:25,839 --> 00:07:30,199 analysts who are helping me, you know, kind of continuously evaluate markets. 99 00:07:30,199 --> 00:07:34,079 Markets are probabilistic, which you know fits really well with the AI theme. 100 00:07:34,120 --> 00:07:38,319 You know, so there are really no binary I mean, there are binary 101 00:07:38,319 --> 00:07:44,439 outcomes in markets. You know you're either successful or not, but the analysis 102 00:07:44,160 --> 00:07:50,279 is super probabilistic. Okay, So so where do you think AI fits in 103 00:07:50,920 --> 00:07:55,720 to finance and all that. I mean, hey, yeah, thinks me 104 00:07:55,839 --> 00:08:03,279 like fraud detection, money laundering, and maybe not so much as predicting the 105 00:08:03,279 --> 00:08:11,480 future, but it's saving you from things that you might otherwise be better off 106 00:08:11,480 --> 00:08:16,560 without. Yeah, well, well, I think like it's tempting to say 107 00:08:16,600 --> 00:08:18,920 like AI is going to automate everything. I think you really have to still 108 00:08:20,160 --> 00:08:24,600 have a view and have a driving thesis and then understand basically how that AI 109 00:08:24,680 --> 00:08:28,879 is going to hold your hand through those ups and downs and wherever it's going. 110 00:08:28,079 --> 00:08:31,799 So you know, first first kind of concept I would say is like 111 00:08:31,919 --> 00:08:35,720 for markets, the biggest risk I find is when all markets are being driven 112 00:08:35,759 --> 00:08:39,879 by a single factor. In twenty twenty two, all markets were being driven 113 00:08:39,879 --> 00:08:43,919 by rate hikes. Is like did not matter what else was going on, 114 00:08:43,279 --> 00:08:46,879 every company is falling be through the rate hikes and the fear around that, 115 00:08:46,320 --> 00:08:50,679 and of course COVID crash, all markets being being driven by onset of COVID. 116 00:08:52,039 --> 00:08:56,519 So right now, I would say like the most useful kind of AI 117 00:08:56,559 --> 00:09:01,799 tool is sort of like analyze are being markets by a variety of factors or 118 00:09:01,799 --> 00:09:05,279 by a single factor, And I think what explains market's doing well right now 119 00:09:05,639 --> 00:09:09,519 is markets being driven by a variety of factors. It's maybe rate cuts, 120 00:09:09,559 --> 00:09:16,399 maybe increases and decreases in labor availability, increases or decreases in inflation. You 121 00:09:16,440 --> 00:09:20,840 know, it's like I could list off ten or fifteen different factors that are 122 00:09:20,039 --> 00:09:24,399 influencing each sector, and to me, that's a healthy market. That's a 123 00:09:24,399 --> 00:09:28,879 healthy market that can continue. Okay, So yeah, so kind of talking 124 00:09:28,919 --> 00:09:35,799 about markets that are just being dominated by emotions rather than fact But you know, 125 00:09:37,000 --> 00:09:41,279 some would argue there's only two emotions, fear and greed, and then 126 00:09:41,320 --> 00:09:46,519 you have fear and greed's fomo and kind of a combination of the two. 127 00:09:46,200 --> 00:09:50,879 But it's a little more complicated than that, isn't it. Yeah, it 128 00:09:50,919 --> 00:09:52,279 definitely is. I mean, we're definitely in a fomo stage right now. 129 00:09:52,279 --> 00:09:56,639 I'm getting more calls of like, why do we hold any cash at all? 130 00:09:56,080 --> 00:09:58,320 You know, we should, you know, And that's just like rearview 131 00:09:58,559 --> 00:10:01,480 mirror, and you have to make decisions based in the future and not the 132 00:10:01,519 --> 00:10:05,879 past, and buying the S and P now or whatever, it doesn't give 133 00:10:05,879 --> 00:10:09,759 you the eighteen or twenty percent that you missed out on in the last year 134 00:10:09,879 --> 00:10:15,840 or so. And of course that breeds risk right like call markets make make 135 00:10:15,879 --> 00:10:20,080 for risky your markets. Some of the things I'm concerned about right now. 136 00:10:20,519 --> 00:10:24,720 One is just like massive institutionalization of call selling. You know, there's been 137 00:10:24,720 --> 00:10:31,200 a long, long time, a long project by JP Morgan other banks to 138 00:10:31,279 --> 00:10:37,279 sell products that just have automated call selling behind them. And anytime you make 139 00:10:37,320 --> 00:10:39,919 a one sided market where they're just like, oh, we're just going to 140 00:10:39,960 --> 00:10:43,200 harvest yield on call selling carves siealed, it's eventually going to crack, right. 141 00:10:43,279 --> 00:10:48,600 It's it's too much imbalance on one side of an options market. And 142 00:10:48,720 --> 00:10:52,480 so like I wouldn't touch any of those products that are that are that are 143 00:10:52,720 --> 00:10:56,679 call selling. I also don't love the concept. You know, if I 144 00:10:56,720 --> 00:10:58,799 own equity, I want. I want unlimited upside. I don't want to 145 00:11:00,200 --> 00:11:03,120 my upside by selling a call trying to eke out one or two percent on 146 00:11:03,159 --> 00:11:07,399 a position. I know people do it opportunistically, but what I've seen, 147 00:11:07,960 --> 00:11:11,039 you know you don't want to sell calls on your apples so I can get 148 00:11:11,039 --> 00:11:16,840 a called away missed? You know whatever next generation of you know you think 149 00:11:18,000 --> 00:11:20,000 tech can't jump twenty percent, and then you see you do it in a 150 00:11:20,080 --> 00:11:26,679 day and then kick yourself about why you sold calls on it. Kicking yourself. 151 00:11:26,000 --> 00:11:31,840 Yeah, well, you know, I understand a covered call strategy. 152 00:11:33,200 --> 00:11:37,879 I think it can be effective. But the problem is, like who thought 153 00:11:37,960 --> 00:11:43,399 the market was taken off in April? Everybody was predicting the recession, you 154 00:11:43,440 --> 00:11:48,159 know, the old saying economists has successfully called five out of the last two 155 00:11:48,240 --> 00:11:54,639 recessions. Yeah, they're never right. And anytime you see experts any headlight 156 00:11:54,720 --> 00:12:01,039 of any article or it says experts say you can just put in parentheses. 157 00:12:01,279 --> 00:12:05,360 People who never get it right. Yeah, well the experts are get it 158 00:12:05,480 --> 00:12:07,840 right. The problem with calling him an experts is like you're giving them a 159 00:12:07,919 --> 00:12:13,279 veil of an anonymity. Like I want to hear which expert like is it 160 00:12:13,320 --> 00:12:15,679 Paul Krugman, because like I don't want to hear what he has to say 161 00:12:16,000 --> 00:12:20,240 about where tech is going or stand Drucklin Mall or some of that. Who 162 00:12:20,279 --> 00:12:26,120 is like incredibly influential for financial markets? Yeah yeah, yeah, Like okay, 163 00:12:26,159 --> 00:12:31,480 one man's expert is another man's uber driver. You know, yeah, 164 00:12:31,559 --> 00:12:35,120 yeah, exactly, your drivers are experts and getting it from point A to 165 00:12:35,480 --> 00:12:43,679 point bat watching the map on the screen, you know, But does that 166 00:12:43,720 --> 00:12:48,399 mean they're an expert? And who determines boom is an expert? Right right? 167 00:12:50,159 --> 00:12:54,559 Well? Definitely a personal decision, or at least it's it's been a 168 00:12:54,600 --> 00:12:58,559 super personal decision for me, and I like, I like being aggressive in 169 00:12:58,600 --> 00:13:01,879 my own mind of like I will absolutely never listen to a thing this person 170 00:13:01,960 --> 00:13:05,279 says. I mean, maybe they'll be right on some topics for me. 171 00:13:05,679 --> 00:13:09,480 I don't know. Maybe we'll we'll we'll have some fun to take some shots 172 00:13:09,480 --> 00:13:15,440 of people. But like Fessor Galloway has been like a perennial like issue for 173 00:13:15,519 --> 00:13:18,039 me, Like I don't want to I don't want to follow his ideas or 174 00:13:18,080 --> 00:13:22,320 his trends, even though he's got a lot of press. I just think 175 00:13:22,399 --> 00:13:26,159 I just don't like his uh, his framing and his angle. You know, 176 00:13:26,600 --> 00:13:31,080 ultimately you're framing is a culmination of your experience, and whatever experience he 177 00:13:31,200 --> 00:13:35,039 has has brought him to this level. But meanwhile, I love listening to 178 00:13:35,120 --> 00:13:39,720 Dan Dan Miller. Yeah, you know, kind of jury's out when it 179 00:13:39,759 --> 00:13:46,840 comes to who's the bond? Who's the bond? Guy Double Linear, Jeff 180 00:13:46,840 --> 00:13:50,639 Gunlot. I'm kind of like Jurry's you have to you're on expert? Yeah, 181 00:13:50,759 --> 00:13:54,399 no, I got you, And you know, it's kind of you 182 00:13:54,480 --> 00:14:01,759 got to choose your expert. But eventually experts are like employees. Eventually they 183 00:14:01,799 --> 00:14:05,960 all disappoint you. Yeah, it's like I never meet your hero, right, 184 00:14:07,000 --> 00:14:09,120 and you held them in higher status in your mind than they could ever 185 00:14:09,840 --> 00:14:13,679 drew up to. You know, I'm going to remember that one because I 186 00:14:13,720 --> 00:14:18,320 think it's totally true. And yet you can't know everything. You got to 187 00:14:18,320 --> 00:14:24,519 trust somebody in this world, and you know, with you, trust is 188 00:14:24,559 --> 00:14:28,840 a big issue because you're putting in, you know, millions of dollars into 189 00:14:28,879 --> 00:14:33,279 a startup and you got to know and you know, Leeyakoka once said there's 190 00:14:33,320 --> 00:14:37,399 two things you could never know about a person. Number one is if he 191 00:14:37,720 --> 00:14:43,240 or she is honest, and number two is if they're hard working. Now, 192 00:14:43,240 --> 00:14:48,480 I think number two you can figure that out based on prior accomplishments. 193 00:14:48,519 --> 00:14:52,639 You can get some idea, but the honesty test is really difficult. You 194 00:14:52,679 --> 00:14:58,879 could give them a battery of of psychological profiles. I would say what he 195 00:14:58,000 --> 00:15:03,000 was really saying there. You can never tell if somebody is a sociopath until 196 00:15:03,039 --> 00:15:07,360 you see them in action, you know. Yeah, with one of the 197 00:15:09,120 --> 00:15:13,440 some of the really seasoned veteran venture capitalists that they've factored in that like ten 198 00:15:13,440 --> 00:15:16,840 percent of their you know, founders or some number that will be like flat 199 00:15:16,840 --> 00:15:20,279 out lying to him, not out to them, right, and they just 200 00:15:20,279 --> 00:15:26,960 have to model. Hey, and you know, like nobody wants to be 201 00:15:26,000 --> 00:15:31,200 the bearer of bad tidings. Easier to be a yes man than it is 202 00:15:31,240 --> 00:15:37,159 to be a no man, right right, Yeah, yeah, I mean 203 00:15:37,200 --> 00:15:39,399 I I I tend to think optimism is the is the better strategy, especially 204 00:15:39,440 --> 00:15:43,840 being a young person. It's like lots of time to let things not go 205 00:15:43,919 --> 00:15:48,720 well and then and then get kittyer wins. You know. The best thing 206 00:15:48,799 --> 00:15:52,120 is I think all about asymmetric upside. So you have to take a risk, 207 00:15:52,240 --> 00:15:56,960 you have to let some things fail I think even Ken Ken Griffin. 208 00:16:00,120 --> 00:16:03,919 You know, if Citadel says like we've lost more money than any other edge 209 00:16:03,919 --> 00:16:07,600 fund, he's also made more money than any other edge fund. I think 210 00:16:07,639 --> 00:16:08,559 it just goes hand in hand. You have to have you have to be 211 00:16:08,559 --> 00:16:15,000 willing to take losses. Yeah. Yeah, yeah, there's a lot of 212 00:16:15,080 --> 00:16:18,720 wisdom out there, but it's choosing between it. Now, with the Internet 213 00:16:18,759 --> 00:16:22,159 and all that, you have unlimited access to it, all the good, 214 00:16:22,200 --> 00:16:25,840 the bad, and the ugly, and most of it is ugly. Hey, 215 00:16:26,000 --> 00:16:33,240 So trends looking ahead? Fin tech is your your baireiwick there? What 216 00:16:33,240 --> 00:16:37,720 what can we look forward to here? You know? Well, I would 217 00:16:37,720 --> 00:16:42,639 say, you know, within within fintech. Just one of the frustrations with 218 00:16:42,720 --> 00:16:48,440 the field is if you watch the Apple Development conference from this week and you 219 00:16:48,440 --> 00:16:52,879 see the things that they're able to do with the devices, right, They're 220 00:16:52,919 --> 00:17:00,159 they're leveraging machine learning there, you know, optical character recognition, you know, 221 00:17:00,360 --> 00:17:03,519 an enormous number of automations to roll them out to Apple products, and 222 00:17:03,559 --> 00:17:07,079 it's like pushing the technology to the absolute limit of what it can do. 223 00:17:07,440 --> 00:17:11,559 And then you get back to fintech and you get like we struggle with like 224 00:17:11,599 --> 00:17:15,680 basic math or ledgers or like you see all the different like failures of the 225 00:17:15,720 --> 00:17:18,920 different kind of what was the most. I haven't been following it down to 226 00:17:18,960 --> 00:17:22,720 the detail, but there was a couple. There was a regional bank that 227 00:17:22,720 --> 00:17:27,359 failed that was maybe commingling accounts, and like it's such it's from a technology 228 00:17:27,400 --> 00:17:33,799 perspective and from a math perspective because my background is in mathematics. It's just 229 00:17:33,079 --> 00:17:37,240 like regular algebra, right, and it's so it's not hard from a math 230 00:17:37,240 --> 00:17:40,400 perspective, it's not hard from a concept perspective. For some reason, it's 231 00:17:40,440 --> 00:17:45,279 like the technology lags and fintech in that area by just I don't know, 232 00:17:45,400 --> 00:17:49,079 decade two decades. Like if we take what Apple is doing, we would 233 00:17:49,119 --> 00:17:56,400 dramatically improve, you know, what's going on in the fintech world. One 234 00:17:56,440 --> 00:17:59,880 other trend, though, what the trend? The trend that I would say 235 00:17:59,920 --> 00:18:03,519 is capturing my attention the most right now, I have a call later on 236 00:18:03,559 --> 00:18:07,640 this today I'm trying to piece it together is quantum and it's not necessarily to 237 00:18:07,680 --> 00:18:15,839 fintech, but it is a really important kind of emerging merging concept and if 238 00:18:15,880 --> 00:18:18,319 I get a couple of minutes, I can frame it for you. Please, 239 00:18:18,519 --> 00:18:22,960 I think is interesting. So we're hitting the physical limits of what you 240 00:18:22,000 --> 00:18:27,359 know in video GPUs and computing can do. The physical limits are defined right 241 00:18:27,359 --> 00:18:30,599 now by energy. So it's like, you can build a bunch of data 242 00:18:30,599 --> 00:18:33,200 center. It's actually not hard. It's not as hard to build the data 243 00:18:33,200 --> 00:18:36,960 center as it is to build more electricity. And how do you get the 244 00:18:36,960 --> 00:18:40,319 electricity? Is it going to be sole It can't be solar because you need 245 00:18:41,200 --> 00:18:44,799 it can't be renewables because you need consistency for the data centers. You can't 246 00:18:44,839 --> 00:18:48,960 afford to go down. I mean, I guess you could put a battery, 247 00:18:48,160 --> 00:18:53,039 a megapack battery or two or three or some of them are so big 248 00:18:53,079 --> 00:18:59,799 you probably need twenty of them ton and then they consume just an unbelievable amount 249 00:18:59,759 --> 00:19:03,640 of ER and then you have, you know, the five nines of reliability. 250 00:19:03,640 --> 00:19:06,519 You can only have four minutes a year of downtime, not like anything 251 00:19:06,519 --> 00:19:07,440 more than that. No one's going to use your data sare So it's like, 252 00:19:08,200 --> 00:19:11,680 so do you do nuclear? Well, it's going to take I think 253 00:19:11,279 --> 00:19:15,680 Bill Gates said today they're building a nuclear power planet. It'll be alive by 254 00:19:15,720 --> 00:19:18,599 twenty thirty. So it's like, what are we going to do for the 255 00:19:18,640 --> 00:19:21,279 next six years. You know, it's like you need you need things now. 256 00:19:21,359 --> 00:19:25,200 So anyways, I think about quantum because if we're going to hit the 257 00:19:25,279 --> 00:19:29,720 limits of what we can do with traditional computing, you know, quantum. 258 00:19:30,000 --> 00:19:33,559 The word quantum is really into etymologies. It helps you, like understand the 259 00:19:33,559 --> 00:19:38,240 framing. Quantum is a reference to the pieces that are inside the atoms. 260 00:19:38,920 --> 00:19:44,759 And so when we build viewers now the smallest we can get the transistors to 261 00:19:44,799 --> 00:19:48,480 sort of like twenty atoms wide. But now I know that's not a perfect 262 00:19:48,559 --> 00:19:52,599 description for actually how it works, but that's kind of the that's the limit 263 00:19:52,680 --> 00:19:55,119 we've had. So if we want to get even smaller, we have to 264 00:19:55,200 --> 00:19:59,200 use pieces of atoms. Those are quantum, you know, quantum or quantum, 265 00:20:00,160 --> 00:20:03,160 and then if you want to use the computer based on those, you 266 00:20:03,200 --> 00:20:07,440 can basically dramatically scale up its processing power. I don't really understand completely how 267 00:20:07,440 --> 00:20:11,000 it works on every level, and I don't think anyone really does. There 268 00:20:11,000 --> 00:20:15,079 are some really weird things that happen in quantum computing, quantum mechanics. All 269 00:20:15,119 --> 00:20:18,559 of it is experimental right now. So IBM has the most you know, 270 00:20:18,680 --> 00:20:25,359 kind of advanced current quantum structure. But my understanding is again like they make 271 00:20:25,400 --> 00:20:32,200 more money selling quantum preparedness software and stuff then they do actually selling quantum assets. 272 00:20:32,759 --> 00:20:37,119 So what's going to happen? So my view is, if you could 273 00:20:37,559 --> 00:20:41,200 if it takes six months to train a model an a model on Nvidia GPUs 274 00:20:41,200 --> 00:20:45,480 and it costs three hundred million dollars, you know, you develop in machine 275 00:20:45,519 --> 00:20:51,000 learning algorithm on quantum when it actually functions that would do the same amount of 276 00:20:51,000 --> 00:20:53,240 work in like a minute, right, and that would be you know, 277 00:20:53,240 --> 00:20:59,759 we talked about orders of magnitude of a lot and AI taking six months of 278 00:20:59,799 --> 00:21:02,880 work and compressing town to a minute or something like that. That is like, 279 00:21:03,599 --> 00:21:06,039 you know, it reminds me of what it used to be, like 280 00:21:06,119 --> 00:21:11,039 a computer in an entire room. Now, you know, with the Apple 281 00:21:11,039 --> 00:21:15,880 devices that we're probably talking on, like dramatically more efficient, more powerful, 282 00:21:17,079 --> 00:21:19,319 and they fit you know, in tiny bags. So it's like, you 283 00:21:19,359 --> 00:21:22,920 don't think these order of magnitudes improvements can happen, but they certainly can happen. 284 00:21:23,400 --> 00:21:26,640 So so when is the why an't we going to get breakthroughs with quantum? 285 00:21:26,680 --> 00:21:30,200 I don't know, like it's but to me, it's the only thing 286 00:21:30,240 --> 00:21:34,039 that's going to answer the efficiency issue with with machine learning, Like, we 287 00:21:34,079 --> 00:21:40,240 can't be spending hundreds of billions of dollars to create giant warehouses to train these 288 00:21:40,240 --> 00:21:45,400 models when there is eventually going to be a breakthrough that simplifies that. It's 289 00:21:45,440 --> 00:21:48,920 just that that is a breakthrough. So so where do we stand with it 290 00:21:48,960 --> 00:21:52,400 now? I'm working on this now assuming that at some point over the next 291 00:21:52,480 --> 00:21:56,960 five years there's going to be a really interesting quantum related investment. I don't 292 00:21:57,000 --> 00:21:59,680 know what it's going to look like. I don't know where it's going to 293 00:21:59,720 --> 00:22:03,359 be. If it's going to be IP related, I don't know if it's 294 00:22:03,359 --> 00:22:06,920 going to be momentum because they solved it and they're going to be running away 295 00:22:06,960 --> 00:22:11,440 with the technology into the future. But I think now is the time to 296 00:22:11,480 --> 00:22:14,599 start thinking. Just like if you were thinking about AI ten years ago, 297 00:22:15,079 --> 00:22:18,680 you eventually arrived on GPUs and Nvidia, I think you have to think about 298 00:22:18,720 --> 00:22:22,359 quantum now to see what's going to happen. All right, So you know 299 00:22:22,480 --> 00:22:26,480 during the gold Rush, you know, only a very few miners got wealthy, 300 00:22:26,880 --> 00:22:34,079 but the companies that sold the pickaxes and the dynamite and the clothes the 301 00:22:34,119 --> 00:22:41,000 Leli Strausser's of the world they cleaned up what So you outline the problem here 302 00:22:41,160 --> 00:22:51,519 of the energy shortages electricity particular, because these still are highly regulated industries, 303 00:22:51,599 --> 00:22:57,559 not like what they used to be because got pseudo competition and distribution. You 304 00:22:57,599 --> 00:23:06,400 know, in the favorable economic climates and climates too where people are going to 305 00:23:06,440 --> 00:23:11,960 want to build these multi billion dollar data centers. You know, these utilities 306 00:23:11,960 --> 00:23:15,319 are going to kill it. And I would also say the utilities around the 307 00:23:15,400 --> 00:23:21,440 nation's capital because I don't think they aren't the biggest investor in AI out there 308 00:23:21,440 --> 00:23:27,960 in every aspect of what the government does. So you know, those utilities 309 00:23:29,960 --> 00:23:33,720 are in a bind because, like you said, nukes take ten years with 310 00:23:33,880 --> 00:23:40,440 licensing and everything else. And don't believe modularity because that really doesn't speed up 311 00:23:40,480 --> 00:23:45,160 the process regulation, bog and everything else. So we're going to need more 312 00:23:45,319 --> 00:23:53,559 energy. To think it's going to come from renewables is naive and so you're 313 00:23:53,359 --> 00:23:59,839 you're you're walking into a really interesting topic that's that's fun to explore and not 314 00:23:59,839 --> 00:24:03,079 not an area that I've done enough work on yet. But but you know, 315 00:24:03,359 --> 00:24:08,480 natural gas is the is the sort of fossil fuel solution it's cleaner, 316 00:24:08,720 --> 00:24:15,640 more efficient, you know it it is. It's funny because you know, 317 00:24:15,680 --> 00:24:17,920 we have to have trade offs. We have to have cheap energy, so 318 00:24:17,920 --> 00:24:21,680 we can't like throw out fossil fuel, but you can use natural gas and 319 00:24:21,759 --> 00:24:27,279 get some really compelling results. And so that's still not popular at all among 320 00:24:27,960 --> 00:24:32,720 you know, a Democrat and not the politics you know, conversation. But 321 00:24:32,759 --> 00:24:36,880 it's just not the democratic kind of narrative. You know, it doesn't even 322 00:24:36,960 --> 00:24:40,519 want to talk about natural gas. So there's a lot of energy assets that 323 00:24:40,559 --> 00:24:45,599 I think are really compelling, probably compelling because of what you're talking about, 324 00:24:45,640 --> 00:24:49,640 Like you need to have the energy of the electricity to support either this transformation 325 00:24:49,759 --> 00:24:53,319 or just like power the world. Like I like these stresses, Like there's 326 00:24:53,319 --> 00:24:57,039 no such thing as wealthy com economy without cheap energy. It's like there's not 327 00:24:57,079 --> 00:25:00,440 a still developed economy that didn't have acces to cheap energy. It's like the 328 00:25:00,839 --> 00:25:07,720 mental space. Yeah, so so yeah, I wonder because the last decade 329 00:25:07,519 --> 00:25:11,240 prior to COVID, the last decade of energy Exxon or anything, there's been 330 00:25:11,319 --> 00:25:17,079 like it was horrible, Like from a from an index perspective, if you 331 00:25:17,200 --> 00:25:19,880 look at xl E, that's sort of the benchmark I'm referring to or exon 332 00:25:21,000 --> 00:25:23,799 it was horrible and then all of a sudden, out of COVID. You 333 00:25:23,799 --> 00:25:26,799 know, it's been an unbelievable asset class to own. It's been the only 334 00:25:26,799 --> 00:25:30,720 other kind of forming asset class outside of tech. And so how do we 335 00:25:30,720 --> 00:25:33,759 look at energy going forward? I think it's a really important question to answer 336 00:25:33,799 --> 00:25:37,559 for investors. You know, do you get deep down in the weeds and 337 00:25:37,599 --> 00:25:41,720 you pick you know stocks so you get you know, really well integrated into 338 00:25:41,720 --> 00:25:45,319 the different assets out there, or do you do you benchmarket with an index? 339 00:25:45,359 --> 00:25:49,160 I don't know. Well, you know the good thing if you're getting 340 00:25:49,200 --> 00:25:55,519 into that gas, let's show you're speaking my language now, been a moon 341 00:25:55,599 --> 00:26:00,799 and of it. It's been trading at a discount per BTU to oil for 342 00:26:00,880 --> 00:26:04,359 decades now, and when I was a child growing up through two energy crises, 343 00:26:04,799 --> 00:26:11,680 it traded pretty close to parody. And nice thing is you actually get 344 00:26:11,720 --> 00:26:21,240 paid to weight because they pay out above average dividends almost the couple points behind 345 00:26:21,400 --> 00:26:26,599 the actual inflation rate. But the technology to manage the grid all right, 346 00:26:26,680 --> 00:26:32,160 because the problem with the grid is and most people don't even know it, 347 00:26:32,240 --> 00:26:37,960 like the you have transmission loss fifteen twenty percent, and they kept saying, 348 00:26:37,000 --> 00:26:42,839 well, we're going to come up with the superconductor power transmission lines and we'll 349 00:26:42,880 --> 00:26:48,279 have one or two percent and they'll be nitrogen cooled. Well, evidently that 350 00:26:48,400 --> 00:26:53,119 wasn't too practical, so grid management, and you know, for the rest 351 00:26:53,119 --> 00:27:00,279 of US residential users and commercial users out there in these states where they start 352 00:27:00,279 --> 00:27:06,319 building these data centers, it's going to be a fight for electricity. Now, 353 00:27:06,319 --> 00:27:10,400 in theory, they could bring in their own generator and do it themselves, 354 00:27:10,480 --> 00:27:14,920 and maybe if they own some that gas wells, they could just feed 355 00:27:14,960 --> 00:27:19,799 that generator right off the wells. I mean, cryptomiding, it's like insane, 356 00:27:21,039 --> 00:27:25,039 you know, it's basically the same thing as AI. So you know, 357 00:27:25,559 --> 00:27:29,119 just interesting things. Well, I think you've like helped us look at 358 00:27:29,160 --> 00:27:32,960 trends in a different way here, Max. If we want to connect with 359 00:27:33,000 --> 00:27:36,960 you on the web and take a look at what you're doing, how do 360 00:27:37,039 --> 00:27:41,960 we do that? Yep? So I write a pretty widely read article on 361 00:27:42,000 --> 00:27:47,160 my website, osboncapital dot com. It comes out weekly, so I'll be 362 00:27:47,200 --> 00:27:51,720 writing it today and it'll be out tomorrow morning, Thursday, Thursday morning. 363 00:27:51,759 --> 00:27:56,759 To pay them in this area. It comes out every Thursday morning. That 364 00:27:56,759 --> 00:28:02,440 that article is where I both write down my own thoughts for my own to 365 00:28:02,519 --> 00:28:06,440 codify my own thinking, and to share it with other people, to put 366 00:28:06,480 --> 00:28:11,119 it out publicly, either to you know, get people to throw throw stones 367 00:28:11,119 --> 00:28:15,480 at it and tell me why I'm wrong, or to reansworth it to reamport 368 00:28:15,480 --> 00:28:18,200 at it. Yes, so that's that's my primary things. I write that 369 00:28:18,319 --> 00:28:22,079 article I've been doing every week for many, many, many years. It's 370 00:28:22,119 --> 00:28:26,200 my commitment, all right. Hey, well, the link to your site 371 00:28:26,240 --> 00:28:30,759 is in the show notes to this interview on Financial Survival Network dot com. 372 00:28:30,799 --> 00:28:33,559 When you go there, please sign up for your free newsletter. I got 373 00:28:33,559 --> 00:28:37,279 a question for Max or myself. We'd love to hear from you. Shoot 374 00:28:37,279 --> 00:28:41,359 me an email to kl at Carrie LUTs dot com. Max. Been a 375 00:28:41,359 --> 00:28:45,640 pleasure. We'll definitely talk to you again. And hey, we're gonna sign 376 00:28:45,759 --> 00:28:48,599 up to your blog your newsletter there. Thank you, Gerry, thanks for 377 00:28:48,680 --> 00:28:56,000 listening to carry lets this Financial Survival Network your solution to today's trying times. 378 00:28:56,240 --> 00:29:03,400 For the latest, go to Financial Survivalnetwork dot Cominancial Survival Network now more than ever