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Unity and BrightBuilt factory-built homes share an important feature: They are airtight, part of what makes them 60% more efficient than a standard home. GO Logic says its homes are even more efficient, requiring very little energy to keep cool or warm.
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“Everybody wants to be able to build a house that’s going to take less to heat and cool,” said Unity director Mark Hertzler.

Home efficiency has other indirect benefits. The insulation and airtightness – aided by heat pumps and air exchangers – helps manage the movement of heat, air and moisture, which keeps fresh air circulating and mold growth at bay, according to Hertzler.
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Buntel, a spring allergy sufferer, said his Somerville home’s air exchange has made a noticeable difference in the amount of pollen in the house. And customers have remarked on how quiet their homes are, due to their insulation.

“I’m from New England, so I’ve always lived in drafty, uncomfortable, older houses,” Buntel said. “This is really amazing to me, how consistent it is throughout the year.”
Some panelized home customers are choosing to build not just to reduce their carbon footprint, but because of the looming threat of a warming planet, and the stronger storms it brings.

Burton DeWilde, a Unity homeowner based in Vermont, wanted to build a home that could withstand increasing climate impacts like severe flooding.

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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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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.

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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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