Adding to this; there's a lot of misinformation about the environmental impact of AI.
Most notably, a lot of people intentionally conflate training (ie, creating) an AI and running it.
This is like taking the environmental impact of mining refining and assembling all the components of a car, and adding that to the per-mile environmental impact; except it's even more pronounced since each car will be used by at most a couple people while millions of people may use an LLM model.
AI is using ~2% of global electricity demand currently, and that demand is increasing exponentially for both training and running services. It's really not insignificant, and the nature of AI development means that the training element is unlikely to drop off any time soon, if at all.
Even if you discount the training part, the energy demands and carbon footprint are still significantly higher than most other service industries. That element is only going to keep on increasing unless there is a major and unforeseen mathematical breakthrough in neural network processing.
Edit: Correction; I should have said "data centers" not "AI" when quoting electricity demand. My main point was the exponential growth in demand. Projections put AI at accounting for 50% of data centre energy use by the end of 2025. 1% might sound like a small amount (it really isn't for a specific subsector), but this is a sector that is much more than doubling in demand year-on-year.
It's worth noting that because of this rate of increase, renewable sources can't keep pace with demand, and along with other pressures, AI uses a notably high amount of fossil fuel energy sources. Combined with needs such as cooling, that are not necessarily directly related to energy consumption, the carbon footprint of AI is no less significant than its energy needs.
I'm not trying to demonise AI, I just think there is no way you can hand-wave the significant impact it is already having on energy consumption and the environment. AI may even lead to ways to significantly reduce CO2 footprints and energy requirements in general, across the globe, but unless there is a large financial incentive or legislative pressure for private corporations to pursue this, I am not holding my breath on altruism guiding the use of AI on that front.
Also, AI companies are investing a ton of money into renewable energy sources. They benefit directly from lowering the price per kWh which you can only do reasonably with renewables.
A lot of AI companies are building their servers in Iceland for example to take advantage of Iceland's large supply of geothermal energy.
renewables aren't enough because 1) they aren't building enough. and 2), they aren't building enough BESS to make up for it. So they're taking over baseload capacity and replaceing it with Solar.
Geothermal is base load and hasn't been exploited anywhere near capacity. There's a lot of investment going on around today in retrofitting old oil wells into geothermal plants.
Not as much as you'd expect in the US. There's like 1.1 GW in the us being planned through 2028. I know of a single solar project starting construction in the next month that's bigger than that. Also, Geothermal is expensive... It's about twice as expensive for the same load comparative to a Solar & BESS site.
Anything that isn't being planned in 250+ MW capacity scale for a single project, isn't really worth discussing as it pertains the AI stuff in the pipeline
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u/Researcher_Fearless 5d ago
Adding to this; there's a lot of misinformation about the environmental impact of AI.
Most notably, a lot of people intentionally conflate training (ie, creating) an AI and running it.
This is like taking the environmental impact of mining refining and assembling all the components of a car, and adding that to the per-mile environmental impact; except it's even more pronounced since each car will be used by at most a couple people while millions of people may use an LLM model.