1 00:00:02,520 --> 00:00:07,040 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:21,880 --> 00:00:24,680 Speaker 2: This is Wall Street Week. I'm David Weston, bringing you 3 00:00:24,800 --> 00:00:28,760 Speaker 2: stories of capitalism. For many years, Saudi Arabia has been 4 00:00:28,760 --> 00:00:31,680 Speaker 2: at the center of the world of oil. We travel 5 00:00:31,720 --> 00:00:34,320 Speaker 2: to the kingdom to learn how and why it wants 6 00:00:34,360 --> 00:00:37,600 Speaker 2: to change that. Plus, you saw you knew the world 7 00:00:37,640 --> 00:00:40,559 Speaker 2: of artificial intelligence, but it turns out it comes in 8 00:00:40,600 --> 00:00:44,400 Speaker 2: different flavors with different time horizons. We explore the brave 9 00:00:44,520 --> 00:00:49,800 Speaker 2: new world of mathematical superintelligence and large quantitative models. And 10 00:00:49,920 --> 00:00:52,239 Speaker 2: as we head into the heart of summer, we take 11 00:00:52,280 --> 00:00:55,160 Speaker 2: you to some of the nation's theme parks as traditional 12 00:00:55,200 --> 00:00:58,800 Speaker 2: leaders Disney and Universal are getting some new competition from 13 00:00:59,080 --> 00:01:03,040 Speaker 2: Surprising play. But we start with the Federal Reserve Board 14 00:01:03,080 --> 00:01:06,039 Speaker 2: decision this week and how the Central Bank is grappling 15 00:01:06,040 --> 00:01:08,000 Speaker 2: with all that policy uncertainty. 16 00:01:08,400 --> 00:01:10,160 Speaker 3: The amount of the tariff effects, the size of the 17 00:01:10,200 --> 00:01:12,560 Speaker 3: tariff effects, their duration, and the time it will take 18 00:01:12,560 --> 00:01:16,160 Speaker 3: are all highly uncertain. So that is why we think 19 00:01:16,600 --> 00:01:18,920 Speaker 3: the appropriate thing to do is to hold where we 20 00:01:18,959 --> 00:01:21,760 Speaker 3: are as we learn more, and we think our policy 21 00:01:21,800 --> 00:01:24,160 Speaker 3: stances is in a good place where we're well positioned 22 00:01:24,200 --> 00:01:26,919 Speaker 3: to react to incoming developments. We have to be forward looking, 23 00:01:27,280 --> 00:01:31,000 Speaker 3: and the thing that every forecaster, every outside forecaster, and 24 00:01:31,040 --> 00:01:33,480 Speaker 3: the Fed is saying is that we expect a meaningful 25 00:01:33,920 --> 00:01:36,480 Speaker 3: amount of inflation to arrive in coming months. 26 00:01:37,560 --> 00:01:43,440 Speaker 2: Turning first to our special contributor, Larry Summers of Harvard. So, Larry, 27 00:01:43,440 --> 00:01:46,000 Speaker 2: we heard from the Federal Reserve, the FOMC as well 28 00:01:46,000 --> 00:01:48,520 Speaker 2: as Chair Pale this week. What did you make out 29 00:01:48,560 --> 00:01:51,960 Speaker 2: of what they had to say and particularly their projections. 30 00:01:52,320 --> 00:01:57,120 Speaker 1: I thought what they said was both predictable and reasonable. 31 00:01:57,800 --> 00:02:02,880 Speaker 1: They you can't be changedinging monetary policy with the uncertainty 32 00:02:03,440 --> 00:02:04,200 Speaker 1: that we've. 33 00:02:04,000 --> 00:02:06,280 Speaker 4: Got right now. They were right to. 34 00:02:06,320 --> 00:02:11,240 Speaker 1: Signal that they were being cautious about future changes. What 35 00:02:11,360 --> 00:02:16,840 Speaker 1: struck me most, David, was a quite remarkable combination. The 36 00:02:16,919 --> 00:02:24,320 Speaker 1: dot plot showed unemployment revised upwards, showed inflation revised upwards, 37 00:02:24,919 --> 00:02:28,480 Speaker 1: even a period when we're getting good news about artificial 38 00:02:28,520 --> 00:02:32,480 Speaker 1: intelligence and productivity, and good news about a whale. 39 00:02:33,160 --> 00:02:38,960 Speaker 4: So you see a supply shock coming even though the. 40 00:02:39,040 --> 00:02:42,960 Speaker 1: Natural sources of supply shocks aren't there. 41 00:02:43,800 --> 00:02:46,280 Speaker 4: What is it? It's the tariffs. 42 00:02:46,800 --> 00:02:51,880 Speaker 1: We're imposing a supply shock on ourselves, and that's leading 43 00:02:51,919 --> 00:02:58,080 Speaker 1: to expectations of both higher inflation and higher unemployment making 44 00:02:58,120 --> 00:03:02,560 Speaker 1: the Fed's job that much much more difficult. And the 45 00:03:02,560 --> 00:03:05,280 Speaker 1: Fed's obviously not going to get in a political war 46 00:03:05,919 --> 00:03:07,840 Speaker 1: with the administration. 47 00:03:08,520 --> 00:03:11,800 Speaker 4: But the stark analytic fact is clear. 48 00:03:12,400 --> 00:03:16,079 Speaker 1: It doesn't happen that often that the FED revises up 49 00:03:16,120 --> 00:03:19,760 Speaker 1: on inflation and unemployment at the same time, and I 50 00:03:19,760 --> 00:03:22,960 Speaker 1: don't think there's ever been a time when they revised 51 00:03:23,720 --> 00:03:29,799 Speaker 1: that way in both directions based on administration policy. 52 00:03:30,240 --> 00:03:33,040 Speaker 2: Larry, you mentioned the geopolitical conflict that we're seeing. Certainly 53 00:03:33,280 --> 00:03:36,360 Speaker 2: we have an enormous one between Israel and Iran as 54 00:03:36,400 --> 00:03:39,320 Speaker 2: we speak, with questions about whether the United States might 55 00:03:39,320 --> 00:03:43,040 Speaker 2: get involved. As a macroeconomist, how do you approach that question. 56 00:03:43,760 --> 00:03:47,320 Speaker 4: Look, no one knows. 57 00:03:47,440 --> 00:03:51,120 Speaker 1: I suspect that the President doesn't know completely what he's 58 00:03:51,200 --> 00:03:54,600 Speaker 1: going to do because he is watching. 59 00:03:55,760 --> 00:03:56,200 Speaker 4: Events. 60 00:03:57,120 --> 00:04:00,880 Speaker 1: I'd just say a couple of things, David. One is 61 00:04:00,960 --> 00:04:04,320 Speaker 1: that we got a lot of divisions within our country, 62 00:04:05,040 --> 00:04:07,560 Speaker 1: but I would hope that at a moment like this, 63 00:04:08,480 --> 00:04:13,920 Speaker 1: with respect to the kind of threat that Iran represents, 64 00:04:14,480 --> 00:04:18,279 Speaker 1: that there'd be a lot of desire to come together 65 00:04:19,120 --> 00:04:26,400 Speaker 1: and support policies that will put the greatest stability possible. 66 00:04:27,880 --> 00:04:34,200 Speaker 1: In second thing, I would advise your listeners. What I 67 00:04:34,400 --> 00:04:40,880 Speaker 1: do to track very complex events and spheres where I 68 00:04:40,920 --> 00:04:45,960 Speaker 1: don't have deep expertise is I look for prediction markets. 69 00:04:46,600 --> 00:04:50,080 Speaker 1: Prediction markets aren't perfect. They're sometimes wrong, just like the 70 00:04:50,080 --> 00:04:54,480 Speaker 1: stock market is sometimes wrong about the earnings of companies, 71 00:04:54,960 --> 00:04:59,920 Speaker 1: but they do represent an aggregation of opinion behind based 72 00:05:00,080 --> 00:05:02,840 Speaker 1: on people who are prepared to put some money where 73 00:05:02,880 --> 00:05:08,000 Speaker 1: their mouths are. And the experience now in many spheres, 74 00:05:08,080 --> 00:05:15,960 Speaker 1: from elections to geopolitical events to movie releases, is that 75 00:05:16,040 --> 00:05:22,240 Speaker 1: prediction markets have very good track records relative to experts. 76 00:05:22,880 --> 00:05:26,800 Speaker 1: And what prediction markets are saying is quite interesting. 77 00:05:26,839 --> 00:05:27,919 Speaker 4: They're saying that. 78 00:05:27,839 --> 00:05:33,320 Speaker 1: The odds of a US attack on Iran are close 79 00:05:33,360 --> 00:05:36,240 Speaker 1: to two thirds by the end of this month, close 80 00:05:36,279 --> 00:05:41,680 Speaker 1: to three quarters by the end of next month, and 81 00:05:41,760 --> 00:05:46,960 Speaker 1: that it's a substantial chance, well above fifty percent, that 82 00:05:47,000 --> 00:05:50,360 Speaker 1: the Supreme Leader in Iran will be out of office 83 00:05:50,520 --> 00:05:56,000 Speaker 1: by the end of this year. So what prediction markets 84 00:05:56,440 --> 00:06:03,279 Speaker 1: are judging is likely to happen is potentially quite tumultuous, 85 00:06:03,920 --> 00:06:07,720 Speaker 1: and I think that anyone trying to judge the situation 86 00:06:07,880 --> 00:06:12,560 Speaker 1: as they formed their portfolio would be well advised not 87 00:06:12,640 --> 00:06:16,239 Speaker 1: to rely only on that, but to give those prediction 88 00:06:16,400 --> 00:06:19,520 Speaker 1: market judgments weight as they make their own. 89 00:06:19,400 --> 00:06:23,000 Speaker 2: Judgments if those predictions came true, and as you say, 90 00:06:23,040 --> 00:06:26,159 Speaker 2: we don't know, but let's assume that happened in fact, 91 00:06:26,680 --> 00:06:29,000 Speaker 2: the United States did get involved, and that the Supreme 92 00:06:29,120 --> 00:06:32,800 Speaker 2: Leader left and there was a regime change in Iran. 93 00:06:33,440 --> 00:06:37,120 Speaker 2: What would that mean economically? What sectors of the economy 94 00:06:37,120 --> 00:06:38,640 Speaker 2: would you look at when we all think about oil, 95 00:06:38,680 --> 00:06:41,719 Speaker 2: for example, I've also seen food prices raised in terms 96 00:06:41,760 --> 00:06:44,320 Speaker 2: of fertilizer of Iran. What sectors do you think might 97 00:06:44,360 --> 00:06:45,240 Speaker 2: be affected the moment? 98 00:06:45,320 --> 00:06:50,200 Speaker 1: I think, David, I would quibble with you in one respect. 99 00:06:50,400 --> 00:06:53,680 Speaker 1: I think when you say something's got a sixty percent 100 00:06:53,800 --> 00:06:56,400 Speaker 1: chance of happening, you're saying that it's a sixty percent 101 00:06:56,480 --> 00:06:58,880 Speaker 1: chance of happening, and there's no such thing as the 102 00:06:58,920 --> 00:07:03,080 Speaker 1: prediction coming or the prediction coming faults. Either the sixty 103 00:07:03,080 --> 00:07:06,839 Speaker 1: percent thing will happen or the forty percent thing will happen. 104 00:07:06,920 --> 00:07:10,200 Speaker 1: So I would choose a somewhat different locution. 105 00:07:12,280 --> 00:07:15,920 Speaker 4: Than you did. But to your question, I'd be looking 106 00:07:17,080 --> 00:07:26,840 Speaker 4: primarily at oil and petrochemicals more generally, fossil fuels more generally, 107 00:07:26,920 --> 00:07:34,880 Speaker 4: and that of course includes fertilizers includes plastics. 108 00:07:35,840 --> 00:07:37,920 Speaker 2: Larry to be a bit more parochial, at least for us. 109 00:07:37,960 --> 00:07:40,880 Speaker 2: In New York City. We have a mayor election coming 110 00:07:40,960 --> 00:07:44,680 Speaker 2: up and including a primary in the Democratic Party, and 111 00:07:45,040 --> 00:07:49,360 Speaker 2: we have a fairly stark contrast in economic approaches of 112 00:07:49,400 --> 00:07:51,960 Speaker 2: the two leading candidates, who or Andrew Cuomo, you know, 113 00:07:52,040 --> 00:07:54,520 Speaker 2: well more of a traditional it seems to be Democrat, 114 00:07:54,840 --> 00:07:57,640 Speaker 2: and a man named Zoran Memdani, who seems to have 115 00:07:57,640 --> 00:08:02,480 Speaker 2: a much more extreme people think economic platform. What do 116 00:08:02,520 --> 00:08:03,200 Speaker 2: you make of that? 117 00:08:04,200 --> 00:08:10,119 Speaker 1: In a sense, every American is a citizen of New York. 118 00:08:10,840 --> 00:08:14,640 Speaker 1: It's so much a cultural and financial hub of our 119 00:08:14,720 --> 00:08:20,800 Speaker 1: country that what happens in New York is consequential for 120 00:08:20,920 --> 00:08:21,480 Speaker 1: all of us. 121 00:08:22,280 --> 00:08:24,000 Speaker 4: And I'm not an. 122 00:08:23,880 --> 00:08:28,400 Speaker 1: Expert on the exigencies of the details of New York 123 00:08:28,480 --> 00:08:34,080 Speaker 1: City economic policy, but i do think the Democratic Socialist 124 00:08:34,240 --> 00:08:39,520 Speaker 1: program would be profoundly dangerous for New York, for the 125 00:08:39,559 --> 00:08:46,280 Speaker 1: Democratic Party, and for the United States. Set of measures, 126 00:08:46,520 --> 00:08:53,800 Speaker 1: free college, free childcare, free mass transit, rent control, huge 127 00:08:53,840 --> 00:08:58,959 Speaker 1: increases in the minimum wage, financed only with tax increases 128 00:08:59,120 --> 00:09:04,160 Speaker 1: on the wealthy. Mobile mobile wealthy who will prove to 129 00:09:04,200 --> 00:09:08,840 Speaker 1: be mobile if this program is enacted will, I think 130 00:09:08,960 --> 00:09:14,480 Speaker 1: be extremely dangerous. I have warned again and again on 131 00:09:14,520 --> 00:09:18,640 Speaker 1: your show about the dangers of economic populism of the 132 00:09:18,760 --> 00:09:23,800 Speaker 1: kind President Trump has followed talking about Juan Parone talking 133 00:09:23,840 --> 00:09:30,800 Speaker 1: about the dangers of tariffs many times. Frankly, the Democratic 134 00:09:30,880 --> 00:09:37,120 Speaker 1: Socialist candidate is more populist and more dangerous. 135 00:09:36,600 --> 00:09:41,520 Speaker 4: In his approach on the narrow set of economic issues. 136 00:09:42,080 --> 00:09:46,959 Speaker 1: Even then, President Trump and I think if he were 137 00:09:47,080 --> 00:09:53,560 Speaker 1: to be selected, it would brand the Democratic Party in 138 00:09:53,600 --> 00:09:58,040 Speaker 1: a highly problematic way. It would suggest that the debate 139 00:09:58,240 --> 00:10:03,200 Speaker 1: within the Democratic Party was between the Larren Sanders wing 140 00:10:03,760 --> 00:10:09,360 Speaker 1: and measures that are even more extreme than theirs in 141 00:10:09,480 --> 00:10:13,560 Speaker 1: terms of the politics of envy in terms of government 142 00:10:13,679 --> 00:10:16,040 Speaker 1: control of the economy. 143 00:10:17,400 --> 00:10:20,440 Speaker 2: Next down Wall Street Week, imagining a Saudi Arabia that 144 00:10:20,559 --> 00:10:23,640 Speaker 2: doesn't depend on oil, We go to the Kingdom, where 145 00:10:23,679 --> 00:10:38,760 Speaker 2: the CEO of Aramco lays out a bold vision. This 146 00:10:38,800 --> 00:10:41,560 Speaker 2: is a story about something we haven't seen before, a 147 00:10:41,640 --> 00:10:45,640 Speaker 2: country weaning itself off oil as its primary source of revenue. 148 00:10:45,920 --> 00:10:49,160 Speaker 2: Even as renewed conflict between Israel and Iran has driven 149 00:10:49,200 --> 00:10:52,320 Speaker 2: the price of oil up once again. The Kingdom of 150 00:10:52,360 --> 00:10:55,440 Speaker 2: Saudi Arabia pursues a bold plan to move quickly to 151 00:10:55,480 --> 00:10:59,359 Speaker 2: a diversified economy and the world's biggest oil producer. Aramco 152 00:10:59,679 --> 00:11:02,360 Speaker 2: is in the middle of the transition. Here's our Bloomberg 153 00:11:02,400 --> 00:11:05,000 Speaker 2: TV colleague, Jumanar Bressecchi from Dahran. 154 00:11:08,360 --> 00:11:12,280 Speaker 5: Aramco has long been the beating heart of Saudi Arabia's economy, 155 00:11:12,800 --> 00:11:15,280 Speaker 5: but in less than five years time, the kingdom hopes 156 00:11:15,320 --> 00:11:17,640 Speaker 5: to reach its goal of building an economy that moves 157 00:11:17,640 --> 00:11:19,800 Speaker 5: away from its traditional reliance on oil. 158 00:11:20,360 --> 00:11:23,520 Speaker 6: We think of ourself as a technology company, delivering energy. 159 00:11:23,559 --> 00:11:26,000 Speaker 7: To be honest with you, technology has always been our 160 00:11:26,080 --> 00:11:27,000 Speaker 7: competitive advantage. 161 00:11:27,120 --> 00:11:29,600 Speaker 8: The company has been evolving ever since its inception. 162 00:11:29,800 --> 00:11:34,920 Speaker 9: Aramko plays a significant role in Saudi's diversification agenda. 163 00:11:37,160 --> 00:11:40,880 Speaker 5: Aramco's journey started in nineteen thirty three when the Saudi 164 00:11:40,880 --> 00:11:45,160 Speaker 5: government granted exploration rights to the Standard Oil Company of California. 165 00:11:45,760 --> 00:11:49,720 Speaker 5: That created the Californian Arabian Standard Oil Company and eventually 166 00:11:49,760 --> 00:11:52,640 Speaker 5: led to the discovery of oil in commercial quantities at 167 00:11:52,679 --> 00:11:56,200 Speaker 5: Dammam Well number seven. This marked a turning point in 168 00:11:56,240 --> 00:12:01,760 Speaker 5: Aramco and Saudi Arabian history. Nineteen forty four, the company 169 00:12:01,840 --> 00:12:05,880 Speaker 5: was renamed to ARAMCO, the Arabian American Oil Company, and 170 00:12:06,000 --> 00:12:09,640 Speaker 5: later that became Saudi Aramco, reflecting its transition to a 171 00:12:09,679 --> 00:12:12,200 Speaker 5: fully state owned company by the late eighties. 172 00:12:12,880 --> 00:12:15,760 Speaker 6: Look at that. You can feel the crude here, eh, 173 00:12:17,080 --> 00:12:17,760 Speaker 6: looking at crude. 174 00:12:18,760 --> 00:12:21,880 Speaker 5: Naser joined Aramco in nineteen eighty two as an oil 175 00:12:21,960 --> 00:12:25,120 Speaker 5: engineer before working up the ranks to become CEO in 176 00:12:25,160 --> 00:12:29,760 Speaker 5: twenty fifteen. So this is the geology. Where does the 177 00:12:29,840 --> 00:12:30,959 Speaker 5: technology come into it? 178 00:12:31,559 --> 00:12:34,720 Speaker 6: Well, technology comes in the modeling and some of the 179 00:12:34,760 --> 00:12:37,680 Speaker 6: technology you can see it here. So we digitize all 180 00:12:37,720 --> 00:12:39,839 Speaker 6: of that and we kept the tea so they can 181 00:12:39,920 --> 00:12:43,840 Speaker 6: look at it and then while you know, having more 182 00:12:43,920 --> 00:12:47,000 Speaker 6: data to see rather than only the what you see 183 00:12:47,040 --> 00:12:47,719 Speaker 6: in front. 184 00:12:47,440 --> 00:12:47,959 Speaker 3: Of you here. 185 00:12:48,559 --> 00:12:51,920 Speaker 5: In twenty nineteen, the Saudi government sold down one point 186 00:12:51,960 --> 00:12:55,280 Speaker 5: five percent of the company, raising twenty five point six 187 00:12:55,400 --> 00:13:00,280 Speaker 5: billion dollars, which today remains the largest IPO in history. 188 00:13:00,320 --> 00:13:03,480 Speaker 5: The Saudi government and SOERMN Wealth Funds PIF join the 189 00:13:03,600 --> 00:13:07,839 Speaker 5: own around ninety eight percent of aram coast shares. The 190 00:13:07,840 --> 00:13:11,760 Speaker 5: oil giant accounts for approximately sixty percent of total Saudi 191 00:13:11,840 --> 00:13:15,319 Speaker 5: government revenue, and the broader oil sector, with Aramco is 192 00:13:15,360 --> 00:13:18,280 Speaker 5: the main player, makes up roughly thirty to forty percent 193 00:13:18,360 --> 00:13:19,760 Speaker 5: of the kingdom's GDP. 194 00:13:20,559 --> 00:13:26,240 Speaker 6: Relying on one sector only to drive the Saudi economy 195 00:13:26,320 --> 00:13:28,320 Speaker 6: is not right. And this is where the figion is. 196 00:13:28,440 --> 00:13:33,920 Speaker 6: They are helping other sectors, growing other sectors across the kingdom. 197 00:13:33,920 --> 00:13:37,720 Speaker 6: To grow oil and gas is still important. That's why 198 00:13:37,720 --> 00:13:40,240 Speaker 6: you see the growth see here. We are very pragmatic 199 00:13:40,320 --> 00:13:42,880 Speaker 6: here in the Kingdom. You're talking about one hundred to 200 00:13:42,920 --> 00:13:44,640 Speaker 6: one hundred and ten thirty ge go out of solar 201 00:13:44,679 --> 00:13:47,680 Speaker 6: and wind. We believe in hydrogen where we will be 202 00:13:47,679 --> 00:13:51,079 Speaker 6: happy to produce hydrogen. Actually, we have one of the 203 00:13:51,080 --> 00:13:54,560 Speaker 6: biggest projects in green hydrogen at Leon, and we will 204 00:13:54,600 --> 00:13:57,320 Speaker 6: be more than happy to build more green hydrogen and 205 00:13:57,360 --> 00:14:00,680 Speaker 6: blue hydrogens in the Kingdom. And the same time we're 206 00:14:00,679 --> 00:14:03,480 Speaker 6: in carbon caption and storage, but we are normally not 207 00:14:03,600 --> 00:14:09,800 Speaker 6: neglecting hydrocarbon. We have healthy oil production, we have a 208 00:14:09,840 --> 00:14:13,360 Speaker 6: maximum sustake ABAS with twelve million. We are growing our 209 00:14:13,440 --> 00:14:16,600 Speaker 6: gas by more than sixty percent by twenty thirty. So 210 00:14:16,640 --> 00:14:19,840 Speaker 6: we are focusing in our conventional and growing it while 211 00:14:19,880 --> 00:14:23,520 Speaker 6: decarbonizing at the same time, and we are building the 212 00:14:23,600 --> 00:14:26,200 Speaker 6: new which is solar, wind, hydrogen and others. 213 00:14:26,600 --> 00:14:29,440 Speaker 5: The Kingdom's crown jewel is central to the ambitions of 214 00:14:29,520 --> 00:14:33,360 Speaker 5: vision twenty thirty, the government program aiming to diversify the 215 00:14:33,440 --> 00:14:38,840 Speaker 5: economy away from hydrocarbon dependence, attract foreign investments, and modernize 216 00:14:38,840 --> 00:14:42,880 Speaker 5: the Saudi Arabian society. Carla slam Is chief economists that 217 00:14:43,000 --> 00:14:46,000 Speaker 5: standard chartered covering regions including the Middle East. 218 00:14:46,680 --> 00:14:51,040 Speaker 9: In the past, the diversification strategy was investing petro dollars 219 00:14:51,120 --> 00:14:54,960 Speaker 9: oil revenues abroad so that they would be uncorrelated to 220 00:14:55,040 --> 00:14:58,280 Speaker 9: the price of oil, and for the last decade around 221 00:14:58,280 --> 00:15:02,520 Speaker 9: cost dividends to the budget have contributed indirectly to funding 222 00:15:02,840 --> 00:15:06,360 Speaker 9: a lot of the diversification strategy in the domestic economy, 223 00:15:06,400 --> 00:15:09,560 Speaker 9: so they remain a very important piece of the Saudi 224 00:15:09,600 --> 00:15:13,200 Speaker 9: economy of the revenues in order to fund that government 225 00:15:13,240 --> 00:15:15,320 Speaker 9: spending and that investment. 226 00:15:15,280 --> 00:15:18,920 Speaker 5: From creating Niom, a five hundred billion dollar futuristic city 227 00:15:18,920 --> 00:15:21,800 Speaker 5: in the desert, to hosting the twenty thirty four World 228 00:15:21,880 --> 00:15:24,880 Speaker 5: Cup and building out a new major airport in Riyad 229 00:15:25,080 --> 00:15:29,560 Speaker 5: Vision twenty thirty is well underway. The Kingdom's transition is 230 00:15:29,600 --> 00:15:33,960 Speaker 5: not without its challenges. Opek plus production cuts undermine a 231 00:15:34,080 --> 00:15:38,480 Speaker 5: key source of revenue for the country. Despite diversification efforts. 232 00:15:39,160 --> 00:15:41,920 Speaker 5: In the first quarter of twenty twenty five, Saudi Arabia 233 00:15:41,960 --> 00:15:46,080 Speaker 5: reported its largest budget deficits since twenty twenty one. That's 234 00:15:46,160 --> 00:15:50,200 Speaker 5: impacted spending for some of the kingdom's largest investment projects, 235 00:15:50,400 --> 00:15:53,520 Speaker 5: and ARAMCO has increasingly tapped into debt markets, which the 236 00:15:53,520 --> 00:15:56,120 Speaker 5: company has put down to looking to lower its weighted 237 00:15:56,200 --> 00:15:59,400 Speaker 5: cost of capital and optimizing the capital structure. 238 00:16:00,960 --> 00:16:04,040 Speaker 6: Our gearing today is around five percent, still one of 239 00:16:04,080 --> 00:16:07,560 Speaker 6: the lowest gearing you know, almost half of the average 240 00:16:08,520 --> 00:16:13,440 Speaker 6: compared to other energy industry players in the market. And 241 00:16:13,480 --> 00:16:17,840 Speaker 6: we will continue to tab into that addition and bond 242 00:16:17,960 --> 00:16:25,040 Speaker 6: markets on the future. But we have a low gearing ratio. 243 00:16:25,160 --> 00:16:28,520 Speaker 6: It's still as you considered, terry low considered combat to 244 00:16:28,560 --> 00:16:31,040 Speaker 6: any others, any players in the markets. 245 00:16:32,320 --> 00:16:35,560 Speaker 5: The size of the dividends, especially to its largest shareholder, 246 00:16:35,640 --> 00:16:39,800 Speaker 5: the Saudi government, remains under scrutiny relative to free cash 247 00:16:39,840 --> 00:16:44,560 Speaker 5: flow generated. Geopolitical tensions have also remained an undercurrent of 248 00:16:44,600 --> 00:16:48,480 Speaker 5: concerns since the twenty nineteen attacks on around COO's Upcake facility. 249 00:16:48,960 --> 00:16:52,320 Speaker 5: Although the company resumed partial operations within twenty four hours, 250 00:16:52,640 --> 00:16:56,280 Speaker 5: the incidet triggered a heightened focus on security. In response, 251 00:16:56,320 --> 00:17:00,240 Speaker 5: Saudi Arabia has worked to ease regional tensions, including wearing 252 00:17:00,280 --> 00:17:03,680 Speaker 5: diplomatic ties with Iran in twenty twenty three. Even as 253 00:17:03,680 --> 00:17:06,600 Speaker 5: the company manages near term pressures, Aramco is investing in 254 00:17:06,680 --> 00:17:09,160 Speaker 5: areas that could define its long term future. 255 00:17:09,840 --> 00:17:12,520 Speaker 8: I think gas is going to be a major growth 256 00:17:12,560 --> 00:17:14,959 Speaker 8: area for the company today and this is not known 257 00:17:15,040 --> 00:17:17,600 Speaker 8: to many people. We are a large gas producer. 258 00:17:17,960 --> 00:17:21,879 Speaker 5: Ashchef Rasawi is Aramco's EVP for Strategy and corporate Development. 259 00:17:22,320 --> 00:17:25,399 Speaker 5: He lays out the non oil key strategic pillars of 260 00:17:25,480 --> 00:17:26,000 Speaker 5: the business. 261 00:17:26,760 --> 00:17:29,439 Speaker 8: Our gas business is going to grow by sixty percent 262 00:17:29,920 --> 00:17:33,520 Speaker 8: by twenty thirty compared to the twenty twenty one levels, 263 00:17:33,920 --> 00:17:36,240 Speaker 8: and you will see the company grow and continue to 264 00:17:36,240 --> 00:17:38,720 Speaker 8: invest in a lot of low carbon or new energies. 265 00:17:38,920 --> 00:17:43,000 Speaker 8: In particular, you will see Aramco investing now and renewables, 266 00:17:43,119 --> 00:17:46,720 Speaker 8: energy and hydrogen and ammonia, as well as carbon capture 267 00:17:46,720 --> 00:17:51,040 Speaker 8: and stores technology. Not to mention digital and digitization as 268 00:17:51,080 --> 00:17:54,000 Speaker 8: a big area for US. Further integration down the value 269 00:17:54,119 --> 00:17:57,360 Speaker 8: chain is an important area for you to basically have 270 00:17:57,920 --> 00:18:02,080 Speaker 8: an outlet for these vast hydrocarbon resources. Chemicals to US 271 00:18:02,200 --> 00:18:04,960 Speaker 8: is a main building block for all modern economies and 272 00:18:04,960 --> 00:18:10,200 Speaker 8: modern societies. You'll always need commodities and materials like plastics 273 00:18:10,240 --> 00:18:15,000 Speaker 8: and polymers for any type of economic development going forward. 274 00:18:15,880 --> 00:18:19,000 Speaker 5: Like in most industries, one of its most ambitious bets 275 00:18:19,000 --> 00:18:23,240 Speaker 5: to move the company forward is artificial intelligence AI. 276 00:18:23,680 --> 00:18:26,160 Speaker 7: We see as one of the most important developments in 277 00:18:26,200 --> 00:18:29,080 Speaker 7: this century in terms of technology, and so we have 278 00:18:29,200 --> 00:18:33,600 Speaker 7: been quick to deploy AI in our operations and to 279 00:18:33,680 --> 00:18:35,000 Speaker 7: apply it to our business. 280 00:18:35,640 --> 00:18:39,840 Speaker 5: Ah medel Kite leads tech and innovation at Aramco. Data 281 00:18:39,840 --> 00:18:43,080 Speaker 5: from the company's facilities and operations end up here at 282 00:18:43,119 --> 00:18:47,280 Speaker 5: its fourth Industrial Revolution Center. Last year, a Ramco announced 283 00:18:47,320 --> 00:18:50,240 Speaker 5: it was developing a large scale industrial AI model called 284 00:18:50,480 --> 00:18:51,520 Speaker 5: Ramco Metabrain. 285 00:18:52,280 --> 00:18:55,359 Speaker 7: The Metabrane is a seventy billion parameter model and the 286 00:18:55,400 --> 00:18:59,200 Speaker 7: reason we chose to build a proprietary large language model 287 00:18:59,640 --> 00:19:02,199 Speaker 7: is because we have to use our own data and 288 00:19:02,240 --> 00:19:05,080 Speaker 7: it gives us that competitive advantage. So we have trained 289 00:19:05,119 --> 00:19:10,560 Speaker 7: that model with all of our historical data, engineering reports, standards, 290 00:19:10,960 --> 00:19:14,520 Speaker 7: and that model is now used to advise our engineers 291 00:19:14,520 --> 00:19:17,439 Speaker 7: and operations every single employee in the company. So we 292 00:19:17,520 --> 00:19:21,640 Speaker 7: have deployed that model on seventy thousand workstations across our 293 00:19:21,680 --> 00:19:26,400 Speaker 7: facilities and our offices. But not only is it providing advice, 294 00:19:26,760 --> 00:19:29,520 Speaker 7: but it is also informing for better decisions. It is 295 00:19:29,560 --> 00:19:33,439 Speaker 7: the base foundation for many of the applications we are 296 00:19:33,440 --> 00:19:36,960 Speaker 7: doing in optimization for example and operating our facilities. So 297 00:19:37,000 --> 00:19:39,720 Speaker 7: that's the way we are able to bring AI right 298 00:19:39,760 --> 00:19:40,280 Speaker 7: to the field. 299 00:19:40,359 --> 00:19:42,159 Speaker 6: This is where do you see a lot of the 300 00:19:42,240 --> 00:19:48,200 Speaker 6: use cases delivering results for us. Technology realization in twenty 301 00:19:48,240 --> 00:19:52,440 Speaker 6: twenty three used to be two billion dollars. Is so 302 00:19:52,600 --> 00:19:56,560 Speaker 6: much we realize from technology in twenty four four billion dollars, 303 00:19:56,960 --> 00:19:59,920 Speaker 6: we're looking at two to four billion dollars. Berrie technologized 304 00:20:00,280 --> 00:20:04,919 Speaker 6: AI is in everything embedded, not only in terms of 305 00:20:05,000 --> 00:20:09,960 Speaker 6: allowing us to reduce our cost structure more efficiency, it 306 00:20:10,119 --> 00:20:13,000 Speaker 6: also helps us in reducing our carbon footprint. So it's 307 00:20:13,080 --> 00:20:16,880 Speaker 6: very important and able to see it introducing emissions, increasing 308 00:20:16,920 --> 00:20:20,160 Speaker 6: productivity and with that the number of wolds water production 309 00:20:20,440 --> 00:20:24,560 Speaker 6: and with that emissions and this bumping in everything. It's embedded, 310 00:20:24,760 --> 00:20:29,880 Speaker 6: and we are looking at the benefits of AI integrating 311 00:20:29,880 --> 00:20:31,280 Speaker 6: it and everything that we are doing. 312 00:20:31,960 --> 00:20:35,520 Speaker 5: Even with big strides and digital innovation. Aramco at its 313 00:20:35,560 --> 00:20:39,040 Speaker 5: core remains an energy giant as CEO of one of 314 00:20:39,040 --> 00:20:42,480 Speaker 5: the largest hydrocarbon companies in the world. Nasser has been 315 00:20:42,520 --> 00:20:46,119 Speaker 5: advocating for what he considers a more pragmatic approach to 316 00:20:46,200 --> 00:20:47,160 Speaker 5: the energy transition. 317 00:20:47,840 --> 00:20:51,240 Speaker 6: Well, we have always said that we need transition research 318 00:20:51,320 --> 00:20:55,199 Speaker 6: or a reality check in the transition to deliver on 319 00:20:55,640 --> 00:21:01,040 Speaker 6: our ambition for an zero. What we need is pragmatic 320 00:21:01,240 --> 00:21:06,040 Speaker 6: solutions to deliver on what we are all aiming for. 321 00:21:06,359 --> 00:21:09,520 Speaker 6: Almost seventy to eighty percent of the energy global energy 322 00:21:09,560 --> 00:21:11,480 Speaker 6: and twenty fifty will be in the global salt not 323 00:21:11,640 --> 00:21:15,160 Speaker 6: and the global north. So one size fits all will 324 00:21:15,200 --> 00:21:19,800 Speaker 6: not work. And anything that is driven heavily by incentive 325 00:21:21,400 --> 00:21:26,080 Speaker 6: that's not sustainable. The minute these incentives disappear and they 326 00:21:26,119 --> 00:21:29,400 Speaker 6: will disappear one day, that additional cost will be best 327 00:21:29,440 --> 00:21:33,320 Speaker 6: to consumer, and that's where we are seeing the increase 328 00:21:33,400 --> 00:21:37,600 Speaker 6: in cost. What we need is something that while sustainable, 329 00:21:37,960 --> 00:21:42,439 Speaker 6: is affordable and secure. We have always talked about different 330 00:21:43,040 --> 00:21:44,920 Speaker 6: mix of energy that it will be required. 331 00:21:45,240 --> 00:21:47,960 Speaker 5: Aramco has a net zero twenty to fifty target for 332 00:21:48,040 --> 00:21:51,480 Speaker 5: its Scope one and Scope two emissions and prides itself 333 00:21:51,520 --> 00:21:55,680 Speaker 5: on having the lowest carbon intensity for upstream extraction compared 334 00:21:55,680 --> 00:21:58,920 Speaker 5: to other energy companies, But this does not include Scope 335 00:21:58,920 --> 00:22:01,840 Speaker 5: three emissions, which from end user combustion of oil and 336 00:22:01,880 --> 00:22:05,240 Speaker 5: fossil fuels and constitute the line share of emissions. 337 00:22:05,960 --> 00:22:08,439 Speaker 8: I have to say that not all crude oil is equal. 338 00:22:08,960 --> 00:22:10,879 Speaker 8: You know, we take a lot of pride in the 339 00:22:10,920 --> 00:22:14,560 Speaker 8: fact that we are the lowest upstream carbon intensity producer 340 00:22:15,480 --> 00:22:18,040 Speaker 8: and husband for a while, and that's a result of 341 00:22:18,200 --> 00:22:22,280 Speaker 8: decades of responsible and sustainable operations. You know, it's important 342 00:22:22,280 --> 00:22:25,440 Speaker 8: for us also to adhere to our commitments toward the 343 00:22:25,880 --> 00:22:29,439 Speaker 8: Nazero ambition and keeping an eye on what levers of 344 00:22:29,480 --> 00:22:34,560 Speaker 8: decarbonization are available to us. We have been running flair 345 00:22:34,600 --> 00:22:39,359 Speaker 8: minimization programs for for decades. We have methane intensity that 346 00:22:39,480 --> 00:22:42,440 Speaker 8: is the lowest in the market. All of these combines 347 00:22:42,440 --> 00:22:47,399 Speaker 8: actually is where we position ourselves as the undisputed leader 348 00:22:47,440 --> 00:22:51,480 Speaker 8: when it comes to carbon intensity and environmental metrics out there. 349 00:22:52,080 --> 00:22:56,680 Speaker 5: Aramco looks to redefine its role as Saudi Arabia reimagines 350 00:22:56,800 --> 00:22:57,440 Speaker 5: its future. 351 00:22:58,119 --> 00:23:02,159 Speaker 9: We believe Saudi will remain a major oil producer in 352 00:23:02,200 --> 00:23:05,320 Speaker 9: the global economy. We don't expect this to change, but 353 00:23:05,400 --> 00:23:08,200 Speaker 9: we believe that the non oil GDP expansion will happen 354 00:23:08,320 --> 00:23:13,119 Speaker 9: in parallel to Saudi remaining a major commodity player on 355 00:23:13,160 --> 00:23:15,840 Speaker 9: the global front. On the regional front and its G 356 00:23:15,960 --> 00:23:19,200 Speaker 9: twenty capacity. We just expect that the non oil development 357 00:23:19,240 --> 00:23:22,760 Speaker 9: will happen in tandem in parallel, and this will continue 358 00:23:22,840 --> 00:23:27,119 Speaker 9: to have shifts to how Saudi spends domestically globally in 359 00:23:27,160 --> 00:23:29,480 Speaker 9: the region as well with its regional allies. 360 00:23:29,760 --> 00:23:33,280 Speaker 6: There is a lot of challenges ahead of us, especially 361 00:23:33,320 --> 00:23:38,080 Speaker 6: with sustainability, with the transitions with disruptive technologies. We need 362 00:23:38,119 --> 00:23:41,280 Speaker 6: to be ready. How do we maintain and continue to 363 00:23:41,320 --> 00:23:45,760 Speaker 6: maintain that leadership while also delivering the new energies that 364 00:23:45,880 --> 00:23:46,840 Speaker 6: the world wants. 365 00:23:46,600 --> 00:23:51,160 Speaker 2: Us coming up. Just when you thought you were getting 366 00:23:51,160 --> 00:23:55,359 Speaker 2: your arms around artificial intelligence, large language models along coming 367 00:23:55,600 --> 00:23:59,239 Speaker 2: array of alternatives, we delve into large quantitative models and 368 00:23:59,320 --> 00:24:02,920 Speaker 2: even so for intelligence that's next on Wall Street Week. 369 00:24:12,080 --> 00:24:16,000 Speaker 2: This is a story about thinking ahead, even way ahead. 370 00:24:16,480 --> 00:24:19,600 Speaker 2: We've all heard about the race between companies and countries 371 00:24:19,800 --> 00:24:22,920 Speaker 2: to develop artificial intelligence, but it turns out that there's 372 00:24:23,000 --> 00:24:26,720 Speaker 2: another race going on, one among entirely different approaches to 373 00:24:26,760 --> 00:24:29,320 Speaker 2: AI and what they're racing to achieve. 374 00:24:31,440 --> 00:24:34,960 Speaker 10: Generally, we think the cost of innovation is collapsing here. 375 00:24:35,119 --> 00:24:37,000 Speaker 8: It is going to transform our lives. 376 00:24:37,040 --> 00:24:38,560 Speaker 2: We're going to look back and see this is a 377 00:24:38,640 --> 00:24:39,760 Speaker 2: hugely important era. 378 00:24:40,240 --> 00:24:44,000 Speaker 1: This is obviously the most disruptive technology in the history 379 00:24:44,000 --> 00:24:44,800 Speaker 1: of man can. 380 00:24:47,400 --> 00:24:50,200 Speaker 2: At the center of many of the latest AI breakthroughs 381 00:24:50,280 --> 00:24:54,879 Speaker 2: are large language models or lms, the chat, GPTs and 382 00:24:54,960 --> 00:24:58,400 Speaker 2: geminis of this world. But as powerful as they are becoming, 383 00:24:58,520 --> 00:25:01,959 Speaker 2: we learn more every day about their limitations, how they 384 00:25:02,000 --> 00:25:06,040 Speaker 2: can be prone to errors, hallucinations, and uncertainty. One of 385 00:25:06,040 --> 00:25:08,959 Speaker 2: those trying to address these limitations is none other than 386 00:25:09,080 --> 00:25:12,240 Speaker 2: Vlad Tenef, known to most of us as the CEO 387 00:25:12,400 --> 00:25:16,600 Speaker 2: and co founder of robin Hood Markets. Tenef has become 388 00:25:16,640 --> 00:25:21,040 Speaker 2: a successful entrepreneur, but his background is in mathematics. 389 00:25:22,040 --> 00:25:24,120 Speaker 11: What a lot of people don't know about me is actually, 390 00:25:24,160 --> 00:25:27,919 Speaker 11: before I became an entrepreneur, I was a mathematician, or 391 00:25:28,000 --> 00:25:32,640 Speaker 11: at least an aspiring mathematician. I always had this passion 392 00:25:33,240 --> 00:25:38,480 Speaker 11: for mathematics and for advancing our understanding of reality. And 393 00:25:38,520 --> 00:25:42,600 Speaker 11: so when we saw GPT four come out along with 394 00:25:43,119 --> 00:25:49,280 Speaker 11: a bunch of improvements in the mathematics community around formal verification, Tutor, 395 00:25:49,480 --> 00:25:54,600 Speaker 11: who's my co founder and CEO of Harmonic, and I 396 00:25:54,640 --> 00:25:57,560 Speaker 11: got very very excited about building something. We thought that 397 00:25:57,560 --> 00:26:01,320 Speaker 11: the time was right to actually build something mathematics that 398 00:26:01,440 --> 00:26:03,760 Speaker 11: combine the state of the art in that field with 399 00:26:03,880 --> 00:26:05,920 Speaker 11: the state of the art in AI. 400 00:26:06,800 --> 00:26:09,919 Speaker 2: Tenem's new firm, Harmonic helps to achieve something that still 401 00:26:09,960 --> 00:26:13,840 Speaker 2: belongs to the realm of science fiction. Beyond artificial narrow 402 00:26:13,840 --> 00:26:18,440 Speaker 2: intelligence like chat GPT, which can perform specific and limited tasks, 403 00:26:18,920 --> 00:26:22,399 Speaker 2: beyond even an artificial general intelligence which could learn and 404 00:26:22,440 --> 00:26:26,000 Speaker 2: adapt like humans. Tenef says his goal is to help 405 00:26:26,040 --> 00:26:29,600 Speaker 2: create what he calls a mathematical superintelligence. 406 00:26:30,160 --> 00:26:35,879 Speaker 11: So mathematical superintelligence is artificial intelligence that can reason and 407 00:26:35,920 --> 00:26:40,840 Speaker 11: solve math problems at a level exceeding the most advanced 408 00:26:41,160 --> 00:26:46,000 Speaker 11: mathematics researchers, so professional mathematicians that are out there today. 409 00:26:46,600 --> 00:26:50,679 Speaker 11: And we think that developing such a system will not 410 00:26:50,840 --> 00:26:55,400 Speaker 11: only greatly accelerate the progress of mathematics, but it will 411 00:26:55,440 --> 00:27:00,320 Speaker 11: also accelerate progress in all fields of science and technology 412 00:27:00,680 --> 00:27:02,640 Speaker 11: that depend on mathematics. 413 00:27:03,080 --> 00:27:05,119 Speaker 2: We have heard at this point so much about large 414 00:27:05,200 --> 00:27:08,440 Speaker 2: language models in the AI space. What you describe sounds 415 00:27:08,480 --> 00:27:11,639 Speaker 2: like almost the obverse of large language models, which is, 416 00:27:11,640 --> 00:27:16,400 Speaker 2: I understand operate on language rather than numbers or on mathematics. 417 00:27:16,640 --> 00:27:19,840 Speaker 11: I think the main problem with large language models and 418 00:27:19,960 --> 00:27:24,760 Speaker 11: AI systems as they're currently designed, is that they very 419 00:27:24,880 --> 00:27:28,760 Speaker 11: very confidently can tell you the wrong thing. So there's 420 00:27:28,920 --> 00:27:32,760 Speaker 11: very few controls over what we call hallucinations. You'll ask 421 00:27:32,800 --> 00:27:36,360 Speaker 11: a large language model a question, it'll give you an answer. 422 00:27:36,680 --> 00:27:41,040 Speaker 11: You can ask it to solve a major mathematical conjecture 423 00:27:41,160 --> 00:27:45,000 Speaker 11: and it'll spit out output, and it can be very 424 00:27:45,080 --> 00:27:49,720 Speaker 11: convincing in its incorrectness. And so I think that's a 425 00:27:49,800 --> 00:27:53,359 Speaker 11: huge problem, and that's by and large what's hindered the 426 00:27:53,440 --> 00:27:59,840 Speaker 11: adoption of these AI tools in mission critical industries, and 427 00:28:00,520 --> 00:28:04,679 Speaker 11: the way that Harmonic has designed our AI from the 428 00:28:04,680 --> 00:28:10,640 Speaker 11: beginning is with correctness and verifiability being a first class citizen. 429 00:28:12,560 --> 00:28:16,000 Speaker 2: Last year, Harmonic closed a seventy five million dollars Series 430 00:28:16,040 --> 00:28:19,560 Speaker 2: A funding round led by Sequoia Capital and announced that 431 00:28:19,600 --> 00:28:23,240 Speaker 2: it's AI had performed well in a test of mathematical reasoning. 432 00:28:23,800 --> 00:28:26,800 Speaker 2: But Tennis says there's still work to do before true 433 00:28:26,800 --> 00:28:31,280 Speaker 2: mathematical superintelligence is achieved and before Harmonic can roll out 434 00:28:31,280 --> 00:28:32,959 Speaker 2: a product to consumers. 435 00:28:33,520 --> 00:28:39,960 Speaker 11: We're still in fairly early stages, but we're actually getting 436 00:28:39,960 --> 00:28:45,600 Speaker 11: close to unveiling our technology to the public. So the 437 00:28:45,680 --> 00:28:51,200 Speaker 11: team actually released a big result about nine to twelve 438 00:28:51,280 --> 00:28:57,640 Speaker 11: months ago where we showed really tremendous advancements across a 439 00:28:57,680 --> 00:29:02,560 Speaker 11: few key mathematics benchmarks that were focused on formal mathematics. 440 00:29:02,800 --> 00:29:05,120 Speaker 2: Give us a sense of that development process. I mean, 441 00:29:05,160 --> 00:29:07,240 Speaker 2: are you working toward a prototype or do you have 442 00:29:07,240 --> 00:29:08,320 Speaker 2: a prototype already? 443 00:29:08,640 --> 00:29:13,560 Speaker 11: We have some things internally that we're refining, and basically 444 00:29:15,000 --> 00:29:19,640 Speaker 11: the company is largely focused on research because without a 445 00:29:19,680 --> 00:29:23,000 Speaker 11: strong model that keeps getting better and better, it's not 446 00:29:23,120 --> 00:29:26,840 Speaker 11: as useful. But over the past few months we've started 447 00:29:26,840 --> 00:29:30,280 Speaker 11: to turn more and more of our resources towards commercialization 448 00:29:30,920 --> 00:29:33,760 Speaker 11: and actually figuring out how we're going to put it 449 00:29:33,800 --> 00:29:37,080 Speaker 11: into people's hands. Who the customers are, what the biggest 450 00:29:37,120 --> 00:29:40,200 Speaker 11: pain points we can help solve for customers are. 451 00:29:41,480 --> 00:29:43,840 Speaker 2: While ten If and his colleagues walk the long and 452 00:29:44,040 --> 00:29:47,960 Speaker 2: uncertain road towards superintelligence, Jack Hitory has built a business 453 00:29:48,040 --> 00:29:51,600 Speaker 2: around what he calls large quantitative models, which are trained 454 00:29:51,640 --> 00:29:56,080 Speaker 2: on numbers and data rather than on pros. His company, 455 00:29:56,200 --> 00:29:59,720 Speaker 2: Sandbox AQ, spun off from Alphabet in twenty twenty two. 456 00:30:00,400 --> 00:30:02,600 Speaker 12: What we can do is we can take the equations 457 00:30:02,600 --> 00:30:06,720 Speaker 12: of biology, of chemistry, of physics, of engineering, and we 458 00:30:06,760 --> 00:30:09,440 Speaker 12: can train an AI on those, and that's the world 459 00:30:09,480 --> 00:30:13,760 Speaker 12: now of large quantitative models l qms, and this world 460 00:30:13,760 --> 00:30:19,040 Speaker 12: of lqms impacts eighty percent of our economy and drives 461 00:30:19,040 --> 00:30:23,200 Speaker 12: massive innovation in the companies that use them. And so 462 00:30:23,440 --> 00:30:26,120 Speaker 12: you have large language models on the one hand, and 463 00:30:26,200 --> 00:30:29,719 Speaker 12: from a business point of view, they're mainly there to 464 00:30:29,760 --> 00:30:33,320 Speaker 12: cut some costs. If you have say thirty million dollars 465 00:30:33,320 --> 00:30:36,280 Speaker 12: of costs every year in your company, you could probably 466 00:30:36,280 --> 00:30:39,920 Speaker 12: start lopping off ten, fifteen to twenty million of customer 467 00:30:39,960 --> 00:30:42,120 Speaker 12: service costs per year, and that's going to be a 468 00:30:42,120 --> 00:30:45,360 Speaker 12: great savings for your company. But when it comes to 469 00:30:45,440 --> 00:30:50,280 Speaker 12: creating new product billions of dollars of new revenue, that's 470 00:30:50,400 --> 00:30:52,840 Speaker 12: not really going to be a large language model. That's 471 00:30:52,840 --> 00:30:55,800 Speaker 12: going to be an LQM, a large quantitative model. 472 00:30:56,040 --> 00:30:58,400 Speaker 2: Where are we in developing lqms. 473 00:30:58,880 --> 00:31:01,600 Speaker 12: Lqms are now plating in the B to B land, 474 00:31:01,720 --> 00:31:05,720 Speaker 12: So it's less about consumers using lqms, but it's really 475 00:31:05,720 --> 00:31:09,760 Speaker 12: about businesses using lqms. And right now we announce at 476 00:31:09,760 --> 00:31:12,600 Speaker 12: Sandbox AQ that we're working with Santa Fee, for example, 477 00:31:12,640 --> 00:31:17,240 Speaker 12: a top ten pharma company, using lqms to advance their 478 00:31:17,280 --> 00:31:21,640 Speaker 12: work in life saving medicines. We announce work with chemical 479 00:31:21,680 --> 00:31:25,680 Speaker 12: companies such as a Ramco using lqms to up value 480 00:31:26,080 --> 00:31:29,800 Speaker 12: the hydrocarbons coming out, so we can create new products, 481 00:31:29,800 --> 00:31:32,479 Speaker 12: products that will not be burned in the atmosphere, but 482 00:31:32,600 --> 00:31:36,400 Speaker 12: rather be put into various kinds of vehicles and others 483 00:31:36,440 --> 00:31:40,400 Speaker 12: to lightweight and to add value to those industries as well. 484 00:31:40,680 --> 00:31:44,400 Speaker 2: There's a lot of money being invested in AI right now, 485 00:31:44,960 --> 00:31:45,640 Speaker 2: a lot. 486 00:31:45,560 --> 00:31:49,360 Speaker 13: Hundreds of billions of dollars literally being invested. From what 487 00:31:49,400 --> 00:31:53,840 Speaker 13: you understand, where are the places to look for good 488 00:31:53,840 --> 00:31:57,240 Speaker 13: investments or even better, what would you advise an investor 489 00:31:57,680 --> 00:31:59,680 Speaker 13: to look out for both on the upside in the 490 00:31:59,680 --> 00:32:03,520 Speaker 13: downs side. In considering investing in AI, there's. 491 00:32:03,320 --> 00:32:08,160 Speaker 12: Two real ways to play the AI future. One is 492 00:32:08,240 --> 00:32:12,080 Speaker 12: to focus on a number of mainly private AI companies 493 00:32:12,960 --> 00:32:15,560 Speaker 12: that are that are out there now, and you know, 494 00:32:15,720 --> 00:32:19,440 Speaker 12: various people and various banks are able to put together 495 00:32:19,960 --> 00:32:23,160 Speaker 12: vehicles to invest in these uh and so that's one 496 00:32:23,160 --> 00:32:26,400 Speaker 12: way up to really focus on that. The second is 497 00:32:26,440 --> 00:32:29,160 Speaker 12: to look at the public markets. And we look at 498 00:32:29,200 --> 00:32:33,480 Speaker 12: the public markets again, you can look at the hyperscalers 499 00:32:33,520 --> 00:32:38,040 Speaker 12: such as Amazon, Microsoft, Google and others, and you could, 500 00:32:38,160 --> 00:32:41,320 Speaker 12: you know, place your bets there because essentially those are 501 00:32:41,360 --> 00:32:45,360 Speaker 12: AI driven companies at this point. But another way to 502 00:32:45,480 --> 00:32:48,360 Speaker 12: make your AI play that actually may be more fruitful 503 00:32:49,280 --> 00:32:53,040 Speaker 12: is to look at industry by industry David and understand 504 00:32:53,040 --> 00:32:56,320 Speaker 12: who are going to be the AI winners and AI losers. 505 00:32:56,360 --> 00:33:00,280 Speaker 12: In the pharmaceutical industry, in the energy industry, in the 506 00:33:00,280 --> 00:33:04,720 Speaker 12: telco industry, in the financial services sector. Each of these 507 00:33:04,800 --> 00:33:10,200 Speaker 12: are eight, ten, fifteen trillion dollar sectors, and the winners 508 00:33:10,240 --> 00:33:13,880 Speaker 12: and losers there are going to really determine billions and 509 00:33:13,920 --> 00:33:17,680 Speaker 12: billions of dollars of value of market cap difference as 510 00:33:17,760 --> 00:33:22,160 Speaker 12: those two groups diverge, the winners who are embracing AI 511 00:33:22,640 --> 00:33:26,000 Speaker 12: and the laggards who are not embracing AI fast enough. 512 00:33:27,240 --> 00:33:31,120 Speaker 2: Whoever the winners and losers might be tomorrow, picking them 513 00:33:31,240 --> 00:33:35,840 Speaker 2: today is anything but certain. MIT professor Alex Pentland says 514 00:33:35,880 --> 00:33:38,480 Speaker 2: there will be no one size fits all solution. 515 00:33:38,960 --> 00:33:41,120 Speaker 14: I think it's pretty clear that different AI will be 516 00:33:41,240 --> 00:33:44,320 Speaker 14: used for different purposes. It's just like humans are expert 517 00:33:44,360 --> 00:33:47,000 Speaker 14: in one thing or another. You want to have as 518 00:33:47,080 --> 00:33:54,240 Speaker 14: much sort of information and depth in something like designing drugs, 519 00:33:54,480 --> 00:33:58,520 Speaker 14: so medicines or doing climate change as you possibly can. 520 00:33:58,960 --> 00:34:03,120 Speaker 14: Your climate change model doesn't need to speak twenty different languages, 521 00:34:03,160 --> 00:34:06,960 Speaker 14: so don't waste the power of the language by training 522 00:34:07,000 --> 00:34:08,000 Speaker 14: on that sort of thing. 523 00:34:08,360 --> 00:34:11,040 Speaker 2: You have a deep understanding of artificial intelligence, and you 524 00:34:11,320 --> 00:34:14,160 Speaker 2: are an academic, I'm not going to ask you for 525 00:34:14,280 --> 00:34:18,040 Speaker 2: investment advice, except I am here at Bloomberg. There's an 526 00:34:18,040 --> 00:34:20,239 Speaker 2: awful lot of money, tens of billions, even hundreds of 527 00:34:20,239 --> 00:34:24,360 Speaker 2: billions of dollars going into artificial intelligence. Where should investors 528 00:34:24,400 --> 00:34:28,880 Speaker 2: be looking to really put money into artificial intelligence or 529 00:34:28,920 --> 00:34:31,120 Speaker 2: should they just be trying a lot of different things 530 00:34:31,400 --> 00:34:32,600 Speaker 2: hoping something pays off. 531 00:34:33,080 --> 00:34:36,640 Speaker 14: Well, if you're actually a qualified investor so that you 532 00:34:36,760 --> 00:34:39,400 Speaker 14: have enough money to sort of spread it around. I 533 00:34:39,400 --> 00:34:43,320 Speaker 14: would stick with things that have a very clear, defined 534 00:34:43,440 --> 00:34:48,279 Speaker 14: business case. So I mentioned the accounting right, or say, 535 00:34:48,360 --> 00:34:51,960 Speaker 14: taxes into it is worth a lot of money because 536 00:34:52,080 --> 00:34:56,160 Speaker 14: it uses AI to help you with your taxes. Clear 537 00:34:56,280 --> 00:34:59,000 Speaker 14: business case there, So look for other things like that 538 00:34:59,520 --> 00:35:05,879 Speaker 14: for discovery, for risk evaluation, things like that. One thing 539 00:35:06,000 --> 00:35:09,000 Speaker 14: not to do is assume that whatever it is that 540 00:35:09,040 --> 00:35:12,520 Speaker 14: they're building, this AI that they're building, will never make mistakes, 541 00:35:13,040 --> 00:35:16,960 Speaker 14: because it will. Everything makes mistakes sometimes, and you have 542 00:35:17,000 --> 00:35:18,879 Speaker 14: to make sure that the thing that you're doing when 543 00:35:18,920 --> 00:35:22,760 Speaker 14: it makes that mistake doesn't bankrupt the company. 544 00:35:24,640 --> 00:35:27,600 Speaker 2: Disney World has some new company has a wide array 545 00:35:27,640 --> 00:35:30,040 Speaker 2: of companies and brands try to follow the lead of 546 00:35:30,080 --> 00:35:33,319 Speaker 2: the dominant theme park company. That's next on Wall Street Week. 547 00:35:41,480 --> 00:35:45,360 Speaker 2: This is a story about making dreams come true. For years, 548 00:35:45,520 --> 00:35:49,400 Speaker 2: media and entertainment companies have used their intellectual property to 549 00:35:49,480 --> 00:35:54,080 Speaker 2: create unforgettable live experiences through theme parks, but their success 550 00:35:54,160 --> 00:35:58,600 Speaker 2: is attracting new competition from New Quarters College Scarlett Food. 551 00:35:58,760 --> 00:36:02,440 Speaker 2: As the story. 552 00:36:02,520 --> 00:36:06,120 Speaker 10: Summertime conjures up hot days, late nights, and roller coaster 553 00:36:06,239 --> 00:36:10,279 Speaker 10: rides and answering the call the themed entertainment industry, which 554 00:36:10,320 --> 00:36:13,440 Speaker 10: is currently worth an estimated seventy six billion dollars and 555 00:36:13,480 --> 00:36:15,800 Speaker 10: projected to reach more than one hundred and twenty billion 556 00:36:16,080 --> 00:36:21,200 Speaker 10: by twenty thirty three. The leaders Disney Universal, Merlin Entertainment, 557 00:36:21,239 --> 00:36:24,880 Speaker 10: and chime Long Group of China all generated experience revenues 558 00:36:24,920 --> 00:36:28,680 Speaker 10: in the billions last year, but Disney is a clear standout, 559 00:36:29,280 --> 00:36:32,400 Speaker 10: booking thirty four billion dollars in revenue alone, which is 560 00:36:32,440 --> 00:36:35,920 Speaker 10: almost three times the combined revenue of its smaller competitors, 561 00:36:36,080 --> 00:36:40,439 Speaker 10: and holding it all together fictional characters and immersive storytelling. 562 00:36:41,480 --> 00:36:46,440 Speaker 15: In intellectual property really has become the cornerstone of the 563 00:36:46,480 --> 00:36:51,520 Speaker 15: modern theme park industry, and we've seen them grow exponentially 564 00:36:51,600 --> 00:36:52,440 Speaker 15: through the years. 565 00:36:53,000 --> 00:36:55,640 Speaker 10: Dennis Spiegel is a theme park expert who's been working 566 00:36:55,640 --> 00:36:57,520 Speaker 10: in the industry for more than fifty years. 567 00:36:57,680 --> 00:37:02,160 Speaker 15: There have been some very interesting situations developed through the years. 568 00:37:02,560 --> 00:37:10,880 Speaker 15: Disney bought Marvel, Spider Man, Ironman, all of those wonderful characters. 569 00:37:11,600 --> 00:37:17,600 Speaker 15: Those characters were already being used at Universal Studios, Florida, 570 00:37:17,800 --> 00:37:21,520 Speaker 15: a couple of miles away from Disney World. So in 571 00:37:21,520 --> 00:37:26,240 Speaker 15: that agreement, Disney cannot use the Marvel characters in Orlando. 572 00:37:26,719 --> 00:37:32,719 Speaker 15: In England, there's a Harry Potter Studios tour which is 573 00:37:32,920 --> 00:37:38,440 Speaker 15: very close to where the Universal Studio park will be, 574 00:37:39,160 --> 00:37:42,239 Speaker 15: but at this point in time, they haven't announced if 575 00:37:42,520 --> 00:37:45,840 Speaker 15: Harry Potter is going to be allowed to be used 576 00:37:46,160 --> 00:37:46,480 Speaker 15: in that. 577 00:37:47,080 --> 00:37:50,520 Speaker 10: Now other entertainment companies want in on the action, leveraging 578 00:37:50,520 --> 00:37:51,719 Speaker 10: their most popular ip. 579 00:37:52,680 --> 00:37:54,560 Speaker 11: So my favorite shows are net Place and have been 580 00:37:54,600 --> 00:37:55,040 Speaker 11: real long time. 581 00:37:55,120 --> 00:37:56,399 Speaker 4: But people hear you bring the energy. 582 00:37:56,600 --> 00:37:57,520 Speaker 13: I love Netflix. 583 00:37:57,560 --> 00:37:59,240 Speaker 16: I've obsessed with Stranger. 584 00:37:58,840 --> 00:38:02,600 Speaker 11: Things, Swinging Winter, anything and everything they relate. 585 00:38:02,840 --> 00:38:05,640 Speaker 17: We realized there's really a way here to bring fans 586 00:38:05,640 --> 00:38:08,840 Speaker 17: closer to the stories that they love through live experiences. 587 00:38:09,560 --> 00:38:13,040 Speaker 10: As Netflix expands its library of original content, the streaming 588 00:38:13,080 --> 00:38:16,920 Speaker 10: company is looking beyond its platform. Since twenty twenty, Netflix 589 00:38:16,960 --> 00:38:19,680 Speaker 10: has incorporated characters from some of its biggest hits into 590 00:38:19,719 --> 00:38:23,960 Speaker 10: live experiences, culminating in permanent themed entertainment centers. 591 00:38:24,520 --> 00:38:28,359 Speaker 17: I'd consider Netflix House like a totally new dimension of storytelling, 592 00:38:28,600 --> 00:38:31,560 Speaker 17: because we'll be able to really keep it fresh, you know, 593 00:38:31,600 --> 00:38:34,680 Speaker 17: and sort of maintain that same case of cultural impact 594 00:38:34,719 --> 00:38:38,240 Speaker 17: and conversation that people see from our movies and TV shows. 595 00:38:38,560 --> 00:38:42,359 Speaker 10: Josh Simon is Netflix's Vice president of Consumer Products. He's 596 00:38:42,400 --> 00:38:44,680 Speaker 10: in charge of a new theme park style venture called 597 00:38:44,760 --> 00:38:45,560 Speaker 10: Netflix House. 598 00:38:46,280 --> 00:38:49,920 Speaker 17: Later this year, we'll open our first two Netflix House locations, 599 00:38:49,960 --> 00:38:53,600 Speaker 17: one at the King of Prussia Mall outside of Philadelphia 600 00:38:53,640 --> 00:38:57,160 Speaker 17: and one at the Galleria in Dallas. We recently announced 601 00:38:57,200 --> 00:38:59,200 Speaker 17: that we're also going to be opening a location in 602 00:38:59,239 --> 00:39:01,560 Speaker 17: Las Vegas in twenty twenty seven as well. 603 00:39:01,719 --> 00:39:05,560 Speaker 16: All of those experiences are about engaging with fans and 604 00:39:05,560 --> 00:39:08,440 Speaker 16: then taking all that information and saying, okay, we are 605 00:39:08,560 --> 00:39:11,440 Speaker 16: ready to launch permanent experiences. 606 00:39:12,480 --> 00:39:15,240 Speaker 10: Marion Lee is Netflix's chief marketing officer. 607 00:39:15,640 --> 00:39:18,680 Speaker 16: We'll have Replay, which is sort of that concept of 608 00:39:18,719 --> 00:39:22,440 Speaker 16: an old school arcade, but it will be all obviously 609 00:39:22,560 --> 00:39:25,600 Speaker 16: Netflix shows and movies and games related to that. 610 00:39:25,840 --> 00:39:30,480 Speaker 17: A Netflix bites, restaurant and bar, a retail store, a theater, 611 00:39:30,960 --> 00:39:31,520 Speaker 17: and then. 612 00:39:31,400 --> 00:39:34,480 Speaker 16: We'll have a mini golf squid game and Wednesday and 613 00:39:34,520 --> 00:39:36,920 Speaker 16: one and then one Piece and something else and the 614 00:39:37,000 --> 00:39:38,399 Speaker 16: other and stranger things. 615 00:39:38,520 --> 00:39:41,839 Speaker 17: It's really a great way for fans to experience those 616 00:39:41,880 --> 00:39:45,320 Speaker 17: like hero moments from their favorite Netflix movies and TV shows. 617 00:39:45,840 --> 00:39:49,200 Speaker 16: We are not trying to fit ourselves into like one box. 618 00:39:49,840 --> 00:39:52,360 Speaker 10: Netflix does not break out sales of consumer products and 619 00:39:52,400 --> 00:39:55,640 Speaker 10: live experiences, but in twenty twenty four, the company surpassed 620 00:39:55,640 --> 00:39:59,360 Speaker 10: three hundred million paying memberships, grew revenue by sixteen percent, 621 00:39:59,600 --> 00:40:02,600 Speaker 10: while it's operating income exceeded ten billion dollars for the 622 00:40:02,640 --> 00:40:06,000 Speaker 10: first time ever. And in the past five years, Netflix 623 00:40:06,000 --> 00:40:08,720 Speaker 10: has created more than four hundred experiences in three hundred 624 00:40:08,760 --> 00:40:11,720 Speaker 10: plus cities across the globe. In a world of screens, 625 00:40:11,880 --> 00:40:14,880 Speaker 10: live experiences appear to be in demand, but will they 626 00:40:14,880 --> 00:40:17,080 Speaker 10: sustain viewers' interest over the longer term. 627 00:40:17,440 --> 00:40:20,520 Speaker 17: Well, we're thinking about which live experiences to bring to life. 628 00:40:20,760 --> 00:40:23,600 Speaker 17: There's there's usually a couple of ways we think about it. First, 629 00:40:23,760 --> 00:40:27,920 Speaker 17: is we really follow fan passion. We see this incredible 630 00:40:27,960 --> 00:40:31,040 Speaker 17: love for stories all over the world. The other thing 631 00:40:31,080 --> 00:40:33,880 Speaker 17: is we really look for our experiences to tell a 632 00:40:33,920 --> 00:40:36,840 Speaker 17: new dimension of a story. So you know, we're interested 633 00:40:36,920 --> 00:40:39,000 Speaker 17: in movies and TV shows that we know fans want 634 00:40:39,080 --> 00:40:40,400 Speaker 17: to explore in new ways. 635 00:40:40,880 --> 00:40:47,120 Speaker 16: One of the key critical things that allows us to 636 00:40:47,320 --> 00:40:51,680 Speaker 16: really set ourselves apart is that we have a rabid 637 00:40:51,800 --> 00:40:56,080 Speaker 16: fan base. We have one point two billion fans across 638 00:40:56,160 --> 00:40:58,880 Speaker 16: all of our social media accounts around the world, and 639 00:40:59,000 --> 00:41:02,279 Speaker 16: they are telling us what they want to do. We 640 00:41:02,360 --> 00:41:05,560 Speaker 16: can hear what they're talking about, what kinds of products 641 00:41:05,640 --> 00:41:08,760 Speaker 16: they're buying, what kinds of food that they're eating, whenever 642 00:41:08,800 --> 00:41:11,360 Speaker 16: they go, and then it allows us to take that 643 00:41:11,440 --> 00:41:16,480 Speaker 16: information and invest into future experiences that we can place 644 00:41:16,560 --> 00:41:17,480 Speaker 16: all around the world. 645 00:41:18,520 --> 00:41:21,560 Speaker 10: Even before Netflix entered the picture, the theme park industry 646 00:41:21,880 --> 00:41:24,800 Speaker 10: was a kind of survival of the fittest scenario, smaller 647 00:41:24,800 --> 00:41:28,000 Speaker 10: companies struggling to keep up with changing consumer tastes, the 648 00:41:28,000 --> 00:41:31,520 Speaker 10: biggest players under pressure to roll out new attractions highlighting 649 00:41:31,560 --> 00:41:35,720 Speaker 10: the latest technology, and everyone, no matter their size, spending 650 00:41:35,760 --> 00:41:38,840 Speaker 10: continuously to give visitors a reason to keep coming back. 651 00:41:39,480 --> 00:41:45,640 Speaker 15: Typically a part will fail because either the market isn't ready, 652 00:41:46,560 --> 00:41:50,040 Speaker 15: it's not a good concept. I tell a lot of 653 00:41:50,120 --> 00:41:53,400 Speaker 15: people in our industry just because you have an idea, 654 00:41:53,440 --> 00:41:56,080 Speaker 15: it doesn't mean it's a good one. And we've seen 655 00:41:56,120 --> 00:41:58,280 Speaker 15: the good, the bad, and the ugly of theme parks. 656 00:41:58,360 --> 00:42:00,880 Speaker 10: What are the big guys not understand? What do they 657 00:42:00,920 --> 00:42:01,520 Speaker 10: get wrong? 658 00:42:02,320 --> 00:42:05,839 Speaker 18: Historically the local amusement park went from being a two 659 00:42:05,880 --> 00:42:08,840 Speaker 18: to ninety two family park to a thrill park. I 660 00:42:08,880 --> 00:42:12,239 Speaker 18: think our industry got addicted to the growth that a 661 00:42:12,360 --> 00:42:16,080 Speaker 18: roller coaster growths. But what happened was it really changed 662 00:42:16,120 --> 00:42:19,680 Speaker 18: the demographic of the park. They reduced the amount of entertainment, 663 00:42:19,719 --> 00:42:23,120 Speaker 18: They reduced the amount of show. The culinary experience was 664 00:42:23,160 --> 00:42:26,080 Speaker 18: reduced because they were getting the growth by just focusing 665 00:42:26,120 --> 00:42:29,359 Speaker 18: on roller coasters and thrill rides. And so now they've 666 00:42:29,400 --> 00:42:32,200 Speaker 18: kind of maxed out where the thrill ride can take them. 667 00:42:32,320 --> 00:42:34,600 Speaker 18: And you've seen this with six Flags and some of 668 00:42:34,640 --> 00:42:37,120 Speaker 18: the changes they're trying to make to move back towards 669 00:42:37,120 --> 00:42:40,080 Speaker 18: broader family experiences. So I would say there were some 670 00:42:40,160 --> 00:42:42,840 Speaker 18: mistakes made that brought them to where they are today. 671 00:42:43,560 --> 00:42:46,320 Speaker 10: COVID nineteen dealt a big blow to theme parks, forcing 672 00:42:46,360 --> 00:42:49,200 Speaker 10: them to shut down for weeks and sometimes months. And 673 00:42:49,239 --> 00:42:52,680 Speaker 10: that's exactly when Netflix made its move into live experiences. 674 00:42:53,200 --> 00:42:56,200 Speaker 17: We were looking for a way to bring a stranger 675 00:42:56,280 --> 00:42:59,719 Speaker 17: things to life. People were spending a lot of time 676 00:43:00,600 --> 00:43:03,239 Speaker 17: on their own in their cars. We took over a 677 00:43:03,239 --> 00:43:06,520 Speaker 17: couple hundred thousand square foot parking garage downtown LA and 678 00:43:06,560 --> 00:43:10,280 Speaker 17: basically created like a pop up theme park attraction. 679 00:43:10,800 --> 00:43:13,560 Speaker 15: Well, we haven't seen this really. I mean, this is 680 00:43:13,760 --> 00:43:18,360 Speaker 15: our entertainment industry. From that standpoint, the streaming is really changing. 681 00:43:18,440 --> 00:43:21,600 Speaker 15: It's bringing us that shorter story. 682 00:43:21,480 --> 00:43:25,000 Speaker 18: For our industry. It really is about how do we 683 00:43:25,239 --> 00:43:28,080 Speaker 18: define ourselves as a live experience. There's a lot of 684 00:43:28,080 --> 00:43:31,320 Speaker 18: people who feel that virtual experiences are going to become 685 00:43:31,320 --> 00:43:34,080 Speaker 18: bigger than real life experiences, and so we've got to 686 00:43:34,120 --> 00:43:36,360 Speaker 18: make sure that we continue to make great experiences so 687 00:43:36,400 --> 00:43:38,000 Speaker 18: that doesn't really happen. 688 00:43:39,400 --> 00:43:42,799 Speaker 10: Andrew Wexler is CEO of Hershant, the largest family owned 689 00:43:42,800 --> 00:43:46,400 Speaker 10: a theme attractions company in North America. Hershan's first attraction 690 00:43:46,560 --> 00:43:49,760 Speaker 10: was Silver Dollar City in Branson, Missouri, in nineteen sixty. 691 00:43:50,320 --> 00:43:53,360 Speaker 10: It has since built a portfolio of family friendly entertainment 692 00:43:53,400 --> 00:43:57,239 Speaker 10: brands from the Harlem Globetrotters exhibition basketball team to Dollywood 693 00:43:57,239 --> 00:44:00,920 Speaker 10: in the Great Smoky Mountains in Tennessee. Interest in Netflix. 694 00:44:01,040 --> 00:44:04,239 Speaker 10: Hershan's Silver Dollar City features IP that's tied to its 695 00:44:04,320 --> 00:44:08,360 Speaker 10: local history. Starting with a cave. How did a cave 696 00:44:08,640 --> 00:44:10,239 Speaker 10: spawn a theme park? 697 00:44:10,800 --> 00:44:12,879 Speaker 18: Hugo Mary Hershon went on a road trip. They came 698 00:44:12,920 --> 00:44:15,160 Speaker 18: to southwest Missouri to the Ozarks to enjoy the beauty, 699 00:44:15,600 --> 00:44:18,759 Speaker 18: and they did a cave tour here and really fell 700 00:44:18,800 --> 00:44:21,400 Speaker 18: in love with location, with the cave, with the people, 701 00:44:21,840 --> 00:44:24,200 Speaker 18: and decided they wanted to make it a summer attraction. 702 00:44:24,360 --> 00:44:26,600 Speaker 18: So the cave tour was so popular that there were 703 00:44:26,640 --> 00:44:28,839 Speaker 18: long lines to get in the cave, and they needed 704 00:44:28,880 --> 00:44:30,960 Speaker 18: to give some people something to do. It's kind of 705 00:44:30,960 --> 00:44:33,480 Speaker 18: the first instance of line management, So they built this 706 00:44:33,520 --> 00:44:35,719 Speaker 18: eighteen eighties town on top of the cave so people 707 00:44:35,760 --> 00:44:36,560 Speaker 18: can be entertained. 708 00:44:39,280 --> 00:44:42,239 Speaker 10: Since the nineteen seventies, Hershant has focused on bringing new 709 00:44:42,280 --> 00:44:45,160 Speaker 10: live shows and rides to Silver Dollar City while keeping 710 00:44:45,160 --> 00:44:48,480 Speaker 10: its IP rooted in the area's eighteen eighties lore. As 711 00:44:48,480 --> 00:44:51,839 Speaker 10: a result, the park feels timeless, which is reinforced by 712 00:44:51,840 --> 00:44:52,960 Speaker 10: its long serving staff. 713 00:44:53,000 --> 00:44:55,240 Speaker 2: I've been the vice president of FEUDU service since nineteen 714 00:44:55,320 --> 00:44:57,719 Speaker 2: ninety two, and this is my fiftieth year. 715 00:44:57,760 --> 00:44:59,719 Speaker 4: I've started from the ground up and I'm still here. 716 00:45:00,120 --> 00:45:02,879 Speaker 10: It's also got a cult following, with local families making 717 00:45:02,920 --> 00:45:06,759 Speaker 10: regular pilgrimages generation after generation. All I know is for 718 00:45:06,920 --> 00:45:10,399 Speaker 10: my eighth birthday, that was we went that day. 719 00:45:10,680 --> 00:45:12,680 Speaker 4: It was my one hundred and eighth time building. 720 00:45:12,800 --> 00:45:14,680 Speaker 17: I think, and I remember a lot of my childhood 721 00:45:14,680 --> 00:45:15,160 Speaker 17: coming back. 722 00:45:15,200 --> 00:45:17,040 Speaker 12: They have some rides of six Flags, but these rides 723 00:45:17,080 --> 00:45:17,960 Speaker 12: are like really fun. 724 00:45:18,480 --> 00:45:21,560 Speaker 16: We've been coming since we were little ourselves, Like, I 725 00:45:21,560 --> 00:45:23,840 Speaker 16: don't even remember my first time coming. 726 00:45:24,160 --> 00:45:25,520 Speaker 4: Yeah, how do I remember my first time? 727 00:45:25,640 --> 00:45:27,360 Speaker 7: It's just been always part of our lives. 728 00:45:27,480 --> 00:45:30,080 Speaker 18: If you look at most theme parks across America, they 729 00:45:30,239 --> 00:45:33,640 Speaker 18: were organic. They start off as a petting zoo or 730 00:45:33,640 --> 00:45:37,120 Speaker 18: a campground, and then they added rides and slowly grew 731 00:45:37,160 --> 00:45:41,239 Speaker 18: over time. Most successful theme parks are like that. It's 732 00:45:41,239 --> 00:45:43,759 Speaker 18: really hard to go from zero to one hundred at 733 00:45:43,760 --> 00:45:45,960 Speaker 18: a theme park today just because of the capital intensity 734 00:45:46,320 --> 00:45:49,200 Speaker 18: and the ability to actually draw enough people to make 735 00:45:49,200 --> 00:45:50,320 Speaker 18: it in cash flow positive. 736 00:45:50,600 --> 00:45:54,040 Speaker 10: So you're continuously reinvesting in the business, how do you 737 00:45:54,040 --> 00:45:55,400 Speaker 10: think about return on investment? 738 00:45:55,520 --> 00:45:58,160 Speaker 18: So we know what the return is that our shareholders 739 00:45:58,200 --> 00:46:02,359 Speaker 18: would like on the business. We incorporate that in our 740 00:46:02,400 --> 00:46:05,439 Speaker 18: capital plans, so we actually we do long range plans 741 00:46:05,520 --> 00:46:07,799 Speaker 18: to we try and identify what are our projects over 742 00:46:07,840 --> 00:46:10,080 Speaker 18: the next ten years. Now, you've got to be nimble 743 00:46:10,080 --> 00:46:13,440 Speaker 18: and flexible. It may change. But within that, what's the 744 00:46:13,480 --> 00:46:15,560 Speaker 18: impact of that investment and how's it going to grow 745 00:46:15,640 --> 00:46:17,800 Speaker 18: the park? From an attendance perspective. 746 00:46:17,560 --> 00:46:21,600 Speaker 10: I think about bigger competitors or peers. Universal it engages 747 00:46:21,640 --> 00:46:24,279 Speaker 10: in an IP review every two to three years, and 748 00:46:24,360 --> 00:46:26,799 Speaker 10: it looks critically at its own properties. That also does 749 00:46:26,920 --> 00:46:31,759 Speaker 10: an overall assessment of the media landscape. What does that 750 00:46:31,840 --> 00:46:33,040 Speaker 10: look like on your end? 751 00:46:33,160 --> 00:46:35,640 Speaker 18: It's about gaps and needs. The IP is just one 752 00:46:35,719 --> 00:46:38,879 Speaker 18: element of the experience. What are the frictions that make 753 00:46:38,920 --> 00:46:42,200 Speaker 18: it hard to enjoy the park? Waiting in line, having 754 00:46:42,239 --> 00:46:45,440 Speaker 18: to walk certain distance from one place to another. How 755 00:46:45,440 --> 00:46:48,480 Speaker 18: do you improve that sort of experience? So, while it's 756 00:46:48,520 --> 00:46:50,880 Speaker 18: great they do an IP review for us, it's about 757 00:46:50,960 --> 00:46:53,440 Speaker 18: experience review and how do we make the experience better. 758 00:46:53,800 --> 00:47:00,839 Speaker 15: Theme parks live on repeat visitation, and repeat visitation is 759 00:47:00,920 --> 00:47:04,600 Speaker 15: generated by what we call capex, the dollars that we 760 00:47:04,640 --> 00:47:09,440 Speaker 15: invest every year. So the new rides and attractions that 761 00:47:09,520 --> 00:47:12,959 Speaker 15: we put in every year bring the people back. 762 00:47:13,120 --> 00:47:15,920 Speaker 10: But this is a capital intensive business, so how do 763 00:47:15,960 --> 00:47:17,800 Speaker 10: you plan out how much you're going to spend it. 764 00:47:17,920 --> 00:47:21,160 Speaker 18: Well, fortunately, our business does generate cash, and so we 765 00:47:21,239 --> 00:47:23,920 Speaker 18: have a set percentage of the cash that we generate 766 00:47:23,960 --> 00:47:25,200 Speaker 18: each year that we know is going to go back 767 00:47:25,200 --> 00:47:28,399 Speaker 18: into capital. So really the debt part is irrelevant when 768 00:47:28,400 --> 00:47:30,960 Speaker 18: it comes to our capex unless we wanted to make 769 00:47:31,000 --> 00:47:35,320 Speaker 18: an acquisition or do something that was above and beyond. 770 00:47:37,360 --> 00:47:41,120 Speaker 18: We really are about that live local experience, with the 771 00:47:41,200 --> 00:47:43,560 Speaker 18: idea that if our purpose is the companies that bring 772 00:47:43,560 --> 00:47:46,920 Speaker 18: families closer together, having somebody necessarily sit in front of 773 00:47:47,000 --> 00:47:50,839 Speaker 18: television is not the best way to do that. 774 00:47:50,840 --> 00:47:52,600 Speaker 2: That does it for us Here at Wall Street Week, 775 00:47:52,800 --> 00:47:56,160 Speaker 2: I'm David Weston. See you next week for more stories 776 00:47:56,239 --> 00:47:59,840 Speaker 2: of capitalism.