5 ms·
Mistral reports on the environmental impact of LLMs
- greyadept 1y agoI would really like it if an LLM tool would show me the power consumption and environmental impact of each request I’ve submitted.
- preciz 1y agoAnd each toilet flush you make should also have a Co2 calculation which should go against your daily carbon allowance.
- evrimoztamur 1y agoSpending drinking water for toilet flushes is indeed a problem. Perhaps not CO2 measurements directly, but informing people in general of how much high quality water is wasted on flushes alone will hopefully bring more momentum into more efficient flushing mechanism and introducing grey water systems to new and old buildings alike. Good idea!
- j-pb 1y agopeople downvote your sarcasm, but if you do the calculations you're kinda right. 1Kg of Beef costs: - The energy equivalent of 60.000 ChatGPT queries. - The water equivalent of 50.000.000 ChatGPT queries. Applied to their metric Mistral Large 2 used: - The water equivalent of 18.8 Tons of Beef. - The CO2 equivalent of 204 Tons of Beef. France produces 3836 Tons of Beef per day, and one large LLM per 6 months. So yeah, maybe use ChatGPT to ask for vegan recipes. People will try to blame everything else they can get a hold on before changing the stuff that really has an impact, if it means touching their lifestyle. The LLMs are not the problem here.
- bluefirebrand 1y agoThe difference is that food is important and live-giving and LLMs are a very fancy magic 8-ball
- j-pb 1y agoYou don't need beef, beef is a lifestyle choice. I use LLMs to do all of my coding these days, it's certainly more essential for feeding me than beef.
- deleted 1y ago[deleted]
- leksak 1y agoAlso a lifestyle choice
- j-pb 1y agoYes but one with a much much much smaller impact as we just demonstrated. This is exactly the kind of cognitive dissonance in people that I meant. You literally see the math and go "but I like my meat, why should I give that up if you got your AI". Because, as I just demonstrated, my AI takes a infinitesimal fraction of your meat. It literally takes you only going vegan for a day to offset your entire AI usage of a year.
- jrflowers 1y agoThis is spot on because there can’t be two issues that exist simultaneously. There can only be one thing that wastes enormous amounts of energy and that thing is beef
- j-pb 1y agoYou can try to misconstrue and ridicule the argument, but that won't change the math that if you have one thing that causes 1 unit of damage, and another thing that causes 100.000 units of damage, then for all intents and purposes the thing that produces 1 unit of damage is irrelevant. And any discussion that tries to frame them as somewhat equally important issues is dishonest and either malicious or delusional. My guess, as I've expressed earlier in the comment chain, is that it's emotionally easier for people to bike-shed about the 0.01% of their environmental impact, than to actually tackle things that make up 20%. And no it's not only beef (which is a stand-in for meat and diary), another low hanging fruit is also transport, like switching your car for a bike. But switching from meat and diary to a vegan diet would reduce up to 20% of your personal environmental impact, in terms of CO2. And about 80-90% of rainforest deforestation is driven directly or indirectly by livestock production. So it's simply the easiest most impactful thing everyone can do. (Switching your car for a bike isn't possible for people in rural areas for example.)
- plants 1y agoThose are incredible stats. As a vegan who uses LLMs at work frequently, I would love to have the source as well :)
- j-pb 1y ago- https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai - https://www.statista.com/statistics/1201677/greenhouse-gas-emissions-of-major-food-products/ - https://www.statista.com/chart/9483/how-thirsty-is-our-food/ - https://blog.samaltman.com/the-gentle-singularity - https://x.com/sama/status/1890820962993533232 You got to do the calculations yourself though.
- plants 1y agoWow, thanks. I’m even coming up with 500K chatGPT queries for the amount of energy consumed as a KG of beef, though I might have moved a decimal place somewhere - feel free to check my math :) “average query uses about 0.34 watt-hours of energy” - or 0.00034MWH Using this calculator: https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator#results https://www.epa.gov/energy/greenhouse-gas-equivalencies-calc... - in my zip, 0.0002KG of CO2 per MWH. (Though, I suppose it depends more on the zip where they’re doing inference, however this translation didn’t seem to vary much when I tried other zips) Then, 99.48KG/0.0002KG= 497,400 chatGPT queries worth of CO2 per KG of beef? Thanks for sharing!
- j-pb 1y ago`0.00034MWH`should probably be kilo not mega, but I think you still did it correctly :D I think I used Btu (thermal units) in my calculation, so I only calculated actual energy expenditure for my 60.000 queries result. But you are right, a better metric might be to use CO2-equivalent, because cows emit a lot of methane, whereas chatbots don't. 99.48KG / 0.228kg/kq = 436,315 queries per kg of beef. Yup checks out!
- JimDabell 1y agoThis is a good article on the subject: > Using ChatGPT is not bad for the environment — https://andymasley.substack.com/p/individual-ai-use-is-not-bad-for https://andymasley.substack.com/p/individual-ai-use-is-not-b... He’s done some good followup articles as well: https://andymasley.substack.com/s/ai-and-the-environment https://andymasley.substack.com/s/ai-and-the-environment
- jrflowers 1y agoThis is a good point because being curious about energy usage is the same thing as advocating for an imaginary rule about energy usage
- stonogo 1y agoToilets are already labeled with their usage rate.
- aziaziazi 1y agoI don’t flush my toilet, I Kildwick [0] but J-pd has a more interesting comparaison [0] https://www.kildwick.com/ https://www.kildwick.com/ [1] https://news.ycombinator.com/threads?id=j-pb https://news.ycombinator.com/threads?id=j-pb
- jiehong 1y agoLet’s call it GreenOps
- jeffbee 1y agoThat would be ... thousands of time less useful than giving you the same information at the motor fuel pump. Unfortunately this isn't one of those situations where every little bit counts. There are 2 or 3 things you can do to reduce your environmental impact and not using chatbots isn't one of the things.
- kingstnap 1y agoYou can assume the API price is roughly proportional to electricity usage. If you buy $10 in tokens, that probably folds into ~$3 to $5 dollars in electricity. Which would be around 30 to 90 kWhr in electricity. Depending on the source, it could be anywhere from ~500g/kWhr (for natural gas) and ~24g/kWhr for hydroelectric. It's a really wide spread, but I'd say for $10 in tokens, you'd probably be in the neighbourhood of 1 kg to 40 kg of emissions. What's a good thing is that a lot of the spread comes from the electricity source. So if we can get all of these datacenters on clean energy sources it could change emissions by over an order of magnitude compared to gas turbines (like XAi uses).
- dijit 1y agoI don’t think that you can make this assumption. People are selling AI at a loss right now.
- chessgecko 1y agoif you bought a nvidia h100 at wholesale prices (around $25k) and ran it 24/7 at commercial electric rates (lets say $0.1 per kwh), then it would take you over 40 years to spend the purchase price of the gpu in electricity. Maybe bump it down to 20 for data center cooling. I don't think the cost of the ai is close to converging to the price of power yet. Right now its mostly the price of hardware and data center space minus subsidies.
- jiehong 1y agoSo, using the smallest model for the task would help, as expected. A very small model could run on device to automatically switch and choose the right model based on the request. It would help navigate the difficult naming of each model of each vendor for sure.
- potatolicious 1y ago> ” A very small model could run on device to automatically switch and choose the right model based on the request.” This is harder than it looks. A “router” model often has to be quite large to maintain routing accuracy, especially if you’re trying to understand regular user requests. Small on-device models gating more powerful models most likely just leads to mis-routes.
- jeffbee 1y agoThese conclusions are broadly compatible with "The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink" or, as I prefer, the PDF metadata title that they left in there, "Revamped Happy CO2e Paper". Despite the incredible focus by the press on this topic, Mistral's lifecycle emissions in 18 months were less than the typical annual emissions of a single A320neo in commercial service. https://arxiv.org/pdf/2204.05149 https://arxiv.org/pdf/2204.05149
- ACCount36 1y agoThe press focus is a mix of the usual "new thing BAD", and the much more insidious PR work by fossil fuel megacorps. Fossil fuel companies are damn good at PR, and they know well that they simply can't make themselves look good. The next best thing? Make someone else look worse. If an Average Joe hears "a company that hurts the environment" and thinks OpenAI and not British Petroleum, that's a PR win.
- jeffbee 1y agoI suspect the press is also aligned against machine learning because they are still Big Mad® that the internet destroyed their revenue model (charging individuals $50 to advertise used cars, for example).
- evrimoztamur 1y agoWhat is the levelised cost per token? As in how we calculate levelised cost of energy. If we take the total training footprint and divide that by the number of tokens the model is expected to produce over its lifetime, how does that compare to the marginal operational footprint? My napkin math says per token water and material footprints are up 6-600% and 4-400% higher respectively for tokens on the order of 40B to 400M. I don't have a good baseline on how many tokens Mistral Large 2 will infer over the course of its lifetime, however. Any ideas?
- kurthr 1y agoWithin marginal error, dollars=destruction. Even if the company is "green" they make money, they pay employees/stockholders, those people use the money to buy more things and go on vacations in airplanes. Worse, they invest the money to make more money and consume more goods. Even your gains and vegetables are shipped in to feed you, if you walk to the grocery store. You pay rent/mortgage for a house built with concrete and steel. The highest priced items you pay for are also likely the most energy and environmentally costly. They create GDP. It's a little weird with LLMs right now, because everything is subsidized by VC, Ads, BigCo investment so you can't see real costs. They're probably higher than the $30-200/mo you pay, but they're not 10x the price like your rent, car payment, food, vacation, investment/pension are.
- austinjp 1y agoThis is interesting but I'd love it if they'd split training and inference. Training might be highly expensive and conducted once, while inference might be less expensive but conducted many, many times.
- djoldman 1y agoThey report that the emissions of 400 output tokens, "one page of text," equates to 10 seconds of online video streaming in the USA. So I guess one saves a lot of emissions if one stops tiktok-ing, hulu-ing, instagram reel-ing, etc.
- wmf 1y agoIt's sad to see the French of all people fall for guilt-trip austerity thinking. Just decarbonize the grid and move on. Energy is good.
- _squared_ 1y agoFrance has a pretty low-carbon grid (relatively) already, this doesn't fix the water consumption issue though, which is getting more problematic as climate change cause droughts all over the country.
- eric-burel 1y agoIt's nice to see the French engineers collecting quantitative data to back future decisions thanks to our solid environment agency (the Ademe) work and public-private cooperation.
- readthenotes1 1y agohopefully they didn't fly to a conference in a private jet to report their findings...
- dr_kretyn 1y agoThis is a fantastic report. As someone tasked to get the most of AI at our company, in conversations I'm frequently getting questions about it's environmental impact. Great to have a reference.