1 00:00:12,920 --> 00:00:15,960 Speaker 1: This is Wall Street Week. I'm David Weston, bringing you 2 00:00:16,120 --> 00:00:20,840 Speaker 1: stories of capitalism playing dice with the universe, the strange 3 00:00:20,920 --> 00:00:24,160 Speaker 1: new world of quantum computing and how it may change 4 00:00:24,239 --> 00:00:28,480 Speaker 1: our lives even more than AI plus, coming to terms 5 00:00:28,480 --> 00:00:32,560 Speaker 1: with growing older and lower interest rates as Western nations 6 00:00:32,600 --> 00:00:35,720 Speaker 1: face growing problems providing for the elderly. We take a 7 00:00:35,720 --> 00:00:38,440 Speaker 1: look at the largest set of pension assets in Europe 8 00:00:38,560 --> 00:00:41,479 Speaker 1: and why the Dutch are changing the way they invest 9 00:00:41,520 --> 00:00:46,199 Speaker 1: those assets and turning concerns about data center energy consumption 10 00:00:46,360 --> 00:00:49,400 Speaker 1: into a way to heat our houses. That's what they're 11 00:00:49,440 --> 00:00:53,160 Speaker 1: doing in Finland. But we start with banking and how 12 00:00:53,240 --> 00:00:56,480 Speaker 1: regulators in Europe and the United States are taking increasingly 13 00:00:56,520 --> 00:01:02,240 Speaker 1: different approaches, creating both opportunities and challenges for Annaboutem, executive 14 00:01:02,280 --> 00:01:07,880 Speaker 1: chairman of Spain's leading bank, Santander Bacos. Santander has had 15 00:01:08,000 --> 00:01:11,080 Speaker 1: a big year. Give us a sense of how big 16 00:01:11,080 --> 00:01:11,960 Speaker 1: a year it's been. 17 00:01:12,480 --> 00:01:15,319 Speaker 2: It's been a great year. Our numbers will be totally 18 00:01:15,400 --> 00:01:17,520 Speaker 2: on track to deliver all the numbers in our three 19 00:01:17,600 --> 00:01:20,280 Speaker 2: year plan, and again in twenty five we're going to 20 00:01:20,319 --> 00:01:24,520 Speaker 2: reach our profitability sixteen and a half percent. And for shareholders, 21 00:01:24,680 --> 00:01:29,680 Speaker 2: you know great value creation, increasing different per share. Our 22 00:01:29,720 --> 00:01:32,600 Speaker 2: share price is up one hundred percent, but there's still 23 00:01:32,640 --> 00:01:35,800 Speaker 2: a lot of inherent value in our stock. Our multiples 24 00:01:35,840 --> 00:01:38,560 Speaker 2: are still very attractive compared to US banks. For example, 25 00:01:38,560 --> 00:01:42,520 Speaker 2: we're training a bit under ten times price earnings, and 26 00:01:42,600 --> 00:01:45,320 Speaker 2: we deserve a premium to Europe and I would say 27 00:01:45,360 --> 00:01:48,680 Speaker 2: even to the US banks because our profitability is getting 28 00:01:48,720 --> 00:01:50,640 Speaker 2: better and we have growth. 29 00:01:50,920 --> 00:01:53,120 Speaker 1: What were the main drivers of the success you've had 30 00:01:53,240 --> 00:01:53,720 Speaker 1: this year? 31 00:01:54,760 --> 00:01:57,600 Speaker 2: So I say it's an overnight success, ten years in 32 00:01:57,640 --> 00:02:01,480 Speaker 2: the making. So since I took over inherited a group 33 00:02:01,520 --> 00:02:05,480 Speaker 2: of banks, it was a big bank, but many different geographies, 34 00:02:05,520 --> 00:02:10,360 Speaker 2: different business models, very disconnected and the whole vision is 35 00:02:10,400 --> 00:02:12,720 Speaker 2: to bring them all together and they are a single, 36 00:02:12,960 --> 00:02:16,079 Speaker 2: open financial services platform and that's what we have been 37 00:02:16,120 --> 00:02:19,240 Speaker 2: working on. So this year, every single one of our 38 00:02:19,280 --> 00:02:23,400 Speaker 2: five businesses is growing. We have simplified the organization. We 39 00:02:23,520 --> 00:02:27,960 Speaker 2: sold Poland we bought in the UK, so UK business 40 00:02:28,000 --> 00:02:32,800 Speaker 2: now is at scale and this is really the opportunity. 41 00:02:32,800 --> 00:02:36,079 Speaker 2: At Santandre we have profitable growth for many years. 42 00:02:36,480 --> 00:02:40,440 Speaker 1: Organically sometime there succeeded in selling half of its Polish 43 00:02:40,520 --> 00:02:44,360 Speaker 1: unit this year, while other European banks, including UniCredit and 44 00:02:44,480 --> 00:02:49,200 Speaker 1: BBVA had a tough time getting deals done. As you say, 45 00:02:49,280 --> 00:02:52,600 Speaker 1: you sold Poland, you bought in the UK. There were 46 00:02:52,680 --> 00:02:55,280 Speaker 1: other banks in Europe that tried to do transactions this 47 00:02:55,360 --> 00:02:57,720 Speaker 1: year that didn't go so well. How come you got 48 00:02:57,760 --> 00:03:00,440 Speaker 1: it done well? Y? 49 00:03:00,480 --> 00:03:03,040 Speaker 2: You know, the stale of Poland was the largest cross 50 00:03:03,040 --> 00:03:07,160 Speaker 2: border m and A in Europe in a decade. And 51 00:03:07,919 --> 00:03:11,960 Speaker 2: in today's world, where governments defend their countries and you know, 52 00:03:12,040 --> 00:03:15,760 Speaker 2: regulation is what it is, friendly deals are the way 53 00:03:15,760 --> 00:03:18,040 Speaker 2: to go. And so I believe that's a secret. 54 00:03:19,040 --> 00:03:21,639 Speaker 1: As you say, bacosana there as you inherit it is 55 00:03:21,639 --> 00:03:24,800 Speaker 1: pretty far flung. I mean, you've got obviously Spain, you've 56 00:03:24,840 --> 00:03:28,360 Speaker 1: got Europe, You've got UK, you've got US, Mexico, Brazil. 57 00:03:29,320 --> 00:03:33,040 Speaker 1: How much is that helping baccos on there? That diversification. 58 00:03:34,040 --> 00:03:38,600 Speaker 2: So in today's economy, either you're large and you have 59 00:03:38,640 --> 00:03:41,960 Speaker 2: global scale, or you're very specialized and we have the scale. 60 00:03:42,160 --> 00:03:43,960 Speaker 2: We're one of the largest banks in the world by 61 00:03:44,000 --> 00:03:46,280 Speaker 2: number of customers one hundred and eighty million. That's more 62 00:03:46,320 --> 00:03:48,920 Speaker 2: than the number one and number two bank in the 63 00:03:49,000 --> 00:03:53,040 Speaker 2: United States together. We have added sixty million customers in 64 00:03:53,040 --> 00:03:55,760 Speaker 2: the last ten years. And so you know that scale 65 00:03:56,680 --> 00:03:59,560 Speaker 2: t to benefit from that scale, to have the operating leverage, 66 00:03:59,600 --> 00:04:02,760 Speaker 2: you need to work across the company. You cannot just 67 00:04:02,840 --> 00:04:06,440 Speaker 2: work separately by business or by geographies. 68 00:04:07,000 --> 00:04:09,720 Speaker 1: One of your goals has been efficiency increasing the Efficiency Bank. 69 00:04:09,960 --> 00:04:12,760 Speaker 1: How much success have you had, how much further can 70 00:04:12,760 --> 00:04:13,240 Speaker 1: you take it? 71 00:04:13,480 --> 00:04:16,320 Speaker 2: We're only just scratching the surface of our potential as 72 00:04:16,320 --> 00:04:19,120 Speaker 2: a group. We have gravity, our cooperating system. We have 73 00:04:19,160 --> 00:04:24,320 Speaker 2: our payments core system, which is allowing us to reduce 74 00:04:24,480 --> 00:04:27,240 Speaker 2: cost per transaction in the last few years by a third. 75 00:04:27,839 --> 00:04:30,040 Speaker 2: What is now coming is what you as a customer 76 00:04:30,080 --> 00:04:31,880 Speaker 2: are going to see, which is the Open Bank. The 77 00:04:31,920 --> 00:04:35,640 Speaker 2: front end this year will have flat to downcost and 78 00:04:35,720 --> 00:04:39,159 Speaker 2: growing top line and this should continue into the next 79 00:04:39,160 --> 00:04:43,040 Speaker 2: few years. And again organically, you know, we are in 80 00:04:43,160 --> 00:04:45,960 Speaker 2: markets with one point two one point three billion people 81 00:04:46,240 --> 00:04:49,080 Speaker 2: where we are at scale in each one of them, 82 00:04:49,240 --> 00:04:54,000 Speaker 2: and building our own platforms is something that very few banks, 83 00:04:54,320 --> 00:04:56,080 Speaker 2: very few companies have in the world today. 84 00:04:56,720 --> 00:05:01,360 Speaker 1: One of Santantaier's strongest verticals is it's auto business, working 85 00:05:01,400 --> 00:05:04,920 Speaker 1: with dealerships at fourteen thousand points of sale as well 86 00:05:04,920 --> 00:05:07,400 Speaker 1: as through its digital platform Open Bank. 87 00:05:08,360 --> 00:05:12,040 Speaker 2: The last two years delinquencies were very low during COVID 88 00:05:12,279 --> 00:05:16,080 Speaker 2: have normalized, so they have been going up. But our 89 00:05:16,120 --> 00:05:19,880 Speaker 2: final loss rate is actually stable over the last twelve months, 90 00:05:20,520 --> 00:05:24,880 Speaker 2: and consumers are actually you know, getting up to date 91 00:05:24,920 --> 00:05:27,119 Speaker 2: on their loans even though they get a bit behind. 92 00:05:27,160 --> 00:05:30,760 Speaker 2: So the loss rates are stable and we're not seeing 93 00:05:31,160 --> 00:05:34,000 Speaker 2: anything right now that tells us the US consumer on 94 00:05:34,120 --> 00:05:37,760 Speaker 2: average at least is having any issues. It's very solid. 95 00:05:38,839 --> 00:05:41,560 Speaker 1: We see interest rates coming down in Europe. Now what 96 00:05:41,600 --> 00:05:44,320 Speaker 1: does that do to your bank and the banks generally. 97 00:05:45,279 --> 00:05:49,359 Speaker 2: So the way the terminal rate and you know, we 98 00:05:49,400 --> 00:05:51,839 Speaker 2: can have a debate about what that is in Europe 99 00:05:52,040 --> 00:05:54,400 Speaker 2: or in the US, given the size of a level 100 00:05:54,440 --> 00:05:59,600 Speaker 2: of government debt, given demographics, defence, spending, deg organization. You know, 101 00:05:59,640 --> 00:06:02,720 Speaker 2: we don't see that rate being below two percent in Europe, 102 00:06:02,920 --> 00:06:05,479 Speaker 2: probably below three in the United States something like that. 103 00:06:06,240 --> 00:06:08,799 Speaker 2: And that is a very good level for banks because 104 00:06:09,960 --> 00:06:11,960 Speaker 2: it is high enough for us to have a margin, 105 00:06:12,080 --> 00:06:15,719 Speaker 2: but not that high that the credit gets bad. Rates 106 00:06:15,760 --> 00:06:19,279 Speaker 2: are at a level that I think will allow growth 107 00:06:19,320 --> 00:06:23,200 Speaker 2: to remain around three percent globally right now. By the way, 108 00:06:23,240 --> 00:06:26,120 Speaker 2: that's not fast enough, but at least we're growing. 109 00:06:26,800 --> 00:06:30,400 Speaker 1: Regulation maybe one thing holding down growth in Europe. In 110 00:06:30,440 --> 00:06:34,040 Speaker 1: the last six years, the EU has added thirteen thousand 111 00:06:34,200 --> 00:06:37,560 Speaker 1: new banking rules. Well, the US came up with only 112 00:06:37,640 --> 00:06:41,560 Speaker 1: thirty five hundred. Give us your sense of regulation of 113 00:06:41,560 --> 00:06:44,120 Speaker 1: banks in Europe versus the United States. 114 00:06:44,360 --> 00:06:48,000 Speaker 2: Well, I think regulation, like life, is all about balance, right, 115 00:06:48,560 --> 00:06:52,599 Speaker 2: and so we do believe in smart regulation. But we've 116 00:06:52,640 --> 00:06:56,720 Speaker 2: gone way too far on certain items like capital. You know, 117 00:06:57,360 --> 00:07:00,400 Speaker 2: soundless of banks doesn't just depend on capital, as we've seen. 118 00:07:00,880 --> 00:07:02,440 Speaker 2: You know, if you look at the capital ratios of 119 00:07:02,520 --> 00:07:04,559 Speaker 2: some of the banks that had problems, sore pretty high. 120 00:07:05,000 --> 00:07:07,640 Speaker 2: And so we think against santandrev look at our CDs, 121 00:07:07,640 --> 00:07:09,320 Speaker 2: it's one of the best in the world, including the 122 00:07:09,360 --> 00:07:11,480 Speaker 2: best banks in the United States. Why because it's about 123 00:07:11,520 --> 00:07:16,120 Speaker 2: a strong balance sheet, liquidity, you know, scale, business model, 124 00:07:16,280 --> 00:07:20,920 Speaker 2: et cetera. So you know, we have gone as far 125 00:07:21,000 --> 00:07:22,800 Speaker 2: as I think we need to go on capital, and 126 00:07:22,840 --> 00:07:24,960 Speaker 2: now we need to be supporting growth. 127 00:07:25,720 --> 00:07:28,680 Speaker 1: Mario Dragging came out with a famous report. What's been 128 00:07:28,720 --> 00:07:29,480 Speaker 1: done with that report? 129 00:07:29,600 --> 00:07:32,240 Speaker 2: So the ambition is very high. Even if you don't 130 00:07:32,280 --> 00:07:34,440 Speaker 2: get to that, you're going to do pretty big things. 131 00:07:34,480 --> 00:07:36,040 Speaker 2: And so this is the thing in Europe. What is 132 00:07:36,080 --> 00:07:41,080 Speaker 2: our ambition for growth. Maria Dragi gave us a diagnosis. 133 00:07:41,160 --> 00:07:43,920 Speaker 2: How much have we executed? Not more than ten percent 134 00:07:44,120 --> 00:07:46,480 Speaker 2: in one year. So we have to have a much 135 00:07:46,520 --> 00:07:52,960 Speaker 2: greater ambition on delivering on those recommendations. I've said it publicly. 136 00:07:53,240 --> 00:07:57,720 Speaker 2: You know, if taxes every euro we make in Europe 137 00:07:58,120 --> 00:08:02,200 Speaker 2: fifty eight cents go to the government, every dollar we 138 00:08:02,280 --> 00:08:04,040 Speaker 2: make in the United States forty two, that's not a 139 00:08:04,080 --> 00:08:09,080 Speaker 2: small number, but it's you know, significantly lower. So excess regulation, 140 00:08:09,800 --> 00:08:14,520 Speaker 2: excess taxation actually is a tax on the economy and growth. 141 00:08:14,560 --> 00:08:17,680 Speaker 2: At some point people don't invest, and so this is 142 00:08:17,720 --> 00:08:21,360 Speaker 2: the balance we need to find. And Europe is getting 143 00:08:22,000 --> 00:08:25,120 Speaker 2: further apart from the United States not coming closer. 144 00:08:26,040 --> 00:08:29,040 Speaker 1: We also have regulation of banks at both the European 145 00:08:29,120 --> 00:08:32,840 Speaker 1: level and member state level. To what extent do member 146 00:08:32,880 --> 00:08:33,679 Speaker 1: state whole things back? 147 00:08:33,880 --> 00:08:36,000 Speaker 2: Well, and there's one thing you didn't mention. So there's 148 00:08:36,040 --> 00:08:38,959 Speaker 2: the regulation, and then that's the level two and three. 149 00:08:39,520 --> 00:08:40,959 Speaker 2: Here in the United States, there's a lot of talk 150 00:08:41,000 --> 00:08:44,120 Speaker 2: about the agencies. Clearly there's work to do in the 151 00:08:44,160 --> 00:08:47,120 Speaker 2: United States. In Europe there's even much more work to do, 152 00:08:47,280 --> 00:08:51,640 Speaker 2: right and I show at a conference on regulation only 153 00:08:51,679 --> 00:08:55,440 Speaker 2: financial services regulation without the rest of the interpretation of 154 00:08:55,480 --> 00:08:59,680 Speaker 2: the rules, which is thousands more ninety seven thousand lines, 155 00:08:59,720 --> 00:09:03,840 Speaker 2: which a hundred don quixotes. You know, I showed it there, 156 00:09:04,040 --> 00:09:06,800 Speaker 2: and so that is a second level. And then the 157 00:09:06,840 --> 00:09:10,200 Speaker 2: third is what you say, which is the national rules 158 00:09:10,400 --> 00:09:11,520 Speaker 2: and regulations. 159 00:09:11,920 --> 00:09:14,760 Speaker 1: How do you decide how to allocate your capital for 160 00:09:14,960 --> 00:09:18,199 Speaker 1: growth and to what extent is it affected by things 161 00:09:18,240 --> 00:09:21,400 Speaker 1: like the relative different in regulatory levels. 162 00:09:21,880 --> 00:09:25,319 Speaker 2: Well, that of course matters a lot, right if other 163 00:09:25,360 --> 00:09:28,640 Speaker 2: things equal, every dollar I put in Europe, you know 164 00:09:28,760 --> 00:09:31,160 Speaker 2: fifty eight of the profit goes to the state and 165 00:09:31,200 --> 00:09:34,680 Speaker 2: forty two in the United States, Well, you know Europe 166 00:09:34,720 --> 00:09:37,319 Speaker 2: is going to have to give me higher growth or 167 00:09:37,360 --> 00:09:40,000 Speaker 2: higher profitability of both for us other things equal to 168 00:09:40,040 --> 00:09:43,560 Speaker 2: go there. So yes, it matters a lot. 169 00:09:44,840 --> 00:09:49,120 Speaker 1: There's innovation and creativity in Europe, entrepreneurship in Europe. Do 170 00:09:49,200 --> 00:09:50,480 Speaker 1: the capital market support it. 171 00:09:50,960 --> 00:09:52,720 Speaker 2: We have been pushing for a long time for capital 172 00:09:52,760 --> 00:09:55,920 Speaker 2: markets union. We now have the Savings Union, which is 173 00:09:56,720 --> 00:10:00,880 Speaker 2: not exactly the same, but it's gonna be helpful. The 174 00:10:01,000 --> 00:10:06,160 Speaker 2: reality is that most of SME commercial lending comes from banks, 175 00:10:06,200 --> 00:10:09,760 Speaker 2: and that is why it's so existential and urgent that 176 00:10:09,800 --> 00:10:14,360 Speaker 2: we increase the ambition for change, because we will only 177 00:10:14,920 --> 00:10:17,760 Speaker 2: be more competitive if there's more investment. This is coming 178 00:10:17,760 --> 00:10:20,440 Speaker 2: from smaller, medium sized companies and a lot of that 179 00:10:20,559 --> 00:10:22,839 Speaker 2: lending comes from the banks, and that's why capacity to 180 00:10:22,920 --> 00:10:27,720 Speaker 2: lend has to expand. And that is what you know. Again, regulation, 181 00:10:28,480 --> 00:10:31,600 Speaker 2: smart regulation would be very helpful. 182 00:10:32,120 --> 00:10:35,679 Speaker 1: Is there any prospect of a unified banking regulatory system 183 00:10:35,720 --> 00:10:37,359 Speaker 1: in Europe? 184 00:10:38,160 --> 00:10:40,640 Speaker 2: Well, you know how many years did it take to 185 00:10:40,679 --> 00:10:44,360 Speaker 2: build the United States two hundred Europe we've been going 186 00:10:44,360 --> 00:10:47,680 Speaker 2: at this for fifty or sixty years, so it will happen. 187 00:10:48,320 --> 00:10:49,440 Speaker 2: I'm not sure I will see. 188 00:10:49,320 --> 00:10:53,199 Speaker 1: It coming up. We try to make sense of something 189 00:10:53,240 --> 00:10:56,760 Speaker 1: that Einstein threw up his hands, trying to understand quantum 190 00:10:56,840 --> 00:11:00,200 Speaker 1: mechanics and the revolution it may bring to computing by 191 00:11:00,240 --> 00:11:15,360 Speaker 1: doing some things better than AI. This is a story 192 00:11:15,360 --> 00:11:19,679 Speaker 1: about God playing dice with the universe, something Albert Einstein 193 00:11:19,720 --> 00:11:22,560 Speaker 1: told us he didn't do. Back in nineteen twenty six, 194 00:11:23,120 --> 00:11:27,960 Speaker 1: Einstein was criticizing physicists theory of quantum mechanics. Yet a 195 00:11:28,080 --> 00:11:32,160 Speaker 1: century after Einstein's denial, billions of dollars are being invested 196 00:11:32,200 --> 00:11:36,199 Speaker 1: today in taking that theory and turning it into reality, 197 00:11:36,600 --> 00:11:40,080 Speaker 1: with the prospect of a revolution in computing, potentially larger 198 00:11:40,200 --> 00:11:42,000 Speaker 1: even than generative AI. 199 00:11:43,960 --> 00:11:47,800 Speaker 3: Quantum computing is very high potential Inbastors are increasingly asking 200 00:11:47,920 --> 00:11:50,640 Speaker 3: us about the implications of quantum. 201 00:11:50,240 --> 00:11:55,840 Speaker 4: Computing, quantum computing, quantum computing, political and state level economic 202 00:11:55,880 --> 00:11:58,600 Speaker 4: supports to develop quantum and we want to be part 203 00:11:58,679 --> 00:11:58,880 Speaker 4: of that. 204 00:12:00,240 --> 00:12:03,000 Speaker 1: IBM is one of the companies leading the charge in 205 00:12:03,160 --> 00:12:04,160 Speaker 1: quantum computing. 206 00:12:04,679 --> 00:12:07,719 Speaker 5: Not IBM, we developed some of the very foundations of 207 00:12:07,800 --> 00:12:11,160 Speaker 5: quantum information science starting as early as nineteen seventy. 208 00:12:11,520 --> 00:12:15,479 Speaker 1: Jamie Garcia is the Director of Quantum Partnerships at IBM. 209 00:12:15,720 --> 00:12:20,240 Speaker 1: A PhD chemist, she's working on quantum computers transforming healthcare 210 00:12:20,520 --> 00:12:22,480 Speaker 1: at places like the Cleveland Clinic. 211 00:12:22,760 --> 00:12:27,040 Speaker 5: Quantum computers are just a totally different paradigm to calculate 212 00:12:27,080 --> 00:12:32,040 Speaker 5: solutions to problems, and so what most experts have done 213 00:12:32,440 --> 00:12:36,839 Speaker 5: today that are studying quantum computing for different application spaces 214 00:12:37,240 --> 00:12:40,040 Speaker 5: is to really sit down with the math and figure out, like, 215 00:12:40,120 --> 00:12:42,880 Speaker 5: are the algorithms here that I can use and that 216 00:12:43,040 --> 00:12:45,840 Speaker 5: I can exploit using a quantum computer going to bring 217 00:12:45,880 --> 00:12:49,280 Speaker 5: me any sort of advantage over what can be done 218 00:12:49,320 --> 00:12:52,959 Speaker 5: today in classical sort of state of the art techniques. 219 00:12:54,400 --> 00:12:58,280 Speaker 1: At the core of classical computing are bits, single pieces 220 00:12:58,280 --> 00:13:01,440 Speaker 1: of information that can have the value of zero or one, 221 00:13:02,160 --> 00:13:06,400 Speaker 1: But quantum technology relies on cubits, a unit that can 222 00:13:06,440 --> 00:13:10,760 Speaker 1: have multiple values simultaneously. It's like holding a coin in 223 00:13:10,800 --> 00:13:14,160 Speaker 1: your hand that is heads, tails and everything in between 224 00:13:14,600 --> 00:13:18,640 Speaker 1: until you open your hand to check. Physicist Jerry Chow 225 00:13:18,880 --> 00:13:22,240 Speaker 1: is IBM's director of Quantum Hardware System Development. 226 00:13:22,880 --> 00:13:26,880 Speaker 3: Really fundamentally, there's a different math, right's the mathematics of 227 00:13:27,000 --> 00:13:32,679 Speaker 3: quantum mechanics that is governing how you actually manipulate these 228 00:13:32,920 --> 00:13:36,400 Speaker 3: quantum bits, which then gives rise to a whole host 229 00:13:36,440 --> 00:13:41,520 Speaker 3: of different opportunities for algorithms and types of problems that 230 00:13:41,559 --> 00:13:43,320 Speaker 3: you can actually solve using quantum muters. 231 00:13:43,520 --> 00:13:47,160 Speaker 5: As we're studying things today, we're using a lot of 232 00:13:47,160 --> 00:13:50,640 Speaker 5: something called error mitigation as our approach to dealing with 233 00:13:50,800 --> 00:13:53,439 Speaker 5: errors and ways in the system and in the quantum 234 00:13:53,480 --> 00:13:57,240 Speaker 5: computer itself. This is going to continue to evolve. In fact, 235 00:13:57,320 --> 00:13:59,640 Speaker 5: we think that next year we're going to see examples 236 00:13:59,720 --> 00:14:02,520 Speaker 5: of what we call quantum advantage, which is where you're 237 00:14:02,600 --> 00:14:05,160 Speaker 5: able to come up with a solution to a problem 238 00:14:05,400 --> 00:14:09,680 Speaker 5: that is cheaper, faster, or more accurate than with classical alone. 239 00:14:10,559 --> 00:14:13,920 Speaker 1: A turning point in IBM's efforts to make quantum computing 240 00:14:13,960 --> 00:14:16,880 Speaker 1: a reality came when it made it available to the 241 00:14:16,920 --> 00:14:18,040 Speaker 1: world on the. 242 00:14:17,960 --> 00:14:19,480 Speaker 5: Cloud twenty sixteen. 243 00:14:19,760 --> 00:14:23,440 Speaker 3: The IBM Quantum Experience was really a pivotal moment for 244 00:14:23,600 --> 00:14:28,000 Speaker 3: us in terms of getting quantum computers for the first 245 00:14:28,000 --> 00:14:32,200 Speaker 3: time out onto the cloud and into the hands of anybody, 246 00:14:32,520 --> 00:14:36,000 Speaker 3: really people. Right. What's interesting is that before that period, 247 00:14:36,120 --> 00:14:39,280 Speaker 3: I'd say, it was really much more in the realm 248 00:14:39,360 --> 00:14:44,280 Speaker 3: of physics, right that we were doing experiments on small devices, 249 00:14:44,360 --> 00:14:47,760 Speaker 3: cubit devices that we were looking at, understanding how they worked, 250 00:14:47,920 --> 00:14:51,600 Speaker 3: trying to make them better, but we didn't have any 251 00:14:51,680 --> 00:14:54,480 Speaker 3: kind of real thought about how is this going to 252 00:14:54,480 --> 00:14:55,480 Speaker 3: be used for computation. 253 00:14:55,960 --> 00:14:59,080 Speaker 1: In the nine years since you put Quantum Experience out there, 254 00:14:59,160 --> 00:15:01,480 Speaker 1: what is what have you learned at IBM? 255 00:15:01,720 --> 00:15:04,160 Speaker 3: I think what I learned from that experience really was 256 00:15:04,240 --> 00:15:07,520 Speaker 3: that there was a whole lot of people out there 257 00:15:07,520 --> 00:15:10,520 Speaker 3: who wanted to touch and learn about quantum. I think 258 00:15:10,520 --> 00:15:12,720 Speaker 3: we were sitting there that first night after we launched it, 259 00:15:12,800 --> 00:15:16,840 Speaker 3: watching these circuits coming in and people were actually running things, 260 00:15:16,880 --> 00:15:18,920 Speaker 3: and we were like, oh wow, this is picking up 261 00:15:18,920 --> 00:15:22,160 Speaker 3: some steam here. And then you know, to this point, 262 00:15:22,200 --> 00:15:25,040 Speaker 3: we've had tremendous uptake in terms of using the platform 263 00:15:25,080 --> 00:15:29,280 Speaker 3: to actually generate new papers and research. Thousands of papers 264 00:15:29,280 --> 00:15:31,480 Speaker 3: have been generated which have been would have been impossible 265 00:15:31,480 --> 00:15:34,480 Speaker 3: for us to do, just as individual scientists or researchers 266 00:15:34,480 --> 00:15:37,120 Speaker 3: studying these devices in our own lab and working with 267 00:15:37,480 --> 00:15:40,280 Speaker 3: other scientists and collaborations, and. 268 00:15:40,320 --> 00:15:44,360 Speaker 1: In success, that community could go places that classical computing, 269 00:15:44,640 --> 00:15:48,080 Speaker 1: even using the large language models of AI, could never 270 00:15:48,240 --> 00:15:51,840 Speaker 1: take us. So it's not just speech, it's actual accuracy. 271 00:15:51,960 --> 00:15:56,080 Speaker 1: When we're using classical no matter how infinite we get, 272 00:15:56,320 --> 00:15:57,960 Speaker 1: it's an approximation. 273 00:15:57,480 --> 00:16:00,840 Speaker 3: Right, Absolutely, it's absolutely not just not not a question 274 00:16:00,880 --> 00:16:03,520 Speaker 3: about speed. The whole point of the quantum computer and 275 00:16:03,560 --> 00:16:05,360 Speaker 3: what it can do is that it can give us 276 00:16:05,400 --> 00:16:08,560 Speaker 3: the ability to actually get potentially more accurate results, also 277 00:16:08,880 --> 00:16:13,640 Speaker 3: get results that otherwise are unattainable using a classical computer alone. 278 00:16:14,800 --> 00:16:18,800 Speaker 1: Companies like Google, Microsoft, and Intel are all exploring the 279 00:16:18,800 --> 00:16:22,160 Speaker 1: potential of quantum computing, but there's also a new group 280 00:16:22,160 --> 00:16:25,320 Speaker 1: of contenders, startups that are betting it all on the 281 00:16:25,360 --> 00:16:28,920 Speaker 1: hope that quantum tech will one day become profitable. One 282 00:16:28,960 --> 00:16:32,800 Speaker 1: of those firms is Maryland based ion Q. Its CEO 283 00:16:33,000 --> 00:16:36,600 Speaker 1: is Nicolo Demasi, who believes he has the best horse 284 00:16:36,760 --> 00:16:37,360 Speaker 1: in the race. 285 00:16:38,120 --> 00:16:44,800 Speaker 6: We supply quantum computers to both federal, state and commercial 286 00:16:45,200 --> 00:16:49,480 Speaker 6: customer partners. We also provide quantum key distribution, and we 287 00:16:49,520 --> 00:16:52,560 Speaker 6: do that both on the ground and up in the heavens. 288 00:16:52,680 --> 00:16:56,760 Speaker 6: Quantum key dissolution is effectively quantum cyber security, and we're 289 00:16:56,840 --> 00:16:59,760 Speaker 6: very focused on this not being just proof points in 290 00:16:59,760 --> 00:17:03,880 Speaker 6: the lad lab, but doing useful quantum advantage examples for 291 00:17:03,960 --> 00:17:07,639 Speaker 6: our customers and embedding ourselves into their workflows on an 292 00:17:07,680 --> 00:17:08,480 Speaker 6: ongoing basis. 293 00:17:09,480 --> 00:17:11,760 Speaker 1: So what will it look like as we go beyond 294 00:17:11,760 --> 00:17:15,560 Speaker 1: showing so called quantum advantage in the lab and embedding 295 00:17:15,560 --> 00:17:19,439 Speaker 1: it into real world workflows. One place people look to 296 00:17:19,640 --> 00:17:23,280 Speaker 1: first is in the life sciences work like doctor Garcia 297 00:17:23,400 --> 00:17:25,080 Speaker 1: is doing at the Cleveland Clinic. 298 00:17:25,480 --> 00:17:28,560 Speaker 5: An example of something that we've done is we've taken 299 00:17:28,560 --> 00:17:31,879 Speaker 5: in some of the algorithms that we've worked on for chemistry, 300 00:17:32,440 --> 00:17:37,040 Speaker 5: and alongside Cleveland Clinic, we've started looking at different chemical 301 00:17:37,080 --> 00:17:40,360 Speaker 5: processes that they really care about. So you can think 302 00:17:40,400 --> 00:17:45,240 Speaker 5: about this in the larger context of therapeutics, design, drug discovery, 303 00:17:45,560 --> 00:17:47,679 Speaker 5: that kind of thing, and really what we're doing with 304 00:17:47,720 --> 00:17:53,640 Speaker 5: Cleveland Clinic is pushing the boundaries of algorithm development methodology 305 00:17:54,040 --> 00:17:59,280 Speaker 5: of using quantum computers, again in concert with classical computers 306 00:17:59,600 --> 00:18:03,679 Speaker 5: to come up with solutions to problems that they care about. 307 00:18:03,800 --> 00:18:08,720 Speaker 5: Protein folding is definitely one area mRNA Secondary structure. Understanding 308 00:18:09,160 --> 00:18:12,840 Speaker 5: how things come together and how they look in sort 309 00:18:12,840 --> 00:18:15,520 Speaker 5: of three D is a very interesting area, as you 310 00:18:15,520 --> 00:18:18,520 Speaker 5: can imagine as you're trying to understand how these things 311 00:18:18,600 --> 00:18:22,200 Speaker 5: fit together in a biological system. 312 00:18:22,400 --> 00:18:25,719 Speaker 1: It isn't just life sciences that could be revolutionized by 313 00:18:25,720 --> 00:18:29,959 Speaker 1: the addition of quantum computing. Financial markets are another target 314 00:18:30,000 --> 00:18:34,040 Speaker 1: of opportunity. IBM scored an early advantage this year when 315 00:18:34,240 --> 00:18:38,119 Speaker 1: HSBC said it used the tech company's Heron quantum processor 316 00:18:38,480 --> 00:18:41,480 Speaker 1: to make a thirty four percent improvement in predicting how 317 00:18:41,640 --> 00:18:44,040 Speaker 1: likely a bond will trade at a given price. 318 00:18:44,320 --> 00:18:46,040 Speaker 3: I think there's a lot of excitement in the market 319 00:18:46,160 --> 00:18:51,000 Speaker 3: space as well right especially because optimization is certainly in 320 00:18:51,040 --> 00:18:54,160 Speaker 3: another area which we know is a classically difficult problem, 321 00:18:55,040 --> 00:18:58,119 Speaker 3: and from the point of view of actually using a 322 00:18:58,200 --> 00:19:01,000 Speaker 3: quantum computer to address optimization, are many threads there in 323 00:19:01,119 --> 00:19:06,199 Speaker 3: terms of leveraging this kind of large, exponentially computational space. 324 00:19:06,280 --> 00:19:11,840 Speaker 3: To handle problems such as portfolio optimization right or risk management. 325 00:19:12,200 --> 00:19:15,040 Speaker 3: So there's a lot of interesting ideas there that are 326 00:19:15,080 --> 00:19:17,080 Speaker 3: being looked at by various financial institutions. 327 00:19:17,160 --> 00:19:20,760 Speaker 6: What I can say at this stage is portfolio theory, 328 00:19:20,920 --> 00:19:24,879 Speaker 6: options pricing. These are very much now accessible from a 329 00:19:24,920 --> 00:19:28,960 Speaker 6: quantum advantage perspective using our new tempo system, quantum key 330 00:19:29,000 --> 00:19:33,320 Speaker 6: distribution and cybersecurity that is of course front and center 331 00:19:33,359 --> 00:19:36,680 Speaker 6: for financial services on a global basis, and so security 332 00:19:36,680 --> 00:19:39,639 Speaker 6: and integrity of the data flow is of course vital. 333 00:19:40,440 --> 00:19:43,720 Speaker 6: I always like to jokingly say that you can spot 334 00:19:43,840 --> 00:19:46,960 Speaker 6: our quantum security customers because they are not in the 335 00:19:47,000 --> 00:19:48,720 Speaker 6: news for data breaches. 336 00:19:49,600 --> 00:19:53,240 Speaker 1: Even agriculture could benefit from quantum computing in ways we 337 00:19:53,359 --> 00:19:54,719 Speaker 1: haven't yet imagined. 338 00:19:55,440 --> 00:20:00,480 Speaker 3: Understanding processes such as nitrogen fixation to make things like 339 00:20:00,520 --> 00:20:03,680 Speaker 3: better fertilizer right to help us grow better crops right, 340 00:20:04,480 --> 00:20:09,320 Speaker 3: Understanding things that are critical in impacting climate change right 341 00:20:09,359 --> 00:20:13,920 Speaker 3: and in terms of how carbon is handled right, other 342 00:20:13,960 --> 00:20:19,200 Speaker 3: things including better batteries right in terms of materials discovery. 343 00:20:20,000 --> 00:20:23,399 Speaker 1: The potential may be great, as are the investments being made, 344 00:20:24,000 --> 00:20:27,600 Speaker 1: but when can we expect to see these potentially dramatic results. 345 00:20:28,240 --> 00:20:31,160 Speaker 1: It turns out that that depends on whom you ask. 346 00:20:31,760 --> 00:20:34,640 Speaker 1: IBM has made getting to quantum advantage in the real 347 00:20:34,680 --> 00:20:38,040 Speaker 1: world a strategic priority and has a timeline of getting 348 00:20:38,119 --> 00:20:40,600 Speaker 1: there in a big way by twenty twenty nine. 349 00:20:41,040 --> 00:20:44,080 Speaker 3: Our roadmap really shows the detail in terms of how 350 00:20:44,160 --> 00:20:46,640 Speaker 3: we want to get from today to twenty twenty nine. 351 00:20:47,240 --> 00:20:50,399 Speaker 3: In between, we have this real important milestone also that 352 00:20:50,440 --> 00:20:53,080 Speaker 3: we believe that with the community, we'll be hitting quantum 353 00:20:53,119 --> 00:20:57,200 Speaker 3: advantage right where there will be some problems and claims 354 00:20:57,200 --> 00:21:02,880 Speaker 3: of advantage where we'll see quantum really surpassing any classical 355 00:21:02,920 --> 00:21:06,520 Speaker 3: methods of solving certain types of problems. Right, and we 356 00:21:06,680 --> 00:21:10,720 Speaker 3: are looking at various ways of showing that academically, scientifically 357 00:21:10,800 --> 00:21:14,000 Speaker 3: and also empirically from the ground up in terms of 358 00:21:14,080 --> 00:21:18,520 Speaker 3: compared with various kinds of classical methods today. And then 359 00:21:18,720 --> 00:21:20,520 Speaker 3: we're building a lot of the it's you know, it's 360 00:21:20,560 --> 00:21:24,280 Speaker 3: in the end, it's like architecting a large skyscraper. We're 361 00:21:24,280 --> 00:21:27,399 Speaker 3: building a lot of the foundational elements so that when 362 00:21:27,480 --> 00:21:32,400 Speaker 3: we hit Starling and twenty twenty nine, all the applications 363 00:21:32,400 --> 00:21:35,360 Speaker 3: that people have been developing, all the software stack, all 364 00:21:35,440 --> 00:21:39,399 Speaker 3: the eventual software libraries, they're still going to work that 365 00:21:39,440 --> 00:21:42,280 Speaker 3: they're going to work on a machine that's even more capable, 366 00:21:42,560 --> 00:21:46,080 Speaker 3: something that can run hundreds of millions of gate operations 367 00:21:46,119 --> 00:21:49,280 Speaker 3: compared to several thousands of gate operations on the on 368 00:21:49,359 --> 00:21:51,480 Speaker 3: the advantage level machines that we're building today. 369 00:21:52,280 --> 00:21:55,240 Speaker 1: IBM says it's on track to have quantum computing payoff 370 00:21:55,280 --> 00:21:58,399 Speaker 1: in a big way by twenty twenty nine, but ion 371 00:21:58,520 --> 00:22:00,960 Speaker 1: C's Demasi says they're already there. 372 00:22:01,400 --> 00:22:04,040 Speaker 6: So our machines we announced on September twelfth at our 373 00:22:04,040 --> 00:22:08,800 Speaker 6: Analyst Day are thirty six quadrillion times more powerful than 374 00:22:08,880 --> 00:22:13,359 Speaker 6: anyone else's machine, and that gap is increasing. Not only 375 00:22:13,359 --> 00:22:15,639 Speaker 6: do we believe we are five years ahead of anybody 376 00:22:15,680 --> 00:22:20,960 Speaker 6: else in the quantum computing business, whether it's government programs, adversaries, 377 00:22:21,480 --> 00:22:25,400 Speaker 6: or commercial companies, but we also have the lowest unit economics, 378 00:22:25,600 --> 00:22:29,080 Speaker 6: so we're able to build a fully tolerant two million 379 00:22:29,119 --> 00:22:33,000 Speaker 6: Cuba system and keep our cost of good souls under 380 00:22:33,040 --> 00:22:36,240 Speaker 6: thirty million dollars. Taking that together, it means that we're 381 00:22:36,280 --> 00:22:40,000 Speaker 6: a fully flagged quantum Internet solution. We can provide our 382 00:22:40,080 --> 00:22:45,399 Speaker 6: customer as a platform of computing, cybersecurity, networking, communications and sensing, 383 00:22:45,880 --> 00:22:47,800 Speaker 6: and there's no other company in the history of the 384 00:22:47,840 --> 00:22:51,080 Speaker 6: world that's evering able to supply a complete quantum Internet. 385 00:22:51,880 --> 00:22:54,919 Speaker 1: Everyone in the quantum business seems to agree that Einstein 386 00:22:55,160 --> 00:22:58,800 Speaker 1: was wrong, that it's either coming soon or is already here, 387 00:22:59,240 --> 00:23:02,800 Speaker 1: and that it will be big. But figuring out who's 388 00:23:02,840 --> 00:23:06,760 Speaker 1: ahead in this race sometimes feels like predicting those dice. 389 00:23:07,240 --> 00:23:10,680 Speaker 1: IBM says it's ahead because it has more total cubits 390 00:23:10,720 --> 00:23:14,080 Speaker 1: in its machines. Ion Q says it's not the number 391 00:23:14,080 --> 00:23:17,560 Speaker 1: of cubits, but the number of algorithmic cubits, putting it 392 00:23:17,720 --> 00:23:22,600 Speaker 1: in front. And quantum company Continuum has yet a third 393 00:23:22,640 --> 00:23:25,800 Speaker 1: measure of quantum value. Maybe we shouldn't be surprised that 394 00:23:25,840 --> 00:23:29,159 Speaker 1: there isn't a single measurement. It's like those cubits that 395 00:23:29,200 --> 00:23:32,800 Speaker 1: are both ones and zero's at the same time until 396 00:23:32,880 --> 00:23:36,320 Speaker 1: they're observed. And it looks likely that we will all 397 00:23:36,359 --> 00:23:39,040 Speaker 1: be able to observe what quantum computing can do for 398 00:23:39,119 --> 00:23:45,080 Speaker 1: us in the very near future. Up next, an aging 399 00:23:45,160 --> 00:23:49,360 Speaker 1: population meets lower interest rates. It's a problem countries throughout 400 00:23:49,400 --> 00:23:51,960 Speaker 1: the West are facing. We tell the story of what 401 00:23:52,040 --> 00:24:08,359 Speaker 1: the Netherlands is doing about it. This is a story 402 00:24:08,400 --> 00:24:12,000 Speaker 1: about nest eggs. Those nest eggs were all supposed to 403 00:24:12,040 --> 00:24:15,720 Speaker 1: be putting away for our retirement years, with or without 404 00:24:15,760 --> 00:24:19,720 Speaker 1: the help of the government or employers. Unfortunately, too many 405 00:24:19,720 --> 00:24:22,080 Speaker 1: of us count on support that may or may not 406 00:24:22,240 --> 00:24:27,600 Speaker 1: be enough to carry us in our later years. We 407 00:24:27,680 --> 00:24:31,120 Speaker 1: have still fifty seven million Americans who don't have any 408 00:24:31,400 --> 00:24:35,639 Speaker 1: savings or any retirement plan, whether it's state funded pension 409 00:24:35,640 --> 00:24:39,360 Speaker 1: plans for teachers and policemen or Social Security for everyone. 410 00:24:39,920 --> 00:24:43,200 Speaker 1: We all know about the looming problems in providing adequate 411 00:24:43,240 --> 00:24:46,320 Speaker 1: income for retirees in the United States, but it's not 412 00:24:46,440 --> 00:24:48,440 Speaker 1: just the US that has a problem. 413 00:24:48,720 --> 00:24:52,440 Speaker 7: Many countries made provisions for those promises, and now promises 414 00:24:52,600 --> 00:24:56,639 Speaker 7: are being cashed in, and many countries are saying, oh wait, 415 00:24:57,040 --> 00:24:58,639 Speaker 7: you know we don't want to pay the bill. 416 00:24:59,119 --> 00:25:03,119 Speaker 1: Teresa gillard Ucci is professor of economics and policy analysis 417 00:25:03,119 --> 00:25:05,679 Speaker 1: at the New School in New York and author of 418 00:25:05,920 --> 00:25:10,320 Speaker 1: Rescuing Retirement with Tony James. The challenges faced by retirees 419 00:25:10,359 --> 00:25:13,320 Speaker 1: around much of the world are reflected in higher poverty 420 00:25:13,400 --> 00:25:17,760 Speaker 1: levels of those over sixty five, with the OECD reporting 421 00:25:17,760 --> 00:25:20,640 Speaker 1: that forty percent of the elderly in Korea live on 422 00:25:20,720 --> 00:25:23,640 Speaker 1: less than half of the median income in the country 423 00:25:23,720 --> 00:25:27,440 Speaker 1: and the United States just under twenty five percent. Gilarducci 424 00:25:27,520 --> 00:25:30,359 Speaker 1: says one of the reasons is lower interest rates. 425 00:25:30,800 --> 00:25:34,240 Speaker 7: The life expectancy does not put a strain on pension system, 426 00:25:34,480 --> 00:25:38,480 Speaker 7: but what has changed as over the past twenty years, 427 00:25:38,960 --> 00:25:42,360 Speaker 7: there was a regime of very low interest rates for 428 00:25:42,480 --> 00:25:45,080 Speaker 7: lots of reasons. One of them was a financial crisis. 429 00:25:45,240 --> 00:25:47,399 Speaker 7: A lot of it was the way that we managed 430 00:25:47,440 --> 00:25:51,160 Speaker 7: our economies was to make sure that capital investment was low. 431 00:25:51,520 --> 00:25:54,480 Speaker 7: That distorted a lot of decisions. But one of those 432 00:25:54,480 --> 00:25:57,840 Speaker 7: things that it distorted is that the safe assets like 433 00:25:57,920 --> 00:26:00,639 Speaker 7: government bonds didn't pay much. 434 00:26:01,080 --> 00:26:04,880 Speaker 1: The US is hardly alone in facing the coming retirement crisis, 435 00:26:05,119 --> 00:26:08,679 Speaker 1: but one country, the Netherlands, is doing something about it. 436 00:26:09,040 --> 00:26:12,280 Speaker 1: Adrian Riker's firm is one of those putting those funds 437 00:26:12,320 --> 00:26:12,840 Speaker 1: to work. 438 00:26:13,160 --> 00:26:16,040 Speaker 8: In the Dutch pension system. In the second pillar, there 439 00:26:16,080 --> 00:26:20,760 Speaker 8: are around sixteen hundred billion euros of assets under management, 440 00:26:21,119 --> 00:26:25,199 Speaker 8: which equates to around one point five two times the 441 00:26:25,359 --> 00:26:26,840 Speaker 8: GDP of the Netherlands. 442 00:26:27,240 --> 00:26:30,840 Speaker 1: That one point six trillion euros in Dutch pension assets 443 00:26:30,880 --> 00:26:35,119 Speaker 1: accounts for fifty nine percent of all European pension funds, 444 00:26:35,480 --> 00:26:38,920 Speaker 1: while having only four percent of the population, which means 445 00:26:38,960 --> 00:26:41,960 Speaker 1: that it ranks near the bottom of the OECD numbers 446 00:26:41,960 --> 00:26:46,840 Speaker 1: in elderly poverty at just under five percent, But despite 447 00:26:46,880 --> 00:26:49,920 Speaker 1: having more assets set aside for retirement than any other 448 00:26:50,080 --> 00:26:54,080 Speaker 1: European country, the Netherlands is about to overhaul the fundamentals 449 00:26:54,160 --> 00:26:55,200 Speaker 1: of its pension system. 450 00:26:55,840 --> 00:26:59,960 Speaker 8: Now we are moving from defined benefits to defined country 451 00:27:00,680 --> 00:27:04,440 Speaker 8: and the reason for this change is mainly to increase 452 00:27:04,440 --> 00:27:07,600 Speaker 8: the sustainability of the fund towards the future. 453 00:27:08,280 --> 00:27:11,800 Speaker 1: At first glance, the math seems straightforward. The old model 454 00:27:11,920 --> 00:27:14,919 Speaker 1: wasn't sustainable, it was time for something new, But the 455 00:27:15,000 --> 00:27:18,680 Speaker 1: debate over restructuring the system was anything but simple. 456 00:27:19,320 --> 00:27:22,720 Speaker 9: The private pillar is what is in the process of 457 00:27:22,760 --> 00:27:26,879 Speaker 9: getting reformed now. That reform took a number of years 458 00:27:26,920 --> 00:27:30,920 Speaker 9: to reach. Discussions started in the early two thousands after 459 00:27:30,960 --> 00:27:33,760 Speaker 9: the dot Com crisis, when a number of Dutch pension 460 00:27:33,760 --> 00:27:36,879 Speaker 9: funds sought a coverage ratios drop. It came to a 461 00:27:36,920 --> 00:27:42,320 Speaker 9: conclusion sort of around the started pandemic when the shape 462 00:27:42,359 --> 00:27:44,520 Speaker 9: of the current Pensruon reform was decided upon. 463 00:27:45,240 --> 00:27:48,640 Speaker 1: Stan Voiger is a senior fellow in Economic policy Studies 464 00:27:48,680 --> 00:27:52,200 Speaker 1: at the American Enterprise Institute and director of the Netherland 465 00:27:52,280 --> 00:27:53,400 Speaker 1: America Foundation. 466 00:27:54,160 --> 00:27:57,760 Speaker 9: That didn't mean, of course, that the political discussions around 467 00:27:57,800 --> 00:28:02,440 Speaker 9: the reform completely dissipated. In the outgoing government, the Scove 468 00:28:02,560 --> 00:28:06,760 Speaker 9: Cabinet that was in place for the past year or so, 469 00:28:07,840 --> 00:28:10,800 Speaker 9: there was there was one political party, the New Social 470 00:28:10,840 --> 00:28:16,760 Speaker 9: Contract Party, that was quite aggressively opposed to the Benson 471 00:28:16,840 --> 00:28:19,600 Speaker 9: reform as it had been designed, and they in fact 472 00:28:19,880 --> 00:28:24,040 Speaker 9: tried to derail it by letting individual workers and retiaries 473 00:28:24,600 --> 00:28:28,000 Speaker 9: vote on an industry by industry, or occupation by occupation, 474 00:28:28,080 --> 00:28:32,040 Speaker 9: or even firm by firm basis on whether to remain 475 00:28:32,160 --> 00:28:36,320 Speaker 9: under the old pension system, which is a defined benefit 476 00:28:36,400 --> 00:28:39,280 Speaker 9: system basically, or whether to accept the transition to the new, 477 00:28:39,520 --> 00:28:45,000 Speaker 9: more collective, defined contribution system. That effort by them ultimately failed. 478 00:28:45,080 --> 00:28:47,840 Speaker 9: It lost a vote in Parliament, but only barely, and 479 00:28:47,880 --> 00:28:51,080 Speaker 9: I think that was really the end of political uncertainty 480 00:28:51,120 --> 00:28:54,479 Speaker 9: around this Benson reform, not only because that vote failed, 481 00:28:54,680 --> 00:28:58,480 Speaker 9: but also because the Scove of government fell. This summer 482 00:28:58,840 --> 00:29:02,200 Speaker 9: we had elections and the party most associated with those 483 00:29:02,280 --> 00:29:06,360 Speaker 9: efforts to basically undo the pension reform to a significant extent, 484 00:29:06,480 --> 00:29:08,200 Speaker 9: that party lost all of its seats in Partland. 485 00:29:09,200 --> 00:29:13,000 Speaker 1: The Dutch pension plan changes may be controversial, but necessary 486 00:29:13,320 --> 00:29:16,560 Speaker 1: given the larger forces that all retirement plans in western 487 00:29:16,600 --> 00:29:17,680 Speaker 1: countries are facing. 488 00:29:18,280 --> 00:29:21,680 Speaker 8: The move to define contributions is something that we see 489 00:29:22,160 --> 00:29:24,880 Speaker 8: all across the globe if we look at the pension 490 00:29:24,960 --> 00:29:28,680 Speaker 8: index that is published yearly, if you look at what 491 00:29:28,800 --> 00:29:33,920 Speaker 8: pension advisors and actuaries are saying exactly. These changes are 492 00:29:33,960 --> 00:29:37,840 Speaker 8: not specific to just the Netherlands, but because we have 493 00:29:38,000 --> 00:29:40,840 Speaker 8: such a large pension build up, we have so much 494 00:29:40,840 --> 00:29:44,600 Speaker 8: capital in the system, very high adequacy rates. It is 495 00:29:44,840 --> 00:29:49,880 Speaker 8: very prevalent in the Dutch system. Since the global financial crisis, 496 00:29:49,880 --> 00:29:53,560 Speaker 8: interest rates have been in steady decline, mainly because of 497 00:29:53,720 --> 00:29:59,040 Speaker 8: monetary policy and because of the way that pension liabilities 498 00:29:59,120 --> 00:30:02,800 Speaker 8: are valued. They have a direct link with interest rates, 499 00:30:02,880 --> 00:30:06,560 Speaker 8: and as interest rates decrease, the liabilities of pension funds 500 00:30:06,560 --> 00:30:11,000 Speaker 8: increase and thus place a burden on the pension fund sustainability. 501 00:30:11,320 --> 00:30:14,600 Speaker 8: But also on top of that you have longevity which 502 00:30:14,640 --> 00:30:19,080 Speaker 8: has increased amongst the participants, and coverage in the Netherlands 503 00:30:19,120 --> 00:30:22,719 Speaker 8: of the second pillar pensions is very high. The way 504 00:30:23,000 --> 00:30:26,320 Speaker 8: in the old system that we had, the way it 505 00:30:26,400 --> 00:30:30,680 Speaker 8: worked is that employees would usually stay at the same 506 00:30:30,800 --> 00:30:33,760 Speaker 8: firm that they started at or stay within the same 507 00:30:33,800 --> 00:30:38,680 Speaker 8: industry and work until the retirement age. And if this happened, 508 00:30:39,080 --> 00:30:44,800 Speaker 8: the current pension system was perfectly equipped for this, but 509 00:30:45,040 --> 00:30:48,840 Speaker 8: nowadays we see more and more people moving away from 510 00:30:48,920 --> 00:30:53,320 Speaker 8: a lifetime employment and moving more into self employment. 511 00:30:54,280 --> 00:30:57,080 Speaker 1: One way to address the increased number of people relying 512 00:30:57,080 --> 00:31:00,280 Speaker 1: on their pensions amid lower interest rates might be to 513 00:31:00,320 --> 00:31:03,680 Speaker 1: extend the time when people start receiving their benefits, but 514 00:31:03,720 --> 00:31:06,400 Speaker 1: that is not the way the Netherlands chose to go. 515 00:31:07,040 --> 00:31:11,680 Speaker 8: The reforms mainly are in the way we invest in, 516 00:31:11,800 --> 00:31:16,440 Speaker 8: changing from defined benefits to only defining the contribution. 517 00:31:17,600 --> 00:31:20,120 Speaker 1: The Dutch system is designed to increase the size of 518 00:31:20,160 --> 00:31:23,880 Speaker 1: the available pie by permitting pension asset managers to invest 519 00:31:23,880 --> 00:31:27,400 Speaker 1: in higher risk and higher yield assets for younger workers 520 00:31:27,400 --> 00:31:29,520 Speaker 1: with many years to go until their retirement. 521 00:31:30,120 --> 00:31:33,600 Speaker 8: You now go to a more individual approach with your 522 00:31:33,640 --> 00:31:38,680 Speaker 8: collective investments, in that you have to see what individual 523 00:31:38,720 --> 00:31:43,360 Speaker 8: investors need at certain age age groups. So, for instance, 524 00:31:43,480 --> 00:31:48,400 Speaker 8: a young person on average has less financial capital but 525 00:31:48,520 --> 00:31:52,120 Speaker 8: still has a lot of years to work in its career, 526 00:31:52,560 --> 00:31:55,880 Speaker 8: and what that enables younger investors to do is to 527 00:31:55,920 --> 00:32:01,240 Speaker 8: take on more risk because the biggest determinant of capital 528 00:32:01,680 --> 00:32:05,840 Speaker 8: build up at a young age is the contributions you 529 00:32:05,920 --> 00:32:08,920 Speaker 8: get each year. But as you near the end of 530 00:32:08,960 --> 00:32:13,040 Speaker 8: your career, contributions become less of a big part, less 531 00:32:13,080 --> 00:32:15,720 Speaker 8: of a big influence on the income that you will 532 00:32:15,720 --> 00:32:20,360 Speaker 8: have on retirement, and the income or the focus shifts 533 00:32:20,400 --> 00:32:25,280 Speaker 8: from contributions to investment results that should be stable and 534 00:32:25,440 --> 00:32:26,440 Speaker 8: lower in shocks. 535 00:32:27,160 --> 00:32:30,800 Speaker 1: Whether permitting more flexible investments, particularly riskier ones for earlier 536 00:32:30,840 --> 00:32:33,840 Speaker 1: in a worker's life, will work or not. It does 537 00:32:33,920 --> 00:32:37,640 Speaker 1: relieve the pensions from facing obligations greater than their resources, 538 00:32:37,960 --> 00:32:40,920 Speaker 1: but also means that one's benefits could go up or 539 00:32:41,000 --> 00:32:43,920 Speaker 1: down depending on the markets. Getting people to agree to 540 00:32:43,960 --> 00:32:48,040 Speaker 1: this big change took time and all the stakeholders working together. 541 00:32:48,400 --> 00:32:53,280 Speaker 9: One distinguishing feature of the Dutch system of policy making 542 00:32:54,200 --> 00:32:56,960 Speaker 9: is that there is a lot of focus on consensus 543 00:32:56,960 --> 00:33:01,560 Speaker 9: building between employers, employees, and the government. The fact that 544 00:33:01,560 --> 00:33:07,200 Speaker 9: ANUELYS has these structures that facilitate the coming together of 545 00:33:07,360 --> 00:33:11,440 Speaker 9: business and labor, I think, is particularly helpful in the 546 00:33:11,520 --> 00:33:14,280 Speaker 9: pension context. There are lots of political problems where there 547 00:33:14,280 --> 00:33:17,320 Speaker 9: are all sorts of other stakeholders involved, but in the 548 00:33:17,400 --> 00:33:20,920 Speaker 9: pension context it really still is employers and employees who 549 00:33:20,960 --> 00:33:24,880 Speaker 9: have to come together and reach agreement on on how 550 00:33:24,920 --> 00:33:26,640 Speaker 9: to design the pension system. 551 00:33:27,080 --> 00:33:29,280 Speaker 1: What can the rest of the world learn from the 552 00:33:29,360 --> 00:33:33,120 Speaker 1: Dutch in providing for retirement, perhaps a lesson in persistence. 553 00:33:33,720 --> 00:33:36,160 Speaker 1: The most recent changes are just the latest in a 554 00:33:36,280 --> 00:33:39,320 Speaker 1: series of attempts at pension reform, go back to the 555 00:33:39,360 --> 00:33:43,600 Speaker 1: eighties under Ronald Reagan, when they did take steps to 556 00:33:43,640 --> 00:33:46,640 Speaker 1: try to extend SoC security. What made it possible then, 557 00:33:46,880 --> 00:33:48,480 Speaker 1: that doesn't make it possible now. 558 00:33:48,840 --> 00:33:53,880 Speaker 7: Well, what made it possible for a bipartisan commission and 559 00:33:54,560 --> 00:33:58,560 Speaker 7: of fits to happen was that the crisis was only 560 00:33:58,600 --> 00:34:02,600 Speaker 7: one year away. It had to do with surprise inflation 561 00:34:03,160 --> 00:34:05,920 Speaker 7: and a surprise among the actuaries that they wouldn't have 562 00:34:06,040 --> 00:34:09,279 Speaker 7: enough money in the shortfall. So money needed to be 563 00:34:09,760 --> 00:34:14,400 Speaker 7: infused into the system immediately, and so the Green Span 564 00:34:14,480 --> 00:34:18,400 Speaker 7: Commission under the Reagan administration recommended that the payroll tax 565 00:34:18,440 --> 00:34:22,600 Speaker 7: be increased, and everybody agreed. Later, when it came to Congress, 566 00:34:22,719 --> 00:34:25,719 Speaker 7: there was some political effort to say, well, if we're 567 00:34:25,719 --> 00:34:28,719 Speaker 7: going to raise taxes, we have to really look to 568 00:34:28,800 --> 00:34:32,560 Speaker 7: see how much the taxes have to be increased. And 569 00:34:32,600 --> 00:34:35,799 Speaker 7: so that's when they looked at the past and said, well, 570 00:34:35,840 --> 00:34:39,759 Speaker 7: since everybody's living longer, then we should have a system 571 00:34:39,840 --> 00:34:42,840 Speaker 7: that represents that and will raise the retirement age to 572 00:34:42,880 --> 00:34:45,960 Speaker 7: sixty seven. But that cut and benefit was going to 573 00:34:46,000 --> 00:34:48,799 Speaker 7: be in the future, and they all agreed they needed 574 00:34:48,880 --> 00:34:51,719 Speaker 7: infusion of cash, and taxes were increased. Maybe that's what 575 00:34:51,760 --> 00:34:55,280 Speaker 7: we need to raise taxes, is to have a real 576 00:34:56,760 --> 00:35:01,200 Speaker 7: look at what taxes pay for everyone likes their social 577 00:35:01,200 --> 00:35:03,239 Speaker 7: security benefits, whether. 578 00:35:03,000 --> 00:35:05,880 Speaker 1: It's relying more on the capital markets like the Netherlands, 579 00:35:06,239 --> 00:35:09,480 Speaker 1: or turning to taxpayers to contribute more. The United States 580 00:35:09,480 --> 00:35:12,640 Speaker 1: and other Western nations have some tough choices to make, 581 00:35:12,880 --> 00:35:15,560 Speaker 1: and they need to be made sooner rather than later, 582 00:35:15,680 --> 00:35:18,080 Speaker 1: as people live longer and we want to provide for 583 00:35:18,160 --> 00:35:24,719 Speaker 1: them without stealing from the future. Coming up, getting to 584 00:35:24,920 --> 00:35:38,400 Speaker 1: zero emissions despite those data centers, Finland leads the way. 585 00:35:44,440 --> 00:35:47,480 Speaker 1: This is a story about featuring a problem instead of 586 00:35:47,680 --> 00:35:51,120 Speaker 1: fixing it. This month at COP thirty in Brazil, world 587 00:35:51,239 --> 00:35:53,200 Speaker 1: leaders are trying to get back on the path the 588 00:35:53,320 --> 00:35:57,239 Speaker 1: net zero emissions despite the huge and growing demand of 589 00:35:57,320 --> 00:36:01,759 Speaker 1: data centers for more energy. But European country is already 590 00:36:01,800 --> 00:36:05,680 Speaker 1: a decade ahead. Finland has set the most ambitious climate 591 00:36:05,719 --> 00:36:09,000 Speaker 1: target in the world, pledging to reach carbon neutrality by 592 00:36:09,040 --> 00:36:12,680 Speaker 1: twenty thirty five, and it's featuring the problem of data 593 00:36:12,680 --> 00:36:16,120 Speaker 1: center growth to get there. Bloomberg's Tom mackenzie has the 594 00:36:16,160 --> 00:36:18,200 Speaker 1: story from Helsinki. 595 00:36:27,600 --> 00:36:32,040 Speaker 10: Finland, home to five million people and three million saunas. 596 00:36:33,160 --> 00:36:37,840 Speaker 10: Here warmth isn't just a comfort, it's a culture. But 597 00:36:38,000 --> 00:36:41,239 Speaker 10: now the nation that has perfected staying warm in any 598 00:36:41,320 --> 00:36:49,600 Speaker 10: condition is finding a new way to do it. Fifty 599 00:36:49,680 --> 00:36:53,279 Speaker 10: meters below the streets of Helsinki a hidden network of 600 00:36:53,360 --> 00:36:54,839 Speaker 10: tunnels hums with. 601 00:36:54,840 --> 00:36:56,160 Speaker 1: The sound of machinery. 602 00:36:56,880 --> 00:36:58,760 Speaker 10: Oh so where are we? 603 00:36:58,760 --> 00:37:02,239 Speaker 11: We are at the Helen here pump station where you're 604 00:37:02,360 --> 00:37:07,279 Speaker 11: calling for their helsincodatas and we take the cool and 605 00:37:07,719 --> 00:37:10,279 Speaker 11: sell it as a hereed for the Herzig households. 606 00:37:10,960 --> 00:37:15,160 Speaker 10: Our guide through this underground maze is Oli Circa, CEO 607 00:37:15,400 --> 00:37:19,640 Speaker 10: of helen one of Finland's largest energy providers and the 608 00:37:19,719 --> 00:37:24,080 Speaker 10: company turning data center heat into power for the city. 609 00:37:24,640 --> 00:37:28,680 Speaker 10: Here's how it works. Above ground data centers, the engines 610 00:37:28,719 --> 00:37:32,759 Speaker 10: of our digital lives, generate vast amounts of heat as 611 00:37:32,800 --> 00:37:37,120 Speaker 10: they power everything from AI to streaming video. That heat 612 00:37:37,200 --> 00:37:41,280 Speaker 10: is captured and piped into Helen's system, where heat pumps 613 00:37:41,440 --> 00:37:44,640 Speaker 10: raise its temperature even more and send it through the 614 00:37:44,680 --> 00:37:49,240 Speaker 10: city's district heating network. The same system then returns cooled 615 00:37:49,280 --> 00:37:52,840 Speaker 10: water back to the data centers. It's a test case 616 00:37:52,880 --> 00:37:57,200 Speaker 10: for whether our growing digital appetite for energy can be contained. 617 00:37:58,200 --> 00:38:01,680 Speaker 10: When you have partners like and Microsoft and tell you 618 00:38:01,680 --> 00:38:04,240 Speaker 10: a come to you to work with you and partner 619 00:38:04,239 --> 00:38:07,360 Speaker 10: with Helen, what are they getting exactly in that partnership. 620 00:38:07,800 --> 00:38:10,719 Speaker 12: They have a problem with heat and they need to 621 00:38:10,760 --> 00:38:14,440 Speaker 12: cool down somehow their premises. And now our job is 622 00:38:14,480 --> 00:38:17,840 Speaker 12: to sell heat. So the starting point for this custom 623 00:38:18,200 --> 00:38:22,080 Speaker 12: is really good, and in the end we can actually 624 00:38:22,120 --> 00:38:23,640 Speaker 12: monetize their problem. 625 00:38:24,000 --> 00:38:26,759 Speaker 10: Can you just unpack the business part of that. 626 00:38:27,000 --> 00:38:29,560 Speaker 12: So in normal case, if you build a for example, 627 00:38:29,640 --> 00:38:33,680 Speaker 12: one hundred megawatt data center, almost all of that power, 628 00:38:33,880 --> 00:38:37,239 Speaker 12: practically all of that turns to heat, and they need 629 00:38:37,280 --> 00:38:40,279 Speaker 12: to get rid of that. They need to invest in 630 00:38:40,600 --> 00:38:45,040 Speaker 12: heat pumps and all kinds of cooling equipment. And if 631 00:38:45,040 --> 00:38:48,440 Speaker 12: they cooperate with us, they don't have to do that investment. 632 00:38:48,480 --> 00:38:51,080 Speaker 12: We do it for them, and we take the heat 633 00:38:51,120 --> 00:38:54,640 Speaker 12: out and on top of that, we monetize the excess 634 00:38:54,680 --> 00:38:58,279 Speaker 12: heat by selling it to our customers, so they save 635 00:38:58,440 --> 00:39:01,959 Speaker 12: all the cooling costs and it turns to business for us. 636 00:39:02,120 --> 00:39:06,000 Speaker 10: So that's a big CAPEX outlet, yes for you and 637 00:39:06,080 --> 00:39:08,960 Speaker 10: Capex that they don't have to be putting exagnufacturing into 638 00:39:08,960 --> 00:39:10,560 Speaker 10: their spending plans exactly. 639 00:39:10,200 --> 00:39:13,520 Speaker 12: The CAPEX is needed, but it's done by us and 640 00:39:14,239 --> 00:39:17,760 Speaker 12: we can get a very good profit double business around 641 00:39:17,760 --> 00:39:19,319 Speaker 12: that CAPEX, so it works for us. 642 00:39:20,719 --> 00:39:25,320 Speaker 10: For the local community, the benefits are tangible electricity prices 643 00:39:25,360 --> 00:39:30,319 Speaker 10: that sit below the EU average. Helen's newest partnership is 644 00:39:30,360 --> 00:39:34,240 Speaker 10: expected to provide warmth for roughly fifteen hundred homes. 645 00:39:35,800 --> 00:39:39,440 Speaker 11: We have been able to increase our profits at the 646 00:39:39,480 --> 00:39:42,800 Speaker 11: same time. We have now lowered our prices door times 647 00:39:42,880 --> 00:39:46,839 Speaker 11: in a row during the last four years. 648 00:39:47,080 --> 00:39:50,759 Speaker 10: The impressive progress in Helsinki is set against a challenging 649 00:39:50,920 --> 00:39:56,440 Speaker 10: global backdrop. According to Bloomberg New Energy Finance Research data, 650 00:39:56,480 --> 00:40:01,440 Speaker 10: centers could consume about four point four percent global electricity 651 00:40:01,760 --> 00:40:05,680 Speaker 10: by twenty thirty five. If they were a country, they'd 652 00:40:05,719 --> 00:40:09,960 Speaker 10: rank fourth in electricity use, just behind China, the US, 653 00:40:10,080 --> 00:40:14,200 Speaker 10: and India, and cooling them already takes up nearly a 654 00:40:14,239 --> 00:40:18,879 Speaker 10: third of that energy. According to the World Economic Forum. 655 00:40:19,280 --> 00:40:21,680 Speaker 13: So this is the buzz of the Internet and our 656 00:40:21,680 --> 00:40:25,880 Speaker 13: digital society. So in here you have what we sometimes 657 00:40:25,880 --> 00:40:27,360 Speaker 13: referred to as clouds. 658 00:40:28,040 --> 00:40:31,279 Speaker 10: Helen manages the heat, but it's Equinics that runs the 659 00:40:31,360 --> 00:40:36,120 Speaker 10: data centers, more than two hundred and seventy of them worldwide. 660 00:40:36,200 --> 00:40:39,280 Speaker 13: A data center is a part of everything we do digitally. 661 00:40:39,640 --> 00:40:42,839 Speaker 10: Regina Donata, Dlstrom heads their Nordic operations. 662 00:40:43,440 --> 00:40:46,839 Speaker 13: So inside of these are servers that are collocated by 663 00:40:47,080 --> 00:40:53,080 Speaker 13: enterprise customers of Equinics and Connectivity so connections. So altogether 664 00:40:53,280 --> 00:40:58,400 Speaker 13: we host over four hundred and ninety thousand connections at Tecinics. 665 00:40:57,920 --> 00:41:00,960 Speaker 10: Four hundred ninety thousand connections, and those connects and the 666 00:41:01,040 --> 00:41:03,799 Speaker 10: work that's being done by these service creates a lot 667 00:41:03,800 --> 00:41:06,320 Speaker 10: of heat. You can feel it here in the data center. 668 00:41:06,400 --> 00:41:10,320 Speaker 13: It does, it does. Managing the heat is one of 669 00:41:10,360 --> 00:41:12,640 Speaker 13: the larger parts in operating a data center. 670 00:41:13,760 --> 00:41:17,720 Speaker 10: The heat a reminder that every click, stream and search 671 00:41:17,920 --> 00:41:22,160 Speaker 10: has a footprint somewhere in the real world. Managing it 672 00:41:22,239 --> 00:41:25,320 Speaker 10: is one thing. Finding a way to use it sustainably 673 00:41:25,800 --> 00:41:26,240 Speaker 10: is another. 674 00:41:27,200 --> 00:41:30,480 Speaker 13: The way we measure our data centers is very thoroughly 675 00:41:30,680 --> 00:41:34,520 Speaker 13: with efficiency measures. Per each square meter that's on top 676 00:41:34,560 --> 00:41:37,680 Speaker 13: of mind of any data center operator, because that's money, 677 00:41:38,120 --> 00:41:40,520 Speaker 13: and it's also a proof point to how good of 678 00:41:40,560 --> 00:41:43,959 Speaker 13: a data center you have towards your customers. On top 679 00:41:44,040 --> 00:41:47,280 Speaker 13: of that, we add back to the society in which 680 00:41:47,360 --> 00:41:49,920 Speaker 13: we invest in infrastructure. 681 00:41:50,840 --> 00:41:53,680 Speaker 10: Around the world. The race to build for AI is 682 00:41:53,719 --> 00:41:58,200 Speaker 10: putting new strain on power grids and sparking a backlash. 683 00:41:58,920 --> 00:42:03,280 Speaker 10: A Bloomberg analysis of wholesale electricity prices across the US 684 00:42:03,760 --> 00:42:06,680 Speaker 10: found that electricity now costs as much as two hundred 685 00:42:06,719 --> 00:42:10,680 Speaker 10: and sixty seven percent more for a single month than 686 00:42:10,680 --> 00:42:14,440 Speaker 10: it did five years ago in areas located near it 687 00:42:14,600 --> 00:42:18,080 Speaker 10: significant data center activity. When you look at some of 688 00:42:18,120 --> 00:42:20,239 Speaker 10: your competitors in the data center field, is it a 689 00:42:20,239 --> 00:42:22,360 Speaker 10: sense of frustration or kind of head in your hands 690 00:42:22,400 --> 00:42:23,960 Speaker 10: moment when you look at the fact that a lot 691 00:42:24,000 --> 00:42:27,040 Speaker 10: of these data center operations don't seem to be thinking 692 00:42:27,080 --> 00:42:28,840 Speaker 10: about all the different components that go into it in 693 00:42:28,920 --> 00:42:30,280 Speaker 10: terms of addressing the energy needs. 694 00:42:30,880 --> 00:42:33,440 Speaker 13: No, saying that a data center is a data center 695 00:42:33,600 --> 00:42:36,640 Speaker 13: is like saying a factory is a factory. We do 696 00:42:36,719 --> 00:42:40,920 Speaker 13: cool location services for enterprises, and I would say that 697 00:42:41,280 --> 00:42:44,640 Speaker 13: respecting my peers in that part of the data center industry. 698 00:42:45,080 --> 00:42:47,840 Speaker 13: Most of us do care about sustainability. 699 00:42:47,920 --> 00:42:50,080 Speaker 10: I guess the critics would say, in this rush to 700 00:42:50,120 --> 00:42:52,920 Speaker 10: build out for AI, that corners are going to be 701 00:42:52,920 --> 00:42:56,600 Speaker 10: cut when it comes to energy and to sustainability. 702 00:42:57,280 --> 00:43:01,480 Speaker 13: And I think in any of the technology the waves 703 00:43:01,520 --> 00:43:04,560 Speaker 13: that we've seen, whether that was IoT or five G 704 00:43:05,040 --> 00:43:08,040 Speaker 13: or building up broadband, yes, there are some that get 705 00:43:08,040 --> 00:43:10,359 Speaker 13: it wrong. There are some that cut corners. There are 706 00:43:10,400 --> 00:43:13,120 Speaker 13: some that think they've got it right, and then actually 707 00:43:13,160 --> 00:43:17,000 Speaker 13: the application of the services changes. I think this is 708 00:43:17,040 --> 00:43:17,600 Speaker 13: no different. 709 00:43:18,600 --> 00:43:21,359 Speaker 10: The question now is can the race to get there 710 00:43:21,520 --> 00:43:26,600 Speaker 10: first coexist with the desire to get it right. Nowhere 711 00:43:26,680 --> 00:43:30,040 Speaker 10: is that question more urgent than in the US, home 712 00:43:30,200 --> 00:43:33,960 Speaker 10: to more than five four hundred data centers, more than 713 00:43:34,080 --> 00:43:38,560 Speaker 10: all other major economies combined, and most of the electricity 714 00:43:38,600 --> 00:43:42,120 Speaker 10: to run those data centers still comes from gas and coal, 715 00:43:42,520 --> 00:43:45,120 Speaker 10: which are also expected to meet much of the country's 716 00:43:45,200 --> 00:43:50,120 Speaker 10: new power needs over the next decade. Put simply, Finland 717 00:43:50,400 --> 00:43:54,080 Speaker 10: may offer a glimpse of what's possible, but the real 718 00:43:54,200 --> 00:43:58,520 Speaker 10: test is whether that model can scale worldwide. It's a 719 00:43:58,600 --> 00:44:01,799 Speaker 10: question that Noah Conja has put a lot of time 720 00:44:01,840 --> 00:44:02,560 Speaker 10: into answering. 721 00:44:03,440 --> 00:44:06,080 Speaker 4: The Finnish case is slightly different and across Scandinavia because 722 00:44:06,080 --> 00:44:08,480 Speaker 4: they have a lot of existing heat networks, and in 723 00:44:08,480 --> 00:44:11,520 Speaker 4: a lot of other countries they're not as well developed 724 00:44:11,640 --> 00:44:14,040 Speaker 4: for heat networks. Having said that, it is still possible 725 00:44:14,080 --> 00:44:16,759 Speaker 4: to apply some of the learnings. One of the key 726 00:44:16,800 --> 00:44:20,560 Speaker 4: ones is working with a utility or heat network operator 727 00:44:20,760 --> 00:44:22,080 Speaker 4: that's keen and supportive. 728 00:44:22,840 --> 00:44:27,200 Speaker 10: In Gonja pioneered the technology Equinix uses here in Finland 729 00:44:27,640 --> 00:44:30,560 Speaker 10: and says its applications could be endless. 730 00:44:31,239 --> 00:44:34,040 Speaker 4: It's important to point out that the heat export will 731 00:44:34,040 --> 00:44:36,160 Speaker 4: tend to only work in the right types of climates, 732 00:44:36,160 --> 00:44:38,320 Speaker 4: so those climates where there is a need for heating, 733 00:44:38,600 --> 00:44:41,840 Speaker 4: so it won't be applicable for example in Dubai or 734 00:44:41,880 --> 00:44:44,640 Speaker 4: South Africa where it's a very hot climate. So it'll 735 00:44:44,680 --> 00:44:47,840 Speaker 4: be probably mostly northern Europe and the northern part of 736 00:44:47,880 --> 00:44:50,680 Speaker 4: North America as well. And so what tends to be 737 00:44:50,719 --> 00:44:53,759 Speaker 4: the limiting factor isn't whether you can technically connect in 738 00:44:53,800 --> 00:44:56,640 Speaker 4: the data centers, but it's usually whether there's a partner 739 00:44:56,640 --> 00:45:00,879 Speaker 4: who's actually willing to develop a heat network and make 740 00:45:00,920 --> 00:45:01,840 Speaker 4: the captain investment. 741 00:45:02,120 --> 00:45:04,760 Speaker 10: Do you also do it because it's a valuable revenue stream. 742 00:45:04,880 --> 00:45:07,560 Speaker 4: It's not a really significant revenue stream compared to the 743 00:45:07,600 --> 00:45:10,759 Speaker 4: overall data center business. So we're not looking at heat 744 00:45:10,760 --> 00:45:13,440 Speaker 4: export as a new revenue stream. We're looking because it 745 00:45:13,440 --> 00:45:17,359 Speaker 4: supports our customer sustainability targets and reporting. 746 00:45:17,200 --> 00:45:22,200 Speaker 10: And the model hasn't gone unnoticed. Microsoft, one of the 747 00:45:22,200 --> 00:45:26,960 Speaker 10: world's largest cloud operators, is building its own version, expanding 748 00:45:26,960 --> 00:45:32,040 Speaker 10: the idea at a massive scale. Ian Doherty leads the 749 00:45:32,080 --> 00:45:35,760 Speaker 10: company's cloud operations in Europe, the Middle East and Africa. 750 00:45:36,600 --> 00:45:38,480 Speaker 14: We're very proud of the project that we're working on 751 00:45:38,560 --> 00:45:42,279 Speaker 14: in Finland. We're working with Fordham to leverage the waste 752 00:45:42,320 --> 00:45:46,800 Speaker 14: heat from our data center to decarbonize their local heating 753 00:45:46,840 --> 00:45:50,200 Speaker 14: system and provide heating to local homes over two hundred 754 00:45:50,200 --> 00:45:51,920 Speaker 14: and fifty thousand local homes in vote. 755 00:45:52,800 --> 00:45:55,920 Speaker 10: In the data center, rate efficiency is the new currency, 756 00:45:56,320 --> 00:45:59,560 Speaker 10: and even the world's biggest hyper scalers aren't immune from 757 00:45:59,560 --> 00:46:02,560 Speaker 10: the pressure to balance growth with sustainability. 758 00:46:03,360 --> 00:46:06,799 Speaker 14: Clearly, AI is growing in its use case and diffusion 759 00:46:06,880 --> 00:46:09,560 Speaker 14: across the globe, and we're seeing that in our own business, 760 00:46:10,120 --> 00:46:12,120 Speaker 14: and clearly we need to do more of the same 761 00:46:12,160 --> 00:46:17,000 Speaker 14: things in sustainability and contract further renewable energies. So there's 762 00:46:17,040 --> 00:46:18,960 Speaker 14: a lot of great opportunities that we have ahead of. 763 00:46:19,000 --> 00:46:22,240 Speaker 10: Us, momentum is building. 764 00:46:22,480 --> 00:46:23,040 Speaker 1: In Finland. 765 00:46:23,160 --> 00:46:26,520 Speaker 10: Almost one hundred data center operators are in discussions with 766 00:46:26,600 --> 00:46:30,840 Speaker 10: Helen exploring projects that would feed their own excess heat 767 00:46:31,160 --> 00:46:34,319 Speaker 10: into the city's energy system. What do you think your 768 00:46:34,360 --> 00:46:39,400 Speaker 10: example says about Finland's approach to decarbonizing its economy but 769 00:46:39,560 --> 00:46:41,319 Speaker 10: growing at the same time. 770 00:46:41,880 --> 00:46:45,160 Speaker 12: Well, I think, and I hope we can show to 771 00:46:45,200 --> 00:46:47,239 Speaker 12: the rest of the world that you can do the 772 00:46:47,320 --> 00:46:51,319 Speaker 12: decarbonizing in a profitable way, because I don't believe it's 773 00:46:51,360 --> 00:46:55,080 Speaker 12: going to happen if it's forced by state or EU 774 00:46:55,560 --> 00:46:58,840 Speaker 12: or any other regulatory issues. You have to find a 775 00:46:58,840 --> 00:47:01,520 Speaker 12: way how to go to CEO two zero so that 776 00:47:01,680 --> 00:47:04,360 Speaker 12: you can make money with that. Then it starts to happen, 777 00:47:05,120 --> 00:47:09,000 Speaker 12: and I really hope it can be an example how 778 00:47:09,040 --> 00:47:12,680 Speaker 12: that is done. 779 00:47:11,200 --> 00:47:14,840 Speaker 10: In a moment when our digital lives demand more than ever. 780 00:47:15,280 --> 00:47:20,080 Speaker 10: Helsinki offers a quiet reminder that progress isn't measured only 781 00:47:20,080 --> 00:47:23,319 Speaker 10: in speed and scale, but in the balance we keep 782 00:47:23,560 --> 00:47:25,240 Speaker 10: as the world races ahead. 783 00:47:28,440 --> 00:47:30,279 Speaker 1: That does it for us. Here at Wall Street Week, 784 00:47:30,560 --> 00:47:34,000 Speaker 1: I'm David Weston. See you next week for more stories 785 00:47:34,080 --> 00:47:49,680 Speaker 1: of capitalism.