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Robinson Meyer: Hello, it's Wednesday, May 6th, and the Strait of Hormuz is still closed. In fact, both the United States and Iran claim to control the strait, and energy traders around the world, not to mention policymakers and the general public, are trying to understand the situation.
So today, I want to welcome someone who's made billions of dollars understanding and monitoring situations a lot like this one. John Arnold has a good claim to be the best energy trader of all time. He began his career when he was 21 years old and working in natural gas trading at Enron. He later established Centaurus Advisors, LLC, a hedge fund specializing in energy in Houston.
But since 2008, he and his wife, Laura, have led Arnold Ventures, which is one of the most interesting and I would say one of the most effective philanthropic organizations out there. They work on criminal justice reform, lowering drug prices, reining in sports betting, and for our purposes, how to build more housing, transportation, and infrastructure in the United States, including how to build more electricity infrastructure. For that reason, they've been at the forefront of the permitting reform conversation. In fact, I'd say they helped to drive it, in part because John is also a clean energy investor. He's a co-founder and chairman of Grid United, which is building some of the most ambitious transmission projects in the United States. And he's an investor in the advanced geothermal company Fervo, which we talked about on a recent episode.
So many of the topics, in fact, that we work on or talk about at Shift Key come down to topics that John Arnold thinks about every day.
One goal of Shift Key, in fact, I think is to step back from the news cycle from time to time and have bigger conversations with guests like John. And so today for the first episode in our new occasional “big interview” series, I'm talking to John Arnold about how he reads the current moment in energy, about what he learned during his recent trip to China, where he went to EV factories — it was the first time he'd ever been to that country — and about what clean energy companies can and should learn from fossil fuels. I'm Robinson Meyer, the founding executive editor of Heatmap News, and it's all coming up on ShiftKey, Heatmap's podcast about decarbonization and the shift away from fossil fuels. John Arnold, welcome to Shift Key.
John Arnold: Great to be here.
Robinson Meyer: So my colleague is reading Lloyd Blankfein's memoir and found out in the memoir, he confesses he still trades every day, that he can't get away from it. You're one of the great energy traders. Are you still trading on a day-to-day basis?
John Arnold: I do not trade on a day-to-day basis. I still follow the markets on a day-to-day basis. I think I've become every year a little bit more separated from what's actually going on. And what I don't even know, I don't know increases. I will trade a few times a year.
Robinson Meyer: Do you feel in moments like this one, or in I don't know, March 2020, did you feel the pull to get more involved? Were you like, Oh, my gosh, there's stuff happening. I have to be there. Or was it like, Oh, no, there's too much. I can't possibly trade in this moment.
John Arnold: Oh, for sure. I think, you know, in moments of panic, I think is when the best opportunity exists, particularly for somebody who's not in the day-to-day of it. And so you really have to choose your spots about when that chaos comes in and the market might get mispriced. And that's the opportunity for someone like me at this point.
Robinson Meyer: Speaking of which, let's talk about the current moment. So how do you read this current moment in global energy? I would say in oil specifically, then we can get to natural gas and maybe crucially, is the way the oil market is behaving in response to the Strait of Hormuz's closure and this kind of prolonged ceasefire that may be breaking down literally as we record this, should oil be higher? And is the movement of oil confusing you or do you think kind of makes sense?
John Arnold: Yeah, there was this market chaos whenever I think there was the understanding that the Strait was going to be closed for some period of time. And that's when you saw Brent shoot up to $120 plus, at least intraday, and really had the whole panic because this is what the oil market has been fearing for decades. And obviously, in retrospect, that move had gone too far. I think a few things happened. One was it's three weeks to get cargos from the Middle East to either East Asia or to Europe. It took three weeks for the end user to really stop receiving new cargoes. The market was already soft at the time, so there was some kind of looseness in the market. The commercial inventories were healthy, and the steeply backward-aided curve created a tremendous incentive for anybody with those inventories to try to sell them onto the market.
Strategic reserves started getting sent out. There was a little bit of demand destruction. You had the administration was making all sorts of rhetorical claims that this would end soon or that there was a way to open up the strait. So I think that the whole combination of things has been weighing on the market.
The Saudis and others found ways to reroute a number of the barrels. But now, you know, you're a little bit more than two months in to the strait being closed. And you still have this kind of 10 to 12 million barrels a day that's off market. And that's really starting to add up. And the commercial inventories are being worn down. The three weeks is up, so people are not receiving their cargoes that they were expecting. And so I've made this comment before, but each day that goes by that there's not a settlement, that the straight is not open, the fair value of oil goes up. And it's not going to be a straight line up. It's going to bounce around. It bounced up today, bounced down on last Friday. But you are on this upward trend and i think the problem gets harder with each passing day and that's that's you know not a controversial opinion but i do think it is it just starts getting to be the real dilemma especially with both sides thinking that they can play the waiting game and neither side really has a good card to play as to what to do next what's.
Robinson Meyer: What do you think is the most plausible endgame? You just observed that basically neither side, I think, feels like it's winning or losing — it's a real stalemate — but meanwhile the physical market is deteriorating what maybe what are the scenarios you're thinking through in your head
John Arnold: It has to end with a negotiated settlement. I think it's easy to say, but it's very, very difficult to imagine how that happens, especially how emboldened I think both sides are. This notion of Iran's access to nuclear material that can be used to make a bomb has been a stickler for the West for now decades. And you've had many, many administrations saying that Iran cannot be allowed to get the nuclear weapon. And so the question is, how does this end in a better spot with respect to access to nuclear material than when it started, especially with how emboldened that Iran feels today? And I think that is kind of difficult to imagine. And if I had the answer to this, I would maybe be on National Security Council. But we're kind of in this spot where I think had one war gamed this out beforehand, and there was some probability you get to this point, and you would probably say, like, let's just hope that we don't end up there, because there's no easy way out.
Robinson Meyer: I was talking to a few foreign policy people who worked in the past administration over the weekend. And one of them said something like, you have to say the president has somewhat succeeded here in managing the market so far. Because when Russia invaded Ukraine, Brent went to 140 on fears of a supply disruption. But then a supply disruption never really materialized to the same extent that it has today. Well, today, obviously, we're losing 10 million barrels a day. There is a real supply disruption. And, you know, prices are like flirting with Brent, in this case, is flirting with 110. It kind of goes up to 120, comes back down. But do you think that the administration, the president kind of deserves credit for managing prices or is this all going to backfire as this continues and we don't see a supply response from, say, the U.S. because prices have remained depressed?
John Arnold: Yes and yes. So I think he has done a good job of talking down the market to date. And you hear the open the straight or we're going to blow you to smithereens, open the straight or we're going to blockade, open the straight or we're going to escort friendly ships through. There's the we're very close to a deal that gets talked about oftentimes these statements get released on sunday before markets open and so in that sense you know i think those who are along the market live in fear of one bad headline and you lose ten dollars and there's just an air gap in the market and so i think that provides a level of fear and maybe the risk averse are less comfortable in trying to bid up supplies. That being said, the purpose of prices is to allocate scarce resources. And to the extent that we need higher prices in order to create more demand destruction, we're not getting it today. And again, each day that goes on, the market gets even tighter and tighter physically.
And those who had commercial inventories that they drew down, or they bought them back a month or two deferred in the financial markets because you could make a $7 or $10, $15 by just playing the curve. But then you get to the point where, okay, now you want your barrels. And so to some extent that gets met by the release of strategic reserves. I think countries get more hesitant over time to put out those barrels, but you do end up with, I think keeping prices lower in the short term means higher in the medium term if we get there.
Robinson Meyer: We're getting into kind of full-on oil analysis territory, but like, when would higher prices begin to fetch more supply? Because I was at Sierra Week a few weeks ago, and it seemed like part of the issue the administration faces is that even if we were to bring more supply onto the market, it wouldn't arrive till late, till after the midterms. It's a salient political touchpoint, but in the back half of this year, the very end of this year and the beginning of next year.
John Arnold: Exactly. And I think that's what makes energy markets fascinating is that they're relatively inelastic, both supply and demand in the short term. You have to raise gasoline prices to very high levels to get people to change their driving habits. You have to raise jet fuel prices to high levels to get that to start changing, you know, am I going to go on that plane trip or not? And so demand destruction is limited and very inelastic, as well as the ability to bring new supplies on. Plus, the forward curve now is starting to give that real price signal to producers. But for, you know, the first four or six weeks of this, the curve was in steep backwardation. And so a producer would be looking at it and say, you know, it's still WTI $70 or below for when I'm actually going to get that oil that I'm investing a new CapEx in today. And so that wasn't that appealing, even though the short end of the curve was at the 90, 100 plus level.
Robinson Meyer: Stepping back, looking beyond oil, how are you thinking about the energy fallout from this conflict so far, and especially in its long-term implications? I think folks like Fatih Birol have talked about this as an inflection point in energy, as a moment when a number of countries, I think especially in Southeast Asia, are going to look at the energy security implications of relying on seaborne oil. There's a story about Chinese EV sales surging. Do you buy that story, or do you think there's more inertia in the system than we realize and things will snap back basically once the street reopens? And there might be some change in stocks, but this is not the 1970s all over again.
John Arnold: Right. And I think the challenge here is that energy system is enormous. It is long-lived assets that take a long time to build anything new. And things happen at the margin. And so if you just think about what would it take to increase EV market share of cars on the road globally, it's an enormous amount of effort that would be required an enormous amount of time until that starts to become material. The whole stock versus flow issue, even if you're selling 50% market share of EVs, you're still competing with all the autos on the road today. And I think that metaphor is broadly true across much of the energy industry. You can think about the U.S. generation fleet. And while the vast majority of new generation that came on last year was solar and batteries, you know, solar is still a relatively small percentage of the total U.S. System, right? And so that stock versus flow thing, you're not getting away from. And that being said, I think every country is going to value energy security.
John Arnold: In an increasing manner going forward. Now, what that actually means in practice is a little bit harder. And as you said, this is long-term ramifications. This is not how's the energy system going to change in six months or even in a few years. We're talking about how the decisions that get made today that start showing up in any material ways kind of in the five to 10-year window.
Robinson Meyer:So you recently went to China for the first time. Lots of people, when they go to China for the first time, they have a kind of eye-opening experience. Were you expecting an eye-opening experience? What did you expect and what did you encounter?
John Arnold: Yeah, I mean, the reason I went, and I had been kind of embarrassed that I hadn't been previously. I travel a lot, I go international a lot, and just never had the strong desire or the need to go to China, and so I hadn't. But I was growing interested in China as it was starting to be at the technological edge on many things. And so if you think about just kind of the industrialization of China, you know, it's kind of went up from low value to medium value. It was producing lower quality goods even 10 years ago. If you mentioned any type of good from China or most goods from China in the West were deemed to be of inferior quality. And over the past 10 years, particularly over the past five years, I think that's started to flip. And you see a number of industries like EVs, like batteries and solar panels, telecom equipment, et cetera, where China is now on the leading edge, bleeding edge of technology. And they're enormously cost competitive. And so you're starting to see both the world open their eyes to the quality of many Chinese made goods today, as well as the fact that they are often cheaper than one can produce domestically.
And I think this industrial policy challenge that many countries, including the U.S., face are very real. How do you compete with China on EVs given the technological advancement they have today, their relatively inexpensive labor costs, the automation in the factories, these very robust supply chains that they have, cheap cost of capital, willingness to subsidize or run at zero profits, the industry for a long time. And I think that's true not only of the EV industry, but of many other industries going forward. And what's the right response from the West to China that now looks like that?
I thought that was an interesting question that I couldn't answer. I'm not sure I can answer that today either.
Robinson Meyer: So those are all the questions in your head when you went. Then what did you see? Were you surprised? I mean, were they even more advanced? Were things even more advanced there than you expected? Or did you feel like you were kind of adequately prepared by the discourse, but still, you know, it was striking to see it in person?
John Arnold: One of the things that I was expecting was less automation. You should see more automation in places and industries where you have high labor costs. And China seems to be on the forefront of automation and the robotics revolution. So that was kind of a head scratcher, especially if one of the goals, strategic goals of the country is employment — that they've either been long-term planning there to understand that if you're just going to labor your way through this, you're going to be disrupted at some point. But that China is willing to both invest in the robotics and automation, as well as try to create jobs for its citizens, I think is very forward-looking by the country.
I was also trying to just understand where capital comes from. Where's the risk-taking capital come from? And what are the incentives both kind of within the province level as well as from any private capital sources? Who is funding this EV industry that has massive overcapacity and it doesn't seem to be making any money or clearly is not making any money with the exception of maybe BYD. And I think that's true of other industries as well.
So just trying to understand, where's the capital coming from? Are there investment opportunities? Are there sourcing opportunities for the West, particularly on the electrostack that China is so strong in and that the West, particularly in the United States, now has real shortages of any type of power equipment, the transformers and switch gears and all of that. And China has extra capacity there. And in some sense, we are in this race with China on AI. You need a lot of power in order to do that. The supply chain of the power industry is very constrained in the United States right now. There is spare capacity in China should we be utilizing that as a country in order to try to beat them on the AI side I've.
Robinson Meyer: I’ve heard where we kind of are at this point is, whether we like it or not, as the data centers expand, the kind of quotient of where maybe the government or like companies are willing to allow Chinese technology is creeping closer and closer to the chips themselves.
John Arnold: Yes. Yeah. The best I could tell was that American policymakers were okay with Chinese equipment at the edge of the grid. They did not want it kind of on the backbone of the grid such that if it ever got turned off, that the downside was fairly limited.
Robinson Meyer: Where did you see automation in China? What's an example?
John Arnold: So it went to the Nio auto factory. Nio produces one of the higher end EVs, generally in the kind of $50,000 to $100,000 range. They've also been at the forefront of the replaceable battery. I think there's a different phrase from that, but one that you can pull into a charging station if the machine removes the battery from the bottom of the vehicle and puts in an already charged battery. So it's a three-minute in-out process to get a fully charged battery. They had finished a new plant a couple years ago. I think it took them 17 months from breaking ground to having the first car coming off the line, which is just remarkable.
Robinson Meyer: That's crazy.
John Arnold: And was also just surprised that, you know, going through there and touring it, how much automation there was, how few employees there were in the plant.
Robinson Meyer: Okay, so I'm also in the never been to China, but find myself talking about China all the time, kind of embarrassed camp. And it's going away. But this idea that China is competitive because of low cost labor is one that I feel like we're gradually realizing is not true. I mean, it's part of the picture, but it's a much there's a much wider set of capabilities in Chinese manufacturing. Now than there were even 10 years ago, as you were saying.
Did you wind up thinking that that the consumers are different, too, or that maybe the Chinese EV industry has been able to thrive because it addresses a very different need than the American EV industry? I think one thing I've been trying to figure out in my thinking about China is how much the U.S. Still has in dollar terms, the world's largest market or it's up. It's close. But there's more consumers. There's far more people in China and they all buy a version of the thing. Many of them buy cars, right? And that then creates more capacity for learning to scale. Did seeing some aspect of the economy make you realize how difficult or potentially solvable the challenge is?
John Arnold: I think what was striking was, I had a hard time identifying where the weak spot was for Chinese industry, given that they have a highly educated workforce, low cost of labor, that there is risk capital that's provided. A lot of it comes from the government, but then flows through to venture capital groups who are making roughly similar decisions with some constraints on where they can invest to the end of the industries and the geographies as American ones. Talk about the size of the domestic market, the supply chains there, that they are close both in geography and culturally, you know, without having to do cross-border supply chain management. Seeing that and then trying to understand how other countries compete on the electrostack going forward was very challenging. And I walked away saying, I'm not sure if China would be a good investment or not for somebody from the West. I'm not sure those companies are ever going to make money, but I would be very hesitant to invest much in manufacturing companies in the West that are competing with China. I think the auto manufacturing industry is fascinating for a number of reasons, but most countries that have a domestic manufacturing industry for autos view that as strategic. It's a lot of jobs. There's kind of this pride of making cars. And so there's always been a lot of export hurdles and kind of fences being built around countries of various heights. And America.
Has this decision to make of, do we try to compete with Chinese cars globally, or do we build this big wall around our country and say, you have to make it here with American technology?
And I think the risk is what you're seeing in Canada. So the Canadian and American car industries were kind of tied at the hip since forever. And you saw a lot of car parts flow back and forth across borders. The assembly might be done in Canada, but it would use some combination of Canadian and American parts, be done with an American manufacturer, et cetera. You know, the United States is increasingly saying that we don't want that of cars to be assembled in Canada.
And so then Canada's starting to question what should its domestic manufacturing industry look like? And if America is not going to be a good partner, would somebody else? And China's raising their hand saying, try us. And so there was a deal recently in the past maybe six months, where Canada started allowing a certain number of Chinese imports that were essentially with tariff-free, very low tariffs. And the way I read it, I think the way others read it was, that China is testing the market? Is there demand for the product? And if so, then I think China is going to make a very significant investment in Canada. And Canada is protective of its jobs, its domestic industry. And if America is not a good partner for it, maybe China is.
Robinson Meyer: But it doesn't sound like you walked away. I mean, you kind of said this, but it doesn't sound like you walked away with like, okay, there's a clear way that American manufacturing? Because it's more than just auto industry, right? It's kind of this whole set of technologies around electricity at the bleeding edge that I think American policymakers would consider strategic. And I don't know, I would consider strategic, but it doesn't sound like you walked away with a clear sense of what America could do to compete in those industries.
John Arnold: Correct. I think the challenge of industrial policy is that it can end up being zero-sum, right? If one country starts doing it and then the next country says, well, if they're doing it, then I have to do it. And you can end up in a end state where there's very significant subsidies coming from each state and nobody's necessarily better off. And that seems to be where we're headed now.
And the justification that we're having in America to this is, well, China's doing it. And this was part of the rationale for WTO in trying to standardize what the trade rules were and what subsidies and supports a state could give to industry. And to try to really minimize that has always been tough. There's many, many ways that a state can support an industry. But there's been fights about that. And it was relatively stable. It may have been going up slowly. But I do think that China now being a very already healthy competitor in a number of these areas that are deemed to be the future, including things like drones and motors and magnets, et cetera, that there is that question that's happening. And I'm not sure what the answer is for the United States besides either we're going to do this as well. We're going to show supports for our industries that we deem strategic and or that the world's going to build these new alliances with high walls around it. And we have these trading alliances that get created and there's a lot of trading within those alliances and very little that goes across those alliances.
Robinson Meyer: I think it's hard because it's we kind of knew industrial policy had this race to the bottom or zero sum aspect. But what's new is that it works. What's new is that China seems to be doing it in a way that is working and outcompeting Western companies. It was easy for economists to say, oh, we shouldn't do this industrial policy when it didn't seem to work because they could say, oh, it's a race at the bottom and it doesn't work. Well, in that case, who wants to do it? But if China's doing it and it seems to be working, then suddenly we have real issues because an entire set of policy tools that I think both create real negative dynamics in the global market, but also have like huge strategic implications for the US suddenly seem like they're back on the table, but also... Not fit for our current global trading system.
John Arnold: Yeah, I think that's exactly right. It's an economist will give a hundred reasons why the five-year plan should not work and should end up leading to terrible inefficiencies and tremendous waste. But China has five-year plans in recent times have seemed to have been working pretty well.
Robinson Meyer: Yeah.
John Arnold: And so America is moving a little bit more in that direction than China is moving towards our direction.
Robinson Meyer: Exactly. To be continued, speaking, I guess, of the electrostack. So you're involved with a number of companies around electricity, Fervo, Grid United. On the scale of it's a nuisance to it requires a Manhattan project-like effort, how worried are you about the grid? Yeah.
John Arnold: I think there's a limited number of technologies or solutions that seemingly don't have any trade-off. And you can think about the goals of the energy system, and oftentimes you think about something and there's a trade-off, right? And you have trade-offs between affordability and reliability, or trade-offs between the environmental sustainability versus affordability or reliability, for instance. And there's a limited number that have really kind of no obvious trade-offs, at least with respect to the goals of the energy system. And I think about the goals as a lot of people talk about the four of reliability, affordability, sustainability, and security. I would add, I think, good jobs and I think scalability. So if you want to bring on a data center, can you provide power for that? And building out a more integrated grid helps on every one of those six factors.
I think doing things like demand management also doesn't have obvious trade-offs for it. I think adding batteries to the grid is another one of those solutions without the trade-offs. And those are the technologies I think I'm most excited about — again, because if we're in this fight about, you know, the trade-offs, and yes, it's good here, but it has this trade-off — those things are hard to scale or they are very fragile as you change administrations and the prioritization of those goals changes every four or eight years. But if you truly have solutions that are just a net positive then i think they're much easier to scale much more durable.
Robinson Meyer: Have you become convinced that any one grid in the U.S. or area of the U.S. could have does this right as compared to other parts or other grids?
John Arnold: ERCOT is this interesting example. Everybody loves to examine and analyze ERCOT. It's very good on the scalability of the system, which is one of the reasons why so many data centers are now being built in Texas. That was not the case even a few years ago. I think they were going in many different places, but that you can add demand and add the corresponding generation relatively easily in ERCOT, and that you don't have these very long timeframes for grid interconnection, I think is very positive. But what we're trying to do at Grid United is really go across the seams. So accident of history, we have these three grids in the United States. There's almost no connection across them. The benefits of trade that you get of increasing reliability and affordability just by making the system more efficient, more optimized are very real. And so that's really where we're focused.
Robinson Meyer: The Arnold Foundation, you know, your team is very involved in permitting reform. Are there particular policies you would like to see or that you think would solve these issues relatively quickly or at least provide a big boost?
John Arnold: Yeah. So, you know, it's really kind of a question of how do you get your permit? The certainty that you have once you've received your permit. And you want a system where people have the ability and right to object, that those objections are heard in a timely manner. A decision is made and the project's either greenlit or killed. And that certainty of how that process happens is very important to developers. And then maybe even more important is once you have that permit, that you have real certainty that it's not going to get tied up in the courts, right? That judicial review period is set. And again, that the objections get heard, But after the decision's been made, that it's final and we're moving forward. And there's a saying that time is money. It is very true for development, that the best way for an objector of a project to kill it is just to keep the delays. And the judicial system, as it currently works in practice, allows for some types of projects, this never-ending series of delays that happen. And so developers don't even start.
You see this not only with energy, you see this with any type of linear infrastructure, whether it's pipelines or highways or broadband. And you see this in housing as well. We have less housing because developers know in certain geographies that even though they should have their permit in three months, it's going to take them three years. And the cost of capital makes the project go from a profitable one to a money that was never even started. And so certainly today with the growth in demand and power, we need to be able to build again in this country. And if we're still on this trend of, and it's harder and harder to build each project, which makes it longer to bring on and more expensive, then we're never going to meet the goals of the energy system. It's this remarkable moment where I think almost everybody on the political spectrum recognizes that and recognizes the principles of energy permitting. And they're trying to write the fine print today, but I've never seen this issue have so much bipartisan support.
Robinson Meyer: Do you feel like we're going to get a deal this year? Or give me the probability that you think there's a deal this year.
John Arnold: Yeah, so if I go to the prediction markets, what am I going to see?
Robinson Meyer: Yeah, exactly. I haven't even looked to see if there's a Kalshi market.
John Arnold: There probably is.
Robinson Meyer: I'd be too inclined.
John Arnold: I am very optimistic. And we do a lot of policy work at Arnold Ventures. I know how hard it is to pass laws, especially in this era of political dysfunction. The one thing I think almost every member of Congress I talk to understands is the need to do this. There is support from the administration. There is support from congressional leadership on both sides. There's support from the relevant committee heads. If we can't get this done, then we can't get anything done.
Robinson Meyer: What needs to change or what needs to happen between now and, say, the end of the year for it to actually get done?
John Arnold: Yeah. So I think on an election year, it's very unusual for any big piece of bipartisan legislation to get passed really the whole year. And so what we're really looking at is most likely is that it would get passed after the election in the lame duck period. And so you start working backwards from there and really need to have language that's agreed upon in the next 45 days. It's hard to work over the summer. Congress scatters. Everybody scatters. Then you come back. There's a little bit of work time in September, and then everybody's focused on the elections. So the bill needs to get written today. And then again, in the next 45 days, and there's a lot of work happening behind the scenes. So again, sometimes it's hard to know exactly where it is, but everybody's saying the right things. There's been fits and stops to date, particularly when the administration hit the pause on offshore wind. They've made some changes. They brought Senator Whitehouse back to the negotiating table, for instance. So again, everything I think is looking good, but getting anything passed in DC these days might be a long shot.
Robinson Meyer: Arnold Foundation was involved in the MethaneSAT project. And, you know, methane is an interesting problem. I think natural gas would obviously be a much stronger position on emissions terms if we dealt with the methane pollution problem. Of course, then the administration came in and removed rules that were set to begin regulating methane pollution from the oil and gas sector. Why has methane proven so hard to tackle in the U.S.?
John Arnold: Yeah, I think it's a question of who pays for it. And so that well that, you know, is 50 years old, that's kind of barely economic today. It's leaking a little bit as a standalone well, but in aggregate, the number of very old wells or near end of life wells that are leaking, the title to those wells has changed hands many times over the years. And so the current owner says, right, why am I responsible? I just bought this thing a year ago. And when I bought it, there weren't rules about that I had to pay for it. Otherwise, I would have paid a very different price or wouldn't have bought it at all. So I think that's one. I think the industry probably has some fear of if they lose one fight on this, that there'll be the slippery slope argument on regulation. My argument to industry has been that if you want natural gas to be viewed as a clean fuel, then it actually needs to be a clean fuel. And that there's some low hanging fruit on trying to clean up the industry. And it would be good for you economically to make these investments. Now, that's true of the industry, I think. Again, you get down to, okay, which company is actually paying for it?
Robinson Meyer: I've heard this theory that, okay, the majors might be fine with that. They might say, yeah, sure, we can deal with it, whatever. It's the independents who are going out and killing all of this. And the majors don't mind that the independents are killing it, or the miners are killing it, but they would eat it if they had to. Do you buy this theory? Or if you were to lift the lid on any of these kind of big oil companies that have been more facially supportive of the regulations, they would actually be just as opposed?
John Arnold: I think a few things are true. Number one is that a newer well has lower leaks than an older well. Assuming the infrastructure is built, you know, at times whenever there's flaring, that's not true. But in general, once a well is operational and connected, then the newer it is, especially anything that's been put on the system in this decade, is a relatively low leak molecule. And that the larger companies tend to be the ones that are doing the new drilling. They have the capital. And as wells age, the big companies sell them to the small companies, to companies that have a lower cost of operations.
And so there's that natural trajectory of life of a well. And so I think there is some economic rationale to that. I think the large companies are more concerned about the reputation. I think they're more concerned about what's the long-term value and opportunity for the industry. They have publicly traded stocks that represent what the long-term value of the industry is versus kind of being owned privately and people having a shorter-term focus on the financial return market. And I think you're probably right that the big guys are kind of happy to have the little guys have this fight so they don't have to be criticized publicly.
Robinson Meyer: I guess into the point we know the big guys' names. I couldn't tell you all the names of the independents that would oppose this. What should clean energy companies learn from conventional energy companies or the conventional energy industry?
John Arnold: The conventional industry has, it's mature. It has low cost of capital. It has the robust supply chains. They are well capitalized. Right. Yeah. So they're able to do things, right, that kind of newer industries not able to. Look, the oil and gas sector has become tremendously efficient at scale, right? Scaling anything. So if it works, the oil and gas industry can go scale it. And I back up and just say that's something that happens with time.
Robinson Meyer: Yeah.
John Arnold: And so I'm not sure that the clean energy industry can just say, like, we should be like the oil and gas industry. We just need to copy their ways because they don't have the tools.
Robinson Meyer: I think they would love to say that, actually. Yeah, exactly. You know, I think they'd love the bankability. They'd love the scale. Is there anything they might not think of that they should think about?
John Arnold: I think the political power that the oil and gas industry has. And part of that is also time. If you've been donating to a party or to a candidate for three years, that's very different than if you've been donating for 30 years. Yeah. And so the oil and gas industry just has a lot more political power than the clean energy side does. I think there's just larger policy teams, larger budgets for it. The understanding that collectively, everybody has to participate in those PACs and in the trade organizations that I don't think you're seeing today in the clean energy side.
Robinson Meyer: Your work has been really studiously bipartisan. I think there was a phase in the clean energy industry as recently as a year and a half ago where it was not nearly as bipartisan. Was that a mistake? Should it embrace the kind of more Catholic position of the oil and gas industry, or is it not able to because of the policy landscape?
John Arnold: So it's hard because, again, like the longer an industry has been there, the more ingrained in the fabric of any community it is. And so you still see some Democratic states like New Mexico or Colorado that have oil and gas industries. And because the representatives in those states have to represent their communities, they end up having to get support or they do get support for it. Just because, again, just like the number of jobs that are there, the political organization that they have in those states, the number of companies. And so this takes time. It's like developing and becoming more and more of the fabric. And so the irony is that a lot of the wind producing states, a lot of the solar states are red. But they just haven't been around long enough to really have ingrained themselves into the fabric and into the political institutions in that state. So I think this is just more of a time component.
Robinson Meyer: Last question. So you're a big booster of Houston. And I would say the Houston civic culture. City is growing very quickly, of course, has this long term connection to oil and gas. When people visit Houston, what should they do? Or where should they go to see, not in a tourism sense, but if they're interested truly in what has made Houston different and what makes it different today? Like, what should they make sure they not miss?
John Arnold: The Menil Center is kind of this amazing museum that I think captures Houston's spirit and that the de Menils were part of the Schlumberger founding family that during World War II moved from France to Houston. And so it envelops the cosmopolitan nature of Houston that Houston draws from the entire world, often because of the industry we have here, the energy nature of it, and then the cultural assets that we have here. The Chamber of Commerce likes to talk about, we have the second most number of live theater seats, for instance, after New York. The museums we have, it's not New York, it's not maybe LA, but it's right there after those two. the theater. It's one of maybe four or five cities in the U.S. with a grand opera.
And so it has that cultural component as well as this gritty part of being an industrial city. We build things here, come here for scale. And we like growth. There's a number of communities today that, fight growth, right? They don't want to change. Houston does. Texas does, right? It's a state, it's an area that we want to grow. No politician could take office saying, we want to pause growth. That person would never get elected. And so kind of across the political spectrum, it's maybe, how do you grow? But Houston wants more people, it wants more diversity. It wants more growth, more industry. And that's what's made this community better. It's why people have come here in the first place. And that's what we want to give to the next generation.
Robinson Meyer: Well, there's so much more to talk about, but I'm going to respect your time and leave it there. John Arnold, thank you so much for joining us on Shift Key.
John Arnold: Great being here. Thanks.
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Rob sits down with the Josh Parker, head of sustainability at America’s world-leading chip designer.
America’s tech companies are transforming the electricity system — building entirely new fleets of new solar panels, batteries, and gas turbines — in order to power what are essentially warehouses filled with cutting-edge chips.
Almost all of those chips are made by Nvidia. On this week’s episode of Shift Key, Rob is joined by Josh Parker, Nvidia’s head of sustainability. They discuss the climate and electricity impacts of artificial intelligence, why Josh is incredibly bullish on AI’s ability to cut carbon emissions and whether it has done so so far, and the company's work with clean energy and fossil fuel companies.
Shift Key is hosted by Robinson Meyer, the founding executive editor of Heatmap News.
Subscribe to “Shift Key” and find this episode on Apple Podcasts, Spotify, Amazon, or wherever you get your podcasts.
You can also add the show’s RSS feed to your podcast app to follow us directly.
Here is an excerpt from their conversation:
Robinson Meyer: So Heatmap has been tracking what, to us, has been a very sudden and shocking rise of local pushback against AI data centers. And of course, this has become a larger meme over the past few months, as it’s gotten more attention. For instance, we think about 50 AI data centers or data centers broadly were canceled last year after facing local pushback. And we think more than 50 have already been canceled this year.
Are you seeing that at all at Nvidia? I mean, it doesn’t look — your quarterly results came out yesterday and they were, they absolutely blew out expectations. And so evidently it’s not affecting demand yet. But do you hear it from customers? Is this affecting Nvidia’s business at all? And how do you think about it as a risk going forward?
Josh Parker: So I’m aware of the sentiment, the paranoia around AI, mostly on a personal level because I see it on social media like other people do, as well. I’m not aware of any direct impact on our sales, so I can’t comment on that. But what I will say is, I do think it’s particularly tragic, because this technology has the potential to be the most beneficial, both for environmental goals and for social goals — so things like education and health care, and kind of across-the-board social issues benefit from AI, as well. And the concerns about AI, a lot of them are based on either erroneous data or old data. And I worry that some people don’t fully understand the net impacts, the positive as well as the negative of AI.
Plus, we have the uphill battle of, it’s really hard if the data center is being built a few miles down the road, to tie that data center — which, they don’t always look beautiful and things like that — to the benefits that the whole world is going to get from AI. So if — obviously not promising this — but AI could unlock cancer cures or cures to other diseases, and we’re seeing trends in the direction of cures and treatments and drug discovery and so forth. But it’s really hard for us as humans to draw a line between the infrastructure that we see down the street, and especially the speculative, the moonshot benefits. But even the more fundamental ones, like the benefits and productivity that we’re seeing in potential for wage growth and education and so forth, even though it’s hard for us to draw the line between the infrastructure.
So it’s understandable, but I do think it’s tragic. And I think it’s our responsibility in the tech industry to help people see the bigger picture and to address people’s concerns head on about environmental impacts and social impacts. Because the data really does demonstrate that, by and large, these data centers are pro-sustainability. They don’t have the impacts that most people are concerned about, and they’re manageable. And most data center operators are trying to operate them in a sustainable way.
You can find a full transcript of the episode here.
Mentioned:
Previously on Shift Key: Data Centers Are Creating a New Kind of Battery Monster
Previously on Shift Key: A Skeptic’s Take on AI and Energy Growth
From Heatmap: Exclusive: Local Opposition to Data Centers Explodes in 2026
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Music for Shift Key is by Adam Kromelow.
This transcript has been automatically generated.
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Robinson Meyer:
Hello, it’s Tuesday, March 26, and the second unofficial day of summer here in the United States. yesterday was the first. And at least as of when markets closed last week, the chip maker NVIDIA was the world’s most valuable company. It currently has a market cap of around $5.3 trillion. The next biggest company, Alphabet or Google, is worth $4.6 trillion. Just last week, NVIDIA released its financial results for the first quarter, and it was another blowout. It was expected to generate just under $79 billion in revenue. Instead, it delivered $82 billion. That’s up 20% from the previous quarter and up 85% year over year. NVIDIA has now beaten Wall Street expectations for 14 quarters in a row.
Robinson Meyer:
I go into all of this, not because Shift Key is a technology business podcast, we are not, but to illustrate the centrality of NVIDIA to artificial intelligence and I think to the broader American economy right now.
Robinson Meyer:
NVIDIA produces the physical infrastructure behind the AI and data center boom. And since that boom is the biggest story in electricity, climate, and even energy, NVIDIA is probably the most important company to energy, electricity, and climate too. After all, America’s tech companies are building solar panels and batteries and gas turbines specifically to power NVIDIA chips. When we talk about data centers being built across American communities, we’re talking about warehouses holding NVIDIA chips. Utilities are tripping over themselves to power and have access to warehouses powering NVIDIA chips. NVIDIA chips are where America’s dominance of the global software and AI industries meets America’s physical economy. That is the actual electrons, copper wires, gas molecules, and infrastructure that runs through America’s towns and cities. So I’m excited to welcome to the Shift Key today, Josh Parker. He is NVIDIA’s Head of Sustainability, a role he’s held since 2023. Before that, he was Head of Sustainability and Assistant General Counsel at Western Digital. Josh and I had a good conversation last week. We talked about why he thinks AI is a net good for climate change, about whether AI and NVIDIA are already cutting emissions on the power grid, and about NVIDIA’s work with clean energy companies, as well as fossil fuel companies. It’s a very interesting conversation. I learned a lot from it. I’m Robinson Meyer, the founding executive editor of Heatmap News, and it’s all coming up on Shift Key.
Robinson Meyer:
Josh, welcome to Shift Key.
Josh Parker:
Thanks, I’m thrilled to be here.
Robinson Meyer:
So you joined NVIDIA in August 2023, which was right a few months after ChatGPT came out and completely changed the AI conversation. What did you walk into at the time? And where was the internal conversation around sustainability and climate at that moment in NVIDIA?
Josh Parker:
It was a really unique and wonderful time to join NVIDIA. You know, the company was just doing amazing things. the whole world was starting to wrap its head around the fact that AI was useful and was finally here in ways that would transform the world, transform the economy, and really our existence. And so the timing was fantastic for me, really thrilling just based on where the company was, what it was doing, and the whole conversation around it. The sustainability conversation was one of growing interest at NVIDIA. Jensen, our CEO, really has this vision of technology helping to solve the world’s biggest challenges. And sustainability is, of course, one aspect of that. Things like climate change and materials resources and water conservation. And he believed that AI had a very critical role to play in sustainability in the near future. And the company was looking to expand its sustainability program and efforts. And so I was very fortunate to come in at a time when the company was really trying to accelerate that program and find new ways to use tech for good and also to be a responsible organization ourselves.
Robinson Meyer:
How do you think about NVIDIA and sustainability today? What are the goals that you have? Because obviously at this point depends slightly on the day, but recently it’s the world’s most valuable company. It’s driving this enormous infrastructure boom. NVIDIA provides the physical infrastructure of the AI boom. And so to some degree, it’s an every sector of the economy story. And I wonder, given the company’s enormous importance right now, how do you think about its sustainability goals and what you focus on?
Josh Parker:
NVIDIA is a pretty unique company just across all the metrics. The culture here is very unique, very dynamic, and we could get into that and have a whole podcast on it. But the sustainability space follows that same pattern. We have a very unique approach to sustainability, I think, based on NVIDIA’s role in the ecosystem.
Josh Parker:
One of the first things that I did when I joined NVIDIA was to start some analyses.
Josh Parker:
Some incredible third-party validated products carbon footprints for some of our high-volume projects to figure out what does the data show us about where our lifecycle impacts are. So if you look in gaming or in AI or 3D modeling, pro-visualization, what are the kind of soup to nuts, cradle to grave hotspots for emissions in particular and then other impacts as well? And when you look at that, you very quickly realize that NVIDIA’s direct footprint, and this is something most people would understand just conceptually, NVIDIA’s direct footprint is a tiny, tiny fraction of the total lifecycle impacts of our products. So while traditional sustainability programs, especially tech companies that involve manufacturing and perhaps downstream use as well, really focus on their own footprint, if we focus myopically on our own footprint, we’re missing the forest for the trees. So very quickly realized that Jensen’s vision about sustainability and about AI’s potential to impact sustainability issues was much, much more significant than NVIDIA’s direct impacts through our operations. And so as a result of that, we’ve been focused from day one, really, on trying to unlock applications of AI for sustainability and to work with our value chain partners, both upstream and downstream.
Josh Parker:
To decarbonize, to manage impacts, et cetera, across the value chain. So it’s a lot more outward-focused sustainability program than most, which I think makes a lot of sense based on where NVIDIA sits in the ecosystem.
Robinson Meyer:
And can you talk a little bit maybe about why that is because i think what many listeners i expect will understand but just to be clear here nvidia designs its chips and it operates them as well but it doesn’t actually produce the chips the chips are usually produced by tsmc or another outside chip fab and so I guess from your standpoint, then, that makes these external projects especially important. But like, where did the emissions, I guess, in NVIDIA’s world come from? Do you focus on emissions as, you know, a key metric here?
Josh Parker:
Yes, our top issue for sustainability since I arrived at NVIDIA has been emissions and climate change. So that has been the top focus for us. And yeah, if you look at the value chain emissions and those product carbon footprints that I mentioned, we’ve published summaries of those that are cradle to gate. So they start from the very beginning of the value chain and end kind of when we ship our products to our customers, because we don’t have as good a visibility to how our customers are using our platform. But we are, as a company, historically, it’s accurate to say we were a chip design company. Nowadays, we’re more of kind of a platform infrastructure solutions company, but we are focused very much on the design. So on the AI side, we do very advanced networking. We have CPUs, GPUs, data center architecture. We co-design things like cooling solutions for data centers, and we publish reference designs for those. And then we work with manufacturing partners, contract manufacturers to actually build the systems and then to sell them. And then we do operate some data centers, but most of our business is really selling the tools, the infrastructure to the companies that go out and build great things with that infrastructure.
Robinson Meyer:
What’s the most important metric to focus? I mean, we were talking about emissions, but in terms of understanding kind of NVIDIA sustainability goals, what’s the most important metric to focus on?
Josh Parker:
I think at a moment when AI is growing rapidly, transforming the world, the most useful metric is one that takes into account both the footprint and the handprint. So it takes into account the impacts as well as the potential offsets, the benefits, the transformational impacts down the road. Now, consolidating that into a single metric is really difficult, but there are some studies that have tried to look at least the net impact on greenhouse gas emissions of AI broadly. So that’s, I think, the best indication of, is AI a hero or a villain or somewhere in between in terms of climate change and greenhouse gas emissions in particular? And the very rapidly growing consensus is that AI is most likely to lead to net emissions reductions, especially if it’s deployed broadly. So organizations like the International Energy Agency, World Economic Forum, Boston Consulting Group, Grantham Institute, have all come to that conclusion that AI, because of its transformational impacts on other sectors in particular around energy efficiency and so forth, is poised to drive net emissions reductions. So if I were to pick a metric, I would say, what’s the net impact on emissions that AI is creating? And it’s really a positive one if you look at those studies.
Robinson Meyer:
Can you... So... I think that this is like get set to some degree, the question that I want to talk about while we have your time, which is that there’s enormous focus on the on the energy use from AI, right? And of course, the energy use from chips. And we can talk about chip efficiency and what NVIDIA is doing there. And I think it’d be good to talk about it. But it does seem like to kind of step back that we are in this moment of massive infrastructure investment in AI. And that infrastructure investment is going to happen. And regardless, at this point, I think it’s just AI is too valuable. It’s too obviously useful for that infrastructure investment not to happen. And what we track at Heatmap and we look at data centers get built across the country and we become aware, for instance, that there’s a lot of off-site, you know, behind the meter gas being built to service these data centers. Obviously, there’s going to be a surge in electricity demand and there’s ways
Robinson Meyer:
in which electricity demand increases can be good. But just as we think through the next five years, given that at this point, the AI investment boom is happening and to some degree, you know, the AI story is a foregone conclusion. What needs to be true for AI to have been good for the climate or for NVIDIA’s efforts here to have been good for the climate?
Josh Parker:
The biggest variable in that analysis of what’s the net impact of AI is really, again, if you look at those studies that I mentioned, including the International Energy Agency, is how broadly we apply it in the near term. So yes, the infrastructure is getting built, it’s getting used, And contrary to what most of us consumers conceive of as AI, the vast majority of the really useful cases of AI is not the chatbots that you’re engaging with. It’s not the dogs surfing in Hawaii videos and photos that people create in their spare time. It’s the commercial applications where AI is saving energy. It’s saving material resources and so forth. And that infrastructure is being deployed for that purpose, in addition to the chatbots. And the real opportunity for us is to say, okay, we’ve got these amazing models. You’ve got Claude, you’ve got Gemini, ChatGPT, X.
Josh Parker:
They’re really, really powerful and obviously just growing in capabilities month over month. There’s so much potential there for those to transform manufacturing, for example, digital twins. And we see proof points of AI reducing energy in manufacturing by around 30% across the board if AI is deployed to optimize manufacturing for energy. That happened at one of our manufacturing partners in Guadalajara, Mexico, for example, a 30% reduction in energy. And so the opportunity is, and the risk is that if we build out all this infrastructure and we don’t use it effectively, if we don’t apply the AI to these big problems, then we may miss out on those significant emissions reductions. So what needs to be true, the biggest variable here is, are we taking advantage of what we’ve built? Because the infrastructure, like you said, is being built and it’s being used, but can we deploy it more broadly And can we bring in some of the sustainability-focused organizations to deploy it for good? How do we intentionally use AI for good in addition to the kind of regular efficiency, revenue, and cost-driven allocations that are happening very naturally and have very, very significant gains across sustainability? There are also very purpose-driven applications of AI that can have big impacts as well.
Robinson Meyer:
Do you think that AI by itself increases efficiency where it’s applied in that, you know, if you apply it to manufacturing, for instance, or another one of these industrial uses that it’s going to just increase the efficiency of that process by dint of its application and being very intelligent and finding, you know, ways to streamline processes or skip processes or augment processes that maybe wouldn’t have been considered otherwise? Or does it need to be applied in an intentional way where people say we need to look at this for efficiency or for emissions and that should be our main focus here.
Josh Parker:
So that’s the beauty of the concept of efficiency in free market is that the incentives to reduce costs are really well aligned with sustainability goals of reducing impacts, reducing consumption, and so forth. And so what we are seeing, and I think this will even grow more over time once we get out of this kind of Cambrian explosion of tech innovation that we’re in right now, which is a little chaotic, is that you’ll see optimization of, okay.
Josh Parker:
Using a huge LLM for this problem might be good, but it might not be the best tool for that particular task. Can we use a lighter weight model? And you see tons of innovation in this space. Mixture of experts has been around for a long time. We’re seeing a lot more innovation around how to use more efficient models and target them to specific applications. But the market and kind of customer demands and everything is really driving us. Plus supply constraints, compute constraints are really driving us towards efficiency and to optimize allocation of those resources. And if AI doesn’t end up being the right tool for every task, then it won’t be used there. And we can continue to use traditional techniques. But efficiency does happen to be one of AI’s kind of low-hanging fruits, one of its superpowers that is really easy to unlock and unlocks value immediately across the board. So it is very fundamentally true in general that AI does drive efficiency very, very rapidly in most areas.
Robinson Meyer:
I think what I hear you saying is that a lot of the good that will ultimately come from this build out there will be done from intentionally applying AI to intentional sustainability problems. Is that wrong? Or is it also just the diffusion? I mean, we were just talking about efficiency. So I guess that’s on the other side. But in your kind of first answer, I did hear a sense that a lot of the most important work on sustainability will come from NVIDIA intentionally applying its technology to sustainability problems.
Josh Parker:
I would say that’s important, mostly because it does require us to think about it and to do something. It’s not being driven necessarily automatically by existing incentives and market dynamics. So the market dynamics and the efficiencies that are being driven by that, like a 30% reduction in manufacturing efficiency, it’s really mind-boggling. When you think about we’re concerned about the energy that is being consumed by AI, AI still represents less than 1% of total electricity consumption worldwide. Now, it’s obviously higher in some regions, higher in the United States.
Robinson Meyer:
And it’s about to go up a lot too, is the other side.
Josh Parker:
No, it’s expected to double by 2030. So it’s growing very rapidly. But if you think about AI’s existing footprint, again, less than 1% of global electricity right now, even if it doubles, doubles again, doubles again, it’s still going to be a small share of global electricity. If, as we’re seeing the proof points for, it can reduce energy in much, much larger energy consuming sectors like transportation, like buildings, like industry, which are each in the 20 to 40% range of global electricity, then those savings dwarf AI’s footprint unambiguously. And that incentive is there because companies want to reduce costs. They want to reduce their energy consumption, especially when we’re in this environment of energy constraint, particularly in the United States, the incentives are there. So that is going to happen. I think that’s kind of inevitable because it’s an opportunity. There’s value and there’s sustainability. It’s good for everybody and the stars have aligned. The...
Josh Parker:
Additional piece is applications of AI intentionally for sustainability. And that’s where maybe it won’t happen unless we think about it, unless we try to apply it there. And the potential is just phenomenal. When you think about the way AI is already transforming drug discovery and healthcare and material science, there’s potential in nuclear fusion, advanced fission, geothermal, and carbon capture and storage just across the board. When you add intelligence to these sustainability challenges, you arrive at this wonderful inflection point where we might finally have a technology that can sufficiently complement policy to help us actually prevail on some of these sustainability challenges, help us to kind of reverse things and make progress that we otherwise wouldn’t have the opportunity to do.
Robinson Meyer:
There’s two types of AI that we’re talking about here, and I wonder if we can disambiguate them a little bit, in part just for my understanding. So there’s the large language models, which I feel like are the charismatic megafauna of AI. This is Claude, it’s ChatGPT, it’s Grok. Those are the models that I think people are most likely to have experienced when they think of AI. But there’s also this whole other set of AI applications, which I feel like you’ve alluded to, applying it to manufacturing, applying it to drug discovery, applying it to energy. And my sense is that type of ai it doesn’t look like Claude or it doesn’t look like ChatGPT it might have the same kind of organic structure where it was trained on a large data set and kind of allowed to self train itself on that data but it doesn’t have the same interface it’s much more kind of machine brains than maybe the LLMs of the world and to the extent you could share this data to what extent is ai demand and nvidia’s demand and energy use coming from the LLMs of the world like claude and Grok and ChatGPT versus these other AI applications.
Josh Parker:
It is true. There are very different applications of AI depending on the sector, and the consumer-facing chatbots that you see are one small use case and not where you see the biggest opportunities for advances in sustainability through AI, of course. Things like digital twins, for example, and that’s a really interesting marriage of NVIDIA’s expertise in 3D modeling and AI. And that is a very fundamentally valuable concept and technology for things like the manufacturing optimization that I was talking about.
Robinson Meyer:
You build a digital simulation of a real-life factory or physical space, right? Right.
Josh Parker:
That’s right. Yeah. And they become, it’s a lot more than what it sounds like at first blush, just a 3D rendering of a building. You actually can simulate robots going through this factory, simulate the airflow through the factory and the cooling system and all of the impacts of various factors on it. So it’s very complicated, and the emulations enabled by the AI really make the technology as valuable as it is today. That’s one example of something that is obviously not a chatbot that is fundamentally just extremely valuable when it comes to sustainability applications of AI. But there is actually substantial overlap. So when you see Anthropic training Claude Opus and devoting all of these resources to training that huge LLM, so many parameters, and same thing with ChatGPT and Gemini.
Josh Parker:
Those very large, large language models end up being really useful tools for helping us create more bespoke, lighter weight custom models as well that can do other things. So the multimodality functionality of modern day LLMs is just going through the roof. And the result of that is that these foundational models become even more valuable for lighter weight, more tailored applications of AI. So it’s true that the actual application of them in other areas probably won’t be the exact same model that was the huge foundational model that you started from, but through distillation and other techniques, you may end up using that as the basis for one of those other models.
Robinson Meyer:
There’s been a lot of excitement and i believe nvidia has invested in a number of companies or at least emerald ai companies that are look looking at whether data centers can be flexed up or down to meet the grid needs of the moment so instead of data centers simply being a huge energy suck on the grid they could modulate their usage and their they could modulate their compute and therefore their energy usage to kind of meet the grid’s needs i know nvidia is invested in this Can you give us a sense of where does that project stand right now in between, say, white paper and deployed scale?
Josh Parker:
So we are actively deploying this technology at our data centers. We’re building a data center right now in Virginia that will come online, I believe, later this year, that is, we think, the world’s first entirely flexible data center for AI. And we do see this as the future because it leads to a situation where we’re making better use of existing energy resources. And this is something that’s really, I think, underappreciated. And it might be a little nuanced for most people who don’t follow this to appreciate, but the concept of AI data centers becoming grid assets is really powerful because they’re being deployed rapidly. They’re using a lot of energy. And if they end up being good citizens of the electrical grid, then that can have actually a profound reductive impact on energy prices for retail consumers like you and me. The concept here is you have a grid that is built for peak load. So in the middle of the summer in Texas, when everybody’s running their AC units and you’re consuming the maximum energy that the system can deliver, that is what the system is designed for. So when you’re not at peak load, what does that mean? That means that all of those resources that you’ve built for the peak load are being underutilized.
Josh Parker:
This leads to the conversation about smart grids and virtual power plants, where I think everybody that looks into this closely wants to get where we’re saying, okay, how can we be more flexible, both primarily with our demand, but also on the variable generation side, how can we make better use of wind and solar that aren’t for power sources?
Josh Parker:
Data centers play a huge role in that, especially as they become a higher percentage of electricity consumption in the United States. If a data center can say, okay, I’m in Texas, I’m in the ERCOT region, and it’s a hot day in late July, everybody’s running their AC, I’m going to curtail my electricity draw slightly for a few hours until the system can get back to below peak load, and then I’ll ramp back up. That ends up becoming a net asset because you’re able to soak up the electrons when they’re more available and then reduce your load when they’re less available, which means we’re paying money for electricity that is otherwise being unused with existing grid infrastructure. So it’s fantastic for consumers. It’s fantastic for the energy sector. And it’s good for data centers because it means we can build them sooner and take advantage of existing resources. And one last comment on this, you may know that the concept of Emerald AI and this data center flexibility ties back to a study last year by Tyler Norris at Duke University, who said there’s 100 gigawatts.
Robinson Meyer:
And a Shift Key listener, I believe.
Josh Parker:
Yes, as am I. Yeah, I just want to get that in there as well.
Robinson Meyer:
Thank you.
Josh Parker:
Yeah, no, it’s fantastic work that you do, Shifky and heatmap. So 100 gigawatts, that is a ton of energy that could be accessed if we just ask data centers to be flexible for 1% of the year. And so that’s the concept here. It’s making the energy sector electrical generation more efficient, which leads to lower prices over time and better utilization.
Robinson Meyer:
I think when Tyler’s paper came out last year and when there was the initial wave of discussion about flexible data centers, the thought was that data centers would be flexing their compute, that they would change the operation, the programming, or the level of training that was happening in the data center at that moment to match real-life grid conditions. Since then, the focus has shifted more to data centers flexing how much energy they draw from the grid, but maybe the training itself or whatever compute is happening being more stable. It’s just the question is whether the facility is drawing from the grid or from battery storage that’s on site. When you talk about this data center in Virginia, or when you talk about flexible data centers going forward, are they flexing the compute mostly, or are they mostly flexing their grid use and where they draw electricity from? And sometimes they’re drawing electricity from the grid, and sometimes they’re drawing it from on-site batteries. But most of the flexibility per se is coming from where the electricity is coming from and not how much electricity is being used.
Josh Parker:
It’s really a mix. And where we end up will really depend on what customers the data center is serving, whether it’s a mix, whether they’re being served locally, whether it’s focused primarily on training versus inference. So what we’ll end up seeing is there will be a wide variety, I think, of data centers with different types of flexibility, perhaps, based on the needs of the data center. So if you have a data center that is running critical infrastructure and needs to be available even at peak load, then you may have more incentive to build out a large array of batteries so that you can continue to use that compute even when you’re at peak load on the grid and you can still be a good.
Josh Parker:
Citizen of the electrical grid by reducing your draw from the grid. But there are three different types of flexibility that we’re building into this framework. One of them is what you mentioned with batteries, where you can say, okay, grid’s at peak load. I’m going to use my batteries now temporarily instead. Good citizen. The second is also what we’ve been discussing, which is when you just ramp down your compute, you can say, some of the workloads that I have, I can pause on for a couple hours without deteriorating service or having any significant problems, it’s okay to pause right now. The third type of flexibility that doesn’t get spoken about as much, but that is rapidly developing is geographic flexibility. So if you have workloads that are really vital, but maybe you don’t have the battery storage on site to keep your compute running full steam all the time, you could actually transmit that workload to a different geography. Maybe somewhere in the Pacific Northwest, they’re not experiencing the same heat wave that they are in Texas. And the way a lot of interaction with AI works, that additional latency due to the different geography isn’t a huge factor because there’s already some delay built into the compute.
Robinson Meyer:
So latency is less of a... Is that training or inference that you would move geographically? Like, would you send the inference out to the Pacific Northwest? Or is this, you would actually send a training task out to the Pacific Northwest. And then it doesn’t matter in some ways because training doesn’t happen on a scale that the customer is always aware of.
Josh Parker:
Technically, either is possible. Training, because it’s kind of a large workload, chunking it up into discrete bits and then moving the data to the location where you need to continue the training, does have some additional complexities to it. Inferencing is a little easier to move because it’s smaller chunks, smaller amounts of data. And either one, again, because of the different latency requirements for AI compared to a traditional data center service, are feasible for a lot of workloads. Some inference workloads, the latency doesn’t matter if you’re doing real-time robotics and things like that. You do care about latency, so I don’t want to overstate this. But there’s a lot of inference that can happen where the latency is not a huge issue, and so those types of workloads could be shifted.
Robinson Meyer:
In some ways, the geographic flexing kind of addresses this. But when we talk about flexing compute or flexing grid use and turning data centers into grid assets, I do have to ask, I mean, are data centers getting built in the places where that capacity or that flexibility is useful? Because it often seems like, especially at this point, they’re getting built in places where there’s just energy that’s efficient or profitable to use because compute and energy are so constrained at this moment. And maybe not in the places where, say, that flexibility is useful. Do you see that changing or are we going to go in and maybe make existing data centers flexible in places like, say, the Mid-Atlantic or Texas where that flexibility could be actually useful to customers?
Josh Parker:
Again, I think we’ll end up with a mix. So right now, especially because of the challenges that we see in getting access to energy in the near term, as we’re rushing to build AI, because it’s so valuable and so important to us, you do see data centers being built just where they can get online, where there is electricity available.
Josh Parker:
And you do see increasingly some of these companies bringing their own energy, building new solar farms because they need it, sometimes bringing online new gas. But the good news is this flexibility is available in the future when we need it. And the companies that are bringing their own energy to their data centers, I haven’t heard of any that really want to be off grid. It makes a lot of sense economically and conceptually for data centers to be part of the grid so that they can be assets. They can take advantage of the shared resources, offer benefits to the grid through improved utilization, et cetera, especially with the flex technology. So I think where we end up will be a highly interconnected mesh of data centers that can flex and can transmit data. But we do have some hurdles that we need to cross to get there, especially in the United States. So permitting reform, transmission, of course, the things that we always talk about in the energy sector. This could be the golden moment where there is enough consensus around the importance of AI from an economic development, national security.
Josh Parker:
Scientific discovery, sustainability perspective, that we can find a way to make progress on these important issues and break through some of those backlogs. If we can do that, what we’ll end up with is a smarter grid, more robust economic development, more sustainable outcomes. It really will be good for society generally and help with energy affordability as well.
Robinson Meyer:
So the data center that we were discussing earlier, you said, is set to come on later this year. I think a lot of this conversation about data center flexibility is future focused, is looking at improvements that could happen in the future. Is there a substantive example of using AI on the grid right now to improve the supply side or the overall efficiency of the grid?
Josh Parker:
If you’re asking about kind of the data center flexibility piece, we have run several pilots. In conjunction with Emerald AI in Chicago, Virginia, and the UK to demonstrate that this is viable and it works. I’m not aware of it being implemented fully at a data center yet. I think this Virginia one that we’re building now is going to be the first one that is really built around that concept. But the pilots that we’ve run, the demonstrations have been really impressive. They’ve kind of hit all the metrics that we were hoping to achieve. So we think that it’s been demonstrated conceptually, and we’re excited to see it work in real life with this new Virginia facility.
Robinson Meyer:
So when I think about the AI electricity and AI energy use story, I’m thinking back almost to 2023. I think when AI was first forecast or projected to be a very large user of energy, frankly, from a lot of folks I talked to, including guests we had on very early episodes of this podcast, there was a lot of skepticism. Because if you go back 10 or especially 20, 25 years at the end of the dot-com boom and the beginning of the aughts, there was a lot of fears that electricity, that computers, personal computers in that case, and server farms to a lesser extent, as we called them then, were going to be a major user of electricity across the U.S. And they really weren’t. Those concerns really never panned out. And that’s because the actual chips, the computers themselves, got more efficient. Now, of course, it’s become a big user of electricity. it’s totally transforming the energy system. We’re compute constrained. We’re energy constrained. We’re in a very different moment. And...
Robinson Meyer:
That has put these efficiency gains that NVIDIA has made in its chips in a totally different light. And so NVIDIA has unlocked enormous efficiency gains in recent chips. The new AI chips are far more efficient, I think 95% more efficient than previous generations. But this seems to be contributing to a dynamic like a so-called Jevons paradox where we’re using them more. I wonder how you think about the Jevons paradox and AI and do you think we’re going to get to a point where the raw efficiency gains from AI ultimately do lead to a leveling off of energy or right now are just all those efficiency gains from NVIDIA going basically to just using AI more?
Josh Parker:
So I love Devin’s paradox in this context, because I think it says something really fascinating about the unique moment that we’re in. So absolutely, the efficiency gains that we’re seeing in AI are just astounding. And I’m not aware of any technology in history that has seen the type of efficiency gains, the magnitude of efficiency gains that we’ve seen in AI over the past decade or so. So we’re talking 100,000-time improvement in energy efficiency in the past decade. And the IEA, their estimate, which is actually a little lower than ours, is that on average, we see a 10x improvement in energy efficiency year over year with AI. And that improvement, which means, by the way, if you’re running an AI task now and you run the same AI task in five weeks, on average, it will use half the electricity in just five weeks. Again, aggregate and average if you’re doing the same task.
Josh Parker:
So that is a huge countervailing variable in terms of aggregate energy use by AI. But of course, the reason we’re building out more data centers and we need more energy for them is because AI is so incredibly valuable that even despite those energy efficiency gains, we need more of it. The scaling laws are holding so that more compute does translate into significantly more intelligence. And that intelligence is what is driving value across sectors in so many different areas. So to answer your question about where do we end up, I think it’s very clear based on what we’ve seen over the past couple of years, aggregate energy is growing, that it’s focused on AI. Still relatively low baseline globally again, but it’s growing and we expect it to continue to grow rapidly. Now, the question is, is that a problem? And I think if you look at it, there’s, again, this risk of losing the forest for the trees. On the sustainability front.
Josh Parker:
Do we care if AI uses more energy consumption if at the same time it’s reducing energy in other sectors at a much faster rate? So what we care about with emissions is net emissions. What we care about in energy, it’s actually less clear because sometimes energy growth is actually a good thing for sustainability through advancements in clean energy and so forth. But if you just look at the emissions side, what matters globally is the net. And even if AI grows, doubles, doubles, doubles, and doubles its emissions as well, which I don’t think is the case based on the data, you’ll end up in a world that has emissions reductions because of the huge impacts
Josh Parker:
that it’s having positively in other sectors.
Robinson Meyer:
Is there a current sector, though, where we can point and say emissions reductions are happening on a scale commensurate to the increase in data center electricity use?
Josh Parker:
In the near term, at the sectoral level, I don’t think that’s true. And that’s because we’re not deploying AI rapidly enough. Back to the earlier point about what is the key variable to capturing those emissions reductions. And again, going back to the manufacturing case, that kind of makes sense. Because for the economics of energy efficiency to convince you to tear down your existing manufacturing facility and build a new one that’s optimized, that’s a much harder case. But as everything gets naturally upgraded, as you’re ready to build a new factory, because the old one is ready to come offline, AI is undoubtedly going to be utilized in those circumstances. So over the course of the next decade, we will see entire sectors, I think, driving those net reduction that we’re already seeing the proof points for.
Robinson Meyer:
But it does sound, we are kind of in an interesting moment here where we are making a big infrastructure bet. And I understand why we’re making this infrastructure bet. And it’s kind to be reversible. And we think there’s a benefit on the other side, but we don’t fully know that yet, at least on the emissions front.
Josh Parker:
I would say that’s true, but I don’t think, I haven’t heard any arguments that suggest that the fundamentals don’t compel us in that direction. So again, sticking with manufacturing, but transportation and buildings are similar. If you’re building a new building and you have the option of using AI to manage the HVAC, manage the energy consumption, and you expect a 15 to 20% reduction in your builds, of course you’re going to use it and the economics just work out. So I don’t think it’s a question of if, it’s just a question of how rapidly the AI gets used for those purposes.
Robinson Meyer:
NVIDIA is working with a lot of companies and industries who I think have a very natural and mechanistic interest in improving their efficiency and who are very interested in improving their efficiency. NVIDIA is also working with SLB, which I think of still being called Schlumberger, putting together an AI factory for energy and for conventional energy and unlocking more fossil fuels. And it does seem to me that this is the place where AI could run against some of these sustainability goals, that instead of improving efficiency everywhere, it could cause, in the same way that we’re talking about Jevons Paradox, it could cause a general acceleration and unlock more fossil fuels and unlock more oil and gas and have those fuels be cheaper and have them crowd out the clean energy that I know NVIDIA is also working with clean energy companies too. Can you talk about how your work with SLB fits into the sustainability goals? And it does seem to me, doesn’t it kind of push against this idea that AI applied to every industry is going to make everyone more sustainable and reduce our emissions?
Josh Parker:
Yeah, so that’s a good question. And the truth is, AI really does, back to your original point, drive efficiency very easily across whatever purpose you’re trying to apply it for. So if you want to be more efficient at extracting fossil fuels, it can help with that. Now, where we end up, again, if the important thing is the net.
Josh Parker:
Then we need to look at, okay, is AI poised to accelerate fossil fuels more than it’s poised to accelerate clean energy adoption? And I think the data pretty clearly demonstrates that clean energy is likely to benefit at least as much as fossil fuels, not least because clean energy is already in many cases, if not most cases, the most economic and most secure form of energy that can be used. And then when you layer in things like this growth in energy demand that’s being driven by AI, the companies that build out those AI data centers, by and large, are looking for every clean electron they can find. Their commitments to clean energy are huge.
Josh Parker:
World-leading. And so the demand that AI is creating itself is very much focused on clean energy. That’s what Microsoft and Google and Meta, that’s the type of energy they want. And then you factor in the concepts of smart grids, VPPs, which AI can enable, and the demand flexibility of data centers themselves. That makes variable generation like solar and wind, at least incrementally more valuable relative to fossil fuels. So I think it only accelerates and improves the economics of clean energy relative to fossil fuels. So I think if, you know, agreed, AI can, I think, help fossil fuel companies be more efficient in their operations. But I think the overall demand picture is in the economics of clean energy are driving us unavoidably in that direction.
Josh Parker:
And the last thing I’ll say on this is AI is a fantastic complement to policy. It’s not a replacement. AI is technology agnostic. It helps you be more efficient at whatever you’re doing generally. But if we want policies that drive prioritization of clean energy and things like transmission and permitting reform and smart grids will lead us down that road naturally, then the policies, we should focus on the policies that unlock that feature.
Robinson Meyer:
I agree with that. The current set of companies that are using a lot of NVIDIA’s chips, most of NVIDIA’s chips and are applying AI, especially in the United States, are very focused on these clean energy goals. That’s not true of globally, right? I mean, that’s not true of China. It’s not true of the Gulf states, which I think are the next buyer of some of NVIDIA’s chips. Does this mean when we think about how to regulate AI, focus on keeping it at these American tech companies that have these clean energy goals? Yeah.
Josh Parker:
I’m not our political specialist, so I won’t be able to comment on the geopolitics of everything. But I will mention that I think the trend towards net emissions reductions enabled by AI, to me, looks almost unavoidable at this point, because the technology fundamentally helps us take better advantage of the resources that we have. So even if in the near term, we see an increase in emissions globally due to the build out of AI, I think in the medium and long term, we will end up with net reductions for all the reasons that are covered in those papers that I mentioned.
Robinson Meyer:
So Heatmap has been tracking what to us has been a very sudden and shocking rise of local pushback against AI data centers. And of course, this has become a larger meme over the past few months, as it’s gotten more attention. For instance, we think about 50 AI data centers or data centers broadly were canceled last year after facing local pushback. And we think more than 50 have already been canceled this year. Are you seeing that at all at NVIDIA? I mean, it doesn’t look your quarterly results came out yesterday and they were they absolutely blew out expectations. And so evidently it’s not affecting demand yet. But do you hear it from customers? Is this affecting NVIDIA’s business at all? And how do you think about it as a risk going forward?
Josh Parker:
So I’m aware of the sentiment, the paranoia around AI, mostly on a personal level, because I see it on social media like other people do as well. I’m not aware of any direct impact on our sales, so I can’t comment on that. But what I will say is I do think it’s particularly tragic because this technology has the potential to be the most beneficial, both for environmental goals and for social goals. So things like education and health care and kind of across the board, social issues benefit from AI as well. And the concerns about AI, a lot of them are based on either erroneous data or old data. and I worry that some people.
Josh Parker:
Don’t fully understand the net impacts, the positive as well as the negative of AI. Plus, we have the uphill battle of it’s really hard if the data center is being built a few miles down the road to tie that data center, which they don’t always look beautiful and things like that, to the benefits that the whole world is going to get from AI. So if, obviously not promising this, but AI could unlock cancer cures or cures to other diseases. And we’re seeing trends in the direction of cures and treatments and drug discovery and so forth. But it’s really hard for us as humans to draw a line between the infrastructure that we see down the street and especially the speculative, the moonshot benefits, but even the more fundamental ones, like the benefits and productivity that we’re seeing in potential for wage growth and education and so forth, even though it’s hard for us to draw the line between the infrastructure. So it’s understandable, but I do think it’s tragic. And I think it’s our responsibility in the tech industry to help people see the bigger picture and to address people’s concerns head on about environmental impacts and social impacts. Because the data really does demonstrate that, by and large, these data centers are pro-sustainability. They don’t have the impacts that most people are concerned about, and they’re manageable. And most data center operators are trying to operate them in a sustainable way.
Robinson Meyer:
Josh Parker, so much more to talk about, but we’re going to have to leave it there. Thank you so much for joining us here on Shift Key.
Josh Parker:
My pleasure. Thanks, Rob.
Robinson Meyer:
And that will do it for us on Shift Key today. We’ll be back soon with another episode. Until then, Shift Key is a production of Heatmap News. Our editors are Jillian Goodman and Nico Lauricella. Multimedia editing and audio engineering is by Jacob Lambert and by Nick Woodbury. Our music is by Adam Kromelow. Thanks so much for listening. See you next time.
Plus a startup harvesting energy from roadways nabs a new funding round and more of the week’s big money moves.
Uncertainty may have dried up venture funding for early stage climate, but that doesn’t mean there aren’t still deals getting done — or past commitments now coming to light as funding rounds close. This week, for example, brings early-stage backing for a European startup working to convert wasted kinetic energy from braking vehicles into power at ports, as well as a software company helping utilities visualize and manage the increasingly complex electrical grid. Meanwhile, nuclear company Deep Fission proved that the private markets aren’t the only game in town — after going public via SPAC, it’s now planning to list its shares on the Nasdaq stock exchange.
There’s also some promising news for companies looking to scale up, with thermal battery company Antora turning on its first commercial plant in South Dakota this week. That project was made possible in large part by backing from one Australian billionaire. But there’s also S2G Investments, which last week closed a $1 billion fund focused on growth-stage companies and will perhaps help more climate technologies reach that critical commercial milestone.
Every day, hundreds of millions of vehicles travel the world’s roads, converting fuel into motion and exerting mechanical force on the roads’ surface. Much of that kinetic energy is shed as heat when a vehicle throws on the brakes to navigate curves, intersections, ramps, and traffic signals. Austria-based startup REPS plans to capture some of that wasted energy, raising $23.6 million to “turn roads into power plants” by embedding hydraulic plates into road surfaces in braking zones, converting a vehicle’s momentum into clean electricity.
The mechanism is straightforward: As cars and trucks drive over the plates, they compress hydraulic cylinders built into the system, generating pressure that drives an onsite generator. The resulting electricity is routed to on-site battery storage systems, where it’s put to use powering on-site operations or feeding directly back into the local grid, turning high-traffic roads, ports, industrial sites, and other logistics hubs into their own small power sources. The company claims that capturing the energy lost through traffic could account for about 5% of global electricity demand, at least in theory.
REPS isn’t the first to attempt this form of so-called "energy harvesting,” but it says past efforts have failed due to the inferior efficiency and durability of existing mechanical energy converters. The company says its proprietary system, however, can operate for over 20 years. It’s already got one commercial system up and running in the Port of Hamburg, and says that if it were to install hundreds of such systems around the port, costs could be recovered in under four years. Now the startup is engaging with ports around the world and looking to build installations in other logistics hubs and cities.
At the end of last year, I identified Deep Fission, a startup looking to build small nuclear reactors inside underground, water-filled boreholes, as one of the wackiest recent bets in climate tech. Now the company has announced plans to go public at a target valuation of roughly $1.7 billion, seeking to raise $156 million in the process. Its thesis is that placing car-sized, 15-megawatt reactors about a mile underground could dramatically reduce both costs and safety risks. The surrounding rock would effectively serve as a natural barrier and containment vessel, negating the need for many of the bulky structures typically required to house reactors and prevent radioactive leaks.
The planned Nasdaq listing comes less than a year after the company’s somewhat unusual SPAC merger, which listed Deep Fission on the lesser-known and lightly traded OTCQB stock exchange and netted just $30 million. According to an SEC filing, the stock never actually traded, and at the time of the offering, it read as a quick attempt to secure cash. The startup had been attempting to raise a $15 million seed round earlier in the year that never panned out, and to date has raised only a modest $4 million in venture funding.
Deep Fission’s fortunes might be shifting, however, given that it’s transferring its listing to a major national exchange. The company’s public markets strategy does appear to be working as of late — In February, the startup raised $80 million by selling over 5 million restricted shares directly to investors. Whether this will all be enough to achieve its goal of beginning commercial operations in 2027 or 2028 remains to be seen, however. As a part of the Department of Energy’s Reactor Pilot Program, Deep Fission initially aimed to reach criticality — the point at which a nuclear chain reaction becomes self-sustaining — by this July, a target that now looks highly unlikely.
As utilities scramble to keep pace with surging electricity demand, expanding grid-scale renewables, increasingly extreme weather while also coordinating new, distributed resources coming online, modern grid management is getting too complex for traditional software to keep up. Texture, the startup billing itself “the operating system for the energy grid,” wants to simplify the ecosystem by giving utilities, virtual power plant operators, and grid service companies a unified view of every device and associated data sources across their network — and it just raised a $12.5 million Series A to scale this solution further.
Texture’s software aggregates data from various sources — everything from smart meters to battery storage systems, electric vehicles, and smart thermostats — and consolidates it into a single layer for grid operators, flagging problems such as voltage irregularities or outage risks in real time. The platform sits atop an operator’s legacy software infrastructure, thus avoiding the need for utilities to overhaul their existing systems or implement customized and expensive enterprise solutions that require dedicated engineering teams to maintain.
The tech has gained traction among utility cooperatives — customer-owned nonprofits that often serve rural communities and maintain smaller staffs and tighter budgets than investor-owned utilities. With this latest raise, the startup is looking to access greater scale in the co-op market through a partnership with the National Rural Telecommunications Cooperative, a network of 850 utility cooperatives across the country which will now gain access to some of Texture’s software. As Texture’s CEO Sanjiv Sanghavi said about its co-op customers in the company’s press release, "They wanted to run modern grid programs but didn't have software built for their scale or budget. A co-op serving 15,000 members shouldn't have to build custom technology to launch a battery program or manage transformer load. We built Texture so they don't have to."
I was off last week, which means I missed the chance to bring you a piece of news that I’m particularly excited about: The sustainability-focused firm S2G Investments closed a $1 billion fund in what managing partner Aaron Rudberg described in a post on the firm’s website as “one of the most difficult fundraising environments in over a decade.” What’s more, this fund is specifically designed to help growth-stage companies bridge the persistent capital gap that emerges for climate tech companies after early-stage venture rounds but before institutional investors deem them bankable. This void often prevents startups from building first-of-a-kind facilities or deploying their solutions broadly enough to prove out their tech and drive down costs.
This fund is also a milestone for S2G itself, marking the firm’s first close after spinning off two years ago from Builder’s Vision, a family office managing investments for Walmart heir Lukas Walton. According to Rudberg, the fund is writing checks in the $25 million to $100 million range, and has already invested $300 million across 10 companies, largely in food and agriculture, energy, and ocean systems. The various recipients include the agricultural input startup Exacto, maritime battery supplier Echandia, and the industrial power optimization company ANA, Inc.
So-called missing middle financing is difficult precisely because it often involves technologies that, at least initially, carry a green premium or depend on policy support. But S2G is adamant that there are plenty of competitive startups, even in a political environment where climate policy is on the outs and affordability is a top concern.
“We believe some of the most attractive investment opportunities are in growth-stage businesses that deliver economic superiority through improved efficiency, margins, and resilience in industries fundamental to the global economy,” Rudberg wrote, as companies with unfavorable economics are being weeded out. “What remains are businesses with genuine commercial advantage, and those are the companies this Fund is built to back.”
Bonus: Antora Turns On Colossal 5 Gigawatt-Hour Thermal Battery in South Dakota
Over two years ago, I wrote about how super hot rocks — that is, thermal batteries — were one of the coolest things in climate tech. Since then, the companies I profiled, Rondo Energy and Antora Energy, have both brought their first commercial plants online, with the latter announcing that milestone this week. On Tuesday, as we covered in Heatmap AM, Antora turned on its 5 gigawatt-hour project in South Dakota, which stores excess wind power as heat for a bioethanol plant operated by POET, the world’s largest biofuel producer. Once the facility ramps to full capacity later this year, it will rank among the world’s largest energy storage projects, relying on over 200 of Antora’s thermal batteries.
For this project, Antora’s tech works by absorbing surplus wind power that would otherwise go to waste in windy South Dakota, where generation often outpaces what the region’s congested transmission lines can handle. The startup converts that renewable electricity to heat using resistive heating, essentially the same technology as a toaster. That’s then stored in insulated carbon blocks for later use, where it can be delivered as direct heat to power high-temperature industrial processes, or converted back into electricity. In this case, the heat is transferred to a circulating fluid that carries it to the POET plant, where it’s then delivered as steam to power boilers, distillers, and other machinery used in ethanol production.
Neither POET nor Antora have disclosed the value of this long-term offtake agreement. The sole external investor providing project-level financing was Australian firm Grok Ventures, a climate-focused investment company bankrolled by Mike Cannon-Brookes, co-founder and CEO of enterprise software company Atlassian. One of Australia’s richest people, Cannon-Brookes has emerged as one of world’s foremost climate investors, pledging $1.5 billion of his wealth to climate projects by 2030. Perhaps its telling of the investment environment at large that an Australian billionaire — rather than the U.S. government or institutional investors — had to push this first-of-a-kind project over the finish line.