AI And The Energy Grid: Solving for AI's Power Needs

This episode delves into how the escalating power demands of artificial intelligence (AI) could potentially reshape global energy consumption.

1. AI's Huge Energy Demand: AI could increase global electricity demand significantly, posing challenges and opportunities for the energy sector.
2. Role of Renewables: While renewable energy sources are crucial, their intermittency requires the support of other energy sources like natural gas and nuclear power.
3. Investment Opportunities: The energy sector could see a revaluation due to its critical role in powering AI, with substantial investment potential.
4. Technological Impact on Energy: Technological advancements in AI are driving new demands and solutions in energy production and management.
5. Future Energy Landscape: The episode discusses how energy strategies are adapting to meet the growing needs of AI, emphasizing a balanced approach involving multiple energy sources.

1: Introduction

Overview of the episode's focus on AI's energy demands and its implications for global energy consumption. Briefly outlines the conversation's key topics. Oscar Polito: "The world remains abuzz over artificial intelligence, but rapid advancement and adoption of the technology is poised to drive a significant increase in power demand."

2: The Growing Demand

Discusses the computational power and energy required by large language models like GPT-4, highlighting exponential growth in energy consumption. Will Su: "AI generates millions of images a day. Just one image can consume as much energy as charging your phone."

3: Solutions and Strategies

Explores potential energy solutions to meet AI's demands, including renewables, nuclear power, and the strategic importance of energy efficiency in AI technologies. Will Su: "Renewables are by far the fastest growing source of power generation... but don't count nuclear out in this low carbon way to power AI going forward."

4: Investment Insights

Focuses on investment opportunities in the energy sector driven by AI's power needs, emphasizing the value of energy stocks and the impact of AI on energy companies. Will Su: "Energy is an undervalued sector because the market underappreciates both the volume and the duration for which the world needs oil and gas for the decades to come."

1. Explore Renewable Energy Investments: Consider investing in renewable energy sources which are pivotal in meeting AI's growing power needs.
2. Energy Efficiency in Tech: Invest in technology that improves energy efficiency to mitigate the high power consumption of AI.
3. Support Nuclear Power Initiatives: Understand the role of nuclear power in providing stable, low-carbon energy for AI operations.
4. Consider Energy Sector Stocks: Look into stocks of companies that are innovatively bridging the gap between AI technology and energy requirements.
5. Stay Informed on Energy Policies: Keep abreast of changes in energy policies that could affect investments in AI and energy sectors.

The world remains abuzz over artificial intelligence, but rapid advancement and adoption of the technology is poised to drive a significant increase in power demand, and this demand could redefine energy consumption as we know it. Today we ask the critical question: is the energy sector equipped for the AI power revolution?
Will Su, of BlackRock's Fundamental Equities team, is one of BlackRock’s leading voices on all things energy. Will walks us through the sector’s pivotal role in the build-out and future of AI and digs into the potential investment opportunities and challenges.

Sources: “Electricity Mix” Our world in energy, January 2024; “What is U.S. electricity generation by energy source?” Energy Information Administration, “OpenAI Presents GPT-3, a 175 Billion Parameters Language Model” Nvidia, 2020; GPT-4 Details Revealed, Patrick McGuinness, 2023; Data Centers Around The World, United States International Trade Commission 2021; “North America Data Center Trends H2 2023”, CBRE 2024; “Electric power sector CO2 emissions drop as generation mix shifts from coal to natural gas” EIA, 2021; “Electravision” JPMorgan, March 2024; “Fuel Mix” Ercot, March 2024; “Television, capturing America's attention at prime time and beyond” US bureau of Labor Statistics, September 2018.

This content is for informational purposes only and is not an offer or a solicitation. Reliance upon information in this material is at the sole discretion of the listener.

In the UK and non-European Economic Area countries this is issued by BlackRock Investment Management (UK) Limited who is authorized and regulated by the Financial Conduct Authority and in the European Economic Area this is issued by BlackRock (Netherlands) BV who is authorized and regulated by the Netherlands Authority. For full disclosures go to Blackrock.com/corporate/compliance/bid-disclosures

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Oscar Polito, Will Su

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Oscar Polito
The world remains abuzz over artificial intelligence, but rapid advancement and adoption of the technology is poised to drive a significant increase in power demand. And this demand could redefine energy consumption as we know it. We think there could be up to 1000 terawatt hours of incremental electricity demand for AI by 2030. In aggregate, you can see total Internet demand, including AI, make up six to 7% of global electricity demand by 2030. Today, we ask the critical question, is the energy sector equipped for the AI power revolution?

Welcome to the bid, where we break down what's happening in the markets and explore the forces changing the economy and finance. I'm Oscar Polito. Today I'm joined by Will sue from BlackRock's fundamental equities team. Will is one of BlackRock's leading voices on all things energy. He'll walk us through the sector's pivotal role in the build out and future of AI, as well as dig into the potential investment opportunities and challenges.

Will, thank you for joining us on the bid. Thank you, Oscar. Great to be here. So, Will, we've talked about artificial intelligence on the podcast a lot, and it seems like there's no limits to the growth of this technology except the fact that it consumes a lot of energy, and maybe that's the constraint. Tell us a little bit about why.

AI consumes so much power. So, Oscar, the simple answer to that extremely complicated question is that information processing is energy, and we are processing more information today than we've ever thought of, even from just a few years ago.

AI generates millions of images a day. And according to a recent study, just one image can consume as much energy as charging your phone. At its most fundamental level, computations are just moving electrons around a semiconductor chip. But when you multiply that very small electric current by trillions of calculations, the energy demand adds up very, very quickly. I think Rob Gosling mentioned this.

Will Su
The concept of AI is not really anything new. The MIT AI lab was started in the late 1950s, but we did have a breakthrough moment in 2017, when a team of researchers wrote a paper about the transformer, which then became the architecture for today's large language models, or LLMs.

Now, these models are being trained on trillions of parameters and tokens that make them high quality, high capacity, and able to contextualize the questions that they're being asked. And just to give you an idea of how big the computational power we're talking about is here, Chachi PT four was trained on about 70,000 zeta flops of compute power. That's 70 trillion, trillion operations per second, mind bending numbers. And as that number grows over time, that's why we're seeing this recent interest in meeting the power demand of AI.

Oscar Polito
Did you say Zeta flops? Because I'm going to need a glossary. I think as we talk more about artificial intelligence, it feels like the terminology is new to a lot of people. And when you talk about power and the quantity, help us understand, how much. Are we talking about on a global scale.

Will Su
So, as anyone who tried to model this out can tell you, it's very hard to have a lot of confidence for 1020 years down the road when you're looking at something with such exponential growth. That being said, we did build our own model, because, as they say, all models are wrong, but some are useful. So in building this model, it's helped us understand what the key variables are and maybe how the shape of that future power demand might look like. And the punchline is, we think there could be up to 1000 terawatt hours of incremental electricity demand for AI by 2030, and that will be about 3% of global electricity. And keep in mind that the Internet today already consumes two to 3% of global electricity for things like data centers, networking transmissions, and, increasingly, for blockchains.

In aggregate, you could see total Internet demand, including AI, make up six to 7% of global electricity demand by 2030. And how is the world going to manage that power demand? Because it's incremental on top of what is already the demand for power. Right? Right.

I think we can first dig a little bit into what is driving that AI demand.

There's really three roughly equal buckets in our 2030 outlook. One is for training. So that's the power that it takes to train these very large models. And again, just to give you an idea of the scale, in 2022, chatgpt three came out. It was trained on 175 billion parameters and 300 billion tokens.

And the amount of energy it took to train could power about 90,000 us homes for a year.

Now, you fast forward to 2023, when chat GPT four came out. That model was reportedly trained on 1.8 trillion parameters and 13 trillion tokens. And the energy it took to train that could power two and a half million us homes for a year. And these models are getting bigger by the day. And the good news there is, with each generation of semiconductors, each generation becomes about 50% more power efficient.

So it takes half the amount of power for one calculation. It's not enough to offset just how quickly the models are getting bigger. And then remember, more players are entering this game globally, not just in the US, but also in Europe and Asia. So you add it all together, and training really represents the bulk of the power growth that we see for AI in the coming few years. The second bucket for demand is something called querying.

So that's when consumers, businesses and other computers start to ask questions to these trained large language models. And in our model, we think you could see up to 30 billion AI queries per day by 2030. For comparison, today we make about 10 billion Internet searches per day. But you have to remember that not all queries are created equally. Right?

A text based query takes about the same amount of power as an Internet search. But a AI generated photo takes up to 30 times more power. And a 62nd AI generated video takes up to 7000 times more power than a text query. And video is big. It's 57% of all Internet traffic today.

So how the consumer adapts to AI video is really one of the key variables that will determine just how much energy we're going to require to power AI. And then the third bucket is really for data center operations, mainly for cooling, because when you're doing trillions of calculations per second, these chips run really hot. So, yes, 1000 terawatt hours by 2030. That is a big number. I think it's a challenging task to meet that demand, but not an impossible one.

Oscar Polito
Yeah, maybe you can expand there, because you shared a lot of numbers. You said there were trillions a couple times. The percentage increases that you cited, particularly when you talked about how we use artificial intelligence to query, was quite large. So, what role do renewables play in this energy demand? I'm thinking about things like wind and solar.

Are they the major component, or are there other sources of energy that we're going to rely on? So, renewables are by far the fastest growing source of power generation. In the last 20 years, they've gone from almost nothing to 13% of global power generation, and they will continue to grow at a very fast pace. Without a doubt, renewables are going to play a big part in powering AI, but also empowering this overall theme of electrification of our energy systems. Now, renewables has one really big drawback when it comes to powering AI, which is intermittency.

Will Su
Let's zoom into the ERCOT grid in Texas, which is the largest wind market and the second largest solar market in the US. So it has a lot of renewables, and if you just zoom in, on a typical day, the solar power tends to peak out between 08:00 a.m. and 07:00 p.m. when the sun's shining and the wind peaks. When the wind speeds are the highest, which is usually from midnight to 07:00 a.m.

when you wake up. But peak demand really happens in the hours of 08:00 p.m. to midnight. That's when people are at home, relaxing, watching tv, streaming, checking their social media. And you will see that during that period, natural gas demand really increases to meet that gap that can be met by wind and solar.

And this is probably a good time to talk about nuclear, which people don't think of a lot, but it's actually today, the largest source of carbon free power generation makes up about 9% of global power. But I think as governments around the world start to realize how much electricity growth there's going to be, there's starting to be a change in thinking. And in countries like South Korea, Japan, Italy, and here in the US, you're seeing regulators extending previously planned shutdowns of nuclear plans and even in some cases allowing them to restart after they've already been shut. So definitely don't count nuclear out in this low carbon way to power AI going forward. Right?

Oscar Polito
So it sounds like the demand is so significant that it is causing even some sources of energy that in the past it felt like were becoming less of a priority to reenter the focus. Ultimately, what you've said is there's a lot of different sources of energy that are going to help power the AI demand. You mentioned nuclear, gas, but also renewables. And if I could focus you on the US for just a second. Artificial intelligence is not just the US topic, but it is the part of the world where the build out is really gaining a lot of momentum.

And therefore, how is the US thinking about the power supply for artificial intelligence? We really should talk about one of the biggest unsung triumphs in the energy transition so far, which is the us power grid has decarbonized itself by a third over the last 20 years. And about 60% of that came in the form of cheap and abundant natural gas as a result of the shale revolution that allowed us to substitute out much more polluting coal. You saw coal share in the last 20 years drop from 50% to 16%, and natural gas went up from 19% of us power generation to 42. The other 40% came from renewables.

Will Su
So renewables again grew from almost nothing 20 years ago to 14% of the us power grid today. So there's already a really strong track record of partnerships between natural gas and renewables to combine and help us decarbonize. Now, when you think about AI and you think about data centers, the US has about one third of the total data center capacity in the world. And I'm very confident that share will grow over time because we have the leading technology companies that are leading this AI revolution. And then we are also blessed with abundant resources, both traditional and renewable.

If you look at a map of where these data centers are located in the US, you'll see that they're mostly in these big clusters that are located close to population centers. So almost half of all data centers in the US are in Virginia. They're almost all in this six square mile tiny area called Data center Alley near Arlington. There's other big clusters like Hillsboro near Portland, Oregon. There's also growing clusters around Ohio.

And you'll see a problem if you juxtapose that map onto one where the renewable resources are best in this country. The source of greatest solar radiation is in the southwest Us. So that's places like southern California, Nevada, New Mexico, and where the wind speeds are the highest are down the middle of the US in the windy corridor that goes from the Dakotas down to northern Texas.

They don't really overlap with where the data centers are located today and where the most growth is likely to happen in the coming years. And then, to make matters worse, this country is really falling behind in making long distance transmission investments. We're making one 8th the mileage of new transmission lines than we did ten years ago. And that's a result of a number of regulatory and economic challenges with interstate infrastructure. This is where natural gas is going to come in.

It's a proven, mature technology. It's much cleaner than coal, it plugs easily into different grids. So it shapes my view that I think at least half, if not more, of the incremental power for AI in the US will come from natural gas, and the balance will mostly be met by new renewable developments. Data center alley doesn't sound as glamorous as Silicon Valley, but it seems like it's also very important. Let's come back to your role as an investor.

Oscar Polito
You spend your day thinking about companies to invest in, and if you follow the markets over the last couple of years, it's been all about technology. But we're having a discussion about the energy space. And so presumably that means there's investment opportunities in the energy sector. Where are those? Absolutely.

Will Su
So, as a value minded income investor, I have thought for a long time that energy is an undervalued sector because the market underappreciates both the volume and the duration for which the world needs oil and gas for the decades to come. And I think this recent focus on how do we power AI just shines yet another spotlight on how power hungry our world really is. And over time, I think that will help the sector rerate higher. Now, aside from that, I think the energy sector actually might be one of the most underappreciated beneficiaries for all the technological gains that'll come with better generative AI. Some of the world's largest supercomputers are actually owned by large energy companies.

Why? Because they perform a number of very computationally intensive tasks. Things like asset optimization, algorithmic trading, 4d seismic imaging for new resource discoveries. And I'll give you one specific example, which is the industry is using more and more of what's called a digital twin. So this is like a virtual replica of a real world asset, something like a refinery or an offshore platform.

And it's just got so much data inside of it that you can do a lot of really interesting and exciting things. Things like predictive maintenance, fixing things before they break, things like stress, testing them for severe weather events, or identifying methane leaks, and reducing emissions that way. So I think there's more than one way to win with energy when it comes to the theme of AI that's greatly underappreciated by the market today. I think the other sector that deserves some airtime here is utilities. So utilities are a yield driven, high dividend paying sector that's been somewhat out of favor in the last few years in a rising rate environment.

But as the us grid goes from not having much growth for the last 20 years to needing to grow one or 2% per year going forward, there's a big opportunity for these utilities. It'll come after an initial period of heavy investments. Now, which utilities will win depends very strongly on what regulatory regime and what geography they operate in. And it's interesting just to hear you talk about energy and utilities. I'm reminded, we spoke to your colleague Kerry King, who reminded us that while it has been a very tech driven market in the last couple of years, there are opportunities that are starting to appear, and you're zooming in on the energy and utility sector as a function of artificial intelligence and power demand.

Oscar Polito
But for an investor who is looking at this space, what should they be considering as they think about investing? Today, the energy sector contributes about 10% of the s and p five hundred's net income. But it makes up less than 4% of the index by market cap. And I think that valuation disconnect is driven by this persistent and, in my view, misplaced fear that this sector has no long term growth potential. Because I think as we sit here talking about breakthrough technologies like generative AI, it is important for us to remember that there's many different poles for incremental energy demand in this world, and an or nothing approach to energy just isn't going to work.

Will Su
And we have to find ways to help the traditional energy sources become cleaner and more responsibly sourced. At the same time, we scale up our renewables portfolio together, and only together will they be able to power the world forward in a pragmatic energy transition. Right. The world is evolving. Where the demand for energy will come from is changing.

Oscar Polito
With the number of statistics that you've been able to cite about the energy sector and artificial intelligence, where does this passion come from? How did you get interested in this space? Well, Oscar, I'm having flashbacks to 16 years ago when I started my career at a large investment bank in the equity research department, and my recruiter said, you can either join the Internet team or the energy team. I had no hesitation. I said, energy.

Will Su
It's supply demand driven. It's quantitative. The world needs this stuff. And you fast forward to today. And I think the Internet index has outperformed energy by about 1100%.

But if you gave me a time machine to go back, I will make the same choice all over again. This job has taken me to really exciting places all over the world, offshore Norway, the permian basin in Texas, the Bakken in north Dakota, or deep into the Amazon jungle in Guyana. That's a country that's going to go from the second poorest in South America to having the same gdp per capita as Brazil in less than a decade because of their resource development. So it's been a really thrilling ride so far, and I look forward to more of what's to come. Well, we're glad you made that decision 16 years ago and that you would make it again if you went back in time.

Oscar Polito
Thanks for sharing all this insight on the energy sector, on artificial intelligence, and thank you for doing it here on the bid. Thank you, Oscar. Thanks for listening to this episode of the bid. If you've enjoyed this episode, check out our episode with Rob Goldstein and Lance Bronstein, where they discuss AI through a COO lens and what business leaders are considering as AI is advancing. This content is for informational purposes only and is not an offer or a solicitation reliance upon information in this material is at the sole discretion of the listener.

In the UK and non european economic Area countries, this is authorized and regulated by the Financial Conduct Authority. In the European Economic Area, this is authorized and regulated by the Netherlands Authority for the financial markets. For full disclosures go to blackrock.com. corporate compliance bid disclosures.