1 00:00:02,520 --> 00:00:07,440 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:07,800 --> 00:00:11,160 Speaker 2: Talking about the use of AI for that you need infrastructure. 3 00:00:11,280 --> 00:00:14,000 Speaker 2: We can talk about that now. Nscale, UK, developer for 4 00:00:14,040 --> 00:00:16,720 Speaker 2: AI data centers, is now one of your's most valuable 5 00:00:16,760 --> 00:00:19,360 Speaker 2: startups after raising two billion dollars in a recent round 6 00:00:19,400 --> 00:00:21,560 Speaker 2: which now values the company and a call fourteen point 7 00:00:21,560 --> 00:00:25,800 Speaker 2: six billion dollars. Now the AI hyperscalers are also looking 8 00:00:25,880 --> 00:00:29,480 Speaker 2: to this particular company because they want to be looking 9 00:00:29,800 --> 00:00:32,800 Speaker 2: for more compute. But also they've got some significant leaders 10 00:00:32,840 --> 00:00:36,320 Speaker 2: coming in directors including former British politician Nick Clegg Showl 11 00:00:36,360 --> 00:00:39,159 Speaker 2: Samburg as well longtime chief operating officer of Facebook and 12 00:00:39,200 --> 00:00:41,320 Speaker 2: its parent Meta. And I'm very realased to say we 13 00:00:41,320 --> 00:00:44,200 Speaker 2: can welcome the leadership now n Scale CEO Josh Payin 14 00:00:44,240 --> 00:00:46,080 Speaker 2: along with Cheryl Samburg, and is a joy to have 15 00:00:46,120 --> 00:00:49,280 Speaker 2: you both on the show. And Josh, some huge ambitions 16 00:00:49,280 --> 00:00:52,080 Speaker 2: from n Scale and just the computing power that you 17 00:00:52,120 --> 00:00:54,680 Speaker 2: can bring online, the revenues you're going to be generating 18 00:00:54,680 --> 00:00:56,840 Speaker 2: in the next few years, just talk to us about 19 00:00:56,840 --> 00:00:59,080 Speaker 2: how you achieve that that necessary infrastructure. 20 00:00:59,160 --> 00:01:02,800 Speaker 3: Josh, Well, thank you, Carolina, it's great to be here. 21 00:01:03,120 --> 00:01:05,160 Speaker 3: You know, firstly, what I'll say is this is the 22 00:01:05,160 --> 00:01:08,760 Speaker 3: fourth Industrial Revolution. This market is moving so fast and 23 00:01:08,800 --> 00:01:11,680 Speaker 3: we're still at the beginning. We're talking about a technology 24 00:01:11,680 --> 00:01:15,680 Speaker 3: that is going to lead to atomized automated drug discovery, 25 00:01:15,800 --> 00:01:19,600 Speaker 3: the extension of human life, truly autonomous agents, and that 26 00:01:19,720 --> 00:01:22,840 Speaker 3: the only thing that prevents that future is access to 27 00:01:22,880 --> 00:01:25,520 Speaker 3: the scarce resource, which is the compute. And so n 28 00:01:25,600 --> 00:01:29,200 Speaker 3: scale solves this problem. We buy and build and deploy 29 00:01:29,640 --> 00:01:31,920 Speaker 3: all of that infrastructure to allow for these products to 30 00:01:31,920 --> 00:01:34,440 Speaker 3: be built and operated. And so not only is there 31 00:01:34,480 --> 00:01:36,720 Speaker 3: just huge demand for the sector, but we're capturing it. 32 00:01:37,280 --> 00:01:40,200 Speaker 2: And that's huge demand for your expertise, Sheryl, and to 33 00:01:40,319 --> 00:01:43,399 Speaker 2: join boards. Why did you choose Josh? Why did you 34 00:01:43,440 --> 00:01:44,800 Speaker 2: back end scale? Why on the board? 35 00:01:47,160 --> 00:01:51,520 Speaker 1: Well, the funny part of the story starts with his part, which. 36 00:01:51,320 --> 00:01:56,080 Speaker 3: Is, well, so thinking about how I build the next 37 00:01:56,120 --> 00:01:58,840 Speaker 3: great AI platform, what was most important to me is 38 00:01:58,960 --> 00:02:01,680 Speaker 3: speaking to executive. It was that have built great platforms 39 00:02:01,720 --> 00:02:04,960 Speaker 3: before of global scale, and so certainly none better than 40 00:02:05,040 --> 00:02:07,560 Speaker 3: Cheryl Sandberg. And so I tried for it some time 41 00:02:07,600 --> 00:02:10,760 Speaker 3: to get an introduction to Cheryl, and upon finally doing so, 42 00:02:11,200 --> 00:02:13,680 Speaker 3: we scheduled a thirty minute call and the first thing 43 00:02:13,680 --> 00:02:15,640 Speaker 3: that she said to me was I don't do boards, 44 00:02:15,680 --> 00:02:18,679 Speaker 3: and I don't do these calls. Right, So it was 45 00:02:18,720 --> 00:02:20,120 Speaker 3: an inauspicious beginning. 46 00:02:20,160 --> 00:02:23,239 Speaker 1: But I didn't do boards and I didn't do these calls. 47 00:02:23,280 --> 00:02:25,960 Speaker 1: But what I saw in Josh ninety minutes into our 48 00:02:26,000 --> 00:02:30,200 Speaker 1: thirty minute phone call was what I considered real visionary leadership. 49 00:02:31,320 --> 00:02:33,239 Speaker 1: Over the next few weeks, as he was trying to 50 00:02:33,280 --> 00:02:36,040 Speaker 1: get me to consider joining the board, he went away 51 00:02:36,160 --> 00:02:39,080 Speaker 1: and he wrote a letter to his management team. And 52 00:02:39,120 --> 00:02:41,720 Speaker 1: the only person I'd ever seen right like that was 53 00:02:41,720 --> 00:02:47,600 Speaker 1: Mark Zuckerberg. This combination of a relentless, relentless desire for 54 00:02:47,639 --> 00:02:51,280 Speaker 1: a great, relentless desire for execution, you know. And from 55 00:02:51,280 --> 00:02:53,639 Speaker 1: my point of view, I joined Google when it was 56 00:02:53,680 --> 00:02:56,160 Speaker 1: at two hundred and fifty people left at twenty thousand. 57 00:02:56,200 --> 00:02:58,520 Speaker 1: I joined Facebook when it was five hundred and fifty 58 00:02:58,560 --> 00:03:02,200 Speaker 1: people left, you know, almost one hundred thousand. So the 59 00:03:02,240 --> 00:03:05,360 Speaker 1: opportunity to work with a founder I believe in, I 60 00:03:05,440 --> 00:03:07,480 Speaker 1: joined right as the company was about three hundred and 61 00:03:07,520 --> 00:03:10,799 Speaker 1: four hundred people, so that same spot, and try to 62 00:03:10,840 --> 00:03:13,800 Speaker 1: take some of the lessons we've learned and help a 63 00:03:13,840 --> 00:03:17,080 Speaker 1: company I believe in this much scale really matters. I 64 00:03:17,120 --> 00:03:19,400 Speaker 1: also really believe in the power of AI. I think 65 00:03:19,400 --> 00:03:21,920 Speaker 1: we're at the very beginning I started my career in 66 00:03:21,919 --> 00:03:25,000 Speaker 1: global health. AI is going to mean that anyone in 67 00:03:25,040 --> 00:03:28,160 Speaker 1: a remote village anywhere in the world could get skin 68 00:03:28,280 --> 00:03:32,000 Speaker 1: cancer diagnosed at the same efficacy rate as someone in 69 00:03:32,040 --> 00:03:34,640 Speaker 1: the Mayo clinic. But that is going to take a 70 00:03:34,680 --> 00:03:38,480 Speaker 1: buildout and a buildout of infrastructure and compute, and I 71 00:03:38,520 --> 00:03:41,280 Speaker 1: really believe in Josh and N Scale's ability to do that. 72 00:03:41,320 --> 00:03:42,040 Speaker 1: So I'm happy to. 73 00:03:42,000 --> 00:03:43,680 Speaker 3: Be here, Josh. 74 00:03:44,200 --> 00:03:47,840 Speaker 4: The term neo cloud has actually also become quite broad. 75 00:03:47,840 --> 00:03:50,240 Speaker 4: When I talk to people about nscale, they say, well, 76 00:03:50,360 --> 00:03:54,240 Speaker 4: nscale is modular. How do you set yourselves apart from 77 00:03:54,240 --> 00:03:56,440 Speaker 4: the other neoclouds out there, many many of whom come 78 00:03:56,480 --> 00:03:59,280 Speaker 4: on this program and make quite similar pitches. 79 00:04:01,280 --> 00:04:01,480 Speaker 1: Yeah. 80 00:04:01,480 --> 00:04:03,640 Speaker 3: So I think the key distinction with n scale is 81 00:04:03,680 --> 00:04:06,360 Speaker 3: we are fully vertically integrated. Again, if you think about 82 00:04:06,400 --> 00:04:09,040 Speaker 3: the challenge for the sector, it's actually landing the infrastructure 83 00:04:09,320 --> 00:04:11,560 Speaker 3: on the ground and getting it plugged in. And the 84 00:04:11,600 --> 00:04:14,400 Speaker 3: true scarcity given that the demand in the sector is 85 00:04:14,440 --> 00:04:18,039 Speaker 3: the land, the power, and then the chips and so 86 00:04:18,720 --> 00:04:21,560 Speaker 3: by and large, the neocloud sector is not really vertically 87 00:04:21,560 --> 00:04:23,920 Speaker 3: integrated in that they don't own their own land and power. 88 00:04:24,400 --> 00:04:26,880 Speaker 3: N scale does. We own the land and power, We 89 00:04:26,960 --> 00:04:29,240 Speaker 3: own the chips, and we own the software delivering an 90 00:04:29,320 --> 00:04:33,159 Speaker 3: end to end service to the counterparty. In addition, we 91 00:04:33,240 --> 00:04:37,520 Speaker 3: recently acquired a company called American Intelligence Corporation in West Virginia, 92 00:04:37,560 --> 00:04:40,520 Speaker 3: which adds an even further segment to that, which is 93 00:04:40,560 --> 00:04:42,919 Speaker 3: the ownership of the power. This is a behind the 94 00:04:42,920 --> 00:04:46,400 Speaker 3: meter site, which means that we're effectively taking natural gas 95 00:04:46,839 --> 00:04:50,840 Speaker 3: and producing our own energy, which means it's not connected 96 00:04:50,960 --> 00:04:54,200 Speaker 3: to the local grid and therefore subject to any kind 97 00:04:54,240 --> 00:04:55,839 Speaker 3: of price increases for consumers. 98 00:04:56,839 --> 00:04:59,440 Speaker 4: Soyl, it's great to have you back on Bloomberg Television 99 00:04:59,640 --> 00:05:03,360 Speaker 4: and on Woomberg Tech. You said I don't do boards 100 00:05:03,440 --> 00:05:07,359 Speaker 4: historically with this role with end Scale, I think a 101 00:05:07,360 --> 00:05:09,400 Speaker 4: lot of people are really interested if you go back 102 00:05:09,440 --> 00:05:11,919 Speaker 4: to being an operator. You know, with time, if you 103 00:05:11,920 --> 00:05:15,839 Speaker 4: would join the executive ranks at Ndscale, and whether you 104 00:05:15,880 --> 00:05:18,400 Speaker 4: do or don't kind of operationally, how you think you 105 00:05:18,440 --> 00:05:19,559 Speaker 4: can help the company grow. 106 00:05:20,920 --> 00:05:23,520 Speaker 1: So I've joined as both a board member as an advisor. 107 00:05:23,680 --> 00:05:26,359 Speaker 1: I'm spending real time with Josh and his team. I 108 00:05:26,400 --> 00:05:28,640 Speaker 1: have no plans to go on board full time. They 109 00:05:28,680 --> 00:05:32,479 Speaker 1: have an incredible exec team, and my goal is to 110 00:05:32,760 --> 00:05:36,200 Speaker 1: help them scale, help figure out how we structure, how 111 00:05:36,200 --> 00:05:39,640 Speaker 1: we do corporate governance. I've helped recruit some other great 112 00:05:39,839 --> 00:05:42,520 Speaker 1: board members Nick Clagge you mentioned joined the board with me, 113 00:05:42,960 --> 00:05:47,400 Speaker 1: Sue Decker, who has decades of experience cheering audit committees 114 00:05:47,400 --> 00:05:50,760 Speaker 1: and in the financial world, and work with them to 115 00:05:50,839 --> 00:05:53,920 Speaker 1: really scale their company. What I see in Josh is 116 00:05:53,960 --> 00:05:58,320 Speaker 1: two things is really ambition, like real ambition to make 117 00:05:58,360 --> 00:06:01,880 Speaker 1: a difference in how the AI build out happens, make 118 00:06:01,960 --> 00:06:05,800 Speaker 1: it sustainable, make it clean, commitment to local jobs as 119 00:06:05,839 --> 00:06:09,560 Speaker 1: we scale and build, but also a commitment to excellence, 120 00:06:10,000 --> 00:06:12,479 Speaker 1: to hiring the best people, to getting people into the 121 00:06:12,520 --> 00:06:16,520 Speaker 1: right jobs, to structuring so that we can really execute. 122 00:06:16,720 --> 00:06:19,920 Speaker 1: And it's been it already. Has been a great pleasure 123 00:06:19,920 --> 00:06:23,080 Speaker 1: to work this closely with someone I believe in and 124 00:06:23,160 --> 00:06:26,000 Speaker 1: also Caroline, I know you always care about this. A 125 00:06:26,080 --> 00:06:30,760 Speaker 1: really strong team of senior women. Head of AI Infrastructure, CFO, 126 00:06:31,760 --> 00:06:37,120 Speaker 1: head of security. Josh before me hired what he considers 127 00:06:37,160 --> 00:06:38,800 Speaker 1: who he considers the best people, and a lot of 128 00:06:38,839 --> 00:06:40,000 Speaker 1: great women in those jobs. 129 00:06:40,360 --> 00:06:42,280 Speaker 2: I love that because it's something I'm passionate about it. 130 00:06:42,320 --> 00:06:45,919 Speaker 2: Something that you spend your career advocating for Cheryl is 131 00:06:46,360 --> 00:06:49,480 Speaker 2: diversity within the ranks of talent. But also you're advocating 132 00:06:49,480 --> 00:06:51,560 Speaker 2: as well for clean energy. And I notice what one 133 00:06:51,560 --> 00:06:53,599 Speaker 2: other board seeing with terror dot and that is about 134 00:06:53,640 --> 00:06:56,440 Speaker 2: carbon neutrality. So Josh, I ask you, what about carbon 135 00:06:56,440 --> 00:07:00,080 Speaker 2: neutrality for West Virginia, because that's about actual gas. Do 136 00:07:00,160 --> 00:07:02,080 Speaker 2: you think about that in the longer term? 137 00:07:02,560 --> 00:07:06,039 Speaker 3: Yeah? Sure, so broadly, the company thesis is to take 138 00:07:06,080 --> 00:07:09,159 Speaker 3: sustainable energy and convert it into intelligence. So we first 139 00:07:09,240 --> 00:07:11,880 Speaker 3: do this in the North of Norway. So we operate 140 00:07:11,880 --> 00:07:15,160 Speaker 3: in the North of Norway using only hydropower. The North 141 00:07:15,200 --> 00:07:18,120 Speaker 3: of Norway has such a large oversupply of energy due 142 00:07:18,120 --> 00:07:21,480 Speaker 3: to basically the seasons. Effectively, during the winter all of 143 00:07:21,520 --> 00:07:24,280 Speaker 3: the glaciers melt over and then in the summer they 144 00:07:24,280 --> 00:07:27,560 Speaker 3: all melt and create enormous waterfalls. And the Norwegian government 145 00:07:27,680 --> 00:07:30,840 Speaker 3: has built large hydropower dams to capture that energy. But 146 00:07:30,920 --> 00:07:33,840 Speaker 3: the challenge is it can't be exported and so it's 147 00:07:33,840 --> 00:07:36,320 Speaker 3: got to be consumed in region. So m Scale is 148 00:07:36,320 --> 00:07:38,880 Speaker 3: building some of the largest AI infrastructure projects on the 149 00:07:38,920 --> 00:07:42,600 Speaker 3: European continent in the North of Norway, taking otherwise stranded 150 00:07:42,680 --> 00:07:46,160 Speaker 3: energy and converting it to intelligence. The same goes for 151 00:07:46,280 --> 00:07:49,400 Speaker 3: our projects in Texas as an example. In Texas, you've 152 00:07:49,400 --> 00:07:53,840 Speaker 3: got a similar oversupply of renewables and other energy, but 153 00:07:53,880 --> 00:07:56,320 Speaker 3: it's in remote location. So we're building some of the 154 00:07:56,400 --> 00:08:00,160 Speaker 3: largest infrastructure projects in North America in this location in 155 00:08:00,240 --> 00:08:03,960 Speaker 3: order to convert that to intelligence. Now in West Virginia, 156 00:08:04,040 --> 00:08:06,880 Speaker 3: we're doing the same thing, but slightly different. In West Virginia, 157 00:08:06,920 --> 00:08:09,680 Speaker 3: we're producing our own energy. One of the challenges with 158 00:08:09,720 --> 00:08:13,200 Speaker 3: the North American grid is constrained, and so we felt 159 00:08:13,320 --> 00:08:18,040 Speaker 3: that producing our own energy with natural gas generators behind 160 00:08:18,080 --> 00:08:21,320 Speaker 3: the media was the best way to scale sustainably but 161 00:08:21,400 --> 00:08:26,840 Speaker 3: also not impact local prices and the grid. 162 00:08:28,680 --> 00:08:32,559 Speaker 4: Cheryl, you're very used to being inside companies that are 163 00:08:32,679 --> 00:08:35,800 Speaker 4: just truly global, right listening to what Josh is saying. 164 00:08:36,600 --> 00:08:38,920 Speaker 4: N Scale gets a lot of credit because it's a 165 00:08:39,000 --> 00:08:43,280 Speaker 4: kind of a leader in Europe, it is a footprint 166 00:08:43,320 --> 00:08:46,040 Speaker 4: in the United Kingdom. But we've just been talking about America. 167 00:08:46,280 --> 00:08:48,199 Speaker 4: How much do you want Josh, I know he's sitting 168 00:08:48,240 --> 00:08:51,200 Speaker 4: next to you, to shift gears a little bit and 169 00:08:51,240 --> 00:08:53,839 Speaker 4: move this company in himself to the US. Do you 170 00:08:53,840 --> 00:08:56,120 Speaker 4: want him to focus on the Middle East, where there 171 00:08:56,160 --> 00:08:59,040 Speaker 4: is the capital, there is the will, there is energy 172 00:08:59,080 --> 00:08:59,960 Speaker 4: supply for example. 173 00:09:01,480 --> 00:09:05,280 Speaker 1: Well, I'll let him answer that. But certainly this is global, right, 174 00:09:05,400 --> 00:09:10,800 Speaker 1: This is a global company started in London and continuing 175 00:09:10,880 --> 00:09:15,119 Speaker 1: to expand all over the world. Yeah, I mean today. 176 00:09:16,360 --> 00:09:20,760 Speaker 3: Today we're operating in five countries. We have plans for fifteen. Naturally, 177 00:09:21,040 --> 00:09:24,040 Speaker 3: North America is the center of the universe for artificial intelligence, 178 00:09:24,200 --> 00:09:28,400 Speaker 3: both with startups, with larger customers, with access to capital, 179 00:09:28,720 --> 00:09:30,760 Speaker 3: and so naturally I spent a lot of my time here, 180 00:09:31,000 --> 00:09:33,480 Speaker 3: but as Cheryl said, this is a global market, and 181 00:09:33,559 --> 00:09:35,400 Speaker 3: I'm spending most of my time on a plane as 182 00:09:35,400 --> 00:09:35,800 Speaker 3: a result. 183 00:09:37,640 --> 00:09:40,280 Speaker 4: That's a very familiar tale that you appears have told 184 00:09:40,360 --> 00:09:42,640 Speaker 4: us on this program. To n Scale CEO Josh pay 185 00:09:43,000 --> 00:09:46,400 Speaker 4: and Scale board member and advisor Cheryl Sandberg, it's great 186 00:09:46,440 --> 00:09:47,920 Speaker 4: to have you both on the program.