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Jamesruisk

01 Jul 2025 - 10:24 am

Jan Beutel was half-watching a live stream of Kleines Nesthorn, a mountain peak in the Swiss Alps, when he realized its cacophony of creaks and rumbles was getting louder. He dropped his work, turned up the sound and found himself unable to look away.
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“The whole screen exploded,” he said.

Beutel, a computer engineer specializing in mountain monitoring, had just witnessed a glacier collapse. On May 28, an avalanche of millions of tons of ice and rock barreled down the slope, burying Blatten, a centuries-old village nestled in the valley below.

Local authorities had already evacuated the village after parts of the mountain had crumbled onto the glacier; a 64-year old man believed to have stayed remains missing.

But no one expected an event of this magnitude.

Successive rock avalanches onto the glacier increased the pressure on the ice, causing it to melt faster and the glacier to accelerate, eventually destabilizing it and pushing it from its bed. The collapse was sudden, violent and catastrophic. “This one just left no moment to catch a breath,” Beutel said.
The underlying causes will take time to unravel. A collapse of this magnitude would have been set in motion by geological factors going back decades at least, said Matthias Huss, a glaciologist at the Swiss university ETH Zurich.

But it’s “likely climate change is involved,” he said, as warming temperatures melt the ice that holds mountains together. It’s a problem affecting mountains across the planet.

People have long been fascinated with mountains for their dramatic beauty. Some make their homes beneath them — around 1 billion live in mountain communities — others are drawn by adventure, the challenge of conquering peaks.

These majestic landscapes have always been dangerous, but as the world warms, they are becoming much more unpredictable and much deadlier.

“We do not fully understand the hazard at the moment, nor how the dangers are changing with climate change,” said David Petley, an Earth scientist at the University of Hull in England.

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01 Jul 2025 - 07:19 am

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01 Jul 2025 - 04:59 am

“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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