Data centers for AI will need to embrace flexibility if our electricity system is going to cope. How can large loads support the grid?

17:26Energy Gang Hosts:Either the weather's going to shut me down, some kind of congestion's going to shut me down, you know, everybody's going to put their hairdryer on at the same time. So I think a precedent was set, ironically, in ERCOT, because even though ERCOT has all this talk about firm dispatchable power, the truth is they really actually put in a lot of batteries, and they are very concerned, as they should be, about residential users. And so they were the first state to say, we're passing a law that gives us the right to turn a data center off completely if it means making sure there's no blackout for our residential citizens.

18:08Energy Gang Hosts:And so, you know, do we think that's going to happen in more states? Varun, do you think that changes the conversation you're having with the hyperscalers? Because if that starts to be the regulatory framework across the country, they're going to be forced to think about flexibility. I also want to come back, Shanu, to some of the exciting things you mentioned about multi-data center fabrics. But let's come back to that because this is a critical point. Amy, as you say, grid operators have the service obligation. And the last thing you want to do is have to shut off a residential community or shed rolling blackouts as a result of not being able to meet peak demand.

18:45Energy Gang Hosts:And it's especially bad if the data center has caused this problem, and yet they still get served. And so therefore, what can you do? Amy, you made the point that in Texas, there's now a law on the books that in theory could enable the power system operator, ERCOT to simply shut off data centers. Again, this is why I think hyperscalers, data center operators, tech companies have an incentive and a reason to proactively come up with more graceful solutions than simply getting shut off. You know, I'm really excited to share, this just became public, that NVIDIA and Emerald AI are collaborating to enable a reference architecture for AI factories or AI data centers to have some of these capabilities like flexibility.

19:32Energy Gang Hosts:And here's why that's important. If a data center has this capability, it can provide that flexibility, that demand reduction during a peak moment, for example, in a graceful way that protects the AI customers but also meets the grid's needs. And you don't actually have to wait until the warning lights start flashing red. One of the best conversations I've had early on as I did market research to create Emerald AI, I spoke to the CEO of ERCOT, really a visionary thinker, Pablo Vegas, who shared that his goal would be to never get to the emergency condition to begin with. You never want the warning lights to flash red.

20:12Energy Gang Hosts:Maybe they flash yellow. And that's the point at which you deploy the available resources you have. You know, Amy, as you mentioned today, they're batteries. But data centers could be that flexible resource that as soon as you're in a moment of even remote danger, the data centers are able to help the grid return to a normal operating condition. Now, back to Shana's point, there's trillions of dollars going into these data centers, and they are doing some of the most economically valuable work in our economy. I don't care if you think that generating cat images or images that look like Studio Ghibli is economically valuable or not.

20:45Energy Gang Hosts:the numbers don't lie. The GDP benefit of US data center and AI are staggering. And so therefore, those are the economic activities we do not want to curtail. At the same time, if we can do so gracefully in a way that the AI compute users still remain very satisfied with their quality of service, you have this rare win, win, win, win, win, right? I could go through the five wins, but I think you know what they are. The AI compute user is happy. The grid is happy. You have reliable, safe, clean, and affordable electric power systems. I think I got to five wins. And that's rare in our field.

21:19Varun Sivaram:So Shani, what do you make of this? Does that sound too good to be true?

21:23Energy Gang Hosts:I mean, I think there's a lot of steps between now and there. But I mean, ultimately, I think the long term vision I'd agree with, right? And then point in terms of the different priorities, right? Like if I'm a utility, on the hottest possible day, everyone's operating in their peak low capacity, ACs on, etc. I need to plan for that event. The issue with the operational load of that type of facility, whether it's a colo, whether it's an infrastructure data center or a training data center, there's different utilizations that spike up and down. And as anyone that follows this stuff really closely knows at a chip level, then extrapolating to a data center level, these things are really transient, meaning that the workloads spike.

21:57Energy Gang Hosts:Oftentimes the chips will be idle, operate at 30 % to 40 % of their max thermal capacity, and then spike up to 100 % to 110%. That's a utility's worst nightmare, right? But they're solving for assuming 100 % all the time. And I think in reality, what we see is when these things are done in practice, like the percentage utilization is a lot lower. And that's why I think it's a lot. I've met more in terms of like, it's up to the hyperscalers to figure this out eventually, because you're already seeing utilities start to cap some of the issues associated with the transients. There was a really good paper by a bunch of Microsoft researchers, Power Stabilization for AI Training Data Centers, published in August this year.

22:31Energy Gang Hosts:And it talked about the fact that when you scale up with this many GPUs and they're moving up and down, it kind of creates bad frequencies for grid managers. And so they're already indicating, hey, we're going to cap your limits on how much you can swing up and down because that makes it a lot harder for us to manage the frequencies on the back end. And so I think part of the conversation around flexibility is like there's a different mismatch between the utilities solving for the worst possible scenario. But in reality, the percentage might be a little bit lower. I mean, just today I was reading a report on ERCOT, which we just were talking about.

22:59Energy Gang Hosts:They did a study of data center lows from 2022 to 2024, and they actually only used 50 percent of the megawatts that were initially requested. right and so i think that like that introduces this mismatch and where there's an opportunity for flexibility here where it's like if you requested a gigawatt and end up using 500 megawatts that opens up quite a bit a lot right for the flexibility side and the utility planner side in terms of what's actually being managed according or what's being planned for and then

23:22Varun Sivaram:managed to yeah absolutely i've seen other numbers like that circulating and i think we've got some with mckenzie as well as you say saying although the data center operators talk about five nines availability they're absolutely not used uh they're not using you know 99.99 percent of the full capacity at all times or the full capacity at 99.999 percent of the time you know so there does seem to be some headroom there again just from a grid operator's perspective that doesn't seem to be at all helpful though because you know if you have no visibility into exactly what the variability of the of the demand is going to be if you can't predict when that spare capacity is going to be available and most importantly it's not controlled by you it's not kind of dispatchable effectively it doesn't really help so to your point you know when you say grid operators always prepare for the worst eventuality you can see why they do that right that's totally reasonable from their perspective because if you say oh well this gigawatt data center is only using 500 megawatts but then it at the time of maximum stress on the grid it happens to jump up to one gigawatt then disaster ensues.

24:32So you have to be on the cautious side.

24:35Energy Gang Hosts:Everybody help me here. I mean, I'm the least knowledgeable of the all of us having this conversation. I'm like the lay person. So let's just say, Shana, a very interesting study and very interesting statistic from Texas. So how do we get to a moment where we had this massive blackout and somehow we didn't even have the data centers operating at max capacity. Is it just that so much generation capacity got wiped out? Could that same thing happen in California in a heat wave? I mean, what kind of percentages are we talking about where we can't control this fluctuation at times of grid stress from weather?

25:19Energy Gang Hosts:And then taking it the next step, Shano just frightened me with the whole frequency thing, thinking about Spain. So help me out here as like a lay person. How difficult is this? Sure. I'm happy to jump in here. Let me just break something down for our listeners, which is there are varying timescales at which AI can either create problems or provide solutions. So as Shana was mentioning, there are very short timescales, millisecond transients seconds frequency issues and there are other timescales minutes and hours when the grid is facing a peak load moment and we need to shave that peak across all of these timescales different solutions will be needed and there isn't one single silver bullet for any of them so for example when an ai training run starts up and then it causes a massive tens of megawatt increase in energy consumption.

26:15Energy Gang Hosts:And then all of the GPUs do something called a synchronized checkpoint. It's kind of like saving your work on a Word document. Then the power falls by another several tens of megawatts. These are being addressed, as Shanu mentioned, through certain hardware fixes where NVIDIA's chips help to smooth that curve. There are software fixes, and there's energy storage like batteries that can help you. On the longer timescales, you also have a range of interventions. So I just first want to make the point that there's many different timescales. Now, Amy, the question that you were talking about is typically most visible at the several hours timescale.

26:51Energy Gang Hosts:When you have a mismatch between how much generation is available, let's say a winter storm has knocked out some natural gas generation and or a fire has knocked out power lines and your demand happens to be high. Let's say it's a hot day and there's a lot of air conditioning demand. Data centers may not be a silver bullet. You may not be able to get enough load reduction from the data centers, but if they are flexible, you may be able to get some load reduction and help a little bit. And then there will be other interventions that you'll have to take. Typically, as you know, Amy, it's a great idea for your grids to be larger and more interconnected and to have strengthened transmission such that if you have a larger area, it's harder for any one particular section just to go down.

27:36Energy Gang Hosts:But if you have an isolated grid, then that grid can in fact go down because of a supply-demand imbalance more easily. So Varun, I love that point. So explain to us again, in this context, the idea of having hyperscalers have a cluster of data centers that work in coordination, and therefore we're less have to have that problem because if we had interactions between different grids, we could move resources around better. Exactly. We actually did a real-world test that showcased what the potential might be to avoid blackouts. So as I mentioned, we went to Phoenix, Arizona. We had this Oracle data center, and we reduced consumption of the AI cluster by 25 % for three hours at a moment of peak demand.

28:21Energy Gang Hosts:We then went and re-simulated a case where in California five years ago in August 2020, there were rolling blackouts because a natural gas plant tripped offline. And we simulated what would the demand response curve have to have looked like. And it looks kind of like a stair step to avoid those rolling blackouts. And we showcased that the Emerald Conductor can create that stair step in real time, first providing a little bit of a demand reduction. And then when the grid says, oh my goodness, I need more support, providing even more of a demand reduction while still protecting the performance of the AI workloads.

28:54Energy Gang Hosts:If we were to deploy Emerald conductor at commercial scale across a large network of data centers, it's even more powerful, Amy, because then if you have a problem in Arizona, it's the middle of the summer, your peak load is approaching what your generation can provide, then you're able to move some workloads that are very latency or time sensitive away from Arizona, maybe to the Pacific Northwest, let's say, or over to Illinois, where there is ample wind energy at that moment, let's say. And that's going to enable you to keep the AI workloads running in different parts of the country. And those that could be curtailed or paused in the Phoenix data center, we just reduce the power consumption of those, let's say, fine tuning operations.

29:32Energy Gang Hosts:Taken together, the whole network of data centers completes the work that needs to get done for its AI users, which, as I mentioned, is the most economically valuable work there is. I'm not trying to put a moral judgment on it, but economically, GDP wise, it is the most economically valuable work you can do per unit energy. And at the same time, we have saved the Arizona region from any kind of rolling blackout. That's the vision I want to achieve.

29:56Varun Sivaram:Right. But again, to your point, Varun, about what happens if there's a blackout and people lose power and communities go dark at the same time that data centers are able to keep running. Talk about this being the most economically valuable work that could be done. It's not really going to cut it, right? People will be angry. Regulators will lose their jobs. Politicians will lose their jobs. These are the things. Again, when you think about why regulators and grid operators take the decisions they take, that at the end of the day is the ultimate sanction. That is their hard constraint that they've got.

30:31Varun Sivaram:They have to keep the lights on. And all those other considerations are going to be secondary.

30:37Energy Gang Hosts:And that's what's happening in PJM. Why is PJM in the news? PJM is in the news because they had these capacity market auctions and the prices were stunning. and that made it a political thing not only for everybody involved in maintaining the system in PJM, but also for all the politicians in the different states that are part of that regulatory area.

31:03Varun Sivaram:Well, indeed. And politicians say, oh, well, the capacity market prices are too high. We shouldn't be having to pay for all this. You still need the capacity though. And if you don't incentivize it properly, it's not going to come. And so that's going to be creating problems for you down the road.

31:17Energy Gang Hosts:But the point that Amy makes is dead on, which is the price of electricity, the household bill annually for a household in Columbus, Ohio, on average, went up$240 directly attributable to data centers. That is not a good look. And I think everybody has an incentive to avoid that happening. And that's why we need to be proactive in finding better solutions. Now, I do want to hit a positive part of the story, which is the tremendous pace of technological change. Earlier, Shanu mentioned that you heard from earnings calls from Broadcom, you heard from NVIDIA a couple weeks ago, that the incredible technology progress, not just in the chips, but in the networking, is enabling multiple data centers to act in concert.

32:05Energy Gang Hosts:In fact, NVIDIA has a new technology called Spectrum X that enables such a high bandwidth set of network connections between data centers that it's as if data centers that are spatially separated can act as if they're all part of the same data center complex. And that's a very powerful tool. You know, I feel, again, bringing back this Forrest Gump analogy, I'm here watching all of these tremendous advancements in the tech industry. AI is forging ahead. And every time I hear someone like our colleagues at Oracle, they're our partners, talk about the tremendous fiber optic connections they'll build in between data centers, I get excited for a reason that has nothing to do with why they're excited.

32:47Energy Gang Hosts:They're excited because they're going to serve their AI customers an amazing product. I get excited because I can piggyback on this incredible advance for electric grid purposes. If you have a very well-networked set of data centers, it becomes even easier to shift workloads in between data centers, to pause workloads in one location and make sure they get picked up somewhere else, to coordinate operations, and even to do things like distributed training where you might have many autonomous workers operating in multiple different data centers. Google's DeepMind published a protocol, DeLoco, that does this.

33:23Energy Gang Hosts:And that's a very exciting opportunity because you might, therefore, instead of having to take down a whole training run, you can just pause simple decentralized autonomous workers one at a time in places where grids are particularly stressed without compromising the overall progress of the training run. So I think, again, just to bring this back to a 10 ,000-foot level, the pace of AI is moving and everybody who is advancing AI is focused on AI and its economic potential. I want to be focused on leveraging these advances for helping the grid so that we don't have the situation, Ed, that you mentioned where the data centers keep getting power but the neighborhoods get blacked out.

34:04Energy Gang Hosts:That's a real bad look. Or Columbus, Ohio has bills go up by$240. We've got to avoid those. So Varun, just to restate what you're saying with this autonomous worker so people understand, we have these tests and they're being done instead of being done all in one central data center. And now I can't let that data center go down. It's as if I had human beings, electronic human beings in different locations. and since they're all working separately, and then eventually I'm going to bring all their work product together into one final product, I could tell one of them to go take lunch at a different time than a different one, but we would still meet our target, which is to have the whole job done to upload in a centralized place at a particular time.

34:51Energy Gang Hosts:You have nailed it, Amy, and I'm so glad that you gave that much more understandable analogy. Look, this is still a research direction. Today, a large training run is done in the same facility with synchronized GPUs. But you can imagine, and there's great published work on this and companies like Prime Intellect that are advancing this paradigm. You can imagine what you just said, Amy. The group project gets done by a bunch of different students. And each of them gets to take lunch whenever they want. But they share their notes afterwards and they make sure that the work gets done on a reasonable timescale.

35:23Energy Gang Hosts:And it's really robust and resilient, both to other things that can go wrong, like GPUs failing or outages, but also to Emerald's approach to pausing or slowing workloads when the grid is stressed to provide AI data center flexibility. So think of it as the group project paradigm. We're not there yet, but when we get there, it's a good example of an AI innovation that's going to make it even easier for AI to help the grid. And not only for AI to help the grid. I mean, honestly, all the companies should be working on it because it's an important national security imperative that you have a cyber division that way.

36:01Energy Gang Hosts:And you can't just have something get disrupted because someone can target one particular data center because they have intelligence that that data center is doing something critical. Nailed it. That's right. Shana, you were going to say something. I think I was just trying to connect the two points earlier where I think we were talking about these things at contrast where the utility operator has to decide between keeping homes lit and heated versus the data center running. And I think that's what the tech companies see in the periphery. They're looking down and seeing that, hey, these things could be construed as the and or decision.

36:31Energy Gang Hosts:And that is increasingly going to become a political hot button issue, especially as the shitty inflation accelerates. And so they're already working on these solutions as just a result of their own redundancy and their own uptime initiatives. They want to be decentralized to a point where they can be in control of their operations. Otherwise, they will be forced into these operations where the utilities can say, I'll shut you off. There's an EPOC paper that outlined the power density of the compute being demanded. One of the things they talked about was distributed training and synchronization amongst data center facilities.

37:01Energy Gang Hosts:And right now, there's already a host of labs testing this out at 15 to 50 miles. Broadcom talked about 100 kilometers at their last call. So you're already seeing this stuff happen in the background. It's just not at the forefront today. And that's why I think when Faroon pitches this grand future of kind of the data center flexibility and these different options, whether it be hardware or software or firmware, you know, that's where you can see that naturally we're already headed that way in general, just given the fact that a lot of these companies are already thinking about what the problems are going to come up in the next one, three, five-year timelines.

37:30Energy Gang Hosts:So, Shonda, I have a follow-up question on that. You know, you follow the investment community. you cited these giant numbers. My whole community here in New York, the private equity community, they are just raising money for infrastructure funds right and left. Everybody wants to fund a data center. Everybody wants to fund SMRs. Could we wind up in a situation where it becomes analogous to when everybody wanted to fund shale back in the early 2010s, and then suddenly we didn't need all that energy? Or you think that, no, this is a real thing. And even if some of the technologies that Varun is talking about start to become mainstay, there's just still going to be a giant need.

38:14Energy Gang Hosts:Well, Amy, it's a great point. And if you go back to the paper that Shanu mentioned, which I thought was terrific, a collaboration between EPRI and EPIC AI, the graph that stuck out to me was not the one that said that the power demand is growing for AI at a rate of more than 2x doubling every year, but rather that the rate of computations is growing at a rate of more than 4x per year. That's meaningful to me because it's important to think about what might distinguish this AI explosion and demand and compute and power needs from previous explosions in the increasing compute needs like the internet revolution, the dot-com revolution.

38:55Energy Gang Hosts:In those revolutions, you saw power demand largely flatline because even as the demand for computations went up, the energy efficiency of those operations improved as well. And you flatlined your energy consumption at about 4 % of American electricity use. Today, because of that difference between 4x computations every year and the increasing energy efficiency of data centers, which is happening much slower today than it used to happen. The net result is a 2x or more increase in energy every year. That means we're going to go from today 4 % of American energy to 12 % by 2030 to maybe 25 % sometime mid next decade, where AI becomes the biggest consumer of electricity.

39:43Energy Gang Hosts:So to your question, will there be a slowdown in demand for AI? Quite possibly. But as we look at today's scaling laws, at the diminishing marginal returns of training models, at the increasing use of AI in our economy, it's hard to see why you would have less demand for computation and less demand for energy than even some of the conservative projections. Sorry, than even some of the aggressive projections we're seeing for energy demand today. Yeah, just to build off that, I mean, I think the paper, you know, highlighted, I think, 30 to 50 % efficiency every year, which, you know, is a large, large number.

40:21Energy Gang Hosts:And typically, that would be a lot to dent a curve. But in reality, if your compute is growing 4x a year, it's just a drop in the bucket right now at this point in the cycle. So I think what a lot of the private infra players and everyone else that's raising money are doing right now is they see that directional curve and they want to get ahead of it. So they're investing in infrastructure. I think it ultimately comes down to, one, do we continue to see those trends play out over the next three, five, 10 years? I think it's too early to tell right now. They're making the bet that they can. And then, two, I think the other point that the power players are thinking about, or at least I hope they're thinking about, is the eventual repurposing of the technology.

40:55Energy Gang Hosts:Yes, AI data centers are driving low today, but as we all know, space heating, cooling, electrification, electrification of transport, et cetera, will actually be even larger. So, I mean, if you're owning energy assets that can sell into deregulated markets, then maybe you feel a little bit better about funding that infrastructure. But, Amy, to your point, I mean, we're seeing massive, massive partnerships between private capital providers and energy developers. I mean, there's like 10 I can name off the top of my head. So it does feel like there's a flurry of activity. And I'm not going to sit here and call a bubble.

41:22Energy Gang Hosts:I'm not in the business of that, nor would I be good at it. But, you know, it does feel like at least we're at a relative level of exuberance that, you know, does mirror at least prior cycles in terms of kind of just like crazy behavior out there and the insatiable thirst, let's call it, to finance these deals. So I think Varun makes this point. So it's really an interesting question. Like, where are we in the exuberance field? Because Varun, to your point, if you listen to people from the tech side, you know, I'm going to have these robots in my home and they're going to be able to do all these things for me.

41:58Energy Gang Hosts:so I can just do this podcasting all day long and I'm not going to have to touch a dish. And then my car is going to be automated and Uber's vehicles are going to be automated and everything's going to be automated and that's going to all mean inference, inference, inference. And so it does seem like it could be pretty exponential. But on the flip side, I have, of course, look at this in my work and Shano made allusions to it. But I guess this paper took that all into account. If I am, everybody is using e-commerce and I do have all these AVs and I do have all this AI being applied to airlines and to marine bunker fuel and all this stuff, then I'm going to have a huge gain in energy efficiency.

42:44Energy Gang Hosts:And so maybe I would increase electricity needs in some level, but I'm going to decrease it in other places. is I've been recently working with some professors at NYU on the building sector in New York City, which is very controversial because they've told everybody to electrify. And some of the PE firms are doing some pretty innovative buildings, some of which they're saying, oh, we're not going to really need much energy from the grid because it's called a circular solution where the whole building generates its own electricity internally. And they don't really, the grid is kind of a marginal amount of where the electricity is coming from.

43:25Varun Sivaram:Of course, you know, Amy, what's actually going to happen is the AI is going to do the podcasts, and we're still going to have to do the dishes. I mean, that's the... Yeah, I'm afraid

43:32Energy Gang Hosts:we are going to come to that.

43:34Varun Sivaram:It's a very interesting point. I wanted to bring us back from that kind of future prospect, though, to just, because we're heading towards the end of our time. And I just wanted to get back to this kind of short-term question or shorter-term question because I mean as you say Amy a lot of those issues great deal of uncertainty in the longer term about how much the demand is actually going to be as you were saying Varun earlier a lot of these kind of ideas about flexibility to compute and where that can happen and so on are going to be implementable in the longer term but in the short term there's an enormous amount going on right now as you were saying Janu you know there's whatever it is half a trillion dollars of CapEx being spent this year in 2025.

44:17Varun Sivaram:There's an enormous amount of steel going into the ground, you know, racks of chips being put in all over the country. And so everybody, regulators, policymakers, utilities, you know, the industry in general is working out how to deal with this kind of in real time immediately. And the example of that, I just wanted to get your thoughts on was really interesting this month there's been a lot of pushback to the proposals from PJM. PJM the big power market regional transmission operator covering an area from Illinois to Tennessee to New Jersey to North Carolina and they've basically come up with this idea and let me just check the terminology there's a there's a new acronym they've created right the NCBL which is the non-capacity back load and what they're basically saying as far as I can tell is that if you've got one of these NCBLs then they want to reserve the capacity to shut you off when they think they need to because there's strain on the grid in other words if you don't have backup generation not necessarily kind of co-located but somewhere available on the grid that you can put into the grid to cover your power demand then they're going to insist that you're flexible this plan seems to have gone down very badly.

45:37Varun Sivaram:I was looking at the newsletter heat map that they said, the country's biggest grid has a plan to manage data centers power use. Everyone hates it. And it certainly does seem to be the case that if you look at sort of governors of some of the key states and some of the key companies and industry groups and tech industry groups and utility industry groups all seem to be kind of pushing back a bit. I couldn't quite see why they hated it so much because it felt to me like at the very least PJM is saying look there's a real issue here we need to address it we need to address it quickly and perhaps they're being a bit aggressive in the way they're talking to data centers about it but I mean we're talking earlier about SP6 the Texas bill that basically has said to data centers lodge loads in Texas if we have to shut you down we're going to do that and if you don't like that that's tough and essentially it seems to be PJM kind of thinking about a very similar model.

46:33Varun Sivaram:I don't know who's been, Sean, have you been looking at this and what do you make of what they've been proposing and does it make sense to you or do you see why everyone's unhappy about it?

46:41Energy Gang Hosts:Yeah, I mean, if you look through the commentary and the original proposal, I mean, one of the things I think is markedly, you know, absent from it was that they didn't really at least specify the benefits you'd get from participating. I mean, like you wouldn't pay the capacity, you know, functions or premiums, but you don't get any speed for interconnect. And I think that's the whole trade-off right here is that at the end of the day, it goes back to that economic incentive where it's, do I get any type of benefit for voluntarily shutting my load? And in this case, it wasn't really clear or was spelled out in the original proposal.

47:13Energy Gang Hosts:And so what you see in the comments here is a willingness for demand response if there's some associated benefit, right? Because in this case, then the economic benefit of time to power is a lot greater than this voluntary thing that you can get around by either figuring out flexibility from a software or hardware or storage perspective. And I think that's what was missing. And largely when you look at the commentary from some of the big players, the data center coalitions and et cetera, like Tyler Norris has covered this ad nauseum, they seem constructive. It's just a matter of like, hey, like what are we getting in return for this?

47:41Energy Gang Hosts:Otherwise you're just discriminating against our larger load. Varun, I'm sure you have some opinions on that. Totally. And it's gonna be a push and pull for a little while as we try and find the right compromise. But I'm just glad that folks are thinking proactively about this. Look, I gave a speech recently at the EPRI Summer Seminar. EPRI has been a wonderful partner and the convening body for the DC Flex Initiative, through which energy and technology industry folks are coming together to advance data center flexibility. And what I said was we need three key next steps. The first is for the tech and the energy industries to come together to do demonstrations.

48:19Energy Gang Hosts:We at Emerald AI with Oracle, NVIDIA and the Salt River Project Utility in Arizona did the first one of these demonstrations through EPRI DC Flex. But now we need 10 and 20 and 100 more of these demonstrations at larger and larger scales. We're really excited at Emerald that our next few demonstrations, you know, one is kicking off on Monday in Chicago, also through EPRI DC Flex with Commonwealth Edison. Others are going to happen in the United Kingdom all over the world. The second thing is that we need real progress on accelerated interconnection processes. Shanu, as you mentioned, this is the real incentive that's going to entice data center and cloud companies to come to the table and say, we're willing to do flexibility if we can get faster time to power for a new data center or take an existing data center and get a larger power connection so that you can swap out the GPUs for the latest NVIDIA generation, switch to liquid cooling, etc.

49:10Energy Gang Hosts:And the third thing was we need to advance the technology frontier for how we achieve flexibility. We have so many tools already. We have infrastructural tools like batteries, And we're just at the cusp of commercializing these computational tools like spatial and temporal flexibility that Emerald does. So you do those three things. And I think there's a real forward progress over the next 12 months to scale up data center flexibility to large commercial scale and then to multiple data centers to create, you know, one of the things you talk about, Amy, a virtual power plant of AI data centers.

49:43Energy Gang Hosts:That, I think, is the holy grail solution. It's going to be the most powerful demand-side solution we've ever seen on our power grid because data centers are massive, they're virtually controllable, they have millisecond response time, and they're connected with each other at the speed of light to move work all around the world. I think the sky's the limit at that point.

50:02Varun Sivaram:yeah that is a great point and certainly i think i would have a certain amount of faith in the ability of the free market to deliver solutions here because the rewards are so massive right the incentives if you can get this right if you can work out as you say how to kind of reconcile the irresistible force and the immovable object if you can work out how to get over these issues of flexibility in order to get more capacity connected and operational and on the grid sooner, that's going to be something that is going to be very richly rewarded. That's going to have a huge payoff. And as you say, a lot of people will be very strongly incentivized to make their work, I guess, including you, Varun.

50:47Energy Gang Hosts:I'm super excited to push this work forward. I'm so grateful for the chance to speak with all of you. Congrats on a great show.

50:54Varun Sivaram:Well, thanks very much indeed. Thank you very much for joining us. We do, unfortunately, have to leave it there. But thanks very much indeed, Amy.

51:01Energy Gang Hosts:Thanks, Ed. Thanks, Varun. Thanks, Shano. Always great to see you both.

51:04Varun Sivaram:Yeah, many thanks, Shano.

51:05Energy Gang Hosts:Yeah, thank you, everyone. It was a pleasure joining you all.

51:07Varun Sivaram:Thank you again, Varun. All the best with your efforts. Will be very interesting to see. We should talk again perhaps next year and catch up, see how things are going for you. But certainly hope it all works. Thanks to our producer, Toby Biggins Gilchrist. And above all, of course, as ever, many thanks to all of you for listening. We really do value your feedback. Please do keep that coming. Leave us a review, send us an email, whatever you want to do. And we'll be back in two weeks with all the latest news and views on the energy transition. Until then, goodbye.