I attached a generator with some supercaps and an inverter to a stationary bicycle a few years ago, and even though I mostly use it as a way to feel less guilty watching Youtube videos, it does give me a quite literal feel for some of the items on the lower end of the scale.
- Anything even even halfway approaching a toaster or something with a heater in it is essentially impossible (yes, I know about that one video).
- A vacuum cleaner can be run for about 30 seconds every couple minutes.
- LED lights are really good, you can charge up the caps for a minute and then get some minutes of light without pedaling.
- Maybe I could keep pace with a fridge, but not for a whole day.
- I can do a 3D printer with the heated bed turned off, but you have to keep pedaling for the entire print duration, so you probably wouldn't want to do a 4 hour print. I have a benchy made on 100% human power.
- A laptop and a medium sized floor fan is what I typically run most days.
- A modern laptop alone, with the battery removed and playing a video is "too easy", as is a few LED bulbs or a CFL. An incandescent isn't difficult but why would you?
- A cellphone you could probably run in your sleep
Also gives a good perspective on how much better power plants are at this than me. All I've made in 4 years could be made by my local one in about 10 seconds, and cost a few dollars.
The author Hannah Ritchie works on Our World In Data and also publishes the fantastic Sustainability by Numbers substack. It's in the same vein as the late, great David MacKay's Sustainable Energy Without the Hot Air.
This tool has its own recent substack post. See the comments too, especially the one by Chris Preist that contextualizes the energy usage of streaming video (a topic that has also been discussed on HN before).
She's employed by Our World In Data. She is also a published author of printed books. Her substack does not have paid subscriptions enabled (or at least it did not as of last summer; see this post [1]). Our World In Data is funded by donations:
One thing missing but important to understand is the energy embodied in buying 'stuff'. At a very rough approximation, the cost of stuff, especially consumer goods manufactured cheaply, is quite a high percentage energy.
When you look at people's energy usage, quite a lot of it ends up being the embodied energy in the stuff they buy. For quite a lot of people, it's probably the largest category of energy consumption. I once had a very rough go at calculating this here: https://www.robinlinacre.com/energy_usage/
> So, if I wanted to analogize the energy usage of my use of coding agents, it’s something like running the dishwasher an extra time each day, keeping an extra refrigerator, or skipping one drive to the grocery store in favor of biking there. To me, this is very different than, in Benjamin Todd’s words, “a terrible reason to avoid” this level of AI use. These are the sorts of things that would make me think twice.
I'm not sure it's even a particularly relevant comparison to an hour of use of various other electronic devices. I'm sure the median user is running a lot fewer queries than a Claude Code power-user, but I would guess it's still more than one in a typical session.
I think stuff like this really crystalises how people misunderstand how much energy stuff uses.
My parents for example sweat the small stuff and go around the house turning LED driven lights off to "save electricity" even though it would barely make a dent in their bill.
Granted, they come from a time of incadescants burning 60-100w at a time so I can see why that habit might be deeply ingrained.
It was genuinely a surprise to see how much relative energy petrol cars use (and shame on me - I'm an electrical engineer). I mean I think I knew it intuitively, but this simple chart blew my mind.
When one gets in the weeds on EVs or ICE cars two things become shockingly clear: internal combustion is hilariously inefficient YET gasoline is hilariously energy dense. Most people's intuition is wrong on both of these points but then they cancel each other out.
Train locomotives have used diesel powered generators that then powers electric motors. Would this be less efficient than battery powered EVs? Or better asked, what would be the most efficient use of gasoline?
When it comes to the environment the most efficient use is to leave it in the ground.
Hybrids work for trains because they are so large and don't need big swings of acceleration or to climb steep grades. They can run the diesel generators at maximum efficiency.
Battery power would be better, because you can build even larger power plants running at higher heats and not have to haul them with you, but the costs of sufficient battery is too large, so far. That is changing.
In Japan, my country, this looks a bit different. A lot of electricity still comes from oil- and gas-fired plants. The mechanics differ (gas turbines vs. car engines), but in both cases we’re still relying on combustion. I suppose some countries have the same issue.
The presentation is nice, but some of the conversions are questionable.
For instance: The cost section, wherein 1kWh in the US is figured as having a cost of 9.7 cents.
In reality, it's not that way at all. Unless we're fortunate enough to live in an area where we can walk over to the neighborhood generating station and carry home buckets of freshly-baked electricity to use at home, then we must also pay for delivery.
On average, in 2025, electricity was 17.3 cents per kiloWatt-hour -- delivered -- for residential customers in the US.
Where did you see 9.7 cents per kWh? I looked at the electric car example for the United States. It has 3 kilowatt hours priced at $0.51, 17 cents per kilowatt hour, which seems about right.
1 chatgpt query is a little misleading though. Let's see an 8 hour full bore claude code agent session. Or maybe running 3 agents for several hours a day.
Wow, putting everything in the same units is really informative. Running my 450 watt gpu for a day is approximately equivalent to driving a car 10 miles.
For reference it would be good to have per-passenger numbers for "sitting on a diesel bus", "sitting on an electric bus", "sitting on a tram", "sitting on a commuter train" as well.
I'm surprised that cooling takes less energy than heating. I imagine that depends a lot on the temperature range; they only need so much to cool a room even on a "hot" day in the UK.
Still... AC still feels like magic. I know how it works and understand the over-unity factor. But it feels like it ought to take enormous energy for it to work at all.
I think specifically it's comparing gas heating vs AC. Heat pump heating would probably do better. In other words, it takes less energy to move heat inside/outside than to "create" it
(With caveats like heat pumps are much less effective in extreme cold)
I can't find a github or email for Hannah - if you're reading this i'd like to add Australian energy price data via Open Electricity[0] to the data (reach out via my profile)
Doesn't show the comparative energy waste of bitcoin?
This source[0] says
> One Bitcoin now requires 854,400 kilowatt-hours of electricity to produce. For comparison, the average U.S. home consumes about 10,500 kWh per year, according to the U.S. Energy Information Administration, April 2025, meaning that mining a single Bitcoin in 2026 uses as much electricity as 81.37 years of residential energy use.
OP says one query uses 0.3 Wh. Driving an electric car for 10 miles = 3,000 Wh which is roughly 10,000 Wh per hour.
I'm not sure how many queries is equivalent to an hour of Claude code use, but maybe 5 seconds, which means an hour of continuous use = 216 Wh, or ~50x less than an electric car.
It is not only about raw power consumption. Comparing driving an electric car with using AI only in kW hides a major point: Hyperscale datacenters are massively centralised, which brings it's own problems; a lot of energy is used for cooling, and water consumptions is enormous. Charging electric cars at home is distributed and does not suffer from the same problems as the centralised hyperscalers do. Also, running AI models at home is not much different than a gaming session :)
This is an incredible sequence of assertions, every single one of which is very incorrect.
"A lot of energy used for cooling": hyperscale data centers use the least cooling per unit of compute capacity, 2-3x less than small data centers and 10-100x less than a home computer.
"Water consumption is enormous": America withdraws roughly 300 billion gallons of fresh water daily, of which IT loads are expected to grow to 35-50 billion gallons annually by 2028. Data center water demands are less than a rounding error.
"distributed and does not suffer from the same problems": technically correct I guess but distributed consumption has its own problems that are arguably more severe than centralized power consumption.
This is neat. I think I'm actually more interested in avg ChatGPT query than median single query so that I can enter a large query # and be confident in the associated energy cost for that larger number (e.g. what's the energy cost for 1,000 chat gpt queries)
I like the comparison concept. It's like that "order of magnitudes every programmer should know" list, but applied to anyone who cares about energy.
That said, and hot take: people shouldn't worry about energy independent of what they pay for it. The whole point of a price is to fold a complicated manifold of scarcity-allocation into a set of scalars anyone can rank against each other. Appealing to people's sense of justice or duty to get them to use less energy than they'd otherwise be willing to buy is just asking them to lead a less utility-filled life than they can because you think you can allocate scarcity better than the market. I can't, and you can't either. Nobody can.
If you claim that people should listen to moralized pleadings and not the market because prices don't internalize certain externalities, duty is on you to get those externalities accounted so they can properly factor into prices, not apply ad-hoc patches on top of markets by manipulating people's emotions.
As for getting externalities internalized: as a society, we call the procedure for updating rules "politics", and it's as open to you as to anyone else. If you propose policy X and you can't get X enacted, perhaps it's because X is a bad idea, not because the system is broken.
Not everyone anyone claims is an externality is, in fact, a cost we must account. We should have a prior that costs are accounted and need evidence to rebut it --- and any such rebuttal must involve numbers, not emotional appeals. What specific costs are unaccounted? How large are these costs? Through what specific mechanism are they escaping existing accounting mechanisms? "I feel like we're using too many electrons for X" is not a valid argument for the existence of an unaccounted externality.
That is, unless there's some specific reason to believe otherwise, we should believe market get it right, especially with fungible commodities like kWh.
How do you propose to convince people to get those externalities accounted without emotions? How do you convince people of the value of externalities that are far away in place or time (but not less real)?
Your dismissal of moral concerns is not convincing.
Imagine a world where the only energy you do is use was generated by a stationary bike you had to ride yourself. You would, generally speaking, use that energy differently than energy you would pay for--you would generally reserve your effort for worthwhile things, and would be averse to farming energy yourself just to power frivolity or vice. How you determine what to put your energy into would explicitly be a moral question.
Instead in our world we an abstractions conceals the source of the energy. But if the moral concerns from the first world had any weight, they haven't lost it now; if energy is anything short of completely free we should by the same logic be averse to expending energy on worthless work or vice. The human being is not a utility monster, but something very different, and moral questions of this sort are central to how it navigates the world, they should not be dismissed.
Doesn't this argument hinge on equivocating between two different definitions of aversion, though? I'm averse to bananas, but that doesn't mean I think it's immoral to eat them. The moral dimension kicks in if somebody else had to ride that stationary bike for you, because then you'd be wasting their time on frivolities.
Of course I'd use energy differently if it cost more. If I had to generate energy by pedaling a bike, I'd consider it costly indeed. So what? Energy doesn't cost as much as it would if I had to manually generate it, and who are you to say allocation decisions made under that regiment are good and ones made under ours are bad?
Wouldn't your argument also compel us to use steel as if it were gold? Salt as if it were saffron?
> As for getting externalities internalized: as a society, we call the procedure for updating rules "politics", and it's as open to you as to anyone else.
Ok so I do need to worry about energy so that I can identify these unaddressed externalities and work towards updating the rules. You can to care before you can get involved in this stuff. You can't tell me not to worry about it and then also say that it's basically my fault for not getting involved if the price is wrong.
> any such rebuttal must involve numbers, not emotional appeals
Who are you arguing with? You're commenting about a website that has strictly numbers and nothing else.
What’s startling to me is how many comments in this thread just take the provided values as gospel without asking questions that methodology answers either in the abstract or barely describes. Also going giving a cost for “United States” is absolutely nonsense - electricity, gas and gasoline prices vary widely across the country. There is no one cost for each, and the average is worthless for this kind of thing (especially since the average of each - gas vs. electric vs. gasoline cost - are independent variables that have no relation to each other on a region by region basis).
My first question was: "Is this whitewashing LLM energy usage?"
And yes, that seems to be the undercurrent here. Complete with linking to themselves to validate the data they used to make their estimates.
Either these companies need to build these massive data centers that consume massive amounts of electricity OR these LLMs don't use a lot of electricity.
You don't get both. If LLMs don't require a lot of electricity, then why are we building so much more capacity? If all of that capacity is required, then what is the real cost of sending a query to these LLMs?
Hannah Ritchie is a quite well reputed writer and data scientist squarely in the climate field. She's written two books on climate and I found the one I read (Not The End of the World) was quite good and data-driven.
I'm not sure I understand where the issue is here - something can use a small amount of energy per use but a large amount in aggregate because of lots of use.
LLMs don't use a lot of electricity per user. Why should the fact that the energy usage happens in data centers instead of each user's house be an important moral factor?
You have set up a false conflict. The data centers are "huge" and they also consume about the same power as 1 airplane. These things are both true.
It is also not really true that they are huge, it is a misconception driven by biased reporting about facilities that really aren't very remarkable compared to material distribution warehouses, beverage bottling plants, and suchlike.
> You don't get both. If LLMs don't require a lot of electricity, then why are we building so much more capacity?
A small number times a large number is often a large number. Have you heard of the concept called "per capita"? In any case, electricity is going towards data centers in proportion to the degree to which these data centers do useful work. AI companies buy the electricity fairly on an open market, sometimes even subsidizing this market by funding new generating capacity.
If all these people and companies are making electricity allocation decisions that make sense to them with their own money, who are you to stop in and say that their voluntary transactions are incorrect? Who died and made you the king?
Useful work is debatable here, a lot of people just talk to the thing or use it instead of searching the internet.
The owners surely think, or at least want us to think that it is very useful indeed, otherwise we'd see no point in burning through piles of investors cash to buy overpriced ram, storage, gpus, cpus, nics, secure the power to run it and then subsidise the users to use it.
I do think that transaction is wrong and it's going to bite them in the ass in the long term, but I don't have the money to outbid them for the power. I do get to see them crash and burn when the investors get impatient.
They’re not even saying they shouldn’t do it or that they’re not useful or not worth it but you Cannot logically say both “these things do not use a lot of power” and “we need to build more power plants to handle these things”
It isn't all new capacity. The popular discourse hardly ever mentions it but AI is a small fraction of why we need new datacenters and the bulk of the demand is driven by general IT needs, particularly consolidation of small, grossly wasteful corporate data racks into vastly more efficient cloud services.
Edited to answer:
The question has also been addressed by the same author as the article: USA spent a quarter century not building generators and that negligence has finally caught up to us, despite objectively heroic efficiency efforts on the part of the IT sector.
Indeed, looking at a "single median query" totally disregard the fact that:
- first, those queries are mostly useless and we could totally do without them, so it's still a net pollution
- they are being integrated everywhere, so soon enough, just browsing the web for a few hours is going to general 100k+ such equivalent "small queries" (in the background, by the processes analyzing what the user is doing, or summarizing the page, etc). At that time, the added pollution is no longer negligible. And most of this will be done just to sell more ads
I attached a generator with some supercaps and an inverter to a stationary bicycle a few years ago, and even though I mostly use it as a way to feel less guilty watching Youtube videos, it does give me a quite literal feel for some of the items on the lower end of the scale.
- Anything even even halfway approaching a toaster or something with a heater in it is essentially impossible (yes, I know about that one video).
- A vacuum cleaner can be run for about 30 seconds every couple minutes.
- LED lights are really good, you can charge up the caps for a minute and then get some minutes of light without pedaling.
- Maybe I could keep pace with a fridge, but not for a whole day.
- I can do a 3D printer with the heated bed turned off, but you have to keep pedaling for the entire print duration, so you probably wouldn't want to do a 4 hour print. I have a benchy made on 100% human power.
- A laptop and a medium sized floor fan is what I typically run most days.
- A modern laptop alone, with the battery removed and playing a video is "too easy", as is a few LED bulbs or a CFL. An incandescent isn't difficult but why would you?
- A cellphone you could probably run in your sleep
Also gives a good perspective on how much better power plants are at this than me. All I've made in 4 years could be made by my local one in about 10 seconds, and cost a few dollars.
The author Hannah Ritchie works on Our World In Data and also publishes the fantastic Sustainability by Numbers substack. It's in the same vein as the late, great David MacKay's Sustainable Energy Without the Hot Air.
This tool has its own recent substack post. See the comments too, especially the one by Chris Preist that contextualizes the energy usage of streaming video (a topic that has also been discussed on HN before).
https://hannahritchie.substack.com/p/does-that-use-a-lot-of
And wrote a great book: Not the End of the World
Who pays for their research?
She's employed by Our World In Data. She is also a published author of printed books. Her substack does not have paid subscriptions enabled (or at least it did not as of last summer; see this post [1]). Our World In Data is funded by donations:
https://ourworldindata.org/funding
[1] https://hannahritchie.substack.com/p/reflections-on-substack
* https://en.wikipedia.org/wiki/Hannah_Ritchie
You would have to figure out where the grant money comes from for their department, but doesn't scream compromised to me.
One thing missing but important to understand is the energy embodied in buying 'stuff'. At a very rough approximation, the cost of stuff, especially consumer goods manufactured cheaply, is quite a high percentage energy.
When you look at people's energy usage, quite a lot of it ends up being the embodied energy in the stuff they buy. For quite a lot of people, it's probably the largest category of energy consumption. I once had a very rough go at calculating this here: https://www.robinlinacre.com/energy_usage/
I see it has a ChatGPT median query, but for those of us using coding agents this isn't so relevant.
Here's a post that makes an estimate:
https://www.simonpcouch.com/blog/2026-01-20-cc-impact/
> So, if I wanted to analogize the energy usage of my use of coding agents, it’s something like running the dishwasher an extra time each day, keeping an extra refrigerator, or skipping one drive to the grocery store in favor of biking there. To me, this is very different than, in Benjamin Todd’s words, “a terrible reason to avoid” this level of AI use. These are the sorts of things that would make me think twice.
I'm not sure it's even a particularly relevant comparison to an hour of use of various other electronic devices. I'm sure the median user is running a lot fewer queries than a Claude Code power-user, but I would guess it's still more than one in a typical session.
I think stuff like this really crystalises how people misunderstand how much energy stuff uses.
My parents for example sweat the small stuff and go around the house turning LED driven lights off to "save electricity" even though it would barely make a dent in their bill.
Granted, they come from a time of incadescants burning 60-100w at a time so I can see why that habit might be deeply ingrained.
It was genuinely a surprise to see how much relative energy petrol cars use (and shame on me - I'm an electrical engineer). I mean I think I knew it intuitively, but this simple chart blew my mind.
When one gets in the weeds on EVs or ICE cars two things become shockingly clear: internal combustion is hilariously inefficient YET gasoline is hilariously energy dense. Most people's intuition is wrong on both of these points but then they cancel each other out.
The tyranny if the rocket/horse equation: You need energy to carry the energy you need to move.
There's a good reason so many sprawling civilizations of the past involve leveraging wind-power for transport.
Train locomotives have used diesel powered generators that then powers electric motors. Would this be less efficient than battery powered EVs? Or better asked, what would be the most efficient use of gasoline?
[delayed]
Nissan makes a range of these under the e-power branding:
https://www.nissan-global.com/EN/INNOVATION/TECHNOLOGY/ARCHI...
When it comes to the environment the most efficient use is to leave it in the ground.
Hybrids work for trains because they are so large and don't need big swings of acceleration or to climb steep grades. They can run the diesel generators at maximum efficiency.
Battery power would be better, because you can build even larger power plants running at higher heats and not have to haul them with you, but the costs of sufficient battery is too large, so far. That is changing.
Isn't it better for trains to just to draw from the electric grid?
In Japan, my country, this looks a bit different. A lot of electricity still comes from oil- and gas-fired plants. The mechanics differ (gas turbines vs. car engines), but in both cases we’re still relying on combustion. I suppose some countries have the same issue.
The presentation is nice, but some of the conversions are questionable.
For instance: The cost section, wherein 1kWh in the US is figured as having a cost of 9.7 cents.
In reality, it's not that way at all. Unless we're fortunate enough to live in an area where we can walk over to the neighborhood generating station and carry home buckets of freshly-baked electricity to use at home, then we must also pay for delivery.
On average, in 2025, electricity was 17.3 cents per kiloWatt-hour -- delivered -- for residential customers in the US.
https://www.eia.gov/electricity/monthly/epm_table_grapher.ph...
Where did you see 9.7 cents per kWh? I looked at the electric car example for the United States. It has 3 kilowatt hours priced at $0.51, 17 cents per kilowatt hour, which seems about right.
Glad it has AI. AI has nothing on cars. Save a car trip a week even if electric is way more than 10k queries.
1 chatgpt query is a little misleading though. Let's see an 8 hour full bore claude code agent session. Or maybe running 3 agents for several hours a day.
[delayed]
chatgpt use should be in the default set since energy use of ai is so often in the news now - and more often in social media
Wow, putting everything in the same units is really informative. Running my 450 watt gpu for a day is approximately equivalent to driving a car 10 miles.
I doubt your 450w gpu runs at that wattage 24 hrs, unless you're mining with it.
My (admittedly old) gpu+CPU idles around 50-75w.
During training it’s running at around 410. But yeah idling at 450 would be pretty crazy.
For reference it would be good to have per-passenger numbers for "sitting on a diesel bus", "sitting on an electric bus", "sitting on a tram", "sitting on a commuter train" as well.
I'm surprised that cooling takes less energy than heating. I imagine that depends a lot on the temperature range; they only need so much to cool a room even on a "hot" day in the UK.
Still... AC still feels like magic. I know how it works and understand the over-unity factor. But it feels like it ought to take enormous energy for it to work at all.
I think specifically it's comparing gas heating vs AC. Heat pump heating would probably do better. In other words, it takes less energy to move heat inside/outside than to "create" it
(With caveats like heat pumps are much less effective in extreme cold)
Yeah without knowing the climate, temperature delta and insulation these values don't really mean much.
I can't find a github or email for Hannah - if you're reading this i'd like to add Australian energy price data via Open Electricity[0] to the data (reach out via my profile)
[0] https://explore.openelectricity.org.au/
Her github is here: https://github.com/HannahRitchie
thank you!
> Desktop computer - 1 hour of use - 50 Wh
That seems low...
Doesn't show the comparative energy waste of bitcoin?
This source[0] says
> One Bitcoin now requires 854,400 kilowatt-hours of electricity to produce. For comparison, the average U.S. home consumes about 10,500 kWh per year, according to the U.S. Energy Information Administration, April 2025, meaning that mining a single Bitcoin in 2026 uses as much electricity as 81.37 years of residential energy use.
[0] https://www.compareforexbrokers.com/us/bitcoin-mining/
One hour of Claude code— well, I’d guess it would be comparable to an hour of driving an electric car. How to know?
OP says one query uses 0.3 Wh. Driving an electric car for 10 miles = 3,000 Wh which is roughly 10,000 Wh per hour.
I'm not sure how many queries is equivalent to an hour of Claude code use, but maybe 5 seconds, which means an hour of continuous use = 216 Wh, or ~50x less than an electric car.
OP has a longer article about LLM energy usage: https://hannahritchie.substack.com/p/ai-footprint-august-202...
It is not only about raw power consumption. Comparing driving an electric car with using AI only in kW hides a major point: Hyperscale datacenters are massively centralised, which brings it's own problems; a lot of energy is used for cooling, and water consumptions is enormous. Charging electric cars at home is distributed and does not suffer from the same problems as the centralised hyperscalers do. Also, running AI models at home is not much different than a gaming session :)
This is an incredible sequence of assertions, every single one of which is very incorrect.
"A lot of energy used for cooling": hyperscale data centers use the least cooling per unit of compute capacity, 2-3x less than small data centers and 10-100x less than a home computer.
"Water consumption is enormous": America withdraws roughly 300 billion gallons of fresh water daily, of which IT loads are expected to grow to 35-50 billion gallons annually by 2028. Data center water demands are less than a rounding error.
"distributed and does not suffer from the same problems": technically correct I guess but distributed consumption has its own problems that are arguably more severe than centralized power consumption.
This is neat. I think I'm actually more interested in avg ChatGPT query than median single query so that I can enter a large query # and be confident in the associated energy cost for that larger number (e.g. what's the energy cost for 1,000 chat gpt queries)
I like the comparison concept. It's like that "order of magnitudes every programmer should know" list, but applied to anyone who cares about energy.
That said, and hot take: people shouldn't worry about energy independent of what they pay for it. The whole point of a price is to fold a complicated manifold of scarcity-allocation into a set of scalars anyone can rank against each other. Appealing to people's sense of justice or duty to get them to use less energy than they'd otherwise be willing to buy is just asking them to lead a less utility-filled life than they can because you think you can allocate scarcity better than the market. I can't, and you can't either. Nobody can.
If you claim that people should listen to moralized pleadings and not the market because prices don't internalize certain externalities, duty is on you to get those externalities accounted so they can properly factor into prices, not apply ad-hoc patches on top of markets by manipulating people's emotions.
As for getting externalities internalized: as a society, we call the procedure for updating rules "politics", and it's as open to you as to anyone else. If you propose policy X and you can't get X enacted, perhaps it's because X is a bad idea, not because the system is broken.
Not everyone anyone claims is an externality is, in fact, a cost we must account. We should have a prior that costs are accounted and need evidence to rebut it --- and any such rebuttal must involve numbers, not emotional appeals. What specific costs are unaccounted? How large are these costs? Through what specific mechanism are they escaping existing accounting mechanisms? "I feel like we're using too many electrons for X" is not a valid argument for the existence of an unaccounted externality.
That is, unless there's some specific reason to believe otherwise, we should believe market get it right, especially with fungible commodities like kWh.
How do you propose to convince people to get those externalities accounted without emotions? How do you convince people of the value of externalities that are far away in place or time (but not less real)?
Sure, by your own argument, you should somehow increase the price of people telling other people what to avoid spending money on
Your dismissal of moral concerns is not convincing.
Imagine a world where the only energy you do is use was generated by a stationary bike you had to ride yourself. You would, generally speaking, use that energy differently than energy you would pay for--you would generally reserve your effort for worthwhile things, and would be averse to farming energy yourself just to power frivolity or vice. How you determine what to put your energy into would explicitly be a moral question.
Instead in our world we an abstractions conceals the source of the energy. But if the moral concerns from the first world had any weight, they haven't lost it now; if energy is anything short of completely free we should by the same logic be averse to expending energy on worthless work or vice. The human being is not a utility monster, but something very different, and moral questions of this sort are central to how it navigates the world, they should not be dismissed.
Doesn't this argument hinge on equivocating between two different definitions of aversion, though? I'm averse to bananas, but that doesn't mean I think it's immoral to eat them. The moral dimension kicks in if somebody else had to ride that stationary bike for you, because then you'd be wasting their time on frivolities.
Of course I'd use energy differently if it cost more. If I had to generate energy by pedaling a bike, I'd consider it costly indeed. So what? Energy doesn't cost as much as it would if I had to manually generate it, and who are you to say allocation decisions made under that regiment are good and ones made under ours are bad?
Wouldn't your argument also compel us to use steel as if it were gold? Salt as if it were saffron?
How am I as an individual supposed to get externalities priced in?
And given that right now they are clearly not, what’s your plan until then?
Which specific externalities are you concerned about? Do they affect you directly?
Climate change and pollution, and yes they do.
> As for getting externalities internalized: as a society, we call the procedure for updating rules "politics", and it's as open to you as to anyone else.
Ok so I do need to worry about energy so that I can identify these unaddressed externalities and work towards updating the rules. You can to care before you can get involved in this stuff. You can't tell me not to worry about it and then also say that it's basically my fault for not getting involved if the price is wrong.
> any such rebuttal must involve numbers, not emotional appeals
Who are you arguing with? You're commenting about a website that has strictly numbers and nothing else.
What’s startling to me is how many comments in this thread just take the provided values as gospel without asking questions that methodology answers either in the abstract or barely describes. Also going giving a cost for “United States” is absolutely nonsense - electricity, gas and gasoline prices vary widely across the country. There is no one cost for each, and the average is worthless for this kind of thing (especially since the average of each - gas vs. electric vs. gasoline cost - are independent variables that have no relation to each other on a region by region basis).
Why are people so gullible?
My first question was: "Is this whitewashing LLM energy usage?"
And yes, that seems to be the undercurrent here. Complete with linking to themselves to validate the data they used to make their estimates.
Either these companies need to build these massive data centers that consume massive amounts of electricity OR these LLMs don't use a lot of electricity.
You don't get both. If LLMs don't require a lot of electricity, then why are we building so much more capacity? If all of that capacity is required, then what is the real cost of sending a query to these LLMs?
Hannah Ritchie is a quite well reputed writer and data scientist squarely in the climate field. She's written two books on climate and I found the one I read (Not The End of the World) was quite good and data-driven.
https://hannahritchie.com/
You're going to have to make a stronger case that this data is biased towards LLM than that.
I'm not sure I understand where the issue is here - something can use a small amount of energy per use but a large amount in aggregate because of lots of use.
What about it is whitewashing? This seems like it would be a great resource if you wanted to contextualize the argument you're gesturing at.
War is Peace,
Freedom is Slavery,
Facts are Whitewashing.
Much like when people discuss whether these companies are profitable: training costs don't count.
LLMs don't use a lot of electricity per user. Why should the fact that the energy usage happens in data centers instead of each user's house be an important moral factor?
You have set up a false conflict. The data centers are "huge" and they also consume about the same power as 1 airplane. These things are both true.
It is also not really true that they are huge, it is a misconception driven by biased reporting about facilities that really aren't very remarkable compared to material distribution warehouses, beverage bottling plants, and suchlike.
> You don't get both. If LLMs don't require a lot of electricity, then why are we building so much more capacity?
A small number times a large number is often a large number. Have you heard of the concept called "per capita"? In any case, electricity is going towards data centers in proportion to the degree to which these data centers do useful work. AI companies buy the electricity fairly on an open market, sometimes even subsidizing this market by funding new generating capacity.
If all these people and companies are making electricity allocation decisions that make sense to them with their own money, who are you to stop in and say that their voluntary transactions are incorrect? Who died and made you the king?
Useful work is debatable here, a lot of people just talk to the thing or use it instead of searching the internet.
The owners surely think, or at least want us to think that it is very useful indeed, otherwise we'd see no point in burning through piles of investors cash to buy overpriced ram, storage, gpus, cpus, nics, secure the power to run it and then subsidise the users to use it.
I do think that transaction is wrong and it's going to bite them in the ass in the long term, but I don't have the money to outbid them for the power. I do get to see them crash and burn when the investors get impatient.
It’s new capacity!
They’re not even saying they shouldn’t do it or that they’re not useful or not worth it but you Cannot logically say both “these things do not use a lot of power” and “we need to build more power plants to handle these things”
Yeah you can, though to be fair its referred to as jevons paradox because it is counterintuitive.
I’m not saying it’s inefficient. I’m saying cloud computing uses a lot of power.
It isn't all new capacity. The popular discourse hardly ever mentions it but AI is a small fraction of why we need new datacenters and the bulk of the demand is driven by general IT needs, particularly consolidation of small, grossly wasteful corporate data racks into vastly more efficient cloud services.
Edited to answer: The question has also been addressed by the same author as the article: USA spent a quarter century not building generators and that negligence has finally caught up to us, despite objectively heroic efficiency efforts on the part of the IT sector.
https://hannahritchie.substack.com/p/usa-electricity-growth
If so, why do they need to build new power plants for it?
Indeed, looking at a "single median query" totally disregard the fact that:
- first, those queries are mostly useless and we could totally do without them, so it's still a net pollution
- they are being integrated everywhere, so soon enough, just browsing the web for a few hours is going to general 100k+ such equivalent "small queries" (in the background, by the processes analyzing what the user is doing, or summarizing the page, etc). At that time, the added pollution is no longer negligible. And most of this will be done just to sell more ads
LLM calls are getting cheaper every day.