Sign In or Create an Account.

By continuing, you agree to the Terms of Service and acknowledge our Privacy Policy

Technology

What Does OpenAI’s New Breakthrough Mean for Energy Consumption?

Why the new “reasoning” models might gobble up more electricity — at least in the short term

A robot with a smokestack coming out of its head.
Heatmap Illustration/Getty Images

What happens when artificial intelligence takes some time to think?

The newest set of models from OpenAI, o1-mini and o1-preview, exhibit more “reasoning” than existing large language models and associated interfaces, which spit out answers to prompts almost instantaneously.

Instead, the new model will sometimes “think” for as long as a minute or two. “Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes,” OpenAI announced in a blog post last week. The company said these models perform better than their existing ones on some tasks, especially related to math and science. “This is a significant advancement and represents a new level of AI capability,” the company said.

But is it also a significant advancement in energy usage?

In the short run at least, almost certainly, as spending more time “thinking” and generating more text will require more computing power. As Erik Johannes Husom, a researcher at SINTEF Digital, a Norwegian research organization, told me, “It looks like we’re going to get another acceleration of generative AI’s carbon footprint.”

Discussion of energy use and large language models has been dominated by the gargantuan requirements for “training,” essentially running a massive set of equations through a corpus of text from the internet. This requires hardware on the scale of tens of thousands of graphical processing units and an estimated 50 gigawatt-hours of electricity to run.

Training GPT-4 cost “more than” $100 million OpenAI chief executive Sam Altman has said; the next generation models will likely cost around $1 billion, according to Anthropic chief executive Dario Amodei, a figure that might balloon to $100 billion for further generation models, according to Oracle founder Larry Ellison.

While a huge portion of these costs are hardware, the energy consumption is considerable as well. (Meta reported that when training its Llama 3 models, power would sometimes fluctuate by “tens of megawatts,” enough to power thousands of homes). It’s no wonder that OpenAI’s chief executive Sam Altman has put hundreds of millions of dollars into a fusion company.

But the models are not simply trained, they're used out in the world, generating outputs (think of what ChatGPT spits back at you). This process tends to be comparable to other common activities like streaming Netflix or using a lightbulb. This can be done with different hardware and the process is more distributed and less energy intensive.

As large language models are being developed, most computational power — and therefore most electricity — is used on training, Charlie Snell, a PhD student at University of California at Berkeley who studies artificial intelligence, told me. “For a long time training was the dominant term in computing because people weren’t using models much.” But as these models become more popular, that balance could shift.

“There will be a tipping point depending on the user load, when the total energy consumed by the inference requests is larger than the training,” said Jovan Stojkovic, a graduate student at the University of Illinois who has written about optimizing inference in large language models.

And these new reasoning models could bring that tipping point forward because of how computationally intensive they are.

“The more output a model produces, the more computations it has performed. So, long chain-of-thoughts leads to more energy consumption,” Husom of SINTEF Digital told me.

OpenAI staffers have been downright enthusiastic about the possibilities of having more time to think, seeing it as another breakthrough in artificial intelligence that could lead to subsequent breakthroughs on a range of scientific and mathematical problems. “o1 thinks for seconds, but we aim for future versions to think for hours, days, even weeks. Inference costs will be higher, but what cost would you pay for a new cancer drug? For breakthrough batteries? For a proof of the Riemann Hypothesis? AI can be more than chatbots,” OpenAI researcher Noam Brown tweeted.

But those “hours, days, even weeks” will mean more computation and “there is no doubt that the increased performance requires a lot of computation,” Husom said, along with more carbon emissions.

But Snell told me that might not be the end of the story. It’s possible that over the long term, the overall computing demands for constructing and operating large language models will remain fixed or possibly even decline.

While “the default is that as capabilities increase, demand will increase and there will be more inference,” Snell told me, “maybe we can squeeze reasoning capability into a small model ... Maybe we spend more on inference but it’s a much smaller model.”

OpenAI hints at this possibility, describing their o1-mini as “a smaller model optimized for STEM reasoning,” in contrast to other, larger models that “are pre-trained on vast datasets” and “have broad world knowledge,” which can make them “expensive and slow for real-world applications.” OpenAI is suggesting that a model can know less but think more and deliver comparable or better results to larger models — which might mean more efficient and less energy hungry large language models.

In short, thinking might use less brain power than remembering, even if you think for a very long time.

Blue

You’re out of free articles.

Subscribe today to experience Heatmap’s expert analysis 
of climate change, clean energy, and sustainability.
To continue reading
Create a free account or sign in to unlock more free articles.
or
Please enter an email address
By continuing, you agree to the Terms of Service and acknowledge our Privacy Policy
Hotspots

Fox News Goes After a Solar Farm

And more of this week’s top renewable energy fights across the country.

Map of U.S. renewable energy.
Heatmap Illustration

1. Otsego County, Michigan – The Mitten State is proving just how hard it can be to build a solar project in wooded areas. Especially once Fox News gets involved.

  • Last week, the Michigan Department of Natural Resources said it wanted to lease more than 400 acres of undeveloped state-owned forestland for part of a much larger RWE Clean Energy solar project near the northern Michigan town of Gaylord.
  • Officials said they were approached by the company about the land. But the news sparked an immediate outcry, as state elected Republicans – and some Democrats – demanded to know why a forest would be cleared for ‘green’ energy. Some called for government firings.
  • Then came the national news coverage. On Friday, Fox News hosted a full four-minute segment focused on this one solar farm featuring iconoclastic activist Michael Shellenberger.
  • A few days later, RWE told the media it would not develop the project on state lands.
  • “[D]uring the development process, we conducted outreach to all landowners adjacent to the project location, including the Michigan Department of Natural Resources,” the company said in a statement to the Petoskey News-Review, adding it instead decided to move forward with leasing property from two private landowners.

2. Atlantic County, New Jersey – Opponents of offshore wind in Atlantic City are trying to undo an ordinance allowing construction of transmission cables that would connect the Atlantic Shores offshore wind project to the grid.

Keep reading...Show less
Policy Watch

How to Solve a Problem Like a Wind Ban

And more of this week’s top policy news around renewables.

Trump.
Heatmap Illustration/Getty Images

1. Trump’s Big Promise – Our nation’s incoming president is now saying he’ll ban all wind projects on Day 1, an expansion of his previous promise to stop only offshore wind.

  • “They litter our country like paper, like dropping garbage in a field,” Trump said at a press conference Tuesday. “We’re going to try and have a policy where no windmills are built.”
  • Is this possible? It would be quite tricky, as the president only has control over the usage of federal lands and waters. While offshore wind falls entirely under the president’s purview, many onshore wind projects themselves fall entirely on state lands.
  • This is where the whole “wind kills birds” argument becomes important. Nearly all wind projects have at least some federal nexus because of wildlife protection laws, such as the Endangered Species Act and Migratory Bird Treaty Act.
  • Then there are the cables connecting these projects to the grid and interstate transmission projects that may require approval from the Federal Energy Regulatory Commission.
  • I’m personally doubtful he will actually stop all wind in the U.S., though I do think offshore wind in its entirety is at risk (which I’ve written about). Trump has a habit of conflating things, and in classic fashion, he only spoke at the press conference about offshore wind projects. I think he was only referring to offshore wind, though I’m willing to eat my words.

2. The Big Nuclear Lawsuit – Texas and Utah are suing to kill the Nuclear Regulatory Commission’s authority to license small modular reactors.

Keep reading...Show less
Q&A

Are Anti-Renewables Activists Going Unchallenged?

A conversation with J. Timmons Roberts, executive director of Brown University’s Climate Social Science Network


J. Timmons Roberts
Heatmap Illustration

This week’s interview is with Brown University professor J. Timmons Roberts. Those of you familiar with the fight over offshore wind may not know Roberts by name, but you’re definitely familiar with his work: He and his students have spearheaded some of the most impactful research conducted on anti-offshore wind opposition networks. This work is a must-read for anyone who wants to best understand how the anti-renewables movement functions and why it may be difficult to stop it from winning out.

So with Trump 2.0 on the verge of banning offshore wind outright, I decided to ask Roberts what he thinks developers should be paying attention to at this moment. The following interview has been lightly edited for clarity.

Keep reading...Show less