Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Estimating AI energy use

spectrum.ieee.org

Post reply on HN
Print view View original

51–60 of 104 posts

Re: Estimating AI energy use

#51

Post by lovecg »

epistasis wrote: post #41
ch4s3 wrote: post #27

Earlier quoted context omitted.

I wouldn’t be so sure about that. Serves of the big names in this space have green energy pledges and are actively building out nuclear power.

Nobody is actively building out nuclear power. Microsoft is turning on a recently decommissioned facility. New nuclear is too expensive to make sense. At most there are small investments in flash-in-the-pan startups that are failing to deliver plans for small modular reactors. The real build out that will happen is solar/wind with tons of batteries, which is so commonplace that it doesn't even make the news. Those ca…

> The real build out that will happen is solar/wind with tons of batteries

That actually sounds awesome, is there a downside I’m not seeing?

Re: Estimating AI energy use

#52

Post by quaintdev »

gaoshan wrote: post #14

One thing it's doing is jacking up electricity rates for US States that are part of the [PJM Interconnection grid]( https://en.wikipedia.org/wiki/PJM_Interconnection ). It's a capacity auction price that is used to guarantee standby availability and it is [up significantly]( https://www.toledochamber.com/blog/watts-up-why-ohios-electr... ) at $270.43 per MW/day, which is far above prior years (~$29–58/MW/day) and thi…

In India, we have different energy consumption bands like 0-200kWh, 200-400kWh and so on. People whose consumption is in 0-200kWh pay less as compared to 200-400kWh and so on.

Re: Estimating AI energy use

#53

Post by Ekaros »

givemeethekeys wrote: post #18
gaoshan wrote: post #14

One thing it's doing is jacking up electricity rates for US States that are part of the [PJM Interconnection grid]( https://en.wikipedia.org/wiki/PJM_Interconnection ). It's a capacity auction price that is used to guarantee standby availability and it is [up significantly]( https://www.toledochamber.com/blog/watts-up-why-ohios-electr... ) at $270.43 per MW/day, which is far above prior years (~$29–58/MW/day) and thi…

Why are consumers paying for electricity used by server farms? Why can't the electricity companies charge the server farms instead? Where I live, the utility company bills you at a higher rate if you use more electricity.

Are they paying for electricity used by server farms. Or are they just paying more profits for owners of electricity producers? Do server farms get electricity below market price?

Ofc, possible long term contracts and options are involved in some of these markets. But there the option sellers would bear the cost.

Re: Estimating AI energy use

#54

Post by justlikereddit »

givemeethekeys wrote: post #18
gaoshan wrote: post #14

One thing it's doing is jacking up electricity rates for US States that are part of the [PJM Interconnection grid]( https://en.wikipedia.org/wiki/PJM_Interconnection ). It's a capacity auction price that is used to guarantee standby availability and it is [up significantly]( https://www.toledochamber.com/blog/watts-up-why-ohios-electr... ) at $270.43 per MW/day, which is far above prior years (~$29–58/MW/day) and thi…

Why are consumers paying for electricity used by server farms? Why can't the electricity companies charge the server farms instead? Where I live, the utility company bills you at a higher rate if you use more electricity.

This is a recurrent question and not just for servers.

In Europe it is constantly >"why does the households of half of Europe pay for German unwillingness to have a good power mix? Why should anyone want more cross country or long range interconnects if it drives up local prices?"

Say Norway with abundant hydropower, they should by all right have cheap power. But reality is not so in half of the country because they're sufficiently interconnected to end up on a common bidders euro market and end up paying blood money for the poor political choices of countries they don't even share a border with.

Addition: this also creates perverse incentives. A good solution for many of the interconnected flat euro countries would love enormous hydropower overcapacity to be built in Norway at the cost of the local nature. This is great for whoever sells the hydropower. This is great for whoever is a politician that can show off their green all-hydro power mix in a country as hilly as a neutron star. But this is not great for whoever gets their backyard hiking trails reduced to a hydro reservoir.

But hey we do it with everything else too, "open pit mines are too destructive to have in our country, so we'll buy it from china and pretend we're making green choice. Globalism in a nutshell: Export your responsibility.

Re: Estimating AI energy use

#55

Post by globular-toast »

kurthr wrote: post #34
ugurs wrote: post #32

Earlier quoted context omitted.

Without knowing the cumulative amount of energy consumption it is not a fair comparison. If there are one billion llm sessions every day, it is still a lot of energy.

No, not really. A billion people (15% of the population) drive more than a mile a day. Well over 100 million laptops are sold every year. These are easy numbers to look up. Just look at your own life and see how much of each you would use.

So do LLMs mean fewer people have to drive a mile every day?

Re: Estimating AI energy use

#56

Post by tylervigen »

gaoshan wrote: post #14

One thing it's doing is jacking up electricity rates for US States that are part of the [PJM Interconnection grid]( https://en.wikipedia.org/wiki/PJM_Interconnection ). It's a capacity auction price that is used to guarantee standby availability and it is [up significantly]( https://www.toledochamber.com/blog/watts-up-why-ohios-electr... ) at $270.43 per MW/day, which is far above prior years (~$29–58/MW/day) and thi…

One thing we should be careful about regarding calculations related to the larger set of "all data centers" vs only "GenAI" is that the data centers include all the predictive algorithms for social media and advertising. I, for one, would not want to misdirect ire at ChatGPT that really belongs directed at ads.

Re: Estimating AI energy use

#57

Post by exitb »

globular-toast wrote: post #55
kurthr wrote: post #34

Earlier quoted context omitted.

No, not really. A billion people (15% of the population) drive more than a mile a day. Well over 100 million laptops are sold every year. These are easy numbers to look up. Just look at your own life and see how much of each you would use.

So do LLMs mean fewer people have to drive a mile every day?

These don't have to be dependent to be meaningful.

Re: Estimating AI energy use

#58

Post by qnleigh »

ugurs wrote: post #32
qnleigh wrote: post #31

For reference, global energy consumption is about 180,000 TWh[1]. So while the numbers in this article are large, they're not a significant fraction of the total. Traveling and buying things are probably a much bigger part of your carbon footprint. For example: - 25 LLM queries: ~8.5 Wh - driving one mile: ~250-1000 Wh - one glass bottle: ~1000 Wh [2] - a new laptop: ~600,000 Wh [3] - round-trip flight from LA to Tok…

Without knowing the cumulative amount of energy consumption it is not a fair comparison. If there are one billion llm sessions every day, it is still a lot of energy.

Yes quoting energy use per query isn't the full picture, though it is still a useful benchmark for understanding the relative impact of one's use as an individual. As for cumulative impact, the ieee article gives an estimate of 347 TWh per year by 2030, which is still a very small fraction of global energy consumption today.

Re: Estimating AI energy use

#59

Post by logicallee »

The energy used for manufacturing the datacenters including the GPU's must also be rather high. Manufacturing is an energy-intensive sector.

Edit: I asked ChatGPT-5:

https://chatgpt.com/share/68e36c19-a9a8-800b-884e-48fafbe0ec...

it says:

>the manufacturing of GPUs and datacenters themselves consumes a large amount of energy, not just their operation. The operational energy use (for AI training, inference, cooling, etc.) gets most of the attention, but the embodied energy — the energy used to extract raw materials, manufacture chips and components, and construct facilities — is substantial.

and summarizes it with:

    4. Bottom Line

     • Manufacturing GPUs and datacenters is highly energy-intensive, but operational energy dominates over time.
     • For a single GPU, embodied energy ≈ 0.5–1 MWh.
     • For a datacenter, embodied energy ≈ 6–12 months of its operational energy.
     • Given AI-scale deployments (millions of GPUs), the embodied manufacturing energy already reaches terawatt-hours globally — roughly comparable to the annual electricity use of a small country.

Re: Estimating AI energy use

#60

Post by dayjaby »

qnleigh wrote: post #31

For reference, global energy consumption is about 180,000 TWh[1]. So while the numbers in this article are large, they're not a significant fraction of the total. Traveling and buying things are probably a much bigger part of your carbon footprint. For example: - 25 LLM queries: ~8.5 Wh - driving one mile: ~250-1000 Wh - one glass bottle: ~1000 Wh [2] - a new laptop: ~600,000 Wh [3] - round-trip flight from LA to Tok…

What about LLM training? What about training all the discarded or unused LLMs?
Post reply on HN