Save The Planet
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Laughs in total recall
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I'm really OOTL when it comes to AI GHG impact. How is it any worse than crypto farms, or streaming services?
How do their outputs stack up to traditional emitters like Ag and industry? I need a measuring stick
How is it any worse than crypto farms, or streaming services?
These two things are so different.
Streaming services are extremely efficient; they tend to be encode-once and decode-on-user's-device. Video was for a long time considered a tough thing to serve, so engineers put tons of effort into making it efficient.
Crypto currency is literally designed to be as wasteful as possible while still being feasible. "Proof-of-work" (how Bitcoin and many other currencies operate) literally means that crypto mining algorithms must waste as much computation as they can get away with doing pointless operations just to say they tried. It's an abomination.
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Maybe you should stop smelling text and try reading it instead.
Running an LLM in deployment can be done locally on one's machine, on a single GPU, and in this case is like playing a video game for under a minute. OpenAI models are larger than by a factor of 10 or more, so it's maybe like playing a video game for 15 minutes (obviously varies based on the response to the query.)
It makes sense to measure deployment usage marginally based on its queries for the same reason it makes sense to measure the environmental impact of a car in terms of hours or miles driven. There's no natural way to do this for training though. You could divide training by the number of queries, to amortize it across its actual usage, which would make it seem significantly cheaper, but it comes with the unintuitive property that this amortization weight goes down as more queries are made, so it's unclear exactly how much of the cost of training should be assigned to a given query. It might make more sense to talk in terms of expected number of total queries during the lifetime deployment of a model.
You're way overcomplicating how it could be done. The argument is that training takes more energy:
Typically if you have a single cost associated with a service, then you amortize that cost over the life of the service: so you take the total energy consumption of training and divide it by the total number of user-hours spent doing inference, and compare that to the cost of a single user running inference for an hour (which they can estimate by the number of user-hours in an hour divided by their global inference energy consumption for that hour).
If these are "apples to orange" comparisons, then why do people defending AI usage (and you) keep making the comparison?
But even if it was true that training is significantly more expensive that inference, or that they're inherently incomparable, that doesn't actually change the underlying observation that inference is still quite energy intensive, and the implicit value statement that the energy spent isn't worth the affect on society
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I'm not really saying that the curve itself is changing (sorry, I was really not clear), only that those other variables reduce actual energy demand later in the day because of the efficiency gains and thermal banking that happens during the peak energy production. The overproduction during max solar hours is still a problem. Even if the utility doesn't have a way of banking the extra supply, individual customers can do it themselves at a smaller scale, even if just by over-cooling their homes to reduce their demand after sundown.
Overall, the problem of the duck curve isn't as much about maxing out the grid, it's about the utility not having instantaneous power availability when the sun suddenly goes down. For people like me who work from home and have the flexibility to keep my home cool enough to need less cooling in the evening, having solar power means I can take advantage of that free energy and bank it to reduce my demand in the evening.
I get what you were saying now, but having solar would absolutely reduce my demand during peak hours.
It's a neat idea to over-cool in order to reduce consumption later on!
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I am trying to understand what Google's motivation for this even is. Surely it is not profitable to be replacing their existing, highly lucrative product with an inferior alternative that eats up way more power?
To make search more lucrative, they've enshitified it and went too far, but for a short time there were great quarterly resukts. Now they're slowly losing users. So they try AI to fix it up.
It's also a signal to the shareholders that they're implementing the latest buzzword, plus they're all worried AI will take off and they've missed that train.
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And when it did it also altered the results, making them worse, because it was trying to satisfy "fuck" as part of your search.
wrote on last edited by [email protected]If you can't search for "fuck," you can't search for "fuck google."
With apologies to Lenny Bruce.
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When I’m told there’s power issues and to conserve power I drop my AC to 60 and leave all my lights on. Only way for them to fix the grid is to break it.
Literally rolling coal to own the cons
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I don’t disagree with you but most of the energy that people complain about AI using is used to train the models, not use them. Once they are trained it is fast to get what you need out of it, but making the next version takes a long time.
This is a specious argument.
Once a model has been trained once they don't just stop training. They refine and/or start training new models. Showing demand for these models is what has encouraged construction on 100s of new datacenters.
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Also they can build nuclear power generators for the data centers but never for the residential power grid.
There's no money in selling residential energy.
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I am trying to understand what Google's motivation for this even is. Surely it is not profitable to be replacing their existing, highly lucrative product with an inferior alternative that eats up way more power?
They don't want to direct you to the thing you're searching for anymore because that means you're off their site quickly. Instead they want to provide themselves whatever it is you were searching for, so you will stay on their site and generate ad money.
They don't care if their results are bad, because that just means you'll stick around longer, looking for an answer. -
️ Immediate to Short-Term (Days to Centuries)- Hours to weeks: Power grids fail; nuclear reactors melt down without maintenance[11].
- Months to decades: Urban areas flood as drainage systems fail; buildings decay from weather and plant growth[6][11].
- 100–300 years: Steel structures collapse; concrete buildings crumble[5][7]. Most cities become overgrown forests[6].
Medium-Term (Thousands of Years)
- 1,000 years: Visible surface structures (e.g., roads, monuments) are buried or eroded. Plastics fragment but persist chemically[5][7].
- 10,000–250,000 years: Nuclear isotopes (e.g., plutonium-239) remain detectable in sediments and ice cores[7]. Mining tunnels fill with sediment but leave identifiable "industrial fossils"[7].
- 500,000 years: Microplastics and polymer layers in ocean sediments endure[5][10].
Long-Term (Millions of Years)
- 1–7 million years: Fossils of humans and domesticated animals persist. Geological strata show elevated carbon levels and mass extinction markers[4][8]. Deep mines and landfills remain as distinct layers[7][10].
- 50–100 million years: Continental drift subducts surface evidence; satellites decay or drift into space[3][10]. Only deep geological traces (e.g., mine shafts, isotope ratios) might endure[3][10].
- 250 million years: Next predicted mass extinction eradicates all mammals, including any remaining human traces[9].
Near-Permanent Traces
- Space artifacts: Lunar landers, Mars rovers, and Voyager probes persist for billions of years[3][10].
- Radio signals: Human broadcasts travel through space indefinitely at light speed[5].
Key Factors
- Detection likelihood: Aliens or future species could find traces for 100+ million years via deep geological analysis or space exploration[5][10].
- Total erasure: Requires Earth's destruction (e.g., solar expansion in 5 billion years)[10].
Citations:
[1] Human extinction https://en.wikipedia.org/wiki/Human_extinction
[2] What If Humans Suddenly Went Extinct? https://www.youtube.com/watch?v=yuOKTZISXhc
[3] How long would it take for all traces of humans to be gone? https://www.reddit.com/r/answers/comments/1azu120/how_long_would_it_take_for_all_traces_of_humans/
[4] What would happen to Earth if humans went extinct? https://www.livescience.com/earth-without-people.html
[5] How long before all human traces are wiped out? https://www.newscientist.com/lastword/2215950-how-long-before-all-human-traces-are-wiped-out/
[6] Vanishing Act: What Earth Will Look Like 100 Years After Humans Disappear - Brilliantio https://brilliantio.com/if-people-dissapeared-what-will-happen-to-earth-in-100-years/
[7] If humans became extinct, how long would it take for all ... https://www.sciencefocus.com/science/if-humans-became-extinct-how-long-would-it-take-for-all-traces-of-us-to-vanish
[8] Nature will need up to five million years to fill the gaps caused by man-made mass extinctions, study finds https://www.independent.co.uk/climate-change/news/mass-extinctions-five-million-years-nature-mammals-crisis-animal-plants-pnas-aarhus-a8585066.html
[9] Humans Will Go Extinct on Earth in 250 Million Years; Mass Extinction Will Occur Sooner if Burning Fossil Fuels Continues [Study] https://www.sciencetimes.com/articles/49951/20240430/humans-will-go-extinct-earth-250-million-years-mass-extinction.htm
[10] How long would it take for all evidence of humanity to be ... https://worldbuilding.stackexchange.com/questions/153618/how-long-would-it-take-for-all-evidence-of-humanity-to-be-erased-from-earth
[11] What Would Happen If Every Human On Earth Just Disappeared? https://www.scienceabc.com/humans/life-like-humans-suddenly-disappeared.htmlStephen Baxter over here. I'm going back to bed, it won't change anything...
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You can also use alternatives like startpage and ecosia which use google results, I believe.
Both of which are probably training their own AI as middle men or stealing your search terms to tell Walmart what type of peanut butter you're most likely to buy if they could lock it up on a plastic covered shelve.
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Worse is Google that insists on shoving a terrible AI-based result in your face every time you do a search, with no way to turn it off.
I'm not telling these systems to generate images of cow-like girls, but I'm getting AI shoved in my face all the time whether I want it or not. (I don't).
Firefox has a plugin that blocks the AI results. It works pretty well most of the time, but it occasionally has hiccups when Google updates stuff or something.
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How is it any worse than crypto farms, or streaming services?
These two things are so different.
Streaming services are extremely efficient; they tend to be encode-once and decode-on-user's-device. Video was for a long time considered a tough thing to serve, so engineers put tons of effort into making it efficient.
Crypto currency is literally designed to be as wasteful as possible while still being feasible. "Proof-of-work" (how Bitcoin and many other currencies operate) literally means that crypto mining algorithms must waste as much computation as they can get away with doing pointless operations just to say they tried. It's an abomination.
I legit don't know much about tech, and it ts showing. I didn't know streaming was so efficient.
What I. Trying to get at (I still have to read that article in the parent comment) is that how is AI any worse than crypto? As far as I can tell crypto impact, while bad, was relatively minor and it drastically decreased in popularity; it's kind of logical AI does the same, unless it's impact is way higher.
Meanwhile we have cargo ships burning bunker crude .
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Let's not forget billionaires in this consideration.
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I watch big state and national grid loads (for fun) and I see two distinct peaks: 7-8AM when everyone goes to work, and then around 5-7 PM when people commute home and heat up dinner.
Otherwise it's a linear diagonal curve coinciding with temperatures.
I personally try to keep my own energy usage a completely flat line so I can benefit from baseline load generator plants like nuclear (located not that far away).
I personally try to keep my own energy usage a completely flat line so I can benefit from baseline load generator plants like nuclear (located not that far away).
If you consume energy during peak hours you are a peak load consumer. Consuming in other hours doesn't change this fact.
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I watch big state and national grid loads (for fun) and I see two distinct peaks: 7-8AM when everyone goes to work, and then around 5-7 PM when people commute home and heat up dinner.
Otherwise it's a linear diagonal curve coinciding with temperatures.
I personally try to keep my own energy usage a completely flat line so I can benefit from baseline load generator plants like nuclear (located not that far away).
Your personal energy use pattern does not determine where you are drawing your power from, wtf logic is this?
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I legit don't know much about tech, and it ts showing. I didn't know streaming was so efficient.
What I. Trying to get at (I still have to read that article in the parent comment) is that how is AI any worse than crypto? As far as I can tell crypto impact, while bad, was relatively minor and it drastically decreased in popularity; it's kind of logical AI does the same, unless it's impact is way higher.
Meanwhile we have cargo ships burning bunker crude .
If you are expecting AI to not have much impact and turn out to be a bubble, then I guess there isn't much reason to believe it it will have much environmental impact. If you expect AI to not be a fad, then yeah it could have big environmental consequences if we can't find renewable power and coolant. If AI is all it is hyped up to be, then it would dwarf the rest of humanity's power consumption down to a footnote. So it really depends on how bullish you are about AI, or at least how bullish you expect the market to be going forward.
Regarding proof-of-work crypto, well, bitcoin is currently at its all-time high in terms of value, exceeding USD$100k/BTC. So I'm not sure I exactly buy the idea that it's less popular, though perhaps people aren't reporting on it as much. If the power consumption of crypto has levelled off, which I don't know if it has, then it might be because it's expensive to build a mining rig and the yield goes down over time as more bitcoin is mined. (It's presumably true of other proof-of-work crypto, too, but as more BTC is mined, the marginal yield of mining more BTC decreases.)
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You're way overcomplicating how it could be done. The argument is that training takes more energy:
Typically if you have a single cost associated with a service, then you amortize that cost over the life of the service: so you take the total energy consumption of training and divide it by the total number of user-hours spent doing inference, and compare that to the cost of a single user running inference for an hour (which they can estimate by the number of user-hours in an hour divided by their global inference energy consumption for that hour).
If these are "apples to orange" comparisons, then why do people defending AI usage (and you) keep making the comparison?
But even if it was true that training is significantly more expensive that inference, or that they're inherently incomparable, that doesn't actually change the underlying observation that inference is still quite energy intensive, and the implicit value statement that the energy spent isn't worth the affect on society
That's a good point. I rescind my argument that training is necessarily more expensive than sum-of-all-deployment.
I still think people overestimate the power draw of AI though, because they're not dividing it by the overall usage of AI. If people started playing high-end video games at the same rate AI is being used, the power usage might be comparable, but it wouldn't mean that an individual playing a video game is suddenly worse for the environment than it was before. However, it doesn't really matter, since ultimately the environmental impact depends only on the total amount of power (and coolant) used, and where that power comes from (could be coal, could be nuclear, could be hydro).
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If you are expecting AI to not have much impact and turn out to be a bubble, then I guess there isn't much reason to believe it it will have much environmental impact. If you expect AI to not be a fad, then yeah it could have big environmental consequences if we can't find renewable power and coolant. If AI is all it is hyped up to be, then it would dwarf the rest of humanity's power consumption down to a footnote. So it really depends on how bullish you are about AI, or at least how bullish you expect the market to be going forward.
Regarding proof-of-work crypto, well, bitcoin is currently at its all-time high in terms of value, exceeding USD$100k/BTC. So I'm not sure I exactly buy the idea that it's less popular, though perhaps people aren't reporting on it as much. If the power consumption of crypto has levelled off, which I don't know if it has, then it might be because it's expensive to build a mining rig and the yield goes down over time as more bitcoin is mined. (It's presumably true of other proof-of-work crypto, too, but as more BTC is mined, the marginal yield of mining more BTC decreases.)
Honestly, all of this is really interesting. It's a whole side of humanity that I very much do NOT think about or follow. I previously spent the last decade much, much, too busy stomping through the forest, so I really didn't follow anything during that time. A new game or phone came out? sure, cool, I might look that up. When I finally emerged from the fens, sodden and fly-bitten, I was very much out of the loop, despite the algorithm trying to cram articles about NFTs, crypto etc., down my throat. I actually tend to avoid tech stuff because it's too much of a learning curve at this point. I get the fundamentals, but beyond that I don't dig in.
I agree with you on the bubble - it depends on the size. I guess my original take is how could it actually get bigger than it is? I just don't see how it can scale beyond begin in phones or used in basic data analysis/like another google. The AIs can definitely get more advanced, sure, but with that should come some sort of efficiency. We're also seemingly on the cusp of quantum computing, which I imagine would reduce power requirements.
Meanwhile (and not to detract from the environmental concerns AI could pose) we have very, very real and very, very large environmental concerns that need addressing. Millions of cubic metres of sulphur are sitting in stockpiles in northern Alberta, and threatening the Athabasca river. That's not even close to the top of the list of things we need to focus on before we can get out in front of the damage AI can cause.
We're in a real mess.
