1 00:00:06,000 --> 00:00:07,960 Speaker 1: Welcome to Fearing Greed Q and a will we ask 2 00:00:08,000 --> 00:00:11,480 Speaker 1: and answer questions about business, investing, economics, politics and more. 3 00:00:11,520 --> 00:00:15,320 Speaker 1: I'm Suan Almer. As AI continues to boom, the biggest challenge, 4 00:00:15,720 --> 00:00:17,959 Speaker 1: at least one of the biggest challenges is likely to 5 00:00:18,000 --> 00:00:21,000 Speaker 1: be electricity demand. How the grid can handle the huge 6 00:00:21,040 --> 00:00:24,639 Speaker 1: power needs of the data centers running AI. With the 7 00:00:24,640 --> 00:00:28,040 Speaker 1: big tech company spending hundreds of billions of dollars literally 8 00:00:28,120 --> 00:00:31,960 Speaker 1: on AI this year alone, data center electricity demand is surging, 9 00:00:32,040 --> 00:00:35,600 Speaker 1: so it's perhaps no surprise at Australia's latest unicorn is 10 00:00:35,640 --> 00:00:39,040 Speaker 1: the company that aims to solve AI's energy supply challenge. 11 00:00:39,200 --> 00:00:41,960 Speaker 1: Nier has just raised ninety million dollars in a funding 12 00:00:42,040 --> 00:00:45,479 Speaker 1: round that values it above one billion dollars. Jack Curtis 13 00:00:45,880 --> 00:00:48,400 Speaker 1: is the co founder and chief commercial officer of Nier. 14 00:00:48,520 --> 00:00:48,720 Speaker 2: Jack. 15 00:00:48,760 --> 00:00:50,919 Speaker 1: Welcome to Fearing Greed Q and a thank you for 16 00:00:50,920 --> 00:00:53,960 Speaker 1: having me Sean. Firstly, congratulations on the business. Nice to 17 00:00:53,960 --> 00:00:55,520 Speaker 1: be able to raise ninety million dollars to get that 18 00:00:55,560 --> 00:00:56,240 Speaker 1: sort of valuation. 19 00:00:56,320 --> 00:00:59,680 Speaker 2: Were you surprised, I think to some extent, I think 20 00:00:59,760 --> 00:01:02,440 Speaker 2: too another extent, you to the points you're just touching 21 00:01:02,440 --> 00:01:06,360 Speaker 2: on the introduction we do benefit from just good timing 22 00:01:06,520 --> 00:01:08,680 Speaker 2: relative to a lot of the macro trends that are 23 00:01:08,720 --> 00:01:12,400 Speaker 2: underpinning the kind of demand for what we do. Sometimes 24 00:01:12,440 --> 00:01:14,360 Speaker 2: it's good to be lucky as well as not too 25 00:01:14,400 --> 00:01:16,960 Speaker 2: bad at what you do. And I think to some extent, 26 00:01:17,280 --> 00:01:19,240 Speaker 2: you know, we really were trying to take advantage of 27 00:01:19,280 --> 00:01:22,959 Speaker 2: those tailwinds. So always pleasantly surprised when things go well, 28 00:01:23,200 --> 00:01:27,200 Speaker 2: but also benefiting from, you know, a lot of momentum 29 00:01:27,200 --> 00:01:28,680 Speaker 2: in the space that we cover as well. 30 00:01:28,680 --> 00:01:30,520 Speaker 1: Now, Jack, in the years to come, If you ever 31 00:01:30,600 --> 00:01:32,880 Speaker 1: list right and someone asks you that question, you say, yeah, 32 00:01:32,880 --> 00:01:36,479 Speaker 1: we're really good. That's very understated. 33 00:01:36,760 --> 00:01:39,039 Speaker 2: If I ever say that, mate, please please remind me 34 00:01:39,120 --> 00:01:39,840 Speaker 2: that I once did it. 35 00:01:42,120 --> 00:01:44,600 Speaker 1: Okay, so tell me what Neira is doing, just like 36 00:01:44,680 --> 00:01:46,080 Speaker 1: Fundat give me a one o one. 37 00:01:46,120 --> 00:01:49,400 Speaker 2: Yeah, sure thing. So obviously we're a software company. We 38 00:01:49,440 --> 00:01:54,200 Speaker 2: build digital models of critical infrastructure, primarily today electricity networks. 39 00:01:54,640 --> 00:01:58,000 Speaker 2: What that means is that we build a three dimensional 40 00:01:58,120 --> 00:02:02,840 Speaker 2: visual representation of power lines and electricity grids. But that's 41 00:02:03,000 --> 00:02:05,800 Speaker 2: probably the most reductive thing that we do. What we're 42 00:02:05,840 --> 00:02:09,160 Speaker 2: really doing that you know, is underpinning I guess the 43 00:02:09,240 --> 00:02:12,800 Speaker 2: traction we've had so far is we're building behavior models. 44 00:02:13,160 --> 00:02:14,959 Speaker 2: And what I mean by that is that we take 45 00:02:15,000 --> 00:02:18,160 Speaker 2: these visual models and we infuse them with all the 46 00:02:18,200 --> 00:02:21,840 Speaker 2: physics and engineering characteristics of the assets. And so what 47 00:02:21,880 --> 00:02:24,760 Speaker 2: that means is that the people that own and operate 48 00:02:24,800 --> 00:02:28,680 Speaker 2: this critical infrastructure, you know, that are responsible for electricity supply, 49 00:02:29,400 --> 00:02:31,840 Speaker 2: we can give them such a level of confidence that 50 00:02:31,880 --> 00:02:35,639 Speaker 2: the digital models we're building are such an accurate, not 51 00:02:35,720 --> 00:02:39,320 Speaker 2: just visual but behavior representation that if they simulate something 52 00:02:39,320 --> 00:02:42,240 Speaker 2: in the digital model, the likelihood that it's going to 53 00:02:42,560 --> 00:02:47,640 Speaker 2: essentially manifest similarly in the physical world is very high. 54 00:02:47,919 --> 00:02:49,560 Speaker 2: And you can only do that when you can bin 55 00:02:49,760 --> 00:02:54,079 Speaker 2: a visual representation with a very accurate behavior representation of 56 00:02:54,120 --> 00:02:54,639 Speaker 2: the assets. 57 00:02:54,880 --> 00:02:56,400 Speaker 1: Okay, so I'm going to try and repeat that to 58 00:02:56,440 --> 00:02:58,520 Speaker 1: you in an example to make sure I've got it right. 59 00:02:58,760 --> 00:03:02,160 Speaker 1: So we'll come to technology in a moment. Let's that's 60 00:03:02,200 --> 00:03:05,280 Speaker 1: a mining company that knows that it's got a big 61 00:03:05,320 --> 00:03:07,640 Speaker 1: mine in central New South Whisos. It's a gold miner. 62 00:03:07,800 --> 00:03:10,079 Speaker 1: Let's call it Kadia, one of Newman's mind that's out there. 63 00:03:10,760 --> 00:03:12,680 Speaker 1: They need power the whole time, but there are certain 64 00:03:12,720 --> 00:03:16,200 Speaker 1: times when they're working they need more power, and so 65 00:03:16,240 --> 00:03:19,040 Speaker 1: it's all about not just setting up a physical representation 66 00:03:19,160 --> 00:03:21,960 Speaker 1: of that, but actually being able to model and give 67 00:03:22,440 --> 00:03:26,680 Speaker 1: the company security over that power supply. So is that 68 00:03:26,800 --> 00:03:27,960 Speaker 1: broadly what we're talking about. 69 00:03:28,000 --> 00:03:31,280 Speaker 2: They're an excellent example, okay, And so think about it 70 00:03:31,320 --> 00:03:34,360 Speaker 2: in two lenses. The lens you described, which is, how 71 00:03:34,400 --> 00:03:38,520 Speaker 2: can we identify where power can be made available even 72 00:03:38,560 --> 00:03:41,080 Speaker 2: if right now we don't know that? And then secondly, 73 00:03:41,440 --> 00:03:44,840 Speaker 2: if something is going to happen externally that impacts the 74 00:03:44,880 --> 00:03:47,640 Speaker 2: reliability of that power. So say, for example, if a 75 00:03:47,680 --> 00:03:50,080 Speaker 2: big dust storm came through or a hurricane came through, 76 00:03:50,600 --> 00:03:53,880 Speaker 2: we can actually preemptively say what is going to happen 77 00:03:53,880 --> 00:03:57,440 Speaker 2: to that infrastructure and help them prepare to mitigate that effect. 78 00:03:57,880 --> 00:04:00,440 Speaker 1: Okay, at the risk of someding really stupid. Where does 79 00:04:00,480 --> 00:04:03,760 Speaker 1: power come from? And I kind of almost mean that literally. 80 00:04:04,040 --> 00:04:07,720 Speaker 1: I understand that it comes from renewables and cold fired 81 00:04:07,760 --> 00:04:12,200 Speaker 1: power stations, et cetera. But it's the transmission mechanism. So 82 00:04:12,280 --> 00:04:14,280 Speaker 1: let's go to a data center in this instance, and 83 00:04:14,440 --> 00:04:15,960 Speaker 1: we're going to know that it's going to be peak 84 00:04:16,200 --> 00:04:18,520 Speaker 1: pool on data centers at certain times of the day, 85 00:04:18,680 --> 00:04:23,560 Speaker 1: presumably yep. Does the provider of the data center have 86 00:04:23,680 --> 00:04:25,839 Speaker 1: to well, they have to understand that they need power, 87 00:04:25,880 --> 00:04:28,000 Speaker 1: But are they the ones that are trying to work 88 00:04:28,040 --> 00:04:29,760 Speaker 1: out the challenge of how to get the power in 89 00:04:30,120 --> 00:04:33,000 Speaker 1: when they need more power, et cetera? Is it them? 90 00:04:33,200 --> 00:04:34,479 Speaker 1: And then where do they get it from? 91 00:04:34,800 --> 00:04:37,680 Speaker 2: Yeah? So where does power come from? It comes from 92 00:04:37,720 --> 00:04:41,520 Speaker 2: two things. It comes from generating assets, so things like solar, 93 00:04:41,680 --> 00:04:45,120 Speaker 2: when gas historically coal, and then it comes from the 94 00:04:45,160 --> 00:04:49,080 Speaker 2: electricity network that sports that generation to the people that 95 00:04:49,160 --> 00:04:52,520 Speaker 2: need it like a data center. Now, over the last 96 00:04:52,600 --> 00:04:57,440 Speaker 2: kind of five ten years, the constraints around generation, the 97 00:04:57,480 --> 00:04:59,920 Speaker 2: ability to bring new generations to the system have gone 98 00:05:00,040 --> 00:05:03,200 Speaker 2: dramatically down, so the cost of renewables has come down. 99 00:05:03,720 --> 00:05:05,719 Speaker 2: You know, there's a whole broader conversation around what the 100 00:05:05,800 --> 00:05:08,440 Speaker 2: energy mix should be. But for quite a while now, 101 00:05:08,600 --> 00:05:11,960 Speaker 2: the problem statement hasn't been is generation available or can 102 00:05:12,000 --> 00:05:15,360 Speaker 2: it be made available? The problem statement is is there 103 00:05:15,480 --> 00:05:20,280 Speaker 2: enough network capacity to bring that generation to new people 104 00:05:20,600 --> 00:05:23,440 Speaker 2: that want a lot more energy? And that goes to 105 00:05:23,480 --> 00:05:25,960 Speaker 2: the crux of the problem statement that we solve, which 106 00:05:26,000 --> 00:05:29,800 Speaker 2: is assume there's readily available generation that can be brought online, 107 00:05:30,160 --> 00:05:34,080 Speaker 2: but the ability to access the grid to receive that 108 00:05:34,200 --> 00:05:38,080 Speaker 2: generation has been challenged for some time now, and so 109 00:05:38,360 --> 00:05:42,360 Speaker 2: to take your specific example, data center developers and operators 110 00:05:42,920 --> 00:05:45,280 Speaker 2: are desperately trying to get more data centers up as 111 00:05:45,320 --> 00:05:48,400 Speaker 2: quickly as possible and running around the world quite literally, 112 00:05:48,800 --> 00:05:52,880 Speaker 2: trying to find those markets where generation is freely available 113 00:05:53,240 --> 00:05:56,560 Speaker 2: and network is available. And what we've discovered on our 114 00:05:56,640 --> 00:05:59,960 Speaker 2: journey in this space is that the number one things 115 00:06:00,040 --> 00:06:03,320 Speaker 2: slowing down more data centers in Australia and everywhere is 116 00:06:03,440 --> 00:06:06,839 Speaker 2: access to energy, and specifically access to the grid or 117 00:06:06,839 --> 00:06:08,320 Speaker 2: access to the electricity network. 118 00:06:09,400 --> 00:06:12,599 Speaker 1: How big an issue is this if we want to 119 00:06:12,640 --> 00:06:17,919 Speaker 1: be an AI slash tech driven economy. 120 00:06:16,760 --> 00:06:19,000 Speaker 2: It's pretty existential. And I don't say that just because 121 00:06:19,000 --> 00:06:20,880 Speaker 2: I play in the space, but if you look at 122 00:06:21,320 --> 00:06:26,560 Speaker 2: the broader kind of policy goals of the Australian government generally, 123 00:06:26,600 --> 00:06:29,719 Speaker 2: and I think they're noble ones. One is to increase productivity, 124 00:06:30,080 --> 00:06:33,640 Speaker 2: One is to increase Australia's ability to export innovation. And 125 00:06:33,720 --> 00:06:38,560 Speaker 2: so we actually are a very appealing destination for data 126 00:06:38,600 --> 00:06:42,080 Speaker 2: center investment. And I heard a scary statistic the other 127 00:06:42,160 --> 00:06:44,680 Speaker 2: day where someone said to me they don't believe there's 128 00:06:44,760 --> 00:06:47,240 Speaker 2: enough money in the world to fund the appetite for 129 00:06:47,360 --> 00:06:50,000 Speaker 2: data centers. I've never heard that before, and so think 130 00:06:50,040 --> 00:06:53,200 Speaker 2: about all this money looking to invest in data centers. 131 00:06:53,640 --> 00:06:58,240 Speaker 2: Australia could be a great repository of data center investment. 132 00:06:58,800 --> 00:07:03,360 Speaker 2: But there's this potential unfortunate irony that unless we make 133 00:07:03,480 --> 00:07:08,120 Speaker 2: access to getting data centers permitted, land permitting, those usual 134 00:07:08,520 --> 00:07:10,840 Speaker 2: you know kind of things that are required to get 135 00:07:10,880 --> 00:07:14,360 Speaker 2: any asset up, but more importantly access to energy, then 136 00:07:14,400 --> 00:07:17,920 Speaker 2: we might actually miss the opportunity for Australia to build 137 00:07:17,960 --> 00:07:20,960 Speaker 2: this pillar of productivity because all the world's data center 138 00:07:21,040 --> 00:07:23,880 Speaker 2: developers are literally just running around the world speaking to 139 00:07:23,960 --> 00:07:27,000 Speaker 2: government saying how quickly can I get data centers up 140 00:07:27,000 --> 00:07:27,600 Speaker 2: in your country? 141 00:07:28,680 --> 00:07:31,320 Speaker 1: Okay, So the next part of that question to me, 142 00:07:31,960 --> 00:07:36,400 Speaker 1: given our capacity now and what's coming online, how much 143 00:07:36,400 --> 00:07:40,440 Speaker 1: of what you've just talked about can be solved through logistics. 144 00:07:40,520 --> 00:07:42,480 Speaker 1: So I'm going to say nearer in this instance as 145 00:07:42,480 --> 00:07:46,160 Speaker 1: an example, and how much I mean, what part of 146 00:07:46,160 --> 00:07:48,680 Speaker 1: one hundred percent can we get to just by doing 147 00:07:48,720 --> 00:07:49,200 Speaker 1: it smarter? 148 00:07:49,840 --> 00:07:51,680 Speaker 2: Yeah, So I think there's really two things to it. 149 00:07:51,920 --> 00:07:55,520 Speaker 2: One is a process problem statement a regulatory problem statement, 150 00:07:55,920 --> 00:07:58,600 Speaker 2: which is, if you're a data center developer and you 151 00:07:58,680 --> 00:08:01,440 Speaker 2: come to Australia. You want to know how fast is 152 00:08:01,440 --> 00:08:06,120 Speaker 2: it for me to get land access, utility access, environmental permitting, 153 00:08:06,240 --> 00:08:07,960 Speaker 2: all the things that go into just getting an asset 154 00:08:07,960 --> 00:08:10,560 Speaker 2: into the ground. So I'd describe it as like half 155 00:08:10,600 --> 00:08:13,800 Speaker 2: a red tape challenge or process challenge, and the other 156 00:08:13,840 --> 00:08:17,480 Speaker 2: half of the challenge is all right, today we've really 157 00:08:17,480 --> 00:08:21,520 Speaker 2: focused on building new electricity grids or transmission infrastructure to 158 00:08:21,600 --> 00:08:25,400 Speaker 2: solve the transportation problem. What we're doing is actually looking 159 00:08:25,440 --> 00:08:28,560 Speaker 2: at the existing grid and saying you can actually get 160 00:08:28,560 --> 00:08:31,720 Speaker 2: a lot more out of it just by smarter analysis, 161 00:08:31,880 --> 00:08:35,880 Speaker 2: smarter assumption, optimization, and really leveraging what we already have. 162 00:08:36,400 --> 00:08:39,640 Speaker 2: So I'd say the answer is twofold technology can solve 163 00:08:39,679 --> 00:08:42,440 Speaker 2: the absolute available problem statement, But then we need to 164 00:08:42,679 --> 00:08:46,320 Speaker 2: supplement that with the right processes and regulatory approvals so 165 00:08:46,360 --> 00:08:48,920 Speaker 2: that assets can move faster into the ground and not 166 00:08:48,960 --> 00:08:50,760 Speaker 2: get caught up in regulatory red tape. 167 00:08:51,240 --> 00:08:54,040 Speaker 1: Are there sectors or maybe economies, because I know you 168 00:08:54,120 --> 00:08:58,000 Speaker 1: work global with global companies that are just doing this better. 169 00:08:58,679 --> 00:09:01,400 Speaker 2: Look, the answer is not, really, this is a problem 170 00:09:01,440 --> 00:09:04,040 Speaker 2: statement that is the world over. It's the problem statement 171 00:09:04,080 --> 00:09:07,679 Speaker 2: that has constrained energy transition policy the world over. So 172 00:09:07,840 --> 00:09:11,160 Speaker 2: this problem statement is exactly the same in renewable energy 173 00:09:11,200 --> 00:09:15,280 Speaker 2: transition policy land lots of renewable generation. It's now very cheap, 174 00:09:15,400 --> 00:09:18,640 Speaker 2: it can now be made reliable, but not enough grid 175 00:09:18,679 --> 00:09:20,880 Speaker 2: to connect it to. And so if you just copy 176 00:09:20,880 --> 00:09:24,120 Speaker 2: paste data center with renewable generating asset, it's the same 177 00:09:24,120 --> 00:09:27,960 Speaker 2: problem statement. Everyone's trying to solve it. I think that 178 00:09:28,200 --> 00:09:30,440 Speaker 2: what's going to happen is that it's going to become 179 00:09:31,400 --> 00:09:35,440 Speaker 2: more and more incumbent on those trying to bring data 180 00:09:35,480 --> 00:09:39,000 Speaker 2: centers forward to actually take the scope into their own hands. 181 00:09:39,200 --> 00:09:41,520 Speaker 2: And so now what you're seeing is big data center 182 00:09:41,559 --> 00:09:44,680 Speaker 2: developers that are building their own generating assets, they're building 183 00:09:44,679 --> 00:09:48,359 Speaker 2: their own network, and so they're creating an entire ecosystem 184 00:09:48,880 --> 00:09:51,960 Speaker 2: just because the amount of money behind bringing data centers 185 00:09:51,960 --> 00:09:54,679 Speaker 2: online is so urgent. And I think to some extent, 186 00:09:54,840 --> 00:09:58,080 Speaker 2: you know, that's great to see people take outcomes into 187 00:09:58,080 --> 00:10:00,959 Speaker 2: their own hands, but also a bit of shame because 188 00:10:00,960 --> 00:10:03,400 Speaker 2: it means that we're not going to fully leverage our 189 00:10:03,400 --> 00:10:07,000 Speaker 2: inherent advantage just because we can't make the things that 190 00:10:07,040 --> 00:10:10,560 Speaker 2: are non called data centers readily available, such as data 191 00:10:10,559 --> 00:10:12,880 Speaker 2: center operators are now taking that into their own hands. 192 00:10:13,400 --> 00:10:15,719 Speaker 1: So I mean that begs the question on regulation and 193 00:10:15,800 --> 00:10:18,440 Speaker 1: government policy. Are we heading in the right direction or 194 00:10:18,480 --> 00:10:19,160 Speaker 1: do we need more? 195 00:10:19,679 --> 00:10:23,120 Speaker 2: I think the momentum behind it, the sentiment behind it 196 00:10:23,160 --> 00:10:26,000 Speaker 2: is excellent. I think it's now how do we move 197 00:10:26,040 --> 00:10:29,240 Speaker 2: that to the most sensible tactical execution. And this whole 198 00:10:29,280 --> 00:10:32,400 Speaker 2: topic about how to make Australia a destination for investment 199 00:10:32,480 --> 00:10:34,880 Speaker 2: beyond the core things that Australia has been built on 200 00:10:35,480 --> 00:10:39,160 Speaker 2: has been well prosecuted for some time. I think now 201 00:10:39,200 --> 00:10:43,520 Speaker 2: it's quite generally without the subjectivity looking to where technology 202 00:10:44,160 --> 00:10:47,800 Speaker 2: can actually accelerate this constraint removal and then having a 203 00:10:47,840 --> 00:10:51,320 Speaker 2: pretty introspective moment around all right, there are other countries 204 00:10:51,320 --> 00:10:53,800 Speaker 2: that manage to get these assets fast into the ground 205 00:10:53,920 --> 00:10:56,960 Speaker 2: without creating other downstream problems that everyone wants to avoid. 206 00:10:57,400 --> 00:10:59,360 Speaker 2: How can we look to best practice in that domain 207 00:10:59,360 --> 00:10:59,760 Speaker 2: as well? 208 00:11:00,559 --> 00:11:02,240 Speaker 1: Jack, I've just changed my mind. I think you actually 209 00:11:02,240 --> 00:11:03,760 Speaker 1: would be a very good CEO. And if you used 210 00:11:03,800 --> 00:11:06,920 Speaker 1: to come, because after that last answer you've got a 211 00:11:07,000 --> 00:11:09,120 Speaker 1: down pad. Well done. Thank you very much for talking 212 00:11:09,120 --> 00:11:09,800 Speaker 1: to Fear and Greed. 213 00:11:10,000 --> 00:11:11,880 Speaker 2: Thank you for the time show. I really appreciate it. 214 00:11:11,880 --> 00:11:14,360 Speaker 1: That was Jack Curtis, co founder and Chief Commercial Officer 215 00:11:14,520 --> 00:11:17,000 Speaker 1: of Nier. I'm Chanelmer And this is fear and greed, 216 00:11:17,040 --> 00:11:17,440 Speaker 1: Q and DA