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Will the rise of machine learning and artificial intelligence break the climate system? In recent months, utilities and tech companies have argued that soaring use of AI will overwhelm electricity markets. Is that true — or is it a sales pitch meant to build more gas plants? And how much electricity do data centers and AI use today?
In this week’s episode, Rob and Jesse talk to Jonathan Koomey, an independent researcher, lecturer, and entrepreneur who studies the energy impacts of the internet and information technology. We discuss why AI may not break the electricity system and the long history of anxiety over computing’s energy use. Shift Key is hosted by Robinson Meyer, executive editor of Heatmap, and Jesse Jenkins, a Princeton professor of energy systems engineering.
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 our conversation:
Robinson Meyer: Before we go any further — and I think you just hinted at your answer, here, but I want to tackle it directly — which is that I think people look at the hockey stick graphs for AI use, and they look at current energy use for AI, and they look at load growth data coming from the utilities, and they go, “Oh my gosh, AI is going to absolutely overrun our energy system. It’s going to cause emissions to shoot up,” because again, this is just extrapolating from what’s recent.
But of course, part of the whole AI mythos is like, once it starts, you can’t stop it. There is a story out there that, frankly, you see as much from folks who are worried about the climate as you do from AI boosters, which is that very soon, we'’e going to be using a huge amount of energy on AI. And I want to ask you this directly: Should we be worried about AI, number one, overrunning the energy system? Or number two, AI causing a massive spike in carbon emissions that dooms us to, let's say, pass 2.5C that uses up the rest of our carbon budget? Is that something you're worried about? And just how do you think about this?
Jonathan Koomey: Everyone needs to calm the heck down. So we talked about the original baseline, right? So the baseline, data centers are 1% of the world's electricity. And maybe AI now is 0.1%, right? For Google, it’s 0.15%, whatever. But 10% of the 1% is AI.
So let’s say that doubles — let’s say that triples in the next few years, or even goes up fivefold. That gets to about half a percent. So I think it will pale in comparison to the other growth drivers that Jesse was talking about in electrification. Because if you think about light vehicles, if you electrified all light vehicles in the U.S., that’s like a 20% or 25% increase in electricity consumption. And if you did that over 20 years, that’s like 1-ish% per year. Right? So that's, that to me is a very credible thing that’s likely to happen. And then when you add heat pumps, you add industrial electrification, a lot more.
I think there will be local impacts. There will be some places where AI and data centers more generally will be important and will drive load growth, but it is not a national story. It is a local story. And so a place like Ireland that has, I think at last count 17%, 18% of its load from data centers, if that grows, that could give them real challenges. Same thing, Loudoun County in Virginia. But you really do have to separate the national story or the global story from the local story.
Jesse Jenkins: I think it was just about a week ago, Nvidia which is the leading producer of the graphics processing units that have become now the main workhorse chips for generative AI computing, they released their new best-in-class chip. And as they revealed that chip, they — for the first time, it sounded like — started to emphasize the energy efficiency improvements of the GPU. And the basic story the CEO told is that it would take about 73% less electricity and a shorter period of time to train AIs on this new chip than it did on their previous best-in-class chip. So that’s just one generation of GPU with nearly three-quarters reduction in the amount of energy consumed per ... I don't know how you measure the units of large language model training, but per smarts trained into generative AI. So yeah, huge gains.
And one might say, well, can that continue forever? And I guess we should maybe get your thoughts on that. But it has continued at least for the last 10 to 20 years. And so there’s a lot of reason to believe that there’s continued gains to be made.
Koomey: Most people, when they think of efficiency, they think of Moore’s Law. They think of shrinking transistors. And anyone who follows this knows that every year or two, there’s another article about how Moore’s Law is ending, or slowing, or you know, it’s getting harder. And there’s no question about it, it’s absolutely getting harder and harder to shrink the transistors. But it turns out shrinking transistors is only one way to improve efficiency and performance. For a long time, the industry relied on that.
From the early days of microprocessors, starting in ’71, over time, they would ramp up the clock speed. And at the same time, they would ramp down the voltage of the chip. And that was called Dennard scaling. It allowed them to keep ramping up performance without getting to crazy levels of leakage current and heat and melting the chip and the whole thing. That worked for a long time, til the early 2000s. And then they hit the threshold voltage for silicon, which is like one volt. So once you hit that, you can no longer do that trick. And they needed new tricks.
So what they did was they, most of you remember who were around at that time, there was this big shift to multiple cores on a chip. That was an innovation in hardware architecture that allowed them, for a time, to improve efficiency by going to software that could run on multiple cores, so you could multiprocess various activities. So that’s one way you can improve things. You can also work on the software — you can improve the efficiency of the software, you can improve the algorithms that you use.
So even if Moore's law shrinkage of transistors stops, which it hasn’t fully stopped. But even if it did, there are a lot of other things we can do. And AI in particular is relatively new. Basically, people threw a whole bunch of money at existing processors because there was this rush to deploy technology. But now, everyone’s stepping back and saying, well, look at the cost of the energy cost and the infrastructure cost. Is there a way to do this better? And sure, there definitely is, and Nvidia proved it in their presentation that you referred to.
This episode of Shift Key is sponsored by…
KORE Power provides the commercial, industrial, and utility markets with functional solutions that advance the clean energy transition worldwide. KORE Power's technology and manufacturing capabilities provide direct access to next generation battery cells, energy storage systems that scale to grid+, EV power & infrastructure, and intuitive asset management to unlock energy strategies across a myriad of applications. Explore more at korepower.com.
Watershed's climate data engine helps companies measure and reduce their emissions, turning the data they already have into an audit-ready carbon footprint backed by the latest climate science. Get the sustainability data you need in weeks, not months. Learn more at watershed.com.
Music for Shift Key is by Adam Kromelow.
Inside episode nine of Shift Key.
Radia is a $1 billion climate tech startup with an unusual pitch: It is trying to build the world’s largest airplane. Its proposed aircraft, the Radia Wind Runner, would be as long as a football field, nearly as wide as a New York city block, and capable of carrying 12 times the volume of a Boeing 747. Such a plane could ferry massive wind-turbine blades, unlocking what the company calls “gigawind” — the ability to build offshore-sized wind turbines on land.
Why is that important? Because the larger the wind turbine, the more electricity that it generates — and the less wind it needs to work with. Radia says that its “gigawind” farms could profitably go into places with slower wind speeds, such as the Northeast or Mississippi Delta. They could also be built in the existing Wind Belt, potentially doubling current output.
In this week’s episode, Rob and Jesse talk to Radia’s chief executive officer, Mark Lundstrom. (Jesse’s consulting firm did some research for Radia while it was in stealth mode, in 2020 and 2023.) We discuss why the world needs a bigger plane, how such a new aircraft gets licensed, and why massive wind turbines could be such a big deal for renewable electricity. Shift Key is hosted by Robinson Meyer, executive editor of Heatmap, and Jesse Jenkins, a Princeton professor of energy systems engineering.
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 our conversation:
Jesse Jenkins: I’m here in the mechanical and aerospace engineering department at Princeton, so we’ve got a lot of students excited about new aerospace applications. I have a six-year-old kid, as well, and he’s also excited about anything that goes fast and is big, so I’m sure he’ll get excited about the eventual Lego kit for the WindRunner that we’ll have to get out in the world. But talk through the size of this aircraft compared to, say, something we’re used to, like a 737 or more conventional aircraft.
Mark Lundstrom: Sure. So before understanding the size, one has to understand the fundamental mission requirements. And so the goal, Radia’s goal is to be able to move up to a 105 meter long object that could weigh up to 75 tons. Now we can also move multiple smaller blades, so two 95s, or three 85s, or four 75s. So the vehicle is quite versatile.
In terms of sheer size, it’s about 12 times the volume of a 747. So it’s very, very large compared to the 747. It’s about nine times the volume of the Antonovs. And yet what's very different about it —
Jenkins: And the Antonov, that’s the largest plane built to date, right?
Lundstrom: Yes, the largest volumetric plane right now. There’s about 14 or 15 of them left in the world, usually Russian or Ukrainian operated.
Robinson Meyer: I was going to say, I remember the biggest plane in the world being destroyed right at the beginning of the Ukraine War and was wondering how that compared to the to the WindRunner vehicle.
Lundstrom: So the Antonov 225, there was one of them. WindRunner is six times bigger in volume than that airplane was, and it’s nine times bigger in volume than the remaining Antonov 124s that are still out there. And so, and what’s additionally unusual about it, in addition to the size, is its ability to land on dirt.
Meyer: Wow.
Lundstrom: Things like Antonovs, 747s, etc., they need to land on about 9,000 feet of steel reinforced concrete, typically. And we designed the WindRunners so we could land on relatively short dirt strips, so just over a mile of a semi-prepared field. And that allows us to bring the payload into a wind farm, and be able to get a very large aircraft out of the wind farm. It’s probably the first time that an aircraft has been designed to optimize around volume, as opposed to mass.
Usually when an aircraft design team starts off, they’ll start off thinking about how much mass has to be moved. We really started off thinking about how much volume has to be moved. So there are aircraft that move larger mass than the WindRunner. There’s absolutely no aircraft that comes close to moving larger volumes and being able to land that volume on a relatively short dirt strip.
This episode of Shift Key is sponsored by…
Advanced Energy United educates, engages, and advocates for policies that allow our member companies to compete to power our economy with 100% clean energy, working with decision makers and energy market regulators to achieve this goal. Together, we are united in our mission to accelerate the transition to 100% clean energy in America. Learn more at advancedenergyunited.org/heatmap
KORE Power provides the commercial, industrial, and utility markets with functional solutions that advance the clean energy transition worldwide. KORE Power's technology and manufacturing capabilities provide direct access to next generation battery cells, energy storage systems that scale to grid+, EV power & infrastructure, and intuitive asset management to unlock energy strategies across a myriad of applications. Explore more at korepower.com.
Music for Shift Key is by Adam Kromelow.
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