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“AI expends a lot of energy being polite, especially if the user is polite, saying ‘please’ and ‘thank you,’”
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Dauner explained. “But this just makes their responses even longer, expending more energy to generate each word.”

For this reason, Dauner suggests users be more straightforward when communicating with AI models. Specify the length of the answer you want and limit it to one or two sentences, or say you don’t need an explanation at all.

Most important, Dauner’s study highlights that not all AI models are created equally, said Sasha Luccioni, the climate lead at AI company Hugging Face, in an email. Users looking to reduce their carbon footprint can be more intentional about which model they chose for which task.

“Task-specific models are often much smaller and more efficient, and just as good at any context-specific task,” Luccioni explained.
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If you are a software engineer who solves complex coding problems every day, an AI model suited for coding may be necessary. But for the average high school student who wants help with homework, relying on powerful AI tools is like using a nuclear-powered digital calculator.

Even within the same AI company, different model offerings can vary in their reasoning power, so research what capabilities best suit your needs, Dauner said.

When possible, Luccioni recommends going back to basic sources — online encyclopedias and phone calculators — to accomplish simple tasks.

Why it’s hard to measure AI’s environmental impact
Putting a number on the environmental impact of AI has proved challenging.

The study noted that energy consumption can vary based on the user’s proximity to local energy grids and the hardware used to run AI models.
That’s partly why the researchers chose to represent carbon emissions within a range, Dauner said.

Furthermore, many AI companies don’t share information about their energy consumption — or details like server size or optimization techniques that could help researchers estimate energy consumption, said Shaolei Ren, an associate professor of electrical and computer engineering at the University of California, Riverside who studies AI’s water consumption.

“You can’t really say AI consumes this much energy or water on average — that’s just not meaningful. We need to look at each individual model and then (examine what it uses) for each task,” Ren said.

One way AI companies could be more transparent is by disclosing the amount of carbon emissions associated with each prompt, Dauner suggested.

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“Generally, if people were more informed about the average
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(environmental) cost of generating a response, people would maybe start thinking, ‘Is it really necessary to turn myself into an action figure just because I’m bored?’ Or ‘do I have to tell ChatGPT jokes because I have nothing to do?’” Dauner said.

Additionally, as more companies push to add generative AI tools to their systems, people may not have much choice how or when they use the technology, Luccioni said.

“We don’t need generative AI in web search. Nobody asked for AI chatbots in (messaging apps) or on social media,” Luccioni said. “This race to stuff them into every single existing technology is truly infuriating, since it comes with real consequences to our planet.”
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With less available information about AI’s resource usage, consumers have less choice, Ren said, adding that regulatory pressures for more transparency are unlikely to the United States anytime soon. Instead, the best hope for more energy-efficient AI may lie in the cost efficacy of using less energy.

“Overall, I’m still positive about (the future). There are many software engineers working hard to improve resource efficiency,” Ren said. “Other industries consume a lot of energy too, but it’s not a reason to suggest AI’s environmental impact is not a problem. We should definitely pay attention.”

Sign up for CNN’s Life, But Greener newsletter. Our limited newsletter series guides you on how to minimize your personal role in the climate crisis — and reduce your eco-anxiety.

A nuclear fusion power plant prototype is already being built outside Boston. How long until unlimited clean energy is real?
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In an unassuming industrial park 30 miles outside Boston, engineers are building a futuristic machine to replicate the energy of the stars. If all goes to plan, it could be the key to producing virtually unlimited, clean electricity in the United States in about a decade.

The donut-shaped machine Commonwealth Fusion Systems is assembling to generate this energy is simultaneously the hottest and coldest place in the entire solar system, according to the scientists who are building it.

It is inside that extreme environment in the so-called tokamak that they smash atoms together in 100-million-degree plasma. The nuclear fusion reaction is surrounded by a magnetic field more than 400,000 times more powerful than the Earth’s and chilled with cryogenic gases close to absolute zero.

The fusion reaction — forcing two atoms to merge — is what creates the energy of the sun. It is the exact opposite of what the world knows now as “nuclear power” — a fission reaction that splits atoms.

Nuclear fusion has far greater energy potential, with none of the safety concerns around radioactive waste.

SPARC is the tokamak Commonwealth says could forever change how the world gets its energy, generating 10 million times more than coal or natural gas while producing no planet-warming pollution. Fuel for fusion is abundant, derived from deuterium, found in seawater, and tritium extracted from lithium. And unlike nuclear fission, there is no atomic waste involved.

The biggest hurdle is building a machine powerful and precise enough to harness the molten, hard-to-tame plasma, while also overcoming the net-energy issue – getting more energy out than you put into it.
“Basically, what everybody expects is when we build the next machine, we expect it to be a net-energy machine,” said Andrew Holland, CEO of the Fusion Industry Association, a trade group representing fusion companies around the globe. “The question is, how fast can you build that machine?”

Commonwealth’s timeline is audacious: With over $2 billion raised in private capital, its goal is to build the world’s first fusion-fueled power plant by the early 2030s in Virginia.

“It’s like a race with the planet,” said Brandon Sorbom, Commonwealth’s chief science officer. Commonwealth is racing to find a solution for global warming, Sorbom said, but it’s also trying to keep up with new power-hungry technologies like artificial intelligence. “This factory here is a 24/7 factory,” he said. “We’re acutely aware of it every minute of every hour of every day.”