12 ms·

Using ChatGPT is not bad for the environment

255 points by returningfory2 2y ago

iTokio 2y ago
> It is extremely bad to distract the climate movement with debates about inconsequential levels of emission This. So we should focus on optimizing transport, heating, energy and food.
mindcrash 2y ago
You are kidding right? OpenAI -- for now -- is planning to build 5 gigawatt data centers (yes, plural) to continue its quest towards AGI. -- see HN archives. Meanwhile they are also looking into private nuclear power for the same purpose. Any serious competitor will likely need to do the same. So there's a rational choice and tradeoff to make: Net zero or AGI. We can't have both.
devmor 2y ago
In the same way that leaving food out doesn’t create a cockroach infestation.
changoplatanero 2y ago
If you use chatgpt somehow saves you from making one trip to the doctor in your car it can offset the entire year worth of chatgpt usage in terms of co2 impact.
- yapyap 2y ago
  if your use of chatgpt saves you from a trip to the doctor I would be very concerned
  - ekianjo 2y ago
    Most doctor visits are for benign matters...
    - BobaFloutist 2y ago
      The point of the doctorate is for them to make that determination.
      - gertlex 2y ago
        More constructively, the middle ground of asking a doctor about some minor symptoms over async messaging or tele-appointments (whatever the term for those is), is probably always something to consider for the trivial stuff.
      - elevaet 2y ago
        My partner works in emergency. Someone came in with a blister on their finger yesterday. They had to see the patient and send them home with a bandaid. Not a good use of resources.
      - ekianjo 2y ago
        There is no need to nitpick obvious comments. If you have a running nose and fever in winter, it's 99.99% a cold and a doctor visit will do nothing to help you, yet millions of people waste doctors time for that
      - realusername 2y ago
        Yes and no, you really don't need a deep expertise to diagnose the very common illness. And that's where chatgpt is doing great.
  - kaonwarb 2y ago
    Early days, but not as crazy as it sounds: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2825395 https://jamanetwork.com/journals/jamanetworkopen/fullarticle... "The LLM alone scored 16 percentage points (95% CI, 2-30 percentage points; P = .03) higher than the conventional resources group."
    - _cenw 2y ago
      Would be much more interesting if this ranked based on severity of misdiagnosis. An LLM that is 50% better at diagnosing a common cold but missed sepsis 10% more often would not be an overall improvement.
  - dragonwriter 2y ago
    ChatGPT is probably adequate to provide a slightly more user-friendly but also slight-less-reliable replacement for a reliable consumer-oriented medical reference book or website for the task of determining whether self-care without seeing a doctor or seeing a doctor is appropriate for symptoms not obviously posing an immediate emergency.
- croes 2y ago
  If ChatGPT somehow makes you eat more burgers it could make it makes water consumption worse.
zdragnar 2y ago
The title does not match the content. A more appropriate title is "Emissions caused by chatgpt use are not significant in comparison to everything else." But, given that title, it becomes somewhat obvious that the article itself doesn't need to exist.
- jonas21 2y ago
  > given that title, it becomes somewhat obvious that the article itself doesn't need to exist. Why? I regularly hear people trying to argue that LLMs are an environmental distaster.
  - _ache_ 2y ago
    Because LLMs are an environmental disaster. It's not about any individual usage. It's the global technology that is yet to prove to be useful and that already have bad for the environment. Any new usage should be free of impact on the environment. (Note: The technology of LLM itself is not an environmental disaster, but how it is put in use currently isn't the way).
    - satvikpendem 2y ago
      > It's the global technology that is yet to prove to be useful Useful for whom, by what definition? I personally find it very useful for my day to day work, whether it be helping me write code, think through ideas, or otherwise.
      - _ache_ 2y ago
        I don't want to be rude but I don't think that your personal experience is of any interest. The only question is "are LLM relevant ?" And the only way to assert that they are is to get numbers (big or small) and to compare them to alternatives.
        satvikpendem 2y ago
        > I don't think that your personal experience is of any interest But you didn't specify what you meant by "useful," hence why I asked the question I did. So under such ambiguity, my assertion is absolutely a counterpoint to what you just said. I will ask again, useful for whom, by what definition?
hexage1814 2y ago
To me the "ChatGPT is destroying the environment "card always felt somewhat like bad faith arguing from the anti-AI crowd trying to find any excuse for being against AI. Like, the same people who complained about "using AI is destroying environment" seemed to have no issue with boarding a plane which would emit a bunch of CO2 so that they can have a vacation in Europe or the like. Selective environmentalism.
- minimaxir 2y ago
  It's less bad faith, more a meme that has become so prevalent that it's impossible to dispell as it's something too nuanced for social media. I've seen more than a few social media posts asking "do they really cut down a rainforest every time someone generates an AI image?"
  - rainonmoon 2y ago
    I mean we can go back and forth all day with credulous clowns on both sides. There are certainly plenty of misguided AI advocates who think what they're using is magic.
- noirbot 2y ago
  I mean, it's a literal net new expenditure of power and water. I also deeply doubt they have "no issue" with plane travel. You're just assuming the worst and most hypocritical position to someone, which seems deeply bad faith as well. It's literally true that most of the AI vendors and their data center partners are writing off energy and water conservation targets they'd had for the near future because of LLM money. That is actually bad in the short and likely long term, especially as people use LLMs for increasingly frivolous things. Is it really necessary to have an LLM essentially do a "I'm Feeling Lucky" Google Search for you at some multiple of that environmental cost? Because that's what most of my friends and coworkers use ChatGPT for. Very rarely are they using it to get anything more complex than just searching wikipedia or documentation you could have had bookmarked. A person has a choice of if they take a flight and if it's worth it for them. They have no power except for raising a complaint in public on if OpenAI or Google or whoever spends vast amounts of money and power to train some new model. If your bar is that no one is allowed to complain about a company burning energy unless they live a totally blameless life farming their own food without electricity then random companies will get to do any destructive act they want.
Kindra 2y ago
[dead]
DeepYogurt 2y ago
I mean.... doing most things are bad for the environment. Do less of everything that you don't need to.
maeil 2y ago
The section on training feels weak, and that's what the discussion is mainly about. Many companies are now trying to train models as big as GPT-4. OpenAI is training models that may well be even much larger than GPT-4 (o1 and o3). Framing it as a one-time cost doesn't seem accurate - it doesn't look like the big companies will stop training new ones any time soon, they'll keep doing it. So one model might only be used half a year. And many models may not end up used at all. This might stop at some point, but that's hypothetical.
- devmor 2y ago
  I am sure that’s intentional, because this article is the same thing we see from e/acc personalities any time the environmental impact is brought up. Deflection away from what actually uses power and pretending the entire system is just an API like anything else.
  - andymasley 2y ago
    I am to put it mildly not an e/acc and referenced being very worried about other risks from advanced AI in the article.
    - devmor 2y ago
      Then I would certainly be interested to know why you spent so much time making the same argument e/acc AI proponents make ad nauseam. As it stands, the majority of your article reads like a debate against a strawman that is criticizing something they don't understand, rather than a refutation of any real criticism of environmental impact from the generative AI industry. If your aim was to shut down bad faith criticism of AI from people who don't understand it, that's admirable and I'd understand the tone of the article, but certainly not the claim of the title.
      - andymasley 2y ago
        The point of the article WAS to debate someone criticizing something they don't understand. AI as a whole is using a lot of energy and we should think about the environmental impacts, but I pretty regularly meet people who think that every individual ChatGPT search is uniquely bad for the environment. I tried to make it as clear as possible that that's the issue I'm responding to, not all AI energy use.
getwiththeprog 2y ago
This is a great article for discussion. However articles like this must link to references. It is one thing to assert, another to prove. I do agree that heating/cooling, car and transport use, and diet play massive roles in climate change that should not be subsumed by other debates. The flip side to the authors argument is that LLMs are not only used by home users doing 20 searches a day. Governments and Mega-Corporations are chewing through GPU hours on god-knows-what. New nuclear and other power facilities are being proposed to power their use, this is not insignificant. Schneider Electric predicts 93 GW of energy spent on AI by 2028. https://www.powerelectronicsnews.com/schneider-electric-predicts-substantial-energy-consumption-for-ai-workloads-globally/ https://www.powerelectronicsnews.com/schneider-electric-pred...
- deleted 2y ago
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- jonas21 2y ago
  > However articles like this must link to references. There are links to sources for every piece of data in the article.
  - blharr 2y ago
    Where? One of the most crucial points "Training an AI model emits as much as 200 plane flights from New York to San Francisco" This seems to come from this blog https://icecat.com/blog/is-ai-truly-a-sustainable-choice/#:~:text=A%20recent%20study%20by%20the,emissions%20of%20an%20average%20car https://icecat.com/blog/is-ai-truly-a-sustainable-choice/#:~.... which refers to this article https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their-lifetimes/ https://www.technologyreview.com/2019/06/06/239031/training-... which is talking about models like *GPT-2, BERT, and ELMo* -- _5+ year old models_ at this point. The keystone statement is incredibly vague, and likely misleading. What is "an AI model"? From what I found, this is referring to GPT-2,
    - KTibow 2y ago
feverzsj 2y ago
Yeah, there are lots of things worse than LLMs. But, at least, they are useful and profitable.
blkhawk 2y ago
what does "water used by data center" even mean? Does it consume the water somehow? What does it turn into? Steam? So uploading a 1GB file boils away nearly 1 liter of water? Or is it turned into bits somehow in some kind of mass to energy conversion? I sorta doubt that. Also this means data centers would have cooling towers like some power stations. Are we talking about the cooling towers of power stations? I think at least that graph is complete non-sense. I will try and have chatGPT explain it to me.
- stonogo 2y ago
  Yes, datacenters have cooling towers. There are lots of good articles about this topic. A good starting point is "water usage effectiveness" (WUE) which is one way this is tracked.
  - blkhawk 2y ago
    The one near here just has heat exchanges. But even if all the others use evaporators then potential water usage is extremely misleading because its not like the water is consumed - its just temporarily unavailable. Also why doesn't uploading a 1GB file to my NAS boil a liter of water? are maybe all the switches and routers used between me and the datacenter water-cooled? I mean I can see such switches existing but I don't see them be the norm. Why doesn't the DSLAM on the Street outside emit steam. Is there maybe one bad switch somewhere that just spews steam? What I am saying is that at least that graph is without further explanation... bad.
    - dragonwriter 2y ago
      > The one near here just has heat exchanges. But even if all the others use evaporators then potential water usage is extremely misleading because its not like the water is consumed Water consumption in all contexts is mostly fresh water returned from immediately usable form to either evaporation or the ocean. It is not "extremely misleading", because when it returns to immediately usable form by, e.g., precipitation, that's when new water is considered to be made available. The normal definitions are internally consistent and useful.
yapyap 2y ago
Such a stupid post, I know people on HN don’t like absolute descriptors like that and sorry for that. Obviously the LLMs and ChatGPT don’t use the most energy when answering your question, they churn through insane amounts of water and energy when training them, so much so that big tech companies do not disclose and try to obscure those amounts as much as possible. You aren’t destroying the environment by using it RIGHT NOW, but you are telling the corresponding company that owns the LLM you use “there is interest in this product”, en masse. With these interest indicators they will plan for the future and plan for even more environmental destruction.
- jna_sh 2y ago
  Similar feelings about the repeated references to the apparently agreed consensus that individual action is pointless vs systematic change like switching to a renewable energy system. Jevons Paradox would like a word.
- simonw 2y ago
  Plenty of companies have revealed exactly how much energy and CO2 they have used training a model. Just off the top of my head, I've seen those numbers are available for Meta's Llama models, Microsoft's Phi series and DeepSeek's models - including their impressive DeepSeek v3 which trained for less than $6m in cost - a huge reduction compared to other similar models, and a useful illustration of how much more effect this stuff can get on the training side of things.
- monero-xmr 2y ago
  [flagged]
  - ben_w 2y ago
    > Charge the consumer of energy the requisite price. If you want to make them pay for some externality, great. > And it is elites only as poors don’t give a shit The poor people are also consumers; raising prices of energy for that group is a fantastic way to get kicked out of office even if you're an actual literal dictator. People are complex. The screeds you're objecting to are part of the political process to tell governments to do something, even if that something ends up being a mix of what you suggest plus subsidies for the poor, or something completely different, in any case to avoid being defenestrated
pixelesque 2y ago
Sort of off-topic, but it does make one think about usage of compute (and the backing energy / resources required for that)... i.e. it doesn't seem too much of an exaggeration to say that we might be getting closer and closer to a situation where LLMs (or any other ML inference) is being run so much for so many different reasons / requests, that the usage does become significant in the future. Similarly, going into detail on what the compute is being used for: i.e. no doubt there are situations currently going on where Person A uses a LLM to expand something like "make a long detailed report about our sales figures", which produces a 20 page report and delivers it to Person B. Person B then says "I haven't time to read all this, LLM please summarise it for me". So you'd basically have LLM inference compute being used as a very inefficient method of data/request transfer, with the sender expanding a short amount of information to deliver to the recipient, and then the said recipient using an LLM on the other side to reduce it back again to something more manage-able.
- lioeters 2y ago
  That sounds like the opposite of data compression (inflation?) where the data size is increased before sending, then on receiving it is compressed back to a smaller form.
  - WD-42 2y ago
    Lossy data inflation.
mossTechnician 2y ago
It's discomforting to me when people compare resource usage of ChatGPT, a computer, to the resource usage of a human being. I've seen charts like this before that compare resource usage of people to corporations, implying corporations are the bigger problem. The implication here seems to be the opposite, and that tone feels just a little eugenicist.
Liquix 2y ago
~90% of the plastic debris in the ocean comes from ten rivers [0]. eight are in china/SEA. millions and billions of single-use items are sitting in warehouses and on store shelves wrapped in plastic. even before the plastic is discarded, the factories these items are produced in dump metric tons of waste into the oceans/soil with little repercussion. point is, none of our "personal lifestyle decisions" - not eating meat, not mining bitcoin, not using chatgpt, not driving cars - are a drop in the bucket compared to standard practice overseas manufacturing. us privileged folks could "just boycott", "buy renewable", "vote with your wallet", etc, but sales will move to a less developed area and the pollution will continue. this is not to say that the environment isn't important - it's critically important. it's just to say that until corporations are forced to do things the right way, it's ludicrous to point fingers at each other and worry that what we do day-to-day is destroying the planet. [0] https://pubs.acs.org/doi/10.1021/acs.est.7b02368 https://pubs.acs.org/doi/10.1021/acs.est.7b02368
- saagarjha 2y ago
  That's definitely not true. Let's take Americans, for example, driving their cars to work. Americans are about 15% of the world's emissions, of which 25% or so is transportation, of which well over half is cars. So you not driving to work is making direct impact on 2-3% of the world's overall emissions. Likewise, your decisions on all the other things, if taken in aggregate, will have a significant impact on overall emissions.
  - jamilton 2y ago
    The amount of people who choose to not drive to work is significantly impacted by policy.
  - irishloop 2y ago
    Meat and dairy specifically accounts for around 14.5% of global greenhouse gas emissions, according to the UN’s Food and Agricultural Organization (FAO). If people collectively just ate a bit less meat and dairy, it would go a long way. Don't even have to be perfect. Just show a little bit of restraint.
yesbut 2y ago
This guy must work at Microsoft.
scottcha 2y ago
Yet we also see that hyperscale cloud emissions targets have been reversed due to AI investment, Datacenter growth is hitting grid capacity limits in many regions, and peaker plant and other non-renewable resources on the grid are being deployed more to handle this specific growth from AI. I think the author, by qualifying on "chatgpt" maybe can make the claims they are making but I don't believe the larger argument would hold for AI as a whole or when you convert the electricity use to emissions. I'm personally on the side that the ROI will probably work out in the long run but not by minimizing the potential impact and keeping the focus on how we can make this technology (currently in its infancy) more efficient. [edit wording]
- seanmcdirmid 2y ago
  Is that true though? Data centers can be placed anywhere in the USA, they could be placed near a bunch of hydro or wind farm resources in the western grid which has little coal anyways outside of one line from Utah to socal. The AI doesn’t have to be located anywhere near to where it is used since fiber is probably easier to run than a high voltage power line.
  - wmf 2y ago
    That was already done years ago and people are predicting that the grid will be maxed out soon.
    - seanmcdirmid 2y ago
      Build new data centers near sources of power, and grid capacity isn’t going to be a problem. Heck, American industry used to follow that (building garment factories on fast moving rivers before electricity was much of a thing, Boeing grew up in the northwest due to cheap aluminum helped out by hydro). Why is AI somehow different from an airplane?
      - wmf 2y ago
        They'll have to build new power generation and build the data centers next to it.
BenFranklin100 2y ago
Just build nuclear.
- namesbc 2y ago
  That doesn't solve the problem
  - jenadine 2y ago
    Indeed, it doesn't solve the problem that people will misinterpret data and spread misinformation to justify their bad feeling about AI with invalid arguments.
Al-Khwarizmi 2y ago
In my country there's a lot of institutional hype about green algorithms. I find the whole idea quite irrelevant (for the reasons explained in this post) but of course, it's a way to get funding for those of us who work in AI/NLP (we don't have much money for GPUs and can't do things like training big LLMs, so it's easy to pitch everything we do as "green", and then get funding because that's considered strategic and yadda yadda). It's funny, but sad, how no one calls the billshit because we would be sabotaging ourselves.
namesbc 2y ago
Data center emissions probably 662% higher than big tech claims. Can it keep up the ruse?: https://www.theguardian.com/technology/2024/sep/15/data-center-gas-emissions-tech https://www.theguardian.com/technology/2024/sep/15/data-cent...
simonw 2y ago
The absolute best thing I've read on this subject is this article here: https://about.bnef.com/blog/liebreich-generative-ai-the-power-and-the-glory/ https://about.bnef.com/blog/liebreich-generative-ai-the-powe... It talks at great length about data center trends relating to generative AI, from the perspective of someone who has been deeply involved in researching power usage and sustainability for two decades. I made my own notes on that piece here (for if you don't have a half hour to spend reading the original): https://simonwillison.net/2025/Jan/12/generative-ai-the-power-and-the-glory/ https://simonwillison.net/2025/Jan/12/generative-ai-the-powe...
- strogonoff 2y ago
  I find the following to be a great point regarding what we ought to consider when adapting our lifestyle to reduce negative environmental impact: > In deciding what to cut, we need to factor in both how much an activity is emitting and how useful and beneficial the activity is to our lives. The further example with a hospital emitting more than a cruise ship is a good illustration of the issue. Continuing this line of thought, when thinking about your use of an LLM like ChatGPT, you ought to weigh not merely its emissions and water usage, but also the larger picture as to how it benefits the human society. For example: Was this tech built with ethically sound methods[0]? What are its the foreseeable long-term effects on human flourishing? Does it cause a detriment to livelihoods of the many people while increasing the wealth gap with the tech elites? Does it negatively impact open information sharing (willingness to run self-hosted original content websites or communities open to public, or even the feasibility of doing so[1][2]), motivation and capability to learn, creativity? And so forth. [0] I’m not going to debate utilitarianism vs. deontology here, will just say that “the ends justify the means” does not strike me as a great principle to live by. [1] https://news.ycombinator.com/item?id=42486481 https://news.ycombinator.com/item?id=42486481 [2] https://news.ycombinator.com/item?id=42549624 https://news.ycombinator.com/item?id=42549624
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- OlivOnTech 2y ago
deleted 2y ago
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sirnicolaz 2y ago
What about training it?
deleted 2y ago
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ternnoburn 2y ago
"Other bad things exist" does not mean this thing isn't bad. Or absolutely could be that all these other things are huge energy wasters AND chat gpt is an energy waster. We have to stop thinking about problems so linearly -- it's not "solve only the worst one first", because we'll forever find reasons to not try and solve that one, and we'll throw up our hands. Like, we're well aware animal agriculture is a huge environmental impact. But getting everyone to go vegetarian before we start thinking about any other emissions source is a recipe for inaction. We're going to have to make progress, little by little, on all of these things.
- XorNot 2y ago
  Except that's not the point of this: the point is that humans have absolutely finite time to think about problems, and so the way you distract from a problem is by inventing a new more exciting one. LLMs are in the news cycle, so sending all the activists after LLMs sure does a good job ensuring they're not going after anything which would be more effective doesn't it? (setting aside my thoughts for the moment of the utility of the 'direct action' type activists who I think have been useless for a good long while now - there could not possibly be more 'awareness' of climate change).
  - ternnoburn 2y ago
    Then again, if you can stall a nascent polluter before it becomes entrenched, maybe that's the right time to intervene. Getting people to not eat meat is hard, we've been eating meat forever. Getting people to not use LLMs? That's where most of us were up until very recently.
    - XorNot 2y ago
      "Don't use LLMs" is just another variant of "don't use electricity". Reframe the problem like that and then realize that no one's going to do it: global electricity use is constantly increasing. Fortunately, global renewable energy use is also growing incredibly rapidly. Which problem seems more tractable? Because reality has already proven it: people will happily switch to clean electricity and keep using electricity. They won't voluntarily use less electricity unless they get some benefit from that - i.e. reduced expenditure, or just plain more stuff (i.e. my LED lights consume a fraction of the power of my previous halogens, but are brighter and I have more of them and also can change light color on a schedule).
titanomachy 2y ago
The major players in AI are collectively burning 1-2 gigawatts, day and night, on research and development of the next generation of LLMs. This is as much as my city of a million people. The impact is real, and focusing on inference cost per query kind of misses the point. Every person who uses these tools contributes to the demand and bears some of the responsibility. Similar to how I have responsibility for the carbon emissions of a flight, even if the plane would have flown without me. I'm saying this as someone who finds LLMs helpful, and uses them without feeling particularly guilty about it. But we should be honest about the costs.
- nharada 2y ago
  Agreed, I feel like the main response seems to be "Does Not!", but it's reasonable to accept that a thing you like has a cost. We all emit carbon every day to do things we don't 100% need, and we should just be willing to admit there's a cost and try and move towards paying them. Personally, I'm not tripping too hard about datacenter energy long term because it's very easy to make carbon free (unlike say ICE cars or aircraft). But it would be nice to see some efforts to incentivize green energy for those datacenters instead of just saying "whatever" and powering them with coal.
  - simonw 2y ago
    "But it would be nice to see some efforts to incentivize green energy for those datacenters instead of just saying "whatever" and powering them with coal." The major datacenter operators all have very aggressive targets for clean energy which they have been mostly sticking to. Google: https://sustainability.google/progress/energy/ https://sustainability.google/progress/energy/ AWS: https://sustainability.aboutamazon.com/products-services/aws-cloud https://sustainability.aboutamazon.com/products-services/aws... Azure: https://azure.microsoft.com/en-us/explore/global-infrastructure/sustainability https://azure.microsoft.com/en-us/explore/global-infrastruct...
01HNNWZ0MV43FF 2y ago
Enforce a global carbon tax, price it in, and tax the land
- LeonB 2y ago
  International tax agreements are crucial if any progress is to be made on preventing climate disaster. Which major parties support it? Who is even talking about it? It’s such an obviously needed mechanism, but hard to get anyone enthused about it. This group have some proposals on the topic — https://en.m.wikipedia.org/wiki/Association_for_the_Taxation_of_Financial_Transactions_and_for_Citizens%27_Action https://en.m.wikipedia.org/wiki/Association_for_the_Taxation...
ZYbCRq22HbJ2y7 2y ago
Comparing magnitudes does not prove the headline, poor analysis.
croes 2y ago
The use of ChatGPT doesn’t replace the others it comes on top of that. MS is missing its CO2 targets because of AI not because of burgers. The whole argument is, it’s not bad because other things are worse. We are racing towards the abyss but don’t worry AI only accelerates a little more.
pluc 2y ago
Using it, sure, now do operating it and building it.
folken 2y ago
"personal carbon footprint" is a term invented by BP and is the single hack that derailed the environment discussion by making people personally responsible and removing the actual polluters from the discussion.
- _cenw 2y ago
  The article could indeed be written by the same kind of people, given it glances over training cost as if AI companies aren't pushing datacenter power/gpu capacities to the limit to produce incrementally better models by brute force. It all falls apart as soon as you stop individualizing the numbers and add back in all of the supposedly non-recurring (but actually recurring because we can't stop ourselves from redoing it) cost.
- andymasley 2y ago
  I specifically mentioned in the article that I think it's mostly a waste of time to worry about your personal carbon footprint and you should aim for big systematic change instead, but because so many people seem to be worried about their personal chatgpt use I wanted to clarify that it doesn't use much energy anyway
gunian 2y ago
A lot of conversations regarding the environment feel so frustrating because they are either qualitative or use aggregate high level data or are like we'll be dead in 50 years (lol my personal favorite) Why not start capturing waste/energy data for all human made items like nutritional data on food? It won't add much overhead or stifle economies as people fear That way when I log in to use any online service or when I buy/drive a car or when I buy an item I can see how much energy was consumed and how much waste I produced exactly
lhl 2y ago
I published this as a comment as well, but it's probably worth nothing that the ChatGPT water/power numbers cited (the one that is most widely cited in these discussions) comes from an April 2023 paper (Li et al, arXiv:2304.03271) that estimates water/power usage based off of GPT-3 (175B dense model) numbers published from OpenAI's original GPT-3 2021 paper. From Section 3.3.2 Inference: > As a representative usage scenario for an LLM, we consider a conversation task, which typically includes a CPU-intensive prompt phase that processes the user’s input (a.k.a., prompt) and a memory-intensive token phase that produces outputs [37]. More specifically, we consider a medium-sized request, each with approximately ≤800 words of input and 150 – 300 words of output [37]. The official estimate shows that GPT-3 consumes an order of 0.4 kWh electricity to generate 100 pages of content (e.g., roughly 0.004 kWh per page) [18]. Thus, we consider 0.004 kWh as the per-request server energy consumption for our conversation task. The PUE, WUE, and EWIF are the same as those used for estimating the training water consumption. There is a slightly newer paper (Oct 2023) that directly measured power usage on a Llama 65B (on V100/A100 hardware) that showed a 14X better efficiency. [2] Ethan Mollick linked to it recently and got me curious since I've recently been running my own inference (performance) testing and it'd be easy enough to just calculate power usage. My results [3] on the latest stable vLLM from last week on a standard H100 node w/ Llama 3.3 70B FP8 was almost a 10X better token/joule than the 2023 V100/A100 testing, which seems about right to me. This is without fancy look-ahead, speculative decode, prefix caching taken into account, just raw token generation. This is 120X more efficient than the commonly cited "ChatGPT" numbers and 250X more efficient than the Llama-3-70B numbers cited in the latest version (v4, 2025-01-15) of that same paper. For those interested in a full analysis/table with all the citations (including my full testing results) see this o1 chat that calculated the relative efficiency differences and made a nice results table for me: https://chatgpt.com/share/678b55bb-336c-8012-97cc-b94f70919daa https://chatgpt.com/share/678b55bb-336c-8012-97cc-b94f70919d... (It's worth point out that that used 45s of TTC, which is a point that is not lost on me!) [1] https://arxiv.org/abs/2304.03271 https://arxiv.org/abs/2304.03271 [2] https://arxiv.org/abs/2310.03003 https://arxiv.org/abs/2310.03003 [3] https://gist.github.com/lhl/bf81a9c7dfc4244c974335e1605dcf22 https://gist.github.com/lhl/bf81a9c7dfc4244c974335e1605dcf22
palata 2y ago
> and it’s completely clear to me that one side is getting it entirely wrong and spreading misleading ideas What a great way to start an article. I get it as: "I am not open to listening to your arguments, and in fact if you disagree with me, I will assume that you are a moron". It reminds me of people saying "planes are not the problem: actually if you compare it to driving a car, it uses less energy per person and per km". Except that as soon as you take a passenger in your car, the car is better (why did you assume that the plane was full and the car almost empty?). And that you don't remotely drive as far with your car as you fly with a plane. Obviously planes are worse than cars. If you need to imagine people commuting by car to the other side of the continent to prove your point, maybe it's not valid? The fact is that the footprint of IT is increasing every year. And quite obviously, LLMs use more energy than "traditional" searches. Any new technology that makes us use more energy is bad for environment. Unless you don't understand how bad the situation is: we have largely missed the goal of keeping global warming to 1.5C (thinking that we could reach it is absurd at this point). To keep 2C, we need to reduce global emissions by 5% every year. That's a Covid crisis every year. Let's be honest, it probably won't happen. So we'll go higher than 2C, fine. At the other end of the spectrum, 4C means that a big stripe (where billions of people live) around the equator will become unlivable for human beings (similar to being on Mars: you need equipment just to survive outside). I guess I don't need to argue how bad that would be, and we are currently going there. ChatGPT is part of that effort, as a new technology that makes us increase our emissions instead of doing the opposite.
- ben_w 2y ago
  I take your general point, but: > Except that it doesn't work if you don't drive your car alone (if you assume the plane is full of passengers, why not assuming that the car is, as well?) These can be measured for averages. Lots of cars with one person in them, seldom cars fully packed; lots of planes fully packed, seldom (but it does happen) that the plane is almost empty. > we have largely missed the goal of keeping global warming to 1.5C (thinking that we could reach it is absurd at this point). Probably, yes; last year passed the threshold — it would be a pleasant *surprise* if that turned out to have been a fluke 14* years early. * 14 because it would take 14 years for the exponential — seen for the last 30 years — for PV to replace all forms of power consumption; not just electricity, everything. But even then we'd also need to make rapid simultaneous progress with non-energy CO2 sources like cattle and concrete. > around the equator will become unlivable for human beings (similar to being on Mars: you need equipment just to survive outside) In so far as your bracket, sure; but there's a huge gap in what equipment you would need. The comparison I often make is that Mars combines the moisture of the Sahara, the warmth of the Antarctic, the air pressure of the peak of Mount Everest, and the soil quality of a superfund cleanup site, before then revealing that it's actually worse on all counts.
thih9 2y ago
Perhaps off topic, what exactly does the “one way european flight” mean in the context of avoiding co2 emissions? I.e. what is the choice or scenario here?
dvorack101 2y ago
Number are wrong. Just trying on topic. Data centers and AI realty consumes a lot more resources that you article poses.
garyfirestorm 2y ago
Why did this get flagged?
- returningfory2 2y ago
  I emailed hn@ to try to find out, I’ve no idea why.
andymasley 2y ago
Hey all I wrote this post. To clear up a few points: I meant this post to tell individuals that worrying about the emissions they personally cause using ChatGPT is silly, not that AI more broadly isn't using a lot of energy. I can't really factor in how demand for ChatGPT is affecting the future of AI. If you don't want to use ChatGPT because you're worried about creating more demand, that's more legit, but worry about the emissions associated with individual searches right now on their own is a silly distraction. One criticism is that I didn't talk about training enough. I included a section on training in the emissions and water sections, but if there's more you think I should address or change I'm all ears. Please either share them in the comments on the post or here. I saw someone assumed I'm an e/acc. I'm very much not and am pretty worried about risks from advanced AI. Had hoped the link to an 80,000 Hours article might've been a clue there. Someone else assumed I work for Microsoft. I actually exclusively use Claude but wanted to write this for a general audience and way fewer people know about Claude. I used ChatGPT for some research here that I could link people to just to show what it can do.
celticninja 2y ago
This used to be the stick they used to beat bitcoin with. I guess it's a good stick because you can hit any technology with it and you can conveniently forget all the terrible uses to which electricity is put.
originalvichy 2y ago
Where in the world are you getting the numbers for how much video streaming uses energy? I am quite sure that just as with LLMs, most of the energy goes into the initial encoding of the video, and nowadays any rational service encodes videos to several bitrates to avoid JIT transcoding. Networking can’t take that much energy, unless perhaps we are talking about purely wireless networking with cell towers?
- oneplane 2y ago
  LLM Inference is still quite power-hungry, Video decoding with hardware acceleration is much more efficient. But we can do some estimates, heck, we can even ask GPT for some numbers. Say you want to do 30 minutes of video (h265) or 30 minutes of LLM inferencing on a generic consumer device, ignoring the source of the model or source of encoded video, you get about 4x difference: Energy usage for 30 minutes of H.265 decoding: ~15–20 Wh. Energy usage for 30 minutes of Llama3 inference: ~40–60 Wh. This is optimised already, so a working hardware H.265 decoder is assumed, and for inferencing, something on the level of an RTX 3050, but can also be a TPU or NE. While not the most scientific comparison, it's perhaps good to know that video decoding is practically always local, and for streaming services it will use whatever is available and might even switch codecs (i.e. AV1, H.265, H.264 depending on what is available, and what licenses are used). And if you have older hardware, some codecs won't even exist in hardware, to the point where you start doing software decoding (very inefficient). AI inferencing is mostly remote (at least the heavy loads) in a datacenter because local availability of hardware is pretty hit and miss, models are pretty big and spinning one up every time you just wanted to ask something is not very user friendly. Because in a datacenter you tend to pay for amperage per rack, you spec your AI inferencing hardware to eat that power since you're not saving any money or hardware life when you don't use it. That means that efficiency is important (more use out of a rack) but scaling/idling isn't really that big of a deal (but it has slowly dawned on people that burning power 'because you can' is not really a great model). That AI inferencing in a datacenter is more power-hungry as a result, because they can, because it is faster, and that's what attracts users. I would estimate that the local llama3 inferencing uses less power than when done in a datacenter, because there simply is less power available locally (try finding an end-user device that is used mass-market with enough power available, you won't; only small markets like gaming PCs and workstations will do).
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alganet 2y ago
The part on training is misleading and full of shit. Training is not a "one-time cost". There is an implied never-ending need for training. LLMs are useless (for one of their main purposes) if the models get stale. I can use Musk's own argument on this one. Each model is a plane, fully built, that LLM researchers made into a disposable asset destined to be replaced by a newly built plane on the next training. Just incredibly stupid and inneficient. I know what you're thinking right now: fine-tuning, etc. That is the "reusable" analogy to that, is it not? But fine-tuning is far, far from reusability (the major players don't even care about it that much). It's not even on the "hopper" stage. _Stop training new shit, and the argument becomes valid. How about that?_ --- I am sure the more radical environmentalists know that LLMs can be eco-friendly. The point is: they don't believe it will go that way, so they fight it. I can't blame them, this has happened before. _This monster was made by environment promises that were not met_. If they're not met again, the monster will grow and there's nothing anyone can do about it. I've been more moderate than this article in several occations and still got attacked by it. If not LLMs, it will target something else. Again, can't blame them.
- simonw 2y ago
  > LLMs are useless (for one of their main purposes) if the models get stale. I don't think that's entirely accurate. A lot of people deliberately continue to chose to use the older GPT-4 despite it not being updated since June 2023. GPT-4o has had releases in May, August and November of 2024 - so about one every 3-4 months. Anthropic's Claude 3.5 Sonnet was released in June and had a single update in October. Personally I'd rather have a model with excellent summarization / tool using abilities that can look up recent facts about the world.
  - alganet 2y ago
    LLMs that can replace search (their primary and self-declared goal) cannot survive without repeated training. As I said, this is one of its main purposes. The other main purpose (military application, surveillance, autonomous psyops) is also highly dependent on continous training. Without it, properly educated healthy humans can overcome its reasoning power very quickly. All other user profiles are just cannon fodder. Companies don't give a fuck about people running older models. They'll do whatever they can to make you use a more recent one. That's why I'm being provocative with the "let's stop training new shit" argument. I'm aiming for the heel.
paulcole 2y ago
Anyone who says that LLMs are terrible for the environment will never be swayed from that belief. It is like a new shibboleth for idiocy. When someone says it just reply with, “I see” and move on with your life.
geeknet 2y ago
I just created an account and submitted a post but it does not appear on new section just to me, anyone knows why? can anyone submit this: TikTok Ban in USA and the Hypocrisy of the USA Regime https://justpaste.it/tiktok_ban https://justpaste.it/tiktok_ban
crakhamster01 2y ago
One miss in this post is that the author tries to make their point by comparing energy consumption of LLMs to arbitrary points of reference. We should be comparing them to their relevant parallels. Comparing a ChatGPT query to an hour long Zoom call isn't useful. The call might take up ~1700 mL of water, but that is still wildly more efficient than what we used to do prior - travel/commute to meet in person. The "10x a Google search" point is relevant because for many of the use cases mentioned in this post and others like it (e.g. "try asking factual questions!"), you could just as easily get that with 1 Google search and skimming the results. I have found use for LLMs in software development, but I'd be lying if I said I couldn't live without it. Almost every use case of an LLM has a simple alternative - often just employing critical thinking or learning a new skill. It feels like this post is a long way of saying "yes, there are negative impacts, but I value my time more".
- andymasley 2y ago
  I basically do think that at some threshold it's important to weigh your time against negative impacts. I personally avoid taking flights whenever I can because of the climate and think that's worth my time relative to the emissions saved, but I also never worry about optimizing the energy use of my digital clock because that would take too much time relative to the emissions I could save. ChatGPT exists somewhere between those two things, and my argument in the post is that it's much closer to the digital clock.
  - Retric 2y ago
    On a logarithmic scale, it’s closer to the flight. Flying 1000 miles commercially only represents about 10 gallons of fuel.
    - andymasley 2y ago
      10 gallons of fuel's worth of energy could be used to ask ChatGTP 100,000 questions (assuming 3 Wh per question) or power a digital clock (1-2 W) for 35 years. If you assume you ask ChatGPT 8 questions per day, it's using exactly as much energy as a digital clock. Personal use of ChatGPT is much closer to the clock.
marcelsalathe 2y ago
A very nice article. But the google search and LLM energy estimates are outdated. More recent work put both at 10x less. https://engineeringprompts.substack.com/p/does-chatgpt-use-10x-more-energy?triedRedirect=true https://engineeringprompts.substack.com/p/does-chatgpt-use-1...
- andymasley 2y ago
  Yup I decided to go with the worst estimates given by environmentalist critics of ChatGPT to try to show that even there it doesn't seem like a problem.
Imustaskforhelp 2y ago
I am pretty sure that everybody else has pointed out but the training costs should also be accounted I suppose?
saaaaaam 2y ago
I wish charts like this would score the carbon impact of having children. It would be off the scale.
- bdangubic 2y ago
  yea lets not do that. if we all decided not to have kids we would not have to worry at all about the fucking environment eh? :)
  - saaaaaam 2y ago
    I’m not saying people shouldn’t have children. Just that if you do, you have to stop flying, go vegan, and sort your recycling properly for ever after!
    - bdangubic 2y ago
      thats funny :)
    - aziaziazi 2y ago
      I check every point of your list however I have an European-size house so my biggest consumption is probably heating, after schooling (done) and medical (most still to come). Also beware telling people "not to have children". I know population is the biggest treat because it's a multiplicative factor on hour lifestyle, that we don't like to downgrade. However saying "not having children" is easily arguable as bdangubic did and he's still a bit right: we don't want everybody stop having children altogether. However talking about population have the power to seed ideas in others head, and let themselves make the relation with the number of children they'll have. You convince people by making them convince themselves :)
ghennadude 2y ago
Let's compare everything presented there with just one day of Russian war in Ukraine and we can forget about all CO hesitations in our normal lives.
NBJack 2y ago
Oof. This article misses some important details. Training is not a "one time cost". Training gets you a model that will likely need to be updated (or at least fine-tuned) on newer data. And before GPT4, there was a series of prior, less effective models (likely swept under the rug in press releases) made by the same folks that helped them step forward, but didn't achieve their end goals. And all of this to say nothing of the arms race by the major players all scrambling to outdo each other. It also needs to compare this to the efficiency modern search engines run at. A single traditional query is far less expensive than a single LLM query.
aziaziazi 2y ago
Thinks like heating and car heavily depends on the usage, which I guess is based on the USA average. US houses are HUGE and even here in Europe square m2 / person double in the last decades. - we don’t have a housing problem, we have a surface inflation problem. - heating is directly correlated to the volume to heat. Heating 100m2/person with (coal Chinese steel, resource extracted, logistics…) solar and batteries or heat pump isn’t necessarily more carbon or water efficient that 20m2/person with gas. Bonus point: the resident will have to think twice before filling his property with garbage consumerism. Ps: my GF and I live in 80m2 house, the precedent family where… 2 adults and 3 children! I thing the space is wayyy enough for us but people visiting regularly remark "it’s so tiny/small! "

> It is extremely bad to distract the climate movement with debates about inconsequential levels of emission This. So we should focus on optimizing transport, heating, energy and food.

mindcrash 2y ago

You are kidding right? OpenAI -- for now -- is planning to build 5 gigawatt data centers (yes, plural) to continue its quest towards AGI. -- see HN archives. Meanwhile they are also looking into private nuclear power for the same purpose. Any serious competitor will likely need to do the same. So there's a rational choice and tradeoff to make: Net zero or AGI. We can't have both.

devmor 2y ago

In the same way that leaving food out doesn’t create a cockroach infestation.

changoplatanero 2y ago

If you use chatgpt somehow saves you from making one trip to the doctor in your car it can offset the entire year worth of chatgpt usage in terms of co2 impact.

yapyap 2y ago
if your use of chatgpt saves you from a trip to the doctor I would be very concerned
- ekianjo 2y ago
  Most doctor visits are for benign matters...
  - BobaFloutist 2y ago
    The point of the doctorate is for them to make that determination.
    - gertlex 2y ago
      More constructively, the middle ground of asking a doctor about some minor symptoms over async messaging or tele-appointments (whatever the term for those is), is probably always something to consider for the trivial stuff.
    - elevaet 2y ago
      My partner works in emergency. Someone came in with a blister on their finger yesterday. They had to see the patient and send them home with a bandaid. Not a good use of resources.
    - ekianjo 2y ago
      There is no need to nitpick obvious comments. If you have a running nose and fever in winter, it's 99.99% a cold and a doctor visit will do nothing to help you, yet millions of people waste doctors time for that
    - realusername 2y ago
      Yes and no, you really don't need a deep expertise to diagnose the very common illness. And that's where chatgpt is doing great.
- kaonwarb 2y ago
  Early days, but not as crazy as it sounds: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2825395 https://jamanetwork.com/journals/jamanetworkopen/fullarticle... "The LLM alone scored 16 percentage points (95% CI, 2-30 percentage points; P = .03) higher than the conventional resources group."
  - _cenw 2y ago
    Would be much more interesting if this ranked based on severity of misdiagnosis. An LLM that is 50% better at diagnosing a common cold but missed sepsis 10% more often would not be an overall improvement.
- dragonwriter 2y ago
  ChatGPT is probably adequate to provide a slightly more user-friendly but also slight-less-reliable replacement for a reliable consumer-oriented medical reference book or website for the task of determining whether self-care without seeing a doctor or seeing a doctor is appropriate for symptoms not obviously posing an immediate emergency.
croes 2y ago
If ChatGPT somehow makes you eat more burgers it could make it makes water consumption worse.

zdragnar 2y ago

The title does not match the content. A more appropriate title is "Emissions caused by chatgpt use are not significant in comparison to everything else." But, given that title, it becomes somewhat obvious that the article itself doesn't need to exist.

jonas21 2y ago
> given that title, it becomes somewhat obvious that the article itself doesn't need to exist. Why? I regularly hear people trying to argue that LLMs are an environmental distaster.
- _ache_ 2y ago
  Because LLMs are an environmental disaster. It's not about any individual usage. It's the global technology that is yet to prove to be useful and that already have bad for the environment. Any new usage should be free of impact on the environment. (Note: The technology of LLM itself is not an environmental disaster, but how it is put in use currently isn't the way).
  - satvikpendem 2y ago
    > It's the global technology that is yet to prove to be useful Useful for whom, by what definition? I personally find it very useful for my day to day work, whether it be helping me write code, think through ideas, or otherwise.
    - _ache_ 2y ago
      I don't want to be rude but I don't think that your personal experience is of any interest. The only question is "are LLM relevant ?" And the only way to assert that they are is to get numbers (big or small) and to compare them to alternatives.
      - satvikpendem 2y ago
        > I don't think that your personal experience is of any interest But you didn't specify what you meant by "useful," hence why I asked the question I did. So under such ambiguity, my assertion is absolutely a counterpoint to what you just said. I will ask again, useful for whom, by what definition?

hexage1814 2y ago

To me the "ChatGPT is destroying the environment "card always felt somewhat like bad faith arguing from the anti-AI crowd trying to find any excuse for being against AI. Like, the same people who complained about "using AI is destroying environment" seemed to have no issue with boarding a plane which would emit a bunch of CO2 so that they can have a vacation in Europe or the like. Selective environmentalism.

minimaxir 2y ago
It's less bad faith, more a meme that has become so prevalent that it's impossible to dispell as it's something too nuanced for social media. I've seen more than a few social media posts asking "do they really cut down a rainforest every time someone generates an AI image?"
- rainonmoon 2y ago
  I mean we can go back and forth all day with credulous clowns on both sides. There are certainly plenty of misguided AI advocates who think what they're using is magic.
noirbot 2y ago
I mean, it's a literal net new expenditure of power and water. I also deeply doubt they have "no issue" with plane travel. You're just assuming the worst and most hypocritical position to someone, which seems deeply bad faith as well. It's literally true that most of the AI vendors and their data center partners are writing off energy and water conservation targets they'd had for the near future because of LLM money. That is actually bad in the short and likely long term, especially as people use LLMs for increasingly frivolous things. Is it really necessary to have an LLM essentially do a "I'm Feeling Lucky" Google Search for you at some multiple of that environmental cost? Because that's what most of my friends and coworkers use ChatGPT for. Very rarely are they using it to get anything more complex than just searching wikipedia or documentation you could have had bookmarked. A person has a choice of if they take a flight and if it's worth it for them. They have no power except for raising a complaint in public on if OpenAI or Google or whoever spends vast amounts of money and power to train some new model. If your bar is that no one is allowed to complain about a company burning energy unless they live a totally blameless life farming their own food without electricity then random companies will get to do any destructive act they want.

Kindra 2y ago

[dead]

DeepYogurt 2y ago

I mean.... doing most things are bad for the environment. Do less of everything that you don't need to.

maeil 2y ago

The section on training feels weak, and that's what the discussion is mainly about. Many companies are now trying to train models as big as GPT-4. OpenAI is training models that may well be even much larger than GPT-4 (o1 and o3). Framing it as a one-time cost doesn't seem accurate - it doesn't look like the big companies will stop training new ones any time soon, they'll keep doing it. So one model might only be used half a year. And many models may not end up used at all. This might stop at some point, but that's hypothetical.

devmor 2y ago
I am sure that’s intentional, because this article is the same thing we see from e/acc personalities any time the environmental impact is brought up. Deflection away from what actually uses power and pretending the entire system is just an API like anything else.
- andymasley 2y ago
  I am to put it mildly not an e/acc and referenced being very worried about other risks from advanced AI in the article.
  - devmor 2y ago
    Then I would certainly be interested to know why you spent so much time making the same argument e/acc AI proponents make ad nauseam. As it stands, the majority of your article reads like a debate against a strawman that is criticizing something they don't understand, rather than a refutation of any real criticism of environmental impact from the generative AI industry. If your aim was to shut down bad faith criticism of AI from people who don't understand it, that's admirable and I'd understand the tone of the article, but certainly not the claim of the title.
    - andymasley 2y ago
      The point of the article WAS to debate someone criticizing something they don't understand. AI as a whole is using a lot of energy and we should think about the environmental impacts, but I pretty regularly meet people who think that every individual ChatGPT search is uniquely bad for the environment. I tried to make it as clear as possible that that's the issue I'm responding to, not all AI energy use.

getwiththeprog 2y ago

This is a great article for discussion. However articles like this must link to references. It is one thing to assert, another to prove. I do agree that heating/cooling, car and transport use, and diet play massive roles in climate change that should not be subsumed by other debates. The flip side to the authors argument is that LLMs are not only used by home users doing 20 searches a day. Governments and Mega-Corporations are chewing through GPU hours on god-knows-what. New nuclear and other power facilities are being proposed to power their use, this is not insignificant. Schneider Electric predicts 93 GW of energy spent on AI by 2028. https://www.powerelectronicsnews.com/schneider-electric-predicts-substantial-energy-consumption-for-ai-workloads-globally/ https://www.powerelectronicsnews.com/schneider-electric-pred...

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jonas21 2y ago
> However articles like this must link to references. There are links to sources for every piece of data in the article.
- blharr 2y ago
  Where? One of the most crucial points "Training an AI model emits as much as 200 plane flights from New York to San Francisco" This seems to come from this blog https://icecat.com/blog/is-ai-truly-a-sustainable-choice/#:~:text=A%20recent%20study%20by%20the,emissions%20of%20an%20average%20car https://icecat.com/blog/is-ai-truly-a-sustainable-choice/#:~.... which refers to this article https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their-lifetimes/ https://www.technologyreview.com/2019/06/06/239031/training-... which is talking about models like *GPT-2, BERT, and ELMo* -- _5+ year old models_ at this point. The keystone statement is incredibly vague, and likely misleading. What is "an AI model"? From what I found, this is referring to GPT-2,
  - KTibow 2y ago

feverzsj 2y ago

Yeah, there are lots of things worse than LLMs. But, at least, they are useful and profitable.

blkhawk 2y ago

what does "water used by data center" even mean? Does it consume the water somehow? What does it turn into? Steam? So uploading a 1GB file boils away nearly 1 liter of water? Or is it turned into bits somehow in some kind of mass to energy conversion? I sorta doubt that. Also this means data centers would have cooling towers like some power stations. Are we talking about the cooling towers of power stations? I think at least that graph is complete non-sense. I will try and have chatGPT explain it to me.

stonogo 2y ago
Yes, datacenters have cooling towers. There are lots of good articles about this topic. A good starting point is "water usage effectiveness" (WUE) which is one way this is tracked.
- blkhawk 2y ago
  The one near here just has heat exchanges. But even if all the others use evaporators then potential water usage is extremely misleading because its not like the water is consumed - its just temporarily unavailable. Also why doesn't uploading a 1GB file to my NAS boil a liter of water? are maybe all the switches and routers used between me and the datacenter water-cooled? I mean I can see such switches existing but I don't see them be the norm. Why doesn't the DSLAM on the Street outside emit steam. Is there maybe one bad switch somewhere that just spews steam? What I am saying is that at least that graph is without further explanation... bad.
  - dragonwriter 2y ago
    > The one near here just has heat exchanges. But even if all the others use evaporators then potential water usage is extremely misleading because its not like the water is consumed Water consumption in all contexts is mostly fresh water returned from immediately usable form to either evaporation or the ocean. It is not "extremely misleading", because when it returns to immediately usable form by, e.g., precipitation, that's when new water is considered to be made available. The normal definitions are internally consistent and useful.

yapyap 2y ago

Such a stupid post, I know people on HN don’t like absolute descriptors like that and sorry for that. Obviously the LLMs and ChatGPT don’t use the most energy when answering your question, they churn through insane amounts of water and energy when training them, so much so that big tech companies do not disclose and try to obscure those amounts as much as possible. You aren’t destroying the environment by using it RIGHT NOW, but you are telling the corresponding company that owns the LLM you use “there is interest in this product”, en masse. With these interest indicators they will plan for the future and plan for even more environmental destruction.

jna_sh 2y ago
Similar feelings about the repeated references to the apparently agreed consensus that individual action is pointless vs systematic change like switching to a renewable energy system. Jevons Paradox would like a word.
simonw 2y ago
Plenty of companies have revealed exactly how much energy and CO2 they have used training a model. Just off the top of my head, I've seen those numbers are available for Meta's Llama models, Microsoft's Phi series and DeepSeek's models - including their impressive DeepSeek v3 which trained for less than $6m in cost - a huge reduction compared to other similar models, and a useful illustration of how much more effect this stuff can get on the training side of things.
monero-xmr 2y ago
[flagged]
- ben_w 2y ago
  > Charge the consumer of energy the requisite price. If you want to make them pay for some externality, great. > And it is elites only as poors don’t give a shit The poor people are also consumers; raising prices of energy for that group is a fantastic way to get kicked out of office even if you're an actual literal dictator. People are complex. The screeds you're objecting to are part of the political process to tell governments to do something, even if that something ends up being a mix of what you suggest plus subsidies for the poor, or something completely different, in any case to avoid being defenestrated

pixelesque 2y ago

Sort of off-topic, but it does make one think about usage of compute (and the backing energy / resources required for that)... i.e. it doesn't seem too much of an exaggeration to say that we might be getting closer and closer to a situation where LLMs (or any other ML inference) is being run so much for so many different reasons / requests, that the usage does become significant in the future. Similarly, going into detail on what the compute is being used for: i.e. no doubt there are situations currently going on where Person A uses a LLM to expand something like "make a long detailed report about our sales figures", which produces a 20 page report and delivers it to Person B. Person B then says "I haven't time to read all this, LLM please summarise it for me". So you'd basically have LLM inference compute being used as a very inefficient method of data/request transfer, with the sender expanding a short amount of information to deliver to the recipient, and then the said recipient using an LLM on the other side to reduce it back again to something more manage-able.

lioeters 2y ago
That sounds like the opposite of data compression (inflation?) where the data size is increased before sending, then on receiving it is compressed back to a smaller form.
- WD-42 2y ago
  Lossy data inflation.

mossTechnician 2y ago

It's discomforting to me when people compare resource usage of ChatGPT, a computer, to the resource usage of a human being. I've seen charts like this before that compare resource usage of people to corporations, implying corporations are the bigger problem. The implication here seems to be the opposite, and that tone feels just a little eugenicist.

Liquix 2y ago

~90% of the plastic debris in the ocean comes from ten rivers [0]. eight are in china/SEA. millions and billions of single-use items are sitting in warehouses and on store shelves wrapped in plastic. even before the plastic is discarded, the factories these items are produced in dump metric tons of waste into the oceans/soil with little repercussion. point is, none of our "personal lifestyle decisions" - not eating meat, not mining bitcoin, not using chatgpt, not driving cars - are a drop in the bucket compared to standard practice overseas manufacturing. us privileged folks could "just boycott", "buy renewable", "vote with your wallet", etc, but sales will move to a less developed area and the pollution will continue. this is not to say that the environment isn't important - it's critically important. it's just to say that until corporations are forced to do things the right way, it's ludicrous to point fingers at each other and worry that what we do day-to-day is destroying the planet. [0] https://pubs.acs.org/doi/10.1021/acs.est.7b02368 https://pubs.acs.org/doi/10.1021/acs.est.7b02368

saagarjha 2y ago
That's definitely not true. Let's take Americans, for example, driving their cars to work. Americans are about 15% of the world's emissions, of which 25% or so is transportation, of which well over half is cars. So you not driving to work is making direct impact on 2-3% of the world's overall emissions. Likewise, your decisions on all the other things, if taken in aggregate, will have a significant impact on overall emissions.
- jamilton 2y ago
  The amount of people who choose to not drive to work is significantly impacted by policy.
- irishloop 2y ago
  Meat and dairy specifically accounts for around 14.5% of global greenhouse gas emissions, according to the UN’s Food and Agricultural Organization (FAO). If people collectively just ate a bit less meat and dairy, it would go a long way. Don't even have to be perfect. Just show a little bit of restraint.

yesbut 2y ago

This guy must work at Microsoft.

scottcha 2y ago

Yet we also see that hyperscale cloud emissions targets have been reversed due to AI investment, Datacenter growth is hitting grid capacity limits in many regions, and peaker plant and other non-renewable resources on the grid are being deployed more to handle this specific growth from AI. I think the author, by qualifying on "chatgpt" maybe can make the claims they are making but I don't believe the larger argument would hold for AI as a whole or when you convert the electricity use to emissions. I'm personally on the side that the ROI will probably work out in the long run but not by minimizing the potential impact and keeping the focus on how we can make this technology (currently in its infancy) more efficient. [edit wording]

seanmcdirmid 2y ago
Is that true though? Data centers can be placed anywhere in the USA, they could be placed near a bunch of hydro or wind farm resources in the western grid which has little coal anyways outside of one line from Utah to socal. The AI doesn’t have to be located anywhere near to where it is used since fiber is probably easier to run than a high voltage power line.
- wmf 2y ago
  That was already done years ago and people are predicting that the grid will be maxed out soon.
  - seanmcdirmid 2y ago
    Build new data centers near sources of power, and grid capacity isn’t going to be a problem. Heck, American industry used to follow that (building garment factories on fast moving rivers before electricity was much of a thing, Boeing grew up in the northwest due to cheap aluminum helped out by hydro). Why is AI somehow different from an airplane?
    - wmf 2y ago
      They'll have to build new power generation and build the data centers next to it.

BenFranklin100 2y ago

Just build nuclear.

namesbc 2y ago
That doesn't solve the problem
- jenadine 2y ago
  Indeed, it doesn't solve the problem that people will misinterpret data and spread misinformation to justify their bad feeling about AI with invalid arguments.

Al-Khwarizmi 2y ago

In my country there's a lot of institutional hype about green algorithms. I find the whole idea quite irrelevant (for the reasons explained in this post) but of course, it's a way to get funding for those of us who work in AI/NLP (we don't have much money for GPUs and can't do things like training big LLMs, so it's easy to pitch everything we do as "green", and then get funding because that's considered strategic and yadda yadda). It's funny, but sad, how no one calls the billshit because we would be sabotaging ourselves.

namesbc 2y ago

Data center emissions probably 662% higher than big tech claims. Can it keep up the ruse?: https://www.theguardian.com/technology/2024/sep/15/data-center-gas-emissions-tech https://www.theguardian.com/technology/2024/sep/15/data-cent...

simonw 2y ago

The absolute best thing I've read on this subject is this article here: https://about.bnef.com/blog/liebreich-generative-ai-the-power-and-the-glory/ https://about.bnef.com/blog/liebreich-generative-ai-the-powe... It talks at great length about data center trends relating to generative AI, from the perspective of someone who has been deeply involved in researching power usage and sustainability for two decades. I made my own notes on that piece here (for if you don't have a half hour to spend reading the original): https://simonwillison.net/2025/Jan/12/generative-ai-the-power-and-the-glory/ https://simonwillison.net/2025/Jan/12/generative-ai-the-powe...

strogonoff 2y ago
I find the following to be a great point regarding what we ought to consider when adapting our lifestyle to reduce negative environmental impact: > In deciding what to cut, we need to factor in both how much an activity is emitting and how useful and beneficial the activity is to our lives. The further example with a hospital emitting more than a cruise ship is a good illustration of the issue. Continuing this line of thought, when thinking about your use of an LLM like ChatGPT, you ought to weigh not merely its emissions and water usage, but also the larger picture as to how it benefits the human society. For example: Was this tech built with ethically sound methods[0]? What are its the foreseeable long-term effects on human flourishing? Does it cause a detriment to livelihoods of the many people while increasing the wealth gap with the tech elites? Does it negatively impact open information sharing (willingness to run self-hosted original content websites or communities open to public, or even the feasibility of doing so[1][2]), motivation and capability to learn, creativity? And so forth. [0] I’m not going to debate utilitarianism vs. deontology here, will just say that “the ends justify the means” does not strike me as a great principle to live by. [1] https://news.ycombinator.com/item?id=42486481 https://news.ycombinator.com/item?id=42486481 [2] https://news.ycombinator.com/item?id=42549624 https://news.ycombinator.com/item?id=42549624
- deleted 2y ago
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OlivOnTech 2y ago

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sirnicolaz 2y ago

What about training it?

deleted 2y ago

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ternnoburn 2y ago

"Other bad things exist" does not mean this thing isn't bad. Or absolutely could be that all these other things are huge energy wasters AND chat gpt is an energy waster. We have to stop thinking about problems so linearly -- it's not "solve only the worst one first", because we'll forever find reasons to not try and solve that one, and we'll throw up our hands. Like, we're well aware animal agriculture is a huge environmental impact. But getting everyone to go vegetarian before we start thinking about any other emissions source is a recipe for inaction. We're going to have to make progress, little by little, on all of these things.

XorNot 2y ago
Except that's not the point of this: the point is that humans have absolutely finite time to think about problems, and so the way you distract from a problem is by inventing a new more exciting one. LLMs are in the news cycle, so sending all the activists after LLMs sure does a good job ensuring they're not going after anything which would be more effective doesn't it? (setting aside my thoughts for the moment of the utility of the 'direct action' type activists who I think have been useless for a good long while now - there could not possibly be more 'awareness' of climate change).
- ternnoburn 2y ago
  Then again, if you can stall a nascent polluter before it becomes entrenched, maybe that's the right time to intervene. Getting people to not eat meat is hard, we've been eating meat forever. Getting people to not use LLMs? That's where most of us were up until very recently.
  - XorNot 2y ago
    "Don't use LLMs" is just another variant of "don't use electricity". Reframe the problem like that and then realize that no one's going to do it: global electricity use is constantly increasing. Fortunately, global renewable energy use is also growing incredibly rapidly. Which problem seems more tractable? Because reality has already proven it: people will happily switch to clean electricity and keep using electricity. They won't voluntarily use less electricity unless they get some benefit from that - i.e. reduced expenditure, or just plain more stuff (i.e. my LED lights consume a fraction of the power of my previous halogens, but are brighter and I have more of them and also can change light color on a schedule).

titanomachy 2y ago

The major players in AI are collectively burning 1-2 gigawatts, day and night, on research and development of the next generation of LLMs. This is as much as my city of a million people. The impact is real, and focusing on inference cost per query kind of misses the point. Every person who uses these tools contributes to the demand and bears some of the responsibility. Similar to how I have responsibility for the carbon emissions of a flight, even if the plane would have flown without me. I'm saying this as someone who finds LLMs helpful, and uses them without feeling particularly guilty about it. But we should be honest about the costs.

nharada 2y ago
Agreed, I feel like the main response seems to be "Does Not!", but it's reasonable to accept that a thing you like has a cost. We all emit carbon every day to do things we don't 100% need, and we should just be willing to admit there's a cost and try and move towards paying them. Personally, I'm not tripping too hard about datacenter energy long term because it's very easy to make carbon free (unlike say ICE cars or aircraft). But it would be nice to see some efforts to incentivize green energy for those datacenters instead of just saying "whatever" and powering them with coal.
- simonw 2y ago
  "But it would be nice to see some efforts to incentivize green energy for those datacenters instead of just saying "whatever" and powering them with coal." The major datacenter operators all have very aggressive targets for clean energy which they have been mostly sticking to. Google: https://sustainability.google/progress/energy/ https://sustainability.google/progress/energy/ AWS: https://sustainability.aboutamazon.com/products-services/aws-cloud https://sustainability.aboutamazon.com/products-services/aws... Azure: https://azure.microsoft.com/en-us/explore/global-infrastructure/sustainability https://azure.microsoft.com/en-us/explore/global-infrastruct...

01HNNWZ0MV43FF 2y ago

Enforce a global carbon tax, price it in, and tax the land

LeonB 2y ago
International tax agreements are crucial if any progress is to be made on preventing climate disaster. Which major parties support it? Who is even talking about it? It’s such an obviously needed mechanism, but hard to get anyone enthused about it. This group have some proposals on the topic — https://en.m.wikipedia.org/wiki/Association_for_the_Taxation_of_Financial_Transactions_and_for_Citizens%27_Action https://en.m.wikipedia.org/wiki/Association_for_the_Taxation...

ZYbCRq22HbJ2y7 2y ago

Comparing magnitudes does not prove the headline, poor analysis.

croes 2y ago

The use of ChatGPT doesn’t replace the others it comes on top of that. MS is missing its CO2 targets because of AI not because of burgers. The whole argument is, it’s not bad because other things are worse. We are racing towards the abyss but don’t worry AI only accelerates a little more.

pluc 2y ago

Using it, sure, now do operating it and building it.

folken 2y ago

"personal carbon footprint" is a term invented by BP and is the single hack that derailed the environment discussion by making people personally responsible and removing the actual polluters from the discussion.

_cenw 2y ago
The article could indeed be written by the same kind of people, given it glances over training cost as if AI companies aren't pushing datacenter power/gpu capacities to the limit to produce incrementally better models by brute force. It all falls apart as soon as you stop individualizing the numbers and add back in all of the supposedly non-recurring (but actually recurring because we can't stop ourselves from redoing it) cost.
andymasley 2y ago
I specifically mentioned in the article that I think it's mostly a waste of time to worry about your personal carbon footprint and you should aim for big systematic change instead, but because so many people seem to be worried about their personal chatgpt use I wanted to clarify that it doesn't use much energy anyway

gunian 2y ago

A lot of conversations regarding the environment feel so frustrating because they are either qualitative or use aggregate high level data or are like we'll be dead in 50 years (lol my personal favorite) Why not start capturing waste/energy data for all human made items like nutritional data on food? It won't add much overhead or stifle economies as people fear That way when I log in to use any online service or when I buy/drive a car or when I buy an item I can see how much energy was consumed and how much waste I produced exactly

lhl 2y ago

I published this as a comment as well, but it's probably worth nothing that the ChatGPT water/power numbers cited (the one that is most widely cited in these discussions) comes from an April 2023 paper (Li et al, arXiv:2304.03271) that estimates water/power usage based off of GPT-3 (175B dense model) numbers published from OpenAI's original GPT-3 2021 paper. From Section 3.3.2 Inference: > As a representative usage scenario for an LLM, we consider a conversation task, which typically includes a CPU-intensive prompt phase that processes the user’s input (a.k.a., prompt) and a memory-intensive token phase that produces outputs [37]. More specifically, we consider a medium-sized request, each with approximately ≤800 words of input and 150 – 300 words of output [37]. The official estimate shows that GPT-3 consumes an order of 0.4 kWh electricity to generate 100 pages of content (e.g., roughly 0.004 kWh per page) [18]. Thus, we consider 0.004 kWh as the per-request server energy consumption for our conversation task. The PUE, WUE, and EWIF are the same as those used for estimating the training water consumption. There is a slightly newer paper (Oct 2023) that directly measured power usage on a Llama 65B (on V100/A100 hardware) that showed a 14X better efficiency. [2] Ethan Mollick linked to it recently and got me curious since I've recently been running my own inference (performance) testing and it'd be easy enough to just calculate power usage. My results [3] on the latest stable vLLM from last week on a standard H100 node w/ Llama 3.3 70B FP8 was almost a 10X better token/joule than the 2023 V100/A100 testing, which seems about right to me. This is without fancy look-ahead, speculative decode, prefix caching taken into account, just raw token generation. This is 120X more efficient than the commonly cited "ChatGPT" numbers and 250X more efficient than the Llama-3-70B numbers cited in the latest version (v4, 2025-01-15) of that same paper. For those interested in a full analysis/table with all the citations (including my full testing results) see this o1 chat that calculated the relative efficiency differences and made a nice results table for me: https://chatgpt.com/share/678b55bb-336c-8012-97cc-b94f70919daa https://chatgpt.com/share/678b55bb-336c-8012-97cc-b94f70919d... (It's worth point out that that used 45s of TTC, which is a point that is not lost on me!) [1] https://arxiv.org/abs/2304.03271 https://arxiv.org/abs/2304.03271 [2] https://arxiv.org/abs/2310.03003 https://arxiv.org/abs/2310.03003 [3] https://gist.github.com/lhl/bf81a9c7dfc4244c974335e1605dcf22 https://gist.github.com/lhl/bf81a9c7dfc4244c974335e1605dcf22

palata 2y ago

> and it’s completely clear to me that one side is getting it entirely wrong and spreading misleading ideas What a great way to start an article. I get it as: "I am not open to listening to your arguments, and in fact if you disagree with me, I will assume that you are a moron". It reminds me of people saying "planes are not the problem: actually if you compare it to driving a car, it uses less energy per person and per km". Except that as soon as you take a passenger in your car, the car is better (why did you assume that the plane was full and the car almost empty?). And that you don't remotely drive as far with your car as you fly with a plane. Obviously planes are worse than cars. If you need to imagine people commuting by car to the other side of the continent to prove your point, maybe it's not valid? The fact is that the footprint of IT is increasing every year. And quite obviously, LLMs use more energy than "traditional" searches. Any new technology that makes us use more energy is bad for environment. Unless you don't understand how bad the situation is: we have largely missed the goal of keeping global warming to 1.5C (thinking that we could reach it is absurd at this point). To keep 2C, we need to reduce global emissions by 5% every year. That's a Covid crisis every year. Let's be honest, it probably won't happen. So we'll go higher than 2C, fine. At the other end of the spectrum, 4C means that a big stripe (where billions of people live) around the equator will become unlivable for human beings (similar to being on Mars: you need equipment just to survive outside). I guess I don't need to argue how bad that would be, and we are currently going there. ChatGPT is part of that effort, as a new technology that makes us increase our emissions instead of doing the opposite.

ben_w 2y ago
I take your general point, but: > Except that it doesn't work if you don't drive your car alone (if you assume the plane is full of passengers, why not assuming that the car is, as well?) These can be measured for averages. Lots of cars with one person in them, seldom cars fully packed; lots of planes fully packed, seldom (but it does happen) that the plane is almost empty. > we have largely missed the goal of keeping global warming to 1.5C (thinking that we could reach it is absurd at this point). Probably, yes; last year passed the threshold — it would be a pleasant *surprise* if that turned out to have been a fluke 14* years early. * 14 because it would take 14 years for the exponential — seen for the last 30 years — for PV to replace all forms of power consumption; not just electricity, everything. But even then we'd also need to make rapid simultaneous progress with non-energy CO2 sources like cattle and concrete. > around the equator will become unlivable for human beings (similar to being on Mars: you need equipment just to survive outside) In so far as your bracket, sure; but there's a huge gap in what equipment you would need. The comparison I often make is that Mars combines the moisture of the Sahara, the warmth of the Antarctic, the air pressure of the peak of Mount Everest, and the soil quality of a superfund cleanup site, before then revealing that it's actually worse on all counts.

thih9 2y ago

Perhaps off topic, what exactly does the “one way european flight” mean in the context of avoiding co2 emissions? I.e. what is the choice or scenario here?

dvorack101 2y ago

Number are wrong. Just trying on topic. Data centers and AI realty consumes a lot more resources that you article poses.

garyfirestorm 2y ago

Why did this get flagged?

returningfory2 2y ago
I emailed hn@ to try to find out, I’ve no idea why.

andymasley 2y ago

Hey all I wrote this post. To clear up a few points: I meant this post to tell individuals that worrying about the emissions they personally cause using ChatGPT is silly, not that AI more broadly isn't using a lot of energy. I can't really factor in how demand for ChatGPT is affecting the future of AI. If you don't want to use ChatGPT because you're worried about creating more demand, that's more legit, but worry about the emissions associated with individual searches right now on their own is a silly distraction. One criticism is that I didn't talk about training enough. I included a section on training in the emissions and water sections, but if there's more you think I should address or change I'm all ears. Please either share them in the comments on the post or here. I saw someone assumed I'm an e/acc. I'm very much not and am pretty worried about risks from advanced AI. Had hoped the link to an 80,000 Hours article might've been a clue there. Someone else assumed I work for Microsoft. I actually exclusively use Claude but wanted to write this for a general audience and way fewer people know about Claude. I used ChatGPT for some research here that I could link people to just to show what it can do.

celticninja 2y ago

This used to be the stick they used to beat bitcoin with. I guess it's a good stick because you can hit any technology with it and you can conveniently forget all the terrible uses to which electricity is put.

originalvichy 2y ago

Where in the world are you getting the numbers for how much video streaming uses energy? I am quite sure that just as with LLMs, most of the energy goes into the initial encoding of the video, and nowadays any rational service encodes videos to several bitrates to avoid JIT transcoding. Networking can’t take that much energy, unless perhaps we are talking about purely wireless networking with cell towers?

oneplane 2y ago
LLM Inference is still quite power-hungry, Video decoding with hardware acceleration is much more efficient. But we can do some estimates, heck, we can even ask GPT for some numbers. Say you want to do 30 minutes of video (h265) or 30 minutes of LLM inferencing on a generic consumer device, ignoring the source of the model or source of encoded video, you get about 4x difference: Energy usage for 30 minutes of H.265 decoding: ~15–20 Wh. Energy usage for 30 minutes of Llama3 inference: ~40–60 Wh. This is optimised already, so a working hardware H.265 decoder is assumed, and for inferencing, something on the level of an RTX 3050, but can also be a TPU or NE. While not the most scientific comparison, it's perhaps good to know that video decoding is practically always local, and for streaming services it will use whatever is available and might even switch codecs (i.e. AV1, H.265, H.264 depending on what is available, and what licenses are used). And if you have older hardware, some codecs won't even exist in hardware, to the point where you start doing software decoding (very inefficient). AI inferencing is mostly remote (at least the heavy loads) in a datacenter because local availability of hardware is pretty hit and miss, models are pretty big and spinning one up every time you just wanted to ask something is not very user friendly. Because in a datacenter you tend to pay for amperage per rack, you spec your AI inferencing hardware to eat that power since you're not saving any money or hardware life when you don't use it. That means that efficiency is important (more use out of a rack) but scaling/idling isn't really that big of a deal (but it has slowly dawned on people that burning power 'because you can' is not really a great model). That AI inferencing in a datacenter is more power-hungry as a result, because they can, because it is faster, and that's what attracts users. I would estimate that the local llama3 inferencing uses less power than when done in a datacenter, because there simply is less power available locally (try finding an end-user device that is used mass-market with enough power available, you won't; only small markets like gaming PCs and workstations will do).

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alganet 2y ago

The part on training is misleading and full of shit. Training is not a "one-time cost". There is an implied never-ending need for training. LLMs are useless (for one of their main purposes) if the models get stale. I can use Musk's own argument on this one. Each model is a plane, fully built, that LLM researchers made into a disposable asset destined to be replaced by a newly built plane on the next training. Just incredibly stupid and inneficient. I know what you're thinking right now: fine-tuning, etc. That is the "reusable" analogy to that, is it not? But fine-tuning is far, far from reusability (the major players don't even care about it that much). It's not even on the "hopper" stage. _Stop training new shit, and the argument becomes valid. How about that?_ --- I am sure the more radical environmentalists know that LLMs can be eco-friendly. The point is: they don't believe it will go that way, so they fight it. I can't blame them, this has happened before. _This monster was made by environment promises that were not met_. If they're not met again, the monster will grow and there's nothing anyone can do about it. I've been more moderate than this article in several occations and still got attacked by it. If not LLMs, it will target something else. Again, can't blame them.

simonw 2y ago
> LLMs are useless (for one of their main purposes) if the models get stale. I don't think that's entirely accurate. A lot of people deliberately continue to chose to use the older GPT-4 despite it not being updated since June 2023. GPT-4o has had releases in May, August and November of 2024 - so about one every 3-4 months. Anthropic's Claude 3.5 Sonnet was released in June and had a single update in October. Personally I'd rather have a model with excellent summarization / tool using abilities that can look up recent facts about the world.
- alganet 2y ago
  LLMs that can replace search (their primary and self-declared goal) cannot survive without repeated training. As I said, this is one of its main purposes. The other main purpose (military application, surveillance, autonomous psyops) is also highly dependent on continous training. Without it, properly educated healthy humans can overcome its reasoning power very quickly. All other user profiles are just cannon fodder. Companies don't give a fuck about people running older models. They'll do whatever they can to make you use a more recent one. That's why I'm being provocative with the "let's stop training new shit" argument. I'm aiming for the heel.

paulcole 2y ago

Anyone who says that LLMs are terrible for the environment will never be swayed from that belief. It is like a new shibboleth for idiocy. When someone says it just reply with, “I see” and move on with your life.

geeknet 2y ago

I just created an account and submitted a post but it does not appear on new section just to me, anyone knows why? can anyone submit this: TikTok Ban in USA and the Hypocrisy of the USA Regime https://justpaste.it/tiktok_ban https://justpaste.it/tiktok_ban

crakhamster01 2y ago

One miss in this post is that the author tries to make their point by comparing energy consumption of LLMs to arbitrary points of reference. We should be comparing them to their relevant parallels. Comparing a ChatGPT query to an hour long Zoom call isn't useful. The call might take up ~1700 mL of water, but that is still wildly more efficient than what we used to do prior - travel/commute to meet in person. The "10x a Google search" point is relevant because for many of the use cases mentioned in this post and others like it (e.g. "try asking factual questions!"), you could just as easily get that with 1 Google search and skimming the results. I have found use for LLMs in software development, but I'd be lying if I said I couldn't live without it. Almost every use case of an LLM has a simple alternative - often just employing critical thinking or learning a new skill. It feels like this post is a long way of saying "yes, there are negative impacts, but I value my time more".

andymasley 2y ago
I basically do think that at some threshold it's important to weigh your time against negative impacts. I personally avoid taking flights whenever I can because of the climate and think that's worth my time relative to the emissions saved, but I also never worry about optimizing the energy use of my digital clock because that would take too much time relative to the emissions I could save. ChatGPT exists somewhere between those two things, and my argument in the post is that it's much closer to the digital clock.
- Retric 2y ago
  On a logarithmic scale, it’s closer to the flight. Flying 1000 miles commercially only represents about 10 gallons of fuel.
  - andymasley 2y ago
    10 gallons of fuel's worth of energy could be used to ask ChatGTP 100,000 questions (assuming 3 Wh per question) or power a digital clock (1-2 W) for 35 years. If you assume you ask ChatGPT 8 questions per day, it's using exactly as much energy as a digital clock. Personal use of ChatGPT is much closer to the clock.

marcelsalathe 2y ago

A very nice article. But the google search and LLM energy estimates are outdated. More recent work put both at 10x less. https://engineeringprompts.substack.com/p/does-chatgpt-use-10x-more-energy?triedRedirect=true https://engineeringprompts.substack.com/p/does-chatgpt-use-1...

andymasley 2y ago
Yup I decided to go with the worst estimates given by environmentalist critics of ChatGPT to try to show that even there it doesn't seem like a problem.

Imustaskforhelp 2y ago

I am pretty sure that everybody else has pointed out but the training costs should also be accounted I suppose?

saaaaaam 2y ago

I wish charts like this would score the carbon impact of having children. It would be off the scale.

bdangubic 2y ago
yea lets not do that. if we all decided not to have kids we would not have to worry at all about the fucking environment eh? :)
- saaaaaam 2y ago
  I’m not saying people shouldn’t have children. Just that if you do, you have to stop flying, go vegan, and sort your recycling properly for ever after!
  - bdangubic 2y ago
    thats funny :)
  - aziaziazi 2y ago
    I check every point of your list however I have an European-size house so my biggest consumption is probably heating, after schooling (done) and medical (most still to come). Also beware telling people "not to have children". I know population is the biggest treat because it's a multiplicative factor on hour lifestyle, that we don't like to downgrade. However saying "not having children" is easily arguable as bdangubic did and he's still a bit right: we don't want everybody stop having children altogether. However talking about population have the power to seed ideas in others head, and let themselves make the relation with the number of children they'll have. You convince people by making them convince themselves :)

ghennadude 2y ago

Let's compare everything presented there with just one day of Russian war in Ukraine and we can forget about all CO hesitations in our normal lives.

NBJack 2y ago

Oof. This article misses some important details. Training is not a "one time cost". Training gets you a model that will likely need to be updated (or at least fine-tuned) on newer data. And before GPT4, there was a series of prior, less effective models (likely swept under the rug in press releases) made by the same folks that helped them step forward, but didn't achieve their end goals. And all of this to say nothing of the arms race by the major players all scrambling to outdo each other. It also needs to compare this to the efficiency modern search engines run at. A single traditional query is far less expensive than a single LLM query.

aziaziazi 2y ago

Thinks like heating and car heavily depends on the usage, which I guess is based on the USA average. US houses are HUGE and even here in Europe square m2 / person double in the last decades. - we don’t have a housing problem, we have a surface inflation problem. - heating is directly correlated to the volume to heat. Heating 100m2/person with (coal Chinese steel, resource extracted, logistics…) solar and batteries or heat pump isn’t necessarily more carbon or water efficient that 20m2/person with gas. Bonus point: the resident will have to think twice before filling his property with garbage consumerism. Ps: my GF and I live in 80m2 house, the precedent family where… 2 adults and 3 children! I thing the space is wayyy enough for us but people visiting regularly remark "it’s so tiny/small! "