1 00:00:00,080 --> 00:00:02,160 Speaker 1: Kathy, thank you so much for joining us today. Hugely 2 00:00:02,160 --> 00:00:03,920 Speaker 1: appreciate it. I've been wanting to talk to you for 3 00:00:04,120 --> 00:00:07,720 Speaker 1: well for years at this point. Astley, oh Maren, thank you. 4 00:00:08,039 --> 00:00:10,280 Speaker 1: I'm really happy to be joining you. Thank you for 5 00:00:10,320 --> 00:00:12,719 Speaker 1: inviting me. Now, what I want to start with. I 6 00:00:12,800 --> 00:00:14,920 Speaker 1: know everyone will be will be hanging on to listen 7 00:00:14,920 --> 00:00:17,279 Speaker 1: to all your thoughts on innovation and stocks and the 8 00:00:17,360 --> 00:00:20,480 Speaker 1: portfolios themselves. But before we go there, I want to 9 00:00:20,520 --> 00:00:23,880 Speaker 1: talk to you about the macro environment. Obviously, the change 10 00:00:24,160 --> 00:00:26,400 Speaker 1: in the macro environment around us over the last couple 11 00:00:26,400 --> 00:00:30,040 Speaker 1: of years has been absolutely extraordinary. We've moved from that crazy, 12 00:00:30,080 --> 00:00:32,960 Speaker 1: that very low inflation, very low interest rate environment that 13 00:00:33,520 --> 00:00:36,600 Speaker 1: drove phenomenal returns in your kind of portfolio into something 14 00:00:36,640 --> 00:00:40,919 Speaker 1: completely different, high interest rates, high, very high inflation now 15 00:00:40,920 --> 00:00:43,760 Speaker 1: coming down a bit. So what's a really important thing 16 00:00:43,760 --> 00:00:45,680 Speaker 1: for us to start by talking about is how do 17 00:00:45,720 --> 00:00:48,319 Speaker 1: you see that developing from here? A lot of our 18 00:00:48,360 --> 00:00:50,640 Speaker 1: guests come on and I'm very much higher for longer 19 00:00:50,680 --> 00:00:54,280 Speaker 1: people expecting inflation to be high and volatile for some 20 00:00:54,360 --> 00:00:57,960 Speaker 1: years to come, and interest rate to obviously follow that part. 21 00:00:58,080 --> 00:01:00,200 Speaker 1: So I'm wondering if we can find out where you 22 00:01:00,280 --> 00:01:02,200 Speaker 1: stand on the Great Inflation debate. 23 00:01:03,080 --> 00:01:06,039 Speaker 2: You know, it's interesting. I got into the business a 24 00:01:06,360 --> 00:01:08,840 Speaker 2: very long time ago. I was in college and it 25 00:01:08,959 --> 00:01:13,160 Speaker 2: was in the late seventies, so I experienced that inflation, 26 00:01:13,520 --> 00:01:20,200 Speaker 2: and I experienced Chairman Vulker strangling it. And what we've 27 00:01:20,360 --> 00:01:23,120 Speaker 2: just seen, I think, is nothing like that. And I 28 00:01:23,319 --> 00:01:25,560 Speaker 2: actually think, and I have been saying for quite some time, 29 00:01:26,280 --> 00:01:29,000 Speaker 2: that we're going to see deflation before all of this 30 00:01:29,080 --> 00:01:31,760 Speaker 2: is over, and we're beginning to see it already. We 31 00:01:31,840 --> 00:01:35,720 Speaker 2: think this period of time is much more like the 32 00:01:35,840 --> 00:01:40,759 Speaker 2: nineteen teens than the nineteen seventies. And so what did 33 00:01:40,760 --> 00:01:44,440 Speaker 2: we have in the nineteen teens. We had a war, 34 00:01:45,280 --> 00:01:49,280 Speaker 2: it was World War One. We had a pandemic, it 35 00:01:49,360 --> 00:01:53,960 Speaker 2: was the Spanish flu. They didn't call supply chain problems 36 00:01:54,440 --> 00:01:58,000 Speaker 2: supply chain problems at the time, but they were massive. 37 00:01:58,160 --> 00:02:02,400 Speaker 2: We were on the gold standard, but still inflation hit 38 00:02:02,600 --> 00:02:05,800 Speaker 2: twenty four percent, so it was a supply side shock. 39 00:02:06,760 --> 00:02:11,560 Speaker 2: And it hit twenty four percent in June of nineteen 40 00:02:11,720 --> 00:02:16,280 Speaker 2: twenty and by June of nineteen twenty one we were 41 00:02:16,280 --> 00:02:20,399 Speaker 2: down to minus fifteen percent. And one of the reasons 42 00:02:20,560 --> 00:02:24,360 Speaker 2: was being on the gold standard. We were shrinking the 43 00:02:24,440 --> 00:02:28,720 Speaker 2: money supply in response to that inflation. I think we're 44 00:02:28,760 --> 00:02:31,960 Speaker 2: in the same situation now. Of course, it's just an echo. 45 00:02:32,320 --> 00:02:34,720 Speaker 2: Now we have another war. You know, we have the 46 00:02:35,000 --> 00:02:39,360 Speaker 2: Ukraine War, we now have the war in Israel, and 47 00:02:39,400 --> 00:02:45,959 Speaker 2: of course we had the COVID pandemic. We think that 48 00:02:45,960 --> 00:02:50,639 Speaker 2: that caused a massive supply demand imbalance. I mean, it's 49 00:02:50,680 --> 00:02:55,000 Speaker 2: clear that it did, and that's the main reason inflation 50 00:02:55,680 --> 00:02:59,440 Speaker 2: took off the way it did, and now it is unraveling. 51 00:03:00,120 --> 00:03:04,799 Speaker 2: And I also think China is exporting deflation. And we're 52 00:03:04,840 --> 00:03:08,480 Speaker 2: hearing a lot in Meta Platforms report. They were talking 53 00:03:08,600 --> 00:03:15,040 Speaker 2: about how significant Chinese advertising was for them, advertising to 54 00:03:15,840 --> 00:03:20,880 Speaker 2: developed world consumers, and so I think that's evidence that China. 55 00:03:21,200 --> 00:03:26,280 Speaker 2: China's economy is so weak that it needs to export 56 00:03:26,280 --> 00:03:33,519 Speaker 2: increasingly in order in order to gain foreign exchange. We've 57 00:03:33,560 --> 00:03:36,280 Speaker 2: been watching their dollar reserves. They've gone from one point 58 00:03:36,320 --> 00:03:41,640 Speaker 2: two trillion dollars down to seven hundred and ninety billion dollars, 59 00:03:42,200 --> 00:03:45,520 Speaker 2: and you know, it's been accelerating month by month. So 60 00:03:45,960 --> 00:03:49,720 Speaker 2: we see all kinds of deflationary influences out there. And 61 00:03:49,720 --> 00:03:52,360 Speaker 2: I'm going to give you a statistic. I look at 62 00:03:52,440 --> 00:03:56,440 Speaker 2: it and I've pulled up the chart a number of times, saying, really, 63 00:03:56,560 --> 00:04:00,480 Speaker 2: people do not understand this. If you look at the 64 00:04:00,520 --> 00:04:07,760 Speaker 2: Bloomberg Commodity Price Index, it's BCM on Bloomberg, and you 65 00:04:07,840 --> 00:04:12,400 Speaker 2: take that back through history, it is today where it 66 00:04:12,560 --> 00:04:15,600 Speaker 2: was in the early eighties, and it's been in a 67 00:04:15,640 --> 00:04:20,520 Speaker 2: massive trading range that entire time. That tells me that 68 00:04:20,600 --> 00:04:24,480 Speaker 2: we have not broken out to a new inflation here. 69 00:04:24,600 --> 00:04:27,400 Speaker 2: In fact, if you look at that index, it peaked 70 00:04:27,600 --> 00:04:33,080 Speaker 2: in two thousand and eight and has had lower highs 71 00:04:33,120 --> 00:04:36,239 Speaker 2: ever since, and we think it's going to break down again, 72 00:04:37,920 --> 00:04:41,720 Speaker 2: and we're beginning to get a lot of macro commentary 73 00:04:42,320 --> 00:04:46,520 Speaker 2: suggesting that. And when I say macro commentary, I am 74 00:04:46,640 --> 00:04:50,880 Speaker 2: not talking about the economic statistics coming out of governments. 75 00:04:51,240 --> 00:04:55,039 Speaker 2: I'm talking about what companies are saying. We listen to 76 00:04:55,200 --> 00:04:59,360 Speaker 2: all kinds of earnings calls, and not one of them 77 00:05:00,880 --> 00:05:05,560 Speaker 2: has neglected to mention that the economy is fraying at 78 00:05:05,560 --> 00:05:09,520 Speaker 2: the edges, even meta platforms. So the former Facebook, they 79 00:05:09,520 --> 00:05:13,520 Speaker 2: had a very strong quarter. They mentioned how material the 80 00:05:13,600 --> 00:05:20,440 Speaker 2: Chinese advertising was advertising to developed world customers, but they 81 00:05:20,520 --> 00:05:24,560 Speaker 2: also said October was soft, and almost every company is saying, 82 00:05:24,680 --> 00:05:27,120 Speaker 2: so we think we have entered a recession in the 83 00:05:27,240 --> 00:05:31,919 Speaker 2: United States. I understand that. In Europe, I think I 84 00:05:31,960 --> 00:05:37,400 Speaker 2: think recently, if not today, back to back negative quarters. 85 00:05:37,440 --> 00:05:42,960 Speaker 2: I think in Germany, maybe in the euroeconomy at large. 86 00:05:43,000 --> 00:05:47,359 Speaker 2: So Europe we think is in recession. And I will 87 00:05:47,400 --> 00:05:49,880 Speaker 2: say some of the numbers coming out of Europe are 88 00:05:49,960 --> 00:05:54,080 Speaker 2: surprising US, but I think they're against on the high side, 89 00:05:54,120 --> 00:05:58,760 Speaker 2: I think they're against what was happening last year when 90 00:05:59,000 --> 00:06:03,359 Speaker 2: energy prices went crazy and the consumer was in a 91 00:06:03,400 --> 00:06:08,239 Speaker 2: bit of a pickle. But China, Europe, US we think 92 00:06:08,440 --> 00:06:13,480 Speaker 2: in recession. We also are very interested to watch the 93 00:06:14,400 --> 00:06:19,880 Speaker 2: price of bitcoin here in March. Bitcoin. First of all, 94 00:06:19,920 --> 00:06:22,080 Speaker 2: in March here in the United States, we had a 95 00:06:22,120 --> 00:06:25,960 Speaker 2: regional bank crisis. I'm I'm sure you heard Silicon Valley 96 00:06:26,000 --> 00:06:30,920 Speaker 2: Bank went but and what was fascinating during that period 97 00:06:31,600 --> 00:06:36,240 Speaker 2: was that bitcoins price went from nineteen thousand to thirty thousand. 98 00:06:36,800 --> 00:06:40,440 Speaker 2: It was a flight to safety vehicle. And here you 99 00:06:40,520 --> 00:06:44,600 Speaker 2: see it now bumping up again. And you see the 100 00:06:45,360 --> 00:06:48,640 Speaker 2: KARB index, which is the regional bank index here in 101 00:06:48,640 --> 00:06:53,200 Speaker 2: the United States, breaking below where it was in March's interesting. 102 00:06:53,240 --> 00:06:55,920 Speaker 1: So a lot of people believe that that rise in 103 00:06:55,960 --> 00:07:00,520 Speaker 1: the price of bitcoin is related to inflation protection, but 104 00:07:00,800 --> 00:07:02,800 Speaker 1: you think it's a safe haven flight. 105 00:07:03,560 --> 00:07:06,280 Speaker 2: I don't believe that inflation is why it's going up. 106 00:07:06,640 --> 00:07:10,080 Speaker 2: I know it can serve as a hedge against inflation, 107 00:07:10,720 --> 00:07:14,000 Speaker 2: but it can also serve as a hedge against deflation 108 00:07:15,120 --> 00:07:21,040 Speaker 2: because there's no counterparty risk in bitcoin. It's a completely transparent, 109 00:07:21,800 --> 00:07:25,040 Speaker 2: decentralized network. You can see everything that's going on on 110 00:07:25,080 --> 00:07:28,040 Speaker 2: the network, but you cannot see what's going on inside 111 00:07:28,120 --> 00:07:31,920 Speaker 2: regional banks. You can only surmise because they're losing deposits 112 00:07:33,000 --> 00:07:37,920 Speaker 2: and they have to fund those by selling securities. And 113 00:07:38,840 --> 00:07:42,520 Speaker 2: so they have two classes of maturities at the market 114 00:07:42,560 --> 00:07:46,000 Speaker 2: which they can sell, but they also have classified some 115 00:07:46,200 --> 00:07:49,840 Speaker 2: as hell to maturity, and if they were to mark 116 00:07:49,880 --> 00:07:53,120 Speaker 2: those to market, they go directly against equity. That's what 117 00:07:53,200 --> 00:07:58,320 Speaker 2: happened in March, and the deposit that the deposit flight 118 00:07:58,440 --> 00:08:02,160 Speaker 2: has not stopped, and they're forced to raise interest rates 119 00:08:02,160 --> 00:08:05,320 Speaker 2: to compete against money market funds. So you know that 120 00:08:05,440 --> 00:08:08,320 Speaker 2: problem has not gone away. That problem has not gone away. 121 00:08:08,360 --> 00:08:11,480 Speaker 2: And I think the other thing is it's fascinating to 122 00:08:11,640 --> 00:08:18,360 Speaker 2: watch M two Like in the early nineteen teens, M 123 00:08:18,400 --> 00:08:22,120 Speaker 2: two is negative on a year over year basis from 124 00:08:22,160 --> 00:08:25,440 Speaker 2: a percent change point of view, this has not happened 125 00:08:25,480 --> 00:08:29,120 Speaker 2: since the nineteen thirties, and so you know, just to 126 00:08:29,440 --> 00:08:34,360 Speaker 2: end where we started and this analogy, we have two wars. 127 00:08:34,880 --> 00:08:41,360 Speaker 2: We had a pandemic, We have the FED throttling money 128 00:08:41,400 --> 00:08:45,120 Speaker 2: supply like it did back then. And we do think 129 00:08:45,240 --> 00:08:51,360 Speaker 2: that the CPI and other inflation measures will turn negative 130 00:08:51,720 --> 00:08:54,720 Speaker 2: before all is said and done. And we've gone from 131 00:08:54,800 --> 00:08:59,440 Speaker 2: nine percent to three point seven percent now and I 132 00:08:59,480 --> 00:09:01,960 Speaker 2: think will be negative at some point next year. 133 00:09:02,679 --> 00:09:05,320 Speaker 1: That money supply argument seems pretty convincing, and that one 134 00:09:05,360 --> 00:09:07,080 Speaker 1: of the things that happened before we had this bad 135 00:09:07,160 --> 00:09:09,280 Speaker 1: inflation was a very fast rise in the money supply 136 00:09:09,360 --> 00:09:12,120 Speaker 1: and everyone had forgotten about monetarist economics, and now it 137 00:09:12,120 --> 00:09:14,600 Speaker 1: seems to be explaining what's happening. 138 00:09:15,000 --> 00:09:18,520 Speaker 2: Yeah, and I don't think they're taking this and to 139 00:09:19,600 --> 00:09:25,679 Speaker 2: negative growth seriously. What could be much more serious is 140 00:09:25,960 --> 00:09:30,640 Speaker 2: if we do get fear in the marketplace for whatever reason, 141 00:09:31,559 --> 00:09:36,160 Speaker 2: and people begin to say I'm not going to make 142 00:09:36,200 --> 00:09:38,640 Speaker 2: that purchase, I'm going to hold back because I need 143 00:09:38,679 --> 00:09:41,480 Speaker 2: to see what happens here. That would be the velocity 144 00:09:41,520 --> 00:09:45,680 Speaker 2: of money coming down again. And interestingly, the velocity of 145 00:09:45,720 --> 00:09:49,720 Speaker 2: money peaked, if you look secularly at peaked in nineteen 146 00:09:49,760 --> 00:09:55,160 Speaker 2: ninety seven, had been falling. From a trend point of view, 147 00:09:55,240 --> 00:09:59,040 Speaker 2: it has cyclical upturns, but the trend has been down. 148 00:09:59,559 --> 00:10:03,439 Speaker 2: During OVID, it collapsed again. Everybody seized up, they were 149 00:10:03,480 --> 00:10:07,040 Speaker 2: scared to death, and we've had the rebound from that, 150 00:10:07,080 --> 00:10:10,679 Speaker 2: but it has not hit its downtrend yet. And we 151 00:10:10,840 --> 00:10:15,920 Speaker 2: think that fear is building once again. And if you 152 00:10:16,080 --> 00:10:19,439 Speaker 2: have money negative on a year over year basis, and 153 00:10:19,559 --> 00:10:23,480 Speaker 2: you have the velocity of money slowing down or even 154 00:10:23,520 --> 00:10:27,240 Speaker 2: declining again, that would be a recipe for a very 155 00:10:27,480 --> 00:10:29,800 Speaker 2: serious decline in economic activity. 156 00:10:30,160 --> 00:10:34,240 Speaker 1: The rise in interest rates and inflation and the collapse 157 00:10:34,280 --> 00:10:37,120 Speaker 1: of the bubble in growth stocks or what people now 158 00:10:37,120 --> 00:10:38,480 Speaker 1: say was the bubble. And I know that you did 159 00:10:38,520 --> 00:10:40,559 Speaker 1: not believe in twenty one that it was a bubble. 160 00:10:40,600 --> 00:10:42,800 Speaker 1: You're very clear that this was not a bubble in 161 00:10:42,840 --> 00:10:46,600 Speaker 1: this area of equity. So possibly what happened after that 162 00:10:46,720 --> 00:10:50,599 Speaker 1: was a surprise to you. The rise inflation, rise and 163 00:10:50,640 --> 00:10:52,800 Speaker 1: interest rates, and the collapse and the prices of lots 164 00:10:52,840 --> 00:10:55,280 Speaker 1: of the kind of equities that you invest in. 165 00:10:55,679 --> 00:11:02,360 Speaker 2: Yes, so let's talk about that. In twenty twenty. Yes, 166 00:11:02,600 --> 00:11:06,520 Speaker 2: I think, and I still believe this, and only time 167 00:11:06,559 --> 00:11:11,840 Speaker 2: will tell, but I think you had a lot of 168 00:11:11,880 --> 00:11:14,720 Speaker 2: people putting the chart of the tech and telecom bubble 169 00:11:14,840 --> 00:11:19,120 Speaker 2: up and putting arkk Our flagship on top of it, 170 00:11:19,880 --> 00:11:23,320 Speaker 2: and basically they drew a line and said, Hey, this 171 00:11:23,400 --> 00:11:26,000 Speaker 2: looks just like back then, and the same thing's going 172 00:11:26,040 --> 00:11:27,959 Speaker 2: to happen to it. I did not believe that was 173 00:11:28,000 --> 00:11:32,080 Speaker 2: going to happen, and it did happen, and it happened, 174 00:11:32,480 --> 00:11:36,360 Speaker 2: and in fact, the decline was much worse, or it 175 00:11:36,440 --> 00:11:39,840 Speaker 2: was worse. I mean it was a peak to trough. 176 00:11:40,800 --> 00:11:43,920 Speaker 2: I forget the exact number, seventy six percent or something 177 00:11:44,000 --> 00:11:47,320 Speaker 2: like that. And if you look back at the tech 178 00:11:47,520 --> 00:11:53,720 Speaker 2: and telecom bubble and bust, you understood why that happened. 179 00:11:54,520 --> 00:11:58,200 Speaker 2: The technologies weren't ready. I mean, we didn't get the 180 00:11:58,200 --> 00:12:01,160 Speaker 2: cloud until two thousand and six. We didn't get the 181 00:12:01,240 --> 00:12:06,680 Speaker 2: first big breakthrough in artificial intelligence deep learning until twenty twelve. 182 00:12:06,679 --> 00:12:11,800 Speaker 2: We didn't get this second provocative breakthrough in AI transformer 183 00:12:11,920 --> 00:12:19,160 Speaker 2: architecture until twenty eighteen, and so the technologies weren't ready, 184 00:12:19,360 --> 00:12:23,200 Speaker 2: and even if they were getting close to primetime, they 185 00:12:23,240 --> 00:12:27,160 Speaker 2: were way too expensive. So back then, we didn't sequence 186 00:12:27,240 --> 00:12:30,360 Speaker 2: the first whole human genome until two thousand and three, 187 00:12:30,720 --> 00:12:35,520 Speaker 2: and it costs two point two point seven billion dollars. 188 00:12:35,640 --> 00:12:40,000 Speaker 2: This is just one person's genome. Two point seven billion 189 00:12:40,080 --> 00:12:44,120 Speaker 2: dollars and thirteen years of computing power to get that 190 00:12:44,160 --> 00:12:50,280 Speaker 2: first genome. Today we're down to, depending on whose sequencers 191 00:12:50,320 --> 00:12:53,880 Speaker 2: you use, two hundred to four hundred dollars and a 192 00:12:53,920 --> 00:12:57,240 Speaker 2: few hours of computing power, and that's just twenty over 193 00:12:57,320 --> 00:13:02,280 Speaker 2: twenty years time. So the the technology is ready, the 194 00:13:02,440 --> 00:13:08,600 Speaker 2: costs are low enough. In robotics, energy storage, think electric vehicles, 195 00:13:09,600 --> 00:13:17,880 Speaker 2: artificial intelligence, blockchain technology, and what we're now calling multiomic sequencing. 196 00:13:17,920 --> 00:13:20,199 Speaker 2: We used to call it a sequencing. But it's not 197 00:13:20,280 --> 00:13:24,679 Speaker 2: just DNA, it's RNA, it's protein, it's methylation, it's epigenetics. 198 00:13:24,720 --> 00:13:31,240 Speaker 2: It's complicated. So all of those technologies were dreams in 199 00:13:31,280 --> 00:13:37,080 Speaker 2: the late nineties, and investors chased them, and there was 200 00:13:37,120 --> 00:13:41,920 Speaker 2: too much capital chasing too few opportunities, too soon, and 201 00:13:42,400 --> 00:13:48,080 Speaker 2: the bust was inevitable, and we knew it. Anyone watching 202 00:13:49,080 --> 00:13:54,960 Speaker 2: with any perspective understood that what's happening this time around. 203 00:13:55,800 --> 00:14:00,240 Speaker 2: The technologies are ready, the costs are low enough, and 204 00:14:00,320 --> 00:14:03,840 Speaker 2: investors are running away. They're running for the hills. What 205 00:14:03,880 --> 00:14:07,199 Speaker 2: are the hills? They're benchmarks. And when investors in a 206 00:14:07,320 --> 00:14:12,400 Speaker 2: risk of situation as rising inflation, rising interest rates, and 207 00:14:13,080 --> 00:14:17,640 Speaker 2: you know, hair on fire, fears about much higher inflation 208 00:14:18,400 --> 00:14:23,600 Speaker 2: and for much longer, they took our strategy apart. And 209 00:14:23,800 --> 00:14:30,040 Speaker 2: I say they because our market is dominated by algorithms, 210 00:14:30,400 --> 00:14:33,920 Speaker 2: and it was we saw this in COVID. In fact, 211 00:14:33,960 --> 00:14:38,320 Speaker 2: we think what has happened. We had sort of the 212 00:14:38,360 --> 00:14:42,840 Speaker 2: warm up in COVID and its aftermath in twenty twenty 213 00:14:42,840 --> 00:14:48,160 Speaker 2: and early twenty one. During COVID, the market it was 214 00:14:48,280 --> 00:14:51,440 Speaker 2: just one month when we realized, oh my gosh, this 215 00:14:51,880 --> 00:14:54,800 Speaker 2: is a disaster. This is going to shut down the world. 216 00:14:55,680 --> 00:15:01,760 Speaker 2: In the one month after that realization, we had the markets, 217 00:15:01,800 --> 00:15:05,720 Speaker 2: depending on which measure you use, down twenty to twenty 218 00:15:05,720 --> 00:15:09,480 Speaker 2: five percent, and we were down forty percent. And we 219 00:15:09,560 --> 00:15:13,080 Speaker 2: were back then saying, wait a minute, this is these 220 00:15:13,080 --> 00:15:16,760 Speaker 2: are nothing but algorithms are making these judgment calls. They're 221 00:15:17,320 --> 00:15:22,240 Speaker 2: using only two variables. The variables are cash cushion and 222 00:15:22,400 --> 00:15:26,240 Speaker 2: cash burn. And the lower the cushion and the higher 223 00:15:26,280 --> 00:15:28,760 Speaker 2: the burn, the worse the stock. 224 00:15:29,120 --> 00:15:31,720 Speaker 1: Doesn't that make sense? In a rising interest rate environment. 225 00:15:32,000 --> 00:15:35,360 Speaker 2: Well no, now I'm talking about back then, and we'll 226 00:15:35,360 --> 00:15:39,480 Speaker 2: get to ORC. So I'm talking about when interest rates 227 00:15:39,520 --> 00:15:44,320 Speaker 2: are collapsing in COVID. And we were saying, back then, 228 00:15:45,960 --> 00:15:49,800 Speaker 2: wait a minute this Who do you think is going 229 00:15:49,840 --> 00:15:53,440 Speaker 2: to sequence the virus, Who's going to create the test 230 00:15:53,560 --> 00:15:57,800 Speaker 2: with synthetic biology, who's going to create a vaccine, Who's 231 00:15:57,840 --> 00:16:00,680 Speaker 2: going to solve this problem? Our companies are why are 232 00:16:00,760 --> 00:16:03,920 Speaker 2: you selling those off? And of course what happened then 233 00:16:04,160 --> 00:16:09,800 Speaker 2: was we had a massive turnaround with the multiomic stocks 234 00:16:10,680 --> 00:16:17,320 Speaker 2: being the biggest winners, and and our flagship, which had 235 00:16:17,360 --> 00:16:21,120 Speaker 2: a good smattering of them, up three hundred and sixty percent. 236 00:16:21,160 --> 00:16:23,880 Speaker 2: So it went down forty six percent in one month, 237 00:16:23,920 --> 00:16:27,680 Speaker 2: and it went up three hundred and sixty percent in 238 00:16:27,760 --> 00:16:30,920 Speaker 2: the next tend to eleven months. And you know, toward 239 00:16:30,960 --> 00:16:33,160 Speaker 2: the end of that, we were saying, you know, hold 240 00:16:33,240 --> 00:16:35,840 Speaker 2: your hold some powder dry. You know this is and 241 00:16:35,960 --> 00:16:38,120 Speaker 2: I was telling our team here, I said, there's not 242 00:16:38,240 --> 00:16:44,160 Speaker 2: the real world. You know, when when a market decides 243 00:16:44,200 --> 00:16:47,840 Speaker 2: that anyone can do no wrong, any strategy can do 244 00:16:48,000 --> 00:16:50,880 Speaker 2: no no wrong, it's usually the end for that strategy. 245 00:16:51,280 --> 00:16:54,479 Speaker 2: So we were prepared for a correction, and I definitely 246 00:16:55,400 --> 00:17:00,160 Speaker 2: prepared our team here from their own financial point of 247 00:17:00,200 --> 00:17:06,240 Speaker 2: you just you know, hunker down and keep some powder dry. 248 00:17:07,560 --> 00:17:13,119 Speaker 2: I think that period that I just describe was a 249 00:17:13,160 --> 00:17:19,320 Speaker 2: warm up for the next installment for the last three years, 250 00:17:20,160 --> 00:17:22,399 Speaker 2: and that that equates to the one month period. In 251 00:17:22,440 --> 00:17:25,159 Speaker 2: my mind. For the last three years, it's been the 252 00:17:25,160 --> 00:17:31,840 Speaker 2: same psychology. You know, algorithms they see inflation and interest 253 00:17:31,880 --> 00:17:35,480 Speaker 2: rates up, they make a very I've been in many 254 00:17:35,560 --> 00:17:39,639 Speaker 2: markets where interest rates went up and we blew the 255 00:17:39,720 --> 00:17:43,640 Speaker 2: cover off the ball. Twenty seventeen was a good example. 256 00:17:43,760 --> 00:17:46,919 Speaker 2: Interest rates went up all year, our strategy was up 257 00:17:46,960 --> 00:17:51,280 Speaker 2: eighty seven percent. So but we're in a market right 258 00:17:51,359 --> 00:17:59,240 Speaker 2: now completely controlled by algorithms and they make very simple 259 00:17:59,760 --> 00:18:05,520 Speaker 2: ever calls AI. It's just a simple algorithm and you 260 00:18:05,600 --> 00:18:08,800 Speaker 2: can see it at work. The same thing happened to 261 00:18:08,840 --> 00:18:12,560 Speaker 2: our strategy has happened in that one month period. It 262 00:18:12,960 --> 00:18:19,920 Speaker 2: was destroyed as many investors decided to sell our stocks, 263 00:18:19,960 --> 00:18:23,120 Speaker 2: which are not in benchmarks. For the most part, Tesla 264 00:18:23,280 --> 00:18:27,719 Speaker 2: is now, but for most of our existence it was not. 265 00:18:28,280 --> 00:18:30,399 Speaker 2: But most of the stocks in our portfolio are not 266 00:18:30,480 --> 00:18:34,480 Speaker 2: in the broad based benchmarks, and so portfolio managers who 267 00:18:34,720 --> 00:18:41,520 Speaker 2: are graded by benchmarks, whereas we're benchmark agnostic. They in 268 00:18:41,560 --> 00:18:44,679 Speaker 2: a risk off period, just hug their benchmarks. They look 269 00:18:44,800 --> 00:18:48,119 Speaker 2: very much like their benchmarks. And large cap growth managers 270 00:18:48,440 --> 00:18:50,800 Speaker 2: look very much like one another these days. 271 00:18:50,840 --> 00:18:53,080 Speaker 1: And you have an active chef pushing one hundred percent, 272 00:18:53,119 --> 00:18:53,439 Speaker 1: don't you? 273 00:18:54,160 --> 00:18:59,119 Speaker 2: Yes, we do. And I think I think well, I 274 00:18:59,160 --> 00:19:01,720 Speaker 2: always say to our truth will win out. I am 275 00:19:02,119 --> 00:19:06,840 Speaker 2: much more comfortable now than I was in early twenty one. 276 00:19:07,000 --> 00:19:10,960 Speaker 2: Early twenty one, I was saying, watch out now that 277 00:19:11,320 --> 00:19:15,480 Speaker 2: nobody thinks we can do anything. Right, I feel much 278 00:19:15,480 --> 00:19:19,760 Speaker 2: more comfortable. Expectations are low and honestly. 279 00:19:19,400 --> 00:19:24,000 Speaker 1: And valuations are significantly lower, right, And you know are 280 00:19:24,280 --> 00:19:26,480 Speaker 1: but you're not really valuation driven, are you. 281 00:19:26,720 --> 00:19:28,760 Speaker 2: We are if you give us five years, and if 282 00:19:28,760 --> 00:19:30,760 Speaker 2: you give us five years, then we are a deep 283 00:19:30,840 --> 00:19:34,720 Speaker 2: value manager. We're a deep value manager because and I'll 284 00:19:34,720 --> 00:19:36,560 Speaker 2: give you a sense of what I mean by that, 285 00:19:37,640 --> 00:19:40,879 Speaker 2: most people when they do their valuation, they're looking just 286 00:19:40,920 --> 00:19:45,280 Speaker 2: at this year, maybe next year. And on that basis, 287 00:19:45,720 --> 00:19:50,000 Speaker 2: our enterprise value to Ibadah looks higher, is higher than 288 00:19:50,040 --> 00:19:55,280 Speaker 2: the market. Why because our companies are sacrificing short term 289 00:19:55,320 --> 00:19:59,640 Speaker 2: profitability and investing aggressively to capitalize on some of the 290 00:19:59,680 --> 00:20:04,280 Speaker 2: big opportunities and innovation we've ever seen. And so they 291 00:20:04,320 --> 00:20:08,560 Speaker 2: look high now, and what we assume is that in 292 00:20:08,760 --> 00:20:14,639 Speaker 2: five years they will that valuation will compress. It's a 293 00:20:14,720 --> 00:20:18,679 Speaker 2: headwind we're facing for the next five years. Compress to 294 00:20:19,440 --> 00:20:22,359 Speaker 2: a slight premium to the market as opposed to a 295 00:20:22,480 --> 00:20:26,160 Speaker 2: very significant premium to the market. So that's a big headwind. 296 00:20:27,000 --> 00:20:31,880 Speaker 2: And what we must assume therefore, is that the revenue 297 00:20:31,920 --> 00:20:36,280 Speaker 2: growth potential and margin expansion is going to overwhelm that 298 00:20:36,760 --> 00:20:40,359 Speaker 2: to meet our minimum hurdle rate of return, which is 299 00:20:40,400 --> 00:20:44,640 Speaker 2: a fifteen percent compound annual rate of return. Now many 300 00:20:44,840 --> 00:20:49,320 Speaker 2: over five years, now that's minimum. Many people say, well, 301 00:20:49,440 --> 00:20:52,520 Speaker 2: you've underperformed for the last five years. Yes, that is 302 00:20:52,560 --> 00:20:56,600 Speaker 2: absolutely right. And we have also faced a period that 303 00:20:58,359 --> 00:21:01,800 Speaker 2: none of us has ever faced before, for the FED 304 00:21:02,160 --> 00:21:08,359 Speaker 2: jacking up interest rates twenty two twenty threefold not you 305 00:21:08,400 --> 00:21:10,359 Speaker 2: know what I mean that this has never happened before. 306 00:21:10,480 --> 00:21:14,879 Speaker 2: Even in the early eighties, Chairman Vulker took interest rates 307 00:21:14,960 --> 00:21:19,040 Speaker 2: up from ten to twenty percent. That was twofold. This 308 00:21:19,240 --> 00:21:23,160 Speaker 2: was more than ten times the intensity and any long 309 00:21:23,240 --> 00:21:29,080 Speaker 2: duration asset caught in that moment, including long term bonds. 310 00:21:29,119 --> 00:21:33,440 Speaker 2: Long term bonds have had their worst two year period 311 00:21:34,359 --> 00:21:38,399 Speaker 2: since the seventeen hundreds. It's never been this bad in 312 00:21:38,480 --> 00:21:42,840 Speaker 2: anyone's lifetime. Those are long duration assets. Those are the 313 00:21:42,880 --> 00:21:46,520 Speaker 2: flight to safety assets. We're not flight to safety, but 314 00:21:46,600 --> 00:21:50,040 Speaker 2: we are long duration, and so we had a double 315 00:21:50,040 --> 00:21:55,600 Speaker 2: whammy where equities and long duration. So in that environment, 316 00:21:56,440 --> 00:21:59,040 Speaker 2: we were not going to perform in the environment we 317 00:21:59,119 --> 00:22:03,600 Speaker 2: see ahead. If interest rates, if inflation and interest rates 318 00:22:03,640 --> 00:22:06,720 Speaker 2: were the reason, first the fear of interest rates going 319 00:22:06,800 --> 00:22:09,880 Speaker 2: up into twenty twenty one, you know, the market went 320 00:22:09,920 --> 00:22:12,520 Speaker 2: to all time highs, but we were down. And then 321 00:22:12,600 --> 00:22:16,080 Speaker 2: the reality of interest rates going up, so double discounting 322 00:22:16,440 --> 00:22:20,760 Speaker 2: in twenty two and even while we had a very 323 00:22:20,840 --> 00:22:23,760 Speaker 2: nice run through July, you know, we're back in the 324 00:22:23,800 --> 00:22:29,280 Speaker 2: same kind of algorithm driven environment. And that's because the 325 00:22:29,320 --> 00:22:33,199 Speaker 2: Fed's in higher for longer. We think that will break 326 00:22:33,480 --> 00:22:36,760 Speaker 2: when some of the deflation signals that I'm talking about 327 00:22:36,760 --> 00:22:37,240 Speaker 2: come through. 328 00:22:38,240 --> 00:22:40,440 Speaker 1: Okay, so what has happened over the last few years 329 00:22:40,520 --> 00:22:43,600 Speaker 1: doesn't in any way change the way you want to invest, 330 00:22:43,640 --> 00:22:46,560 Speaker 1: the way you do invest, on the strategies you work with. 331 00:22:46,920 --> 00:22:53,480 Speaker 2: No, these are the biggest investment opportunities, the biggest in 332 00:22:53,880 --> 00:22:57,240 Speaker 2: the world. And you know, you have to go back 333 00:22:57,400 --> 00:23:00,159 Speaker 2: and it's interesting that you have to go back to 334 00:23:00,200 --> 00:23:02,560 Speaker 2: this period, but you have to go back to the 335 00:23:02,840 --> 00:23:09,240 Speaker 2: early nineteen hundreds. Another analogy to see multiple innovation platforms 336 00:23:09,280 --> 00:23:14,600 Speaker 2: evolving at the same time. So back then it was telephone, electricity, 337 00:23:15,040 --> 00:23:19,160 Speaker 2: and internal combustion engine and it transformed the world completely. 338 00:23:20,040 --> 00:23:24,080 Speaker 2: Those were three platforms. Now we have five platforms and 339 00:23:24,119 --> 00:23:28,159 Speaker 2: they involve fourteen different technologies. That's why we've set up 340 00:23:28,160 --> 00:23:34,200 Speaker 2: our analyst responsibilities not by sector or industry or sub industry, 341 00:23:34,359 --> 00:23:39,440 Speaker 2: but by technology. So fourteen different technologies that are going 342 00:23:39,520 --> 00:23:43,600 Speaker 2: to converge, we believe, and create explosive growth opportunities. It's 343 00:23:43,680 --> 00:23:48,280 Speaker 2: really interesting to look at all of history and see 344 00:23:48,280 --> 00:23:56,040 Speaker 2: how technology transforms growth dynamics. And so we've been through 345 00:23:56,280 --> 00:23:59,600 Speaker 2: a very long period of linear growth. That's what it 346 00:23:59,600 --> 00:24:03,639 Speaker 2: invests have gotten used to over the years. With the Internet, 347 00:24:03,680 --> 00:24:07,399 Speaker 2: we got a taste of exponential growth at a high level. 348 00:24:07,680 --> 00:24:13,199 Speaker 2: Amazon in twenty to twenty five years grew in the 349 00:24:13,280 --> 00:24:18,760 Speaker 2: twenty to thirty percent range annual annualized over that period. 350 00:24:18,880 --> 00:24:23,359 Speaker 2: Nobody thought that was possible at the beginning, everybody thought, oh, sure, 351 00:24:23,400 --> 00:24:26,520 Speaker 2: you'll have these super growth rates, but they'll decay very 352 00:24:26,600 --> 00:24:30,600 Speaker 2: quickly to nomenal GDP growth. Amazon broke that mold, and 353 00:24:32,119 --> 00:24:35,560 Speaker 2: we think we're going to see a lot of exponential 354 00:24:35,600 --> 00:24:39,080 Speaker 2: growers thanks to these new technologies. But we will also 355 00:24:39,200 --> 00:24:44,000 Speaker 2: see super exponential growth because of the convergence between and 356 00:24:44,080 --> 00:24:50,800 Speaker 2: among technologies. And the best example there is autonomous taxi platforms. 357 00:24:51,080 --> 00:24:55,360 Speaker 2: That opportunity, which we think is an eight to ten 358 00:24:55,520 --> 00:25:00,400 Speaker 2: trillion dollar revenue opportunity in the next five to ten 359 00:25:00,520 --> 00:25:05,720 Speaker 2: years globally, including China. That opportunity is the convergence among 360 00:25:06,000 --> 00:25:07,760 Speaker 2: three of our platforms. 361 00:25:08,680 --> 00:25:10,800 Speaker 1: Can I sorry, Kathy, I want to interrupt you right there, 362 00:25:10,840 --> 00:25:12,359 Speaker 1: just because one thing that I haven't asked you to 363 00:25:12,400 --> 00:25:15,600 Speaker 1: do is divide up the five platforms for us. So 364 00:25:15,640 --> 00:25:17,320 Speaker 1: can I just ask you to tell us a little 365 00:25:17,320 --> 00:25:19,000 Speaker 1: bit about the five platforms, then we'll come back to 366 00:25:19,000 --> 00:25:20,000 Speaker 1: the three platforms. 367 00:25:20,040 --> 00:25:23,120 Speaker 2: Sure, sure, sure, sure, Okay, So the platforms, So we'll 368 00:25:23,160 --> 00:25:27,119 Speaker 2: start with Since I gave you the story about sequencing 369 00:25:27,200 --> 00:25:31,840 Speaker 2: costs and how quick they've come down, we think that 370 00:25:33,040 --> 00:25:38,040 Speaker 2: the combination of sequencing and artificial intelligence is going to 371 00:25:38,080 --> 00:25:41,640 Speaker 2: help us diagnose cancer in stage one, if not before 372 00:25:41,840 --> 00:25:46,679 Speaker 2: stage one, and think polyps in colorectal cancer. The body 373 00:25:46,760 --> 00:25:50,760 Speaker 2: sets up for cancer. And so we think that with 374 00:25:51,320 --> 00:25:56,880 Speaker 2: multiomic sequencing and artificial intelligence, we're going to diagnose cancer 375 00:25:56,960 --> 00:26:02,000 Speaker 2: and other diseases very early, and then with other technologies 376 00:26:02,160 --> 00:26:06,919 Speaker 2: like Chrisper gene editing, we'll be able to edit those 377 00:26:07,280 --> 00:26:11,000 Speaker 2: those mutations when when we find a mutation, now that 378 00:26:11,080 --> 00:26:16,280 Speaker 2: we can with these sequencing technologies, when we find a mutation, 379 00:26:16,640 --> 00:26:20,520 Speaker 2: which is a programming error, and we have more programming 380 00:26:20,600 --> 00:26:23,760 Speaker 2: errors the older we get when we find a mutation, 381 00:26:24,880 --> 00:26:29,280 Speaker 2: we believe that Chrisper gene editing is going to help 382 00:26:29,440 --> 00:26:34,719 Speaker 2: reprogram the genome and and cure disease. We're already seeing 383 00:26:34,760 --> 00:26:39,640 Speaker 2: this in sickle cell disease beta thalasmia a T t R. 384 00:26:40,800 --> 00:26:45,400 Speaker 2: One of our companies, Christmer Therapeutics. It's UH, it's going 385 00:26:45,480 --> 00:26:53,200 Speaker 2: to it's going to be UH getting a recommendation today 386 00:26:53,440 --> 00:26:59,080 Speaker 2: to the f D A UH to approve it or not, 387 00:26:59,240 --> 00:27:03,320 Speaker 2: and it's up to the But the safety profile has 388 00:27:03,359 --> 00:27:11,399 Speaker 2: been phenomenal and sickle cell disease has been uncurable up 389 00:27:11,480 --> 00:27:15,080 Speaker 2: to now, and this is a cure we believe, so 390 00:27:15,320 --> 00:27:20,280 Speaker 2: we'll get that and by the time this podcast comes out, 391 00:27:20,720 --> 00:27:23,880 Speaker 2: you'll have more effect about Christma therapeutics and sickle cell 392 00:27:23,920 --> 00:27:29,560 Speaker 2: disease in terms of the others. So robotics, you know, 393 00:27:29,600 --> 00:27:36,600 Speaker 2: it's interesting. In the early days, I was we were 394 00:27:36,600 --> 00:27:41,879 Speaker 2: thinking about autonomous vehicles away from this robotics idea. But 395 00:27:42,000 --> 00:27:47,760 Speaker 2: autonomous vehicles are robots. Drones are robots, and so our 396 00:27:47,800 --> 00:27:50,879 Speaker 2: life is going to fill up with a lot of robots, 397 00:27:50,920 --> 00:27:56,320 Speaker 2: we believe because the costs are coming down. Industrial robot 398 00:27:56,400 --> 00:27:58,560 Speaker 2: costs we think are coming down to the eleven twelve 399 00:27:58,640 --> 00:28:01,679 Speaker 2: thousand dollars range, which is a fraction of what you 400 00:28:02,080 --> 00:28:05,320 Speaker 2: pay a person. And you know, robots don't take vacations, 401 00:28:05,400 --> 00:28:10,240 Speaker 2: and you know, they don't take breaks. They might, they 402 00:28:10,240 --> 00:28:14,840 Speaker 2: don't complain, and they take away the menial jobs, the 403 00:28:15,080 --> 00:28:18,639 Speaker 2: really boring, mundane jobs. We have labor shortages around the world. 404 00:28:18,640 --> 00:28:22,560 Speaker 2: So this is going to be a huge boon to productivity. 405 00:28:22,840 --> 00:28:28,240 Speaker 2: But robots are going to be controlled by artificial intelligence also, 406 00:28:29,440 --> 00:28:33,920 Speaker 2: So just like I was starting to explain this convergence, 407 00:28:34,440 --> 00:28:40,800 Speaker 2: you'll see in the autonomous taxi network opportunity. You have 408 00:28:40,840 --> 00:28:45,760 Speaker 2: the autonomous taxis, they are robots. They will be electric too, 409 00:28:46,600 --> 00:28:51,680 Speaker 2: cheaper better cars in the next few years, and they'll 410 00:28:51,720 --> 00:28:56,400 Speaker 2: be controlled by artificial intelligence. All of robots are going 411 00:28:56,480 --> 00:29:00,040 Speaker 2: to fit that bill. So it's interesting to see the 412 00:29:00,160 --> 00:29:04,000 Speaker 2: convergence among these technologies as we you know, think about 413 00:29:04,040 --> 00:29:06,040 Speaker 2: them separately and say, well, wait a minute, we need 414 00:29:06,080 --> 00:29:12,160 Speaker 2: this one to make that happen, or so it's multiomic sequencing, robotics, 415 00:29:12,560 --> 00:29:15,720 Speaker 2: energy storage. We do think by the end of this decade, 416 00:29:15,920 --> 00:29:20,240 Speaker 2: practically all vehicle sales will be electric. And you know 417 00:29:20,320 --> 00:29:23,400 Speaker 2: that's saying quite something given that most of the traditional 418 00:29:23,440 --> 00:29:29,080 Speaker 2: auto manufacturers right now about ninety percent of their sales 419 00:29:29,160 --> 00:29:33,920 Speaker 2: are internal combustion engine cars except in China, and China 420 00:29:34,920 --> 00:29:38,880 Speaker 2: it's much lower. They're moving much faster into electric, which 421 00:29:38,920 --> 00:29:43,400 Speaker 2: is interesting. I mentioned AI, and I'll tell you why 422 00:29:43,520 --> 00:29:48,280 Speaker 2: AI is the catalyst to all of these other technologies. 423 00:29:48,840 --> 00:29:53,960 Speaker 2: It's because AI training costs. The cost to train these 424 00:29:55,200 --> 00:30:02,080 Speaker 2: AIS is dropping seventy percent per year year, and when 425 00:30:02,120 --> 00:30:06,360 Speaker 2: you see the cost of anything dropping seventy percent per year, 426 00:30:06,800 --> 00:30:08,880 Speaker 2: you know that we're going to do more of it 427 00:30:09,000 --> 00:30:13,520 Speaker 2: over time, and that it's probably going to converge with 428 00:30:13,720 --> 00:30:17,200 Speaker 2: all of these other technologies. It's pretty exciting. We've never 429 00:30:17,240 --> 00:30:19,520 Speaker 2: been in a more fertile time for innovation. 430 00:30:20,480 --> 00:30:23,520 Speaker 1: Huh. So when you look at these five platforms, you 431 00:30:23,640 --> 00:30:27,080 Speaker 1: talk about them all converging, But is there any particular 432 00:30:27,200 --> 00:30:30,040 Speaker 1: one of them that is the one you're most excited about. 433 00:30:30,120 --> 00:30:32,800 Speaker 1: We had to choose one to one of your ETFs, 434 00:30:32,800 --> 00:30:35,240 Speaker 1: for example, to invest in, what is the one that 435 00:30:35,280 --> 00:30:38,520 Speaker 1: makes you most excited about it? It's life changing capacity 436 00:30:38,560 --> 00:30:42,000 Speaker 1: for us, and it's a financial capacity for investing. 437 00:30:42,480 --> 00:30:46,120 Speaker 2: We're excited about all of them. The most life changing, 438 00:30:46,160 --> 00:30:50,880 Speaker 2: to use your word, is curing disease once we understand 439 00:30:50,960 --> 00:30:54,800 Speaker 2: the genome. I mean, I don't think that many people 440 00:30:54,880 --> 00:31:00,080 Speaker 2: understand how much of medicine until now has been guesswork. 441 00:31:01,400 --> 00:31:04,920 Speaker 2: We couldn't find the mutations. It was way too expensive 442 00:31:05,000 --> 00:31:10,160 Speaker 2: to sequence a genome. Now you and I are going 443 00:31:10,200 --> 00:31:15,440 Speaker 2: to get our genome sequenced. I'm going to say when 444 00:31:15,480 --> 00:31:18,200 Speaker 2: we get our geneticis that these are all new fields 445 00:31:18,320 --> 00:31:21,640 Speaker 2: every one to two years, because we'll want to know 446 00:31:21,800 --> 00:31:25,640 Speaker 2: as we age, okay, what's mutating and is there a 447 00:31:25,680 --> 00:31:28,400 Speaker 2: therapy out there or is there an edit out there 448 00:31:28,880 --> 00:31:32,920 Speaker 2: that can prevent this disease from progressing and actually reverse it. 449 00:31:34,520 --> 00:31:36,640 Speaker 2: So I think that's going to be the most life 450 00:31:36,760 --> 00:31:44,160 Speaker 2: changing in terms of the biggest revenue opportunity. So this 451 00:31:44,200 --> 00:31:49,280 Speaker 2: is more financial. It is the autonomous taxi platform opportunities. 452 00:31:49,400 --> 00:31:53,800 Speaker 2: So we think the entire opportunity is eight to ten 453 00:31:54,000 --> 00:31:58,320 Speaker 2: trillion dollars in revenue by the turn of the decade, 454 00:31:58,480 --> 00:32:01,800 Speaker 2: in and around the turn of the decade, and we 455 00:32:01,920 --> 00:32:06,280 Speaker 2: believe that half of that will go to the platform companies. 456 00:32:06,440 --> 00:32:09,920 Speaker 2: We think Tesla's going to be one of the platform companies. 457 00:32:10,040 --> 00:32:16,000 Speaker 2: It has collected more real world driving data then I 458 00:32:16,040 --> 00:32:21,320 Speaker 2: would say all other companies around the world combined, because 459 00:32:21,360 --> 00:32:23,680 Speaker 2: it has had this focus on it and now it 460 00:32:23,720 --> 00:32:27,000 Speaker 2: has five million robots out there. I have two of them, 461 00:32:27,040 --> 00:32:31,440 Speaker 2: a Model three and a Model Y, collecting data on 462 00:32:31,520 --> 00:32:35,400 Speaker 2: different streets as I'm driving around and my children are 463 00:32:35,960 --> 00:32:39,840 Speaker 2: driving around. So and because it has all that data, 464 00:32:39,880 --> 00:32:42,080 Speaker 2: it doesn't need all that data. It's not the data 465 00:32:42,160 --> 00:32:46,040 Speaker 2: in and of itself. They have more corner cases. Corner 466 00:32:46,040 --> 00:32:48,840 Speaker 2: cases are okay, what could go wrong? They have more 467 00:32:48,920 --> 00:32:52,560 Speaker 2: corner cases around the world than any other company in 468 00:32:52,680 --> 00:32:54,960 Speaker 2: order to train their cars. 469 00:32:55,520 --> 00:32:58,320 Speaker 1: So as you drive your Tesla, you're gathering data for 470 00:32:58,720 --> 00:33:01,280 Speaker 1: Tesla's future and. 471 00:33:01,200 --> 00:33:03,800 Speaker 2: Sending it back every day, collecting it and you know 472 00:33:03,880 --> 00:33:07,360 Speaker 2: the other thing that's going on this is how provocative 473 00:33:07,400 --> 00:33:11,560 Speaker 2: this new world is. Now. I got my Model three 474 00:33:12,200 --> 00:33:15,600 Speaker 2: in twenty eighteen. I've never had to take it in 475 00:33:15,680 --> 00:33:18,800 Speaker 2: for maintenance. Ever. The only thing I had to do, 476 00:33:18,880 --> 00:33:20,959 Speaker 2: and this had nothing to do with Tesla, is I 477 00:33:20,960 --> 00:33:22,920 Speaker 2: got a nail and a tire and you just can't 478 00:33:22,960 --> 00:33:26,560 Speaker 2: fix that with a software update, you know. But Tesla 479 00:33:26,640 --> 00:33:32,560 Speaker 2: basically anticipates. You know, Tesla does diagnostics on all its 480 00:33:32,600 --> 00:33:36,360 Speaker 2: cars out there, and when it sees something going wrong, 481 00:33:36,640 --> 00:33:40,640 Speaker 2: it fixes it over the air software. So it's a 482 00:33:40,680 --> 00:33:44,320 Speaker 2: really powerful technology and that's why all cars will be 483 00:33:44,400 --> 00:33:48,480 Speaker 2: electric and we think autonomous in the next five to 484 00:33:48,560 --> 00:33:55,000 Speaker 2: ten years. And you're very happy with your holding in Tesla, yes, no, no, 485 00:33:55,560 --> 00:33:59,520 Speaker 2: you know Tesla. We've owned it from the beginning and 486 00:33:59,840 --> 00:34:04,240 Speaker 2: it goes through wild swings and you'll notice when it's 487 00:34:04,600 --> 00:34:10,040 Speaker 2: up a lot and has increased significantly relative to other 488 00:34:10,080 --> 00:34:15,080 Speaker 2: stocks in our portfolio, we will sell some and redeploy 489 00:34:15,280 --> 00:34:19,000 Speaker 2: into stocks that have either been hit by some very 490 00:34:19,040 --> 00:34:24,839 Speaker 2: short term concern or you know, have just performed significantly 491 00:34:24,920 --> 00:34:29,440 Speaker 2: relative to Tesla for some other reason. And likewise, when 492 00:34:29,880 --> 00:34:33,120 Speaker 2: it gets hit we tend to buy it. So but 493 00:34:33,200 --> 00:34:36,160 Speaker 2: it's staying right up near in the top two to 494 00:34:36,239 --> 00:34:39,200 Speaker 2: three names of the portfolio because it is in the 495 00:34:39,239 --> 00:34:43,120 Speaker 2: pole position for this opportunity. And you know, we know 496 00:34:43,320 --> 00:34:46,440 Speaker 2: that next year twenty twenty four, as they launch the 497 00:34:46,480 --> 00:34:51,320 Speaker 2: cyber truck, it's not going to be profitable and it's 498 00:34:51,400 --> 00:34:54,279 Speaker 2: a scaling issue. Just like Model three, there was a 499 00:34:54,320 --> 00:34:59,719 Speaker 2: big controversy around it, and we know they're probably the 500 00:35:00,000 --> 00:35:03,680 Speaker 2: parisons are not going to look that good. But I 501 00:35:03,719 --> 00:35:06,640 Speaker 2: think a couple of things will happen. People when they 502 00:35:06,719 --> 00:35:10,799 Speaker 2: see the cyber truck, and November thirtieth is when they're 503 00:35:10,840 --> 00:35:15,600 Speaker 2: going to debut it, they see it, I think people 504 00:35:15,640 --> 00:35:19,320 Speaker 2: are going to get very excited about the next big 505 00:35:19,440 --> 00:35:23,080 Speaker 2: leg for Tesla. The truck market here in the United 506 00:35:23,080 --> 00:35:26,400 Speaker 2: States is the largest and most profitable market, so that's 507 00:35:26,480 --> 00:35:29,720 Speaker 2: one thing, so you'll get a little bit of excitement 508 00:35:29,760 --> 00:35:33,720 Speaker 2: around that. Nonetheless, we are going to have to live 509 00:35:33,880 --> 00:35:38,759 Speaker 2: through or navigate through a volatile period. Whenever Tesla is 510 00:35:38,880 --> 00:35:42,239 Speaker 2: setting up to do anything, there's usually a lot of 511 00:35:42,280 --> 00:35:45,399 Speaker 2: controversy around it. So controversy around the cyber truck how 512 00:35:45,719 --> 00:35:51,319 Speaker 2: well it will sell or how complicated it will be 513 00:35:51,680 --> 00:35:55,279 Speaker 2: to scale. And the other one is autonomous. You saw 514 00:35:55,600 --> 00:36:01,360 Speaker 2: Cruz Automation has basically taken all all of its autonomous 515 00:36:01,400 --> 00:36:05,960 Speaker 2: cars off the road as autonomous cars now they have 516 00:36:06,040 --> 00:36:09,680 Speaker 2: to be there has to be a safety driver inside 517 00:36:09,960 --> 00:36:13,080 Speaker 2: the car, right behind the wheel. Okay, that dings the 518 00:36:13,120 --> 00:36:17,840 Speaker 2: autonomous probabilities in many people's minds, but not in our mind. 519 00:36:18,040 --> 00:36:23,759 Speaker 2: We think transportation is going autonomous. We you know, we 520 00:36:23,880 --> 00:36:29,399 Speaker 2: listen to Deer and Caterpillar. They're going autonomous. Airplanes are 521 00:36:29,480 --> 00:36:33,279 Speaker 2: practically autonomous. Now we've been moving in this direction for 522 00:36:33,320 --> 00:36:36,120 Speaker 2: a very very long period of time, and the biggest 523 00:36:36,200 --> 00:36:39,359 Speaker 2: question is, okay, what about that last mile? You know, 524 00:36:39,680 --> 00:36:44,680 Speaker 2: are you At one point Elon Musk said impossible. Impossible 525 00:36:45,120 --> 00:36:49,040 Speaker 2: now And we talked to many AI experts and one 526 00:36:49,040 --> 00:36:52,440 Speaker 2: of the main questions we ask is do you believe 527 00:36:52,600 --> 00:36:55,560 Speaker 2: that there will ever be a fully autonomous service? And 528 00:36:56,840 --> 00:36:59,560 Speaker 2: to a person they say yes. 529 00:37:00,040 --> 00:37:01,040 Speaker 1: Well kind of timescale. 530 00:37:02,560 --> 00:37:05,040 Speaker 2: Well, you know, I think they agree with us because 531 00:37:05,040 --> 00:37:08,360 Speaker 2: the breakthroughs in AI are happening so quickly, and that's 532 00:37:08,480 --> 00:37:12,520 Speaker 2: their world. So there's an irony here. The breakthroughs in 533 00:37:12,600 --> 00:37:18,600 Speaker 2: AI are happening very quickly, and Tesla needs them in 534 00:37:18,840 --> 00:37:22,320 Speaker 2: order to reach or to get the last mile done. 535 00:37:22,719 --> 00:37:27,319 Speaker 2: But it didn't know and we didn't know that we 536 00:37:27,400 --> 00:37:32,920 Speaker 2: needed these kinds of breakthroughs in AI to make autonomous possible. 537 00:37:33,000 --> 00:37:35,800 Speaker 2: So that, you know, we have to be very honest 538 00:37:36,120 --> 00:37:40,680 Speaker 2: ourselves about that. Elon's been predicting fully autonomous for maybe 539 00:37:40,760 --> 00:37:43,560 Speaker 2: the last three or four years. Of course, that's very Elon. 540 00:37:43,719 --> 00:37:47,440 Speaker 2: He's driving the company towards that. That's how he motivates 541 00:37:47,480 --> 00:37:51,160 Speaker 2: his employees and gets his suppliers ready and so forth. 542 00:37:51,200 --> 00:37:55,239 Speaker 2: But you know, when we talked to him, he's basically saying, yeah, 543 00:37:55,239 --> 00:37:58,759 Speaker 2: you're right, this is it is a tough problem. And 544 00:37:59,520 --> 00:38:06,480 Speaker 2: because of the regulatory concerns, the autonomous vehicles can't just 545 00:38:06,560 --> 00:38:08,680 Speaker 2: be better than human beings. 546 00:38:09,040 --> 00:38:12,680 Speaker 1: I have to be perfect. Really, No, not really. 547 00:38:12,800 --> 00:38:15,000 Speaker 2: When you think in the US we have forty five 548 00:38:15,080 --> 00:38:18,480 Speaker 2: thousand fatalities in cars per year, and I think around 549 00:38:18,480 --> 00:38:22,160 Speaker 2: the world it's one point two five million, eighty to 550 00:38:22,239 --> 00:38:25,400 Speaker 2: eighty five percent of them are caused by human error. 551 00:38:25,760 --> 00:38:27,480 Speaker 1: So there's a room for a little AI era. 552 00:38:29,040 --> 00:38:32,120 Speaker 2: Well, there will, there will be, and it probably will 553 00:38:32,160 --> 00:38:36,400 Speaker 2: be less AI error than pedestrian error. 554 00:38:36,520 --> 00:38:38,880 Speaker 1: But I wanted to ask you about the space sector 555 00:38:39,160 --> 00:38:41,799 Speaker 1: because I know you're interested in space exploration, innovation, etc. 556 00:38:42,080 --> 00:38:43,399 Speaker 1: I wonder if you tell us a little bit about where 557 00:38:43,400 --> 00:38:44,600 Speaker 1: you see the opportunities there. 558 00:38:45,000 --> 00:38:48,880 Speaker 2: Sure, there are two major opportunities. A lot of people 559 00:38:48,920 --> 00:38:53,040 Speaker 2: think of space tourism. We really don't. That's to us 560 00:38:54,520 --> 00:38:57,120 Speaker 2: not a big opportunity in the short term. But there 561 00:38:57,200 --> 00:39:03,280 Speaker 2: are two opportunities that are quite big. One is connectivity. 562 00:39:03,560 --> 00:39:06,880 Speaker 2: So two and a half to three billion people around 563 00:39:06,880 --> 00:39:10,719 Speaker 2: the world do not have access to the Internet. Now 564 00:39:10,800 --> 00:39:14,160 Speaker 2: is starlink throwing up? I think it's five thousand satellites, 565 00:39:14,440 --> 00:39:17,560 Speaker 2: close to five thousand satellites. We're getting closer and closer 566 00:39:17,600 --> 00:39:21,120 Speaker 2: to the time when there will be connectivity around the world, 567 00:39:21,200 --> 00:39:27,160 Speaker 2: including in the rural areas of the US and the UK, Europe. 568 00:39:28,040 --> 00:39:33,240 Speaker 2: Really the entire world that we believe is an eighty 569 00:39:33,320 --> 00:39:39,400 Speaker 2: billion dollar opportunity if you also count if you also 570 00:39:39,520 --> 00:39:47,120 Speaker 2: count the seas, you know, marine and RV, the r 571 00:39:47,200 --> 00:39:53,520 Speaker 2: V vehicles that people travel around countries in boats, ships 572 00:39:53,560 --> 00:39:58,279 Speaker 2: and so forth. So that's eighty billion. Then if the 573 00:39:58,360 --> 00:40:03,719 Speaker 2: second one is hypersonic flight, and that is getting us 574 00:40:03,840 --> 00:40:10,880 Speaker 2: from let's just say New York City to Sydney, Australia 575 00:40:11,560 --> 00:40:17,080 Speaker 2: in two to three hours instead of twenty two hours, 576 00:40:17,120 --> 00:40:21,520 Speaker 2: and we think that, using very conservative assumptions, is a 577 00:40:21,520 --> 00:40:25,600 Speaker 2: two hundred and seventy billion dollar revenue opportunity. The way 578 00:40:25,920 --> 00:40:28,919 Speaker 2: we got to that number in a piece we put 579 00:40:28,960 --> 00:40:32,799 Speaker 2: out called Big Ideas twenty twenty three. We do a 580 00:40:32,840 --> 00:40:36,040 Speaker 2: Big Ideas every year, and so you can see how 581 00:40:36,080 --> 00:40:40,480 Speaker 2: these Big ideas have evolved. We started it in twenty seventeen, 582 00:40:40,560 --> 00:40:43,440 Speaker 2: so we've got five years worth right now, and you 583 00:40:43,480 --> 00:40:47,600 Speaker 2: can see how right and how wrong we've been. You know, 584 00:40:47,680 --> 00:40:53,279 Speaker 2: these are big ideas. And when you get a pandemic 585 00:40:53,520 --> 00:40:59,000 Speaker 2: and a recession, and a recession and very tight monetary 586 00:40:59,040 --> 00:41:04,360 Speaker 2: policy slowing things down because our modeling is based on units, 587 00:41:05,320 --> 00:41:09,359 Speaker 2: the units of these new technologies scaling, when we get 588 00:41:09,400 --> 00:41:14,360 Speaker 2: into a recession or a pandemic, that interrupts the trend. 589 00:41:14,520 --> 00:41:17,319 Speaker 2: But just to give you a sense, and I know 590 00:41:17,360 --> 00:41:19,680 Speaker 2: you asked about space, those are the two big ideas. 591 00:41:19,880 --> 00:41:22,879 Speaker 2: But I just want to if someone wants to look 592 00:41:23,000 --> 00:41:28,720 Speaker 2: up our track record here in twenty seventeen, we thought 593 00:41:28,719 --> 00:41:31,759 Speaker 2: by twenty twenty two, so five year forecast, that the 594 00:41:31,880 --> 00:41:37,280 Speaker 2: electric vehicle opportunity would be something like seventeen million units. Now, 595 00:41:37,480 --> 00:41:42,879 Speaker 2: the traditional forecasters had something like it wasn't even two 596 00:41:42,920 --> 00:41:49,600 Speaker 2: million units. And the right answer, given the pandemic which 597 00:41:49,600 --> 00:41:54,040 Speaker 2: slowed it all slowed our forecast up was eight million. 598 00:41:54,600 --> 00:41:58,120 Speaker 2: And of course Tesla took off during that time period. 599 00:41:58,280 --> 00:42:00,680 Speaker 2: So who was more right and who was more wrong? 600 00:42:01,600 --> 00:42:05,319 Speaker 2: The behavior or the action of Tesla would tell you 601 00:42:05,400 --> 00:42:08,719 Speaker 2: we were close to the mark. This this electric the 602 00:42:09,200 --> 00:42:14,600 Speaker 2: consumer preference for electric vehicles has occurred and it is accelerating. 603 00:42:14,800 --> 00:42:17,160 Speaker 2: So that's the kind of thing you'll see in the 604 00:42:17,200 --> 00:42:17,760 Speaker 2: track record. 605 00:42:18,160 --> 00:42:20,399 Speaker 1: I don't have an electric car yet, but I must 606 00:42:20,400 --> 00:42:21,840 Speaker 1: get round to that. But I always worry about the 607 00:42:21,880 --> 00:42:24,840 Speaker 1: infrastructure I or about charging points. I worry about getting 608 00:42:25,680 --> 00:42:28,160 Speaker 1: anxiety about how far I can go, all these things 609 00:42:28,200 --> 00:42:31,160 Speaker 1: that I think pull people back. Particularly I don't know 610 00:42:31,200 --> 00:42:33,120 Speaker 1: about in the US, but certainly in the UK we 611 00:42:33,160 --> 00:42:37,040 Speaker 1: have very limited infrastructure for charging and that is beginning 612 00:42:37,040 --> 00:42:39,360 Speaker 1: to put a lead on demand for evs. 613 00:42:39,920 --> 00:42:42,880 Speaker 2: Yeah, that we understand, and that is why a lot 614 00:42:42,920 --> 00:42:46,759 Speaker 2: of a lot of auto manufacturers are now signing on 615 00:42:46,840 --> 00:42:52,000 Speaker 2: to Tesla's charging standard, and we think I think it's 616 00:42:52,040 --> 00:42:54,879 Speaker 2: beginning to happen in the UK, is it, I'm not 617 00:42:55,000 --> 00:42:56,960 Speaker 2: quite sure. I know in the US there's been one 618 00:42:56,960 --> 00:43:01,600 Speaker 2: announcement after another, and not just US auto companies, but 619 00:43:01,680 --> 00:43:05,360 Speaker 2: also foreigner auto companies signing on to Tesla's charging standard. 620 00:43:07,040 --> 00:43:09,200 Speaker 1: A lot, a lot of the people listening will be 621 00:43:09,239 --> 00:43:12,080 Speaker 1: thinking to themselves, you know, there's that We've seen some 622 00:43:12,160 --> 00:43:14,319 Speaker 1: of the big companies that you've talked about. We've seen 623 00:43:14,360 --> 00:43:16,440 Speaker 1: them start small, we've seen them grow, you've seen them 624 00:43:16,800 --> 00:43:18,960 Speaker 1: week the top ten in your portfolio, et cetera. But 625 00:43:19,160 --> 00:43:23,440 Speaker 1: are there any small companies knocking around that we might 626 00:43:23,480 --> 00:43:25,920 Speaker 1: not have heard of yet that are of extraordinary interest 627 00:43:26,000 --> 00:43:26,359 Speaker 1: to you? 628 00:43:27,000 --> 00:43:35,200 Speaker 2: Yes, well, i'll future one. Pacific Biosciences, So pack what's 629 00:43:35,239 --> 00:43:40,160 Speaker 2: fascinating about pac Bio. I've watched Christian Henry, who's the CEO, 630 00:43:40,520 --> 00:43:46,920 Speaker 2: since he was at Illumina. Ilumina is pac Bio's biggest competitor, 631 00:43:47,640 --> 00:43:54,840 Speaker 2: and so they are both sequencing companies. Illumina really became 632 00:43:55,320 --> 00:43:59,600 Speaker 2: the leader in short read sequencing, and the reason it 633 00:43:59,719 --> 00:44:04,800 Speaker 2: chose this short read sequencing is it was lower cost 634 00:44:05,320 --> 00:44:11,640 Speaker 2: and evolving more quickly than long read sequencing. Long read sequencing, 635 00:44:12,880 --> 00:44:18,920 Speaker 2: basically looking at longer stretches of your DNA, RNA and 636 00:44:18,920 --> 00:44:26,319 Speaker 2: so forth, is more accurate, reliable, and comprehensive. But it 637 00:44:26,360 --> 00:44:29,600 Speaker 2: was just too expensive for so long. Illumina made a 638 00:44:29,680 --> 00:44:33,799 Speaker 2: terrible mistake by keeping its genome price for about four 639 00:44:33,880 --> 00:44:37,439 Speaker 2: or five years at one thousand dollars per giving pac 640 00:44:37,520 --> 00:44:41,360 Speaker 2: Bio a chance to catch up with its long read technology. 641 00:44:41,400 --> 00:44:45,040 Speaker 2: And these stocks are being trashed by the market right 642 00:44:45,080 --> 00:44:49,160 Speaker 2: now because they are still an investment stage. We are 643 00:44:49,200 --> 00:44:53,000 Speaker 2: in an early stage for these new technologies, and as 644 00:44:53,040 --> 00:44:56,319 Speaker 2: I mentioned earlier, the ramifications are going to be profound. 645 00:44:56,880 --> 00:45:02,480 Speaker 2: So we have been watching the talent leave Alumina for 646 00:45:02,880 --> 00:45:06,240 Speaker 2: pac Bio, and we think it will become the leader, 647 00:45:07,640 --> 00:45:11,120 Speaker 2: and that means it will grow in revenue to more 648 00:45:11,160 --> 00:45:15,040 Speaker 2: than ten times its size, and we think it will 649 00:45:15,080 --> 00:45:18,080 Speaker 2: take the line's share of the market because it is 650 00:45:18,160 --> 00:45:24,879 Speaker 2: now using artificial intelligence and sequencing in it's combined them 651 00:45:25,360 --> 00:45:29,040 Speaker 2: in its new machines, and we think is moving the 652 00:45:29,080 --> 00:45:31,879 Speaker 2: market ahead much faster than anyone else right now. 653 00:45:32,520 --> 00:45:34,879 Speaker 1: One thing I noticed that was that you had been 654 00:45:34,880 --> 00:45:38,359 Speaker 1: picking up shares in Kamico, and so I'm wondering about 655 00:45:38,360 --> 00:45:40,560 Speaker 1: your interest in that in uranium and by defaultant in 656 00:45:40,600 --> 00:45:41,320 Speaker 1: neu care energy. 657 00:45:41,800 --> 00:45:47,640 Speaker 2: Yes, it's fascinating. You know, we wrote our first report 658 00:45:47,680 --> 00:45:52,800 Speaker 2: on nuclear Unfortunately, when I was with my old team 659 00:45:53,000 --> 00:45:55,600 Speaker 2: at my previous firm. It was a big black book, 660 00:45:56,000 --> 00:45:58,920 Speaker 2: you know, one hundred and fifty pages, and that was 661 00:45:58,920 --> 00:46:02,880 Speaker 2: twenty ten, and then Fukushima happened in twenty eleven, and 662 00:46:02,960 --> 00:46:06,480 Speaker 2: of course the world turned against nuclear. Now in the book, 663 00:46:06,600 --> 00:46:12,840 Speaker 2: we show it's the safest source of energy and with 664 00:46:12,960 --> 00:46:19,200 Speaker 2: the new modular reactors, the risks associated with radiation have 665 00:46:19,360 --> 00:46:26,000 Speaker 2: dropped tremendously. China is moving aggressively into this space with 666 00:46:26,200 --> 00:46:30,680 Speaker 2: the small modular reactors, and we are now seeing environmental 667 00:46:30,960 --> 00:46:36,440 Speaker 2: lists change their tune about nuclear because they're looking at facts. Again, 668 00:46:36,880 --> 00:46:41,799 Speaker 2: we believe it is the cleanest other than hydro. It 669 00:46:41,840 --> 00:46:46,319 Speaker 2: is the cleanest energy source out there. It is the 670 00:46:46,360 --> 00:46:52,080 Speaker 2: safest when you look at accidents associated with exploring and 671 00:46:52,120 --> 00:46:59,440 Speaker 2: developing for energy. And yes, we think that after years, 672 00:47:00,440 --> 00:47:06,640 Speaker 2: you know, ten twelve years of being denigrated, that environmentalists 673 00:47:06,680 --> 00:47:10,200 Speaker 2: and others are now looking at the facts when it 674 00:47:10,239 --> 00:47:15,760 Speaker 2: comes to nuclear and deciding, you know what, we probably 675 00:47:15,800 --> 00:47:17,040 Speaker 2: weren't right on that one. 676 00:47:16,960 --> 00:47:21,080 Speaker 1: Feels like our only logical way out, doesn't it another 677 00:47:21,080 --> 00:47:23,200 Speaker 1: example of being right just a little early. 678 00:47:24,200 --> 00:47:27,760 Speaker 2: Well, that if we hadn't had Fukushima, and oh my gosh, 679 00:47:27,760 --> 00:47:31,320 Speaker 2: that was terrible and it was tragic and so forth, 680 00:47:31,400 --> 00:47:34,560 Speaker 2: and it did scar a lot of people. But you 681 00:47:34,640 --> 00:47:38,319 Speaker 2: had Japan taking down all its nuclear it's changing its 682 00:47:38,360 --> 00:47:41,839 Speaker 2: mind on that. You had Germany taking down all its 683 00:47:41,960 --> 00:47:45,480 Speaker 2: nuclear and depending on other people's new other countries nuclear. 684 00:47:45,560 --> 00:47:50,959 Speaker 2: So I think yes, the world's coming back in this direction. 685 00:47:52,560 --> 00:47:57,200 Speaker 1: Now. Recently started talking about explanding into Europe, and you've 686 00:47:57,520 --> 00:48:00,640 Speaker 1: built Rise and I was wondering if you see anything 687 00:48:00,640 --> 00:48:02,440 Speaker 1: to be excited by in the UK. We've had our 688 00:48:02,480 --> 00:48:05,680 Speaker 1: stop mugs had a pretty torrid time recently, and a 689 00:48:05,680 --> 00:48:08,080 Speaker 1: lot of people look at the UK, particularly from the US, 690 00:48:08,120 --> 00:48:10,200 Speaker 1: and say that that's not somewhere I want to be invested. 691 00:48:10,440 --> 00:48:13,120 Speaker 1: Do you see anything anything here that excites you. 692 00:48:13,880 --> 00:48:16,080 Speaker 2: Well, you know, some of the greatest companies in the 693 00:48:16,080 --> 00:48:18,960 Speaker 2: world have come out of the UK. Arm and deep 694 00:48:19,000 --> 00:48:24,880 Speaker 2: Mind both came from the UK. So you've got wonderful DNA, 695 00:48:25,160 --> 00:48:30,800 Speaker 2: certainly from an AI point of view. So we think 696 00:48:31,040 --> 00:48:35,359 Speaker 2: that because the costs associated with artificial intelligence and all 697 00:48:35,400 --> 00:48:40,840 Speaker 2: of our technologies are declining so rapidly that the pace 698 00:48:40,880 --> 00:48:44,680 Speaker 2: of innovation is going to pick up in many countries. 699 00:48:44,719 --> 00:48:47,280 Speaker 2: I mean, I know the US because of Silicon Valley 700 00:48:47,320 --> 00:48:51,880 Speaker 2: had a disproportionate amount of the market cap associated with innovation, 701 00:48:51,960 --> 00:48:54,359 Speaker 2: but we think that's going to change and we want 702 00:48:54,360 --> 00:48:58,359 Speaker 2: to spread our wings more and are bringing in new 703 00:48:58,440 --> 00:49:03,520 Speaker 2: talent to do so. As far as the UK, we 704 00:49:04,440 --> 00:49:07,840 Speaker 2: are not invested in anything now, but as I said 705 00:49:08,080 --> 00:49:13,520 Speaker 2: indirectly through Alphabet, we have deep mind and arm did 706 00:49:13,960 --> 00:49:17,880 Speaker 2: we passed on it just in terms of the expectations, 707 00:49:18,640 --> 00:49:22,920 Speaker 2: we think are a little stretched because of the AI 708 00:49:23,080 --> 00:49:26,600 Speaker 2: quote unquote hype that we've been through. But again, great company. 709 00:49:26,719 --> 00:49:28,880 Speaker 1: There is one question I have to ask you, and 710 00:49:28,960 --> 00:49:31,400 Speaker 1: I think I already know the answer to this question, 711 00:49:31,800 --> 00:49:34,280 Speaker 1: but everybody who comes on the podcast has to answer 712 00:49:34,320 --> 00:49:38,880 Speaker 1: it at the end. No, it's genuinely compulsory, I'm afraid. 713 00:49:39,840 --> 00:49:41,600 Speaker 1: So if I'm going to give you a choice of 714 00:49:41,640 --> 00:49:44,839 Speaker 1: three asset classes, or three assets, should I say, and 715 00:49:44,920 --> 00:49:47,200 Speaker 1: you have to choose one to hold for ten years, 716 00:49:47,800 --> 00:49:50,040 Speaker 1: You're not going to have to think very hard. The 717 00:49:50,160 --> 00:49:57,200 Speaker 1: three are gold, a deposit account, cash deposit account, or bitcoin. 718 00:49:57,760 --> 00:50:04,040 Speaker 2: Bitcoin hands down, hands down, Bitcoin is a hedge against 719 00:50:04,160 --> 00:50:12,360 Speaker 2: both inflation and deflation. Yes, so is gold, but bitcoin 720 00:50:12,560 --> 00:50:16,520 Speaker 2: is digital and if you look at the incremental demand, 721 00:50:16,560 --> 00:50:20,719 Speaker 2: we're going to see gold already has its demand. You know, 722 00:50:20,960 --> 00:50:28,560 Speaker 2: it's happened right. Bitcoin is new and institutions are barely involved, 723 00:50:28,880 --> 00:50:34,200 Speaker 2: and young people would much prefer to hold bitcoin then 724 00:50:34,360 --> 00:50:39,560 Speaker 2: to hold gold. So you know, it's interesting that both 725 00:50:39,560 --> 00:50:46,680 Speaker 2: gold and bitcoin are hedges against deflation, but bitcoin's been 726 00:50:46,680 --> 00:50:48,000 Speaker 2: doing better recently. 727 00:50:48,560 --> 00:50:54,520 Speaker 1: So so genuinely digital gold, digital gold, Cathy, Thank you 728 00:50:54,560 --> 00:50:54,959 Speaker 1: so much