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Estimating AI energy use

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Re: Estimating AI energy use

#31

Post by qnleigh »

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 Tokyo: ~1,000,000 Wh

[1] https://ourworldindata.org/energy-production-consumption

[2] https://www.beveragedaily.com/Article/2008/03/17/study-finds...

[3] https://www.foxway.com/wp-content/uploads/2024/05/handprint-...

Re: Estimating AI energy use

#32

Post by ugurs »

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.

Re: Estimating AI energy use

#33

Post by s0rce »

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…

180,000 TWh total since the start of time or per year?

Re: Estimating AI energy use

#34

Post by kurthr »

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.

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.

Re: Estimating AI energy use

#35

Post by XorNot »

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.

Because electricity prices are an auction, so increased demand is bidding up the price anyway.

You need strong residential consumer protections to avoid this.

Re: Estimating AI energy use

#36

Post by blueblisters »

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.

> consumers paying for electricity used by server farms

wait what? consumers are literally paying for server farms? this isn't a supply-demand gap?

Re: Estimating AI energy use

#37

Post by kurthr »

s0rce wrote: post #33
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…

180,000 TWh total since the start of time or per year?

It was 170,000 TWh annually in 2021.

Re: Estimating AI energy use

#38

Post by blondie9x »

yen223 wrote: post #25
a_wild_dandan wrote: post #20

Earlier quoted context omitted.

I would bet that it's far lower now. Inference is expensive we've made extraordinary efficiency gains through techniques like distillation. That said, GPT-5 is a reasoning model, and those are notorious for high token burn. So who knows, it could be a wash. But selective pressures to optimize for scale/growth/revenue/independence from MSFT/etc makes me think that OpenAI is chasing those watt-hours pretty doggedly. So…

Yeah, something we are confident about is that a) training is where the bulk of an AI system's energy usage goes (based on a report released by Mistral) b) video generation is very likely a few orders of magnitude more expensive than text generation. That said, I still believe that data centres in general - including AI ones - don't consume a significant amount of energy compared with everything else we do, especiall…

You gotta start thinking about the energy used to mine and refine the raw materials used to make the chips and GPUs. Then take into account the infrastructure and data centers.

The amount of energy is insane.

Re: Estimating AI energy use

#39

Post by blueblisters »

Math comparing new datacenter capacity to electric cars -

Projections estimate anywhere between 10GW to 30GW of US datacenter buildup over the next few years

1GW of continuous power can support uniform draw from ~2.6M Tesla Model 3s assuming 12,000 miles per year, 250Wh/mile.

So 26M on the lower end, 80M Model 3s on the upper end.

That's 10x-30x the cumulative number of Model 3s sold so far

And remember all datacenter draw is concentrated. It will disproportionately going to impact regions where they're being built.

We need new, clean power sources yesterday

Re: Estimating AI energy use

#40

Post by KPGv2 »

geuis wrote: post #11

My thoughts. Current gen AI is going to result in the excess datacenter equivalent of dark fiber from the 2000's. Lots of early buildout and super investment, followed by lack of customer demand and later cheaper access to physical compute. The current neural network software architecture is pretty limited. Hundreds of billions of dollars of investor money has gone into scaling backprop networks and we've quickly hit…

> There's probably some interesting new architectures already in the works either from postdocs or in tiny startups

It is not clear to me why we will have a breakthrough after virtually no movement on this front for decades. Backpropagation is literally 1960s technology.

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