4 ms·

It took about 1GW to train Chat-GPT4. If you look at the locations in the United States (>70% of all AI is in the US), there are only ~63 geographic regions yo

It took about 1GW to train Chat-GPT4. If you look at the locations in the United States (>70% of all AI is in the US), there are only ~63 geographic regions you could put a 1GW data center. As AI models are growing at ~5x per year, it seems like the infrastructure is no in place to keep the AI models growing at that rate. As companies like Google, Meta, and others look to nuclear power (it has the highest up time of any power source), I'm wondering how localities are going to react. Are people who are local to nuclear plants just going to be OK with these gigantic corporations consuming all this power in their backyard with no benefit to them while they take all the risk and impact of that power generation? I'm also wondering how these companies are going to deal with the excess nuclear waste. Ultimately it won't be Google or Meta dealing with the waste. How do we ensure that all the nuclear waste from AI is dealt with responsibly?

steren 1y ago
GW is power. Gwh is energy. Energy is what matters when training a model. Please get your units right. In the meantime, down voted.
- kridsdale1 1y ago
  Upvoted for dimensional analysis pedantry.
- deleted 1y ago
  [deleted]
- barbazoo 1y ago
  > Please get your units right. In the meantime, down voted. I don’t think a reply like this is in the spirit of this site.
  - oijaefiojoijaw 1y ago
    But very in line with their bio... > Product Manager on Google Cloud Platform.
- mmmBacon 1y ago
  I think you missed the forest for the trees. I did incorrectly cite GPT-4 as I was going from memory and that's suspect sometimes. I also didn't elaborate and maybe I should have given the snarky comments I'm seeing. Actually the amount of power available matters because you are consuming energy in time. If I have a 1MW plant and a battery, I can generate 1GWh in about 3 weeks. This seems a little silly though. A Hyperscale DC campus is ~150MW to 200MW. If you plot the larger ones, they are almost all near power stations with >1GW capacity (not all). The industry trend is towards building 1GW datacenters. Last I checked these would consume ~8.7TWh (assuming PUE of 1). However, the 8.7TWh while relevant is meaningless unless the power to the DC can be 1GW. Since the plant itself has to generate more than 1GW (the plant has a cap ratio so more than this, plus other demand, etc..) for such a site, then it follows that there are limited number of sites in the US (this is public info see EIA.gov or Wikipedia). Grok3 is already at 140MW (100 days of training ==> 336GWh) at ~10^26 FLOP. Model FLOP is increasing at ~5x per year so by 2030, we are expecting to be ~10^28 and that would take ~10GW (24PWh). If I am optimistic and say that the efficiency can improve by 1.3x per year, then we still need a very large generating station to meet the demand or we need to distribute among many smaller sites. You can push the numbers around however you like but the conclusion is the same, the timing may be different. There's a reason why all the hyperscalers are investing in nuclear, large generating capacity and the highest cap factor of any form of energy. My 2nd comment still stands, and you left unaddressed (remember the forest?)..
kridsdale1 1y ago
Put all of it in the Greenland tundra. Free cooling. No humans to irradiate.
- barbazoo 1y ago
  The data centers too then? Because those need to be connected to the grid.
- advisedwang 1y ago
  Some challenges: - You get free cooling, but if you use too much you melt the permafrost, which has huge environmental cost. - Building in remote locations is enormously expensive, especially with the requirements of a nuclear generating station. - Now you have to run a city for the operators to live in and ship in everything they need (not to mention hardware to the DC. - Denmark (and so presumably Greenland) has a law against building nuclear generating stations. Besides, building nuclear power stations with the concept that we accept an accident will happen is crazy. Better to invest in preventing them than mitigating them.
XorNot 1y ago
GW is a unit of power, not a unit of energy. The best estimate I can find is 7.2GWh. Which would be...7 hours of output from a 1GW powerplant.
bongodongobob 1y ago
Bzzt, wrong units, this isn't Facebook. Go find some data to back up your obviously incorrect claim and fix your post.
jeffbee 1y ago
Training GPT-4 used (claimed) 62GW-h over 100 days, for an average of 26MW. Rest of your comment follows from this error. 26MW is a fraction of the primary power consumed by a single passenger aircraft, by the way. It is an absolutely trivial energy input.
- freshpots 1y ago
  It is not trivial at all, it's the same energy used as about 9,000 homes and roughly 50-100 L/s of water wasted to evaporative cooling of said hardware. "The Dongfang Electric Corporation's 26 MW offshore wind turbine is the largest in the world, surpassing previous models like the Mingyang 20 MW turbine. This turbine's larger size and capacity enable it to generate about 100 GWh of electricity annually, potentially powering 55,000 Chinese homes or 9,200 American homes." Edit: more info here, https://www.bloomberg.com/graphics/2025-ai-impacts-data-centers-water-data/ https://www.bloomberg.com/graphics/2025-ai-impacts-data-cent...
  - jeffbee 1y ago
    Your water use estimate is high by a large factor. Order of magnitude. Your claim: 50-100 liters per second to cool a 26MW workload. Actual water consumption, according to Google annual report: 730 liters per second, globally, for an average 3GW load.
- energywut 1y ago
  An average US home uses ~10,000 KWh over a year, resulting in about 1 kilowatt average power use. Figures I can find suggest that a 737 uses approximately 7MW to stay aloft. So a couple things I learned -- I think it's still a notable amount of power, enough to power ~6,000 homes for a year just to train a single model. But also, I learned that planes use a whole lot more power than I thought! Training a single model is essentially consuming one plane-year's worth of power, or 3-4 flights continuously while it trains. I had no idea planes used so much energy. But also, I bet most of these companies aren't training one model and calling it done. There's probably 1s or 10s of models being trained per year per company. That's a material amount of energy use. If we could power tens or hundreds of thousands of homes, that isn't 'trivial' energy input. I think it's useful to put it into context next to other things we take for granted, but I don't think it's fair to diminish it as nothing either.
r0m4n0 1y ago
What is the alternative though? I think it’s fair to question a decision but if people put their foot down when they don’t see the answer as good or clear enough then you end up with the status quo. This is the same thing that happened with housing (and building projects in general) in many larger cities. If all the housing projects are squashed for some decent alternative reason, you end up with the alternate reality which is potentially worse. City’s that have massive sprawl, people relying on cars for travel, unaffordable housing, etc. In the energy case, we will be more reliant on non nuclear power: coal, fossil fuel, etc. I’m not sure you can scale “clean energy” at the rate we are moving.
- bryanlarsen 1y ago
  The world added 600GW of solar last year, and is adding at a 1TW annualized rate. We do not have the capacity to add any other power source at that rate.
- epistasis 1y ago
  Clean energy is scaling far faster than gas. Coal is dead. Nuclear takes 10+ years, and the US industry is so small that it can not scale to meet future needs. Look at what was deployed last year, in GW terms: https://www.eia.gov/todayinenergy/detail.php?id=64586#:~:text=Solar%2C%20battery%20storage%20to%20lead%20new%20U.S.%20generating%20capacity%20additions%20in%202025,-Data%20source%3A%20U.S.&text=We%20expect%2063%20gigawatts%20(GW,Monthly%20Electric%20Generator%20Inventory%20report. https://www.eia.gov/todayinenergy/detail.php?id=64586#:~:tex... but note that gas produces at a capacity factor of ~50%, and solar at 25%, so scale solar down by half to better compare gas to solar. Batteries are also here in great force. The average cost of battery-backed solar is cheaper is comparable to gas, and cheaper than new nuclear. The main barrier to new solar and batteries are grid expansion to ship the electricity places. Putting a datacenter next to a proposed site for building solar + batteries that's waiting for its turn to get connected to the grid would probably be the fastest way to scale, if fiber can go there.
  - mmmBacon 1y ago
    The main problem with renewables is their capacity factor (amount of time they can produce their max capacity). In the US this is ~24%, in Germany I think it's ~12% (can be wrong here). The reason for nuclear here is that it has the highest capacity factor of any form of energy (see EIA.gov).

steren 1y ago

GW is power. Gwh is energy. Energy is what matters when training a model. Please get your units right. In the meantime, down voted.

kridsdale1 1y ago
Upvoted for dimensional analysis pedantry.
deleted 1y ago
[deleted]
barbazoo 1y ago
> Please get your units right. In the meantime, down voted. I don’t think a reply like this is in the spirit of this site.
- oijaefiojoijaw 1y ago
  But very in line with their bio... > Product Manager on Google Cloud Platform.
mmmBacon 1y ago
I think you missed the forest for the trees. I did incorrectly cite GPT-4 as I was going from memory and that's suspect sometimes. I also didn't elaborate and maybe I should have given the snarky comments I'm seeing. Actually the amount of power available matters because you are consuming energy in time. If I have a 1MW plant and a battery, I can generate 1GWh in about 3 weeks. This seems a little silly though. A Hyperscale DC campus is ~150MW to 200MW. If you plot the larger ones, they are almost all near power stations with >1GW capacity (not all). The industry trend is towards building 1GW datacenters. Last I checked these would consume ~8.7TWh (assuming PUE of 1). However, the 8.7TWh while relevant is meaningless unless the power to the DC can be 1GW. Since the plant itself has to generate more than 1GW (the plant has a cap ratio so more than this, plus other demand, etc..) for such a site, then it follows that there are limited number of sites in the US (this is public info see EIA.gov or Wikipedia). Grok3 is already at 140MW (100 days of training ==> 336GWh) at ~10^26 FLOP. Model FLOP is increasing at ~5x per year so by 2030, we are expecting to be ~10^28 and that would take ~10GW (24PWh). If I am optimistic and say that the efficiency can improve by 1.3x per year, then we still need a very large generating station to meet the demand or we need to distribute among many smaller sites. You can push the numbers around however you like but the conclusion is the same, the timing may be different. There's a reason why all the hyperscalers are investing in nuclear, large generating capacity and the highest cap factor of any form of energy. My 2nd comment still stands, and you left unaddressed (remember the forest?)..

kridsdale1 1y ago

Put all of it in the Greenland tundra. Free cooling. No humans to irradiate.

barbazoo 1y ago
The data centers too then? Because those need to be connected to the grid.
advisedwang 1y ago
Some challenges: - You get free cooling, but if you use too much you melt the permafrost, which has huge environmental cost. - Building in remote locations is enormously expensive, especially with the requirements of a nuclear generating station. - Now you have to run a city for the operators to live in and ship in everything they need (not to mention hardware to the DC. - Denmark (and so presumably Greenland) has a law against building nuclear generating stations. Besides, building nuclear power stations with the concept that we accept an accident will happen is crazy. Better to invest in preventing them than mitigating them.

XorNot 1y ago

GW is a unit of power, not a unit of energy. The best estimate I can find is 7.2GWh. Which would be...7 hours of output from a 1GW powerplant.

bongodongobob 1y ago

Bzzt, wrong units, this isn't Facebook. Go find some data to back up your obviously incorrect claim and fix your post.

jeffbee 1y ago

Training GPT-4 used (claimed) 62GW-h over 100 days, for an average of 26MW. Rest of your comment follows from this error. 26MW is a fraction of the primary power consumed by a single passenger aircraft, by the way. It is an absolutely trivial energy input.

freshpots 1y ago
It is not trivial at all, it's the same energy used as about 9,000 homes and roughly 50-100 L/s of water wasted to evaporative cooling of said hardware. "The Dongfang Electric Corporation's 26 MW offshore wind turbine is the largest in the world, surpassing previous models like the Mingyang 20 MW turbine. This turbine's larger size and capacity enable it to generate about 100 GWh of electricity annually, potentially powering 55,000 Chinese homes or 9,200 American homes." Edit: more info here, https://www.bloomberg.com/graphics/2025-ai-impacts-data-centers-water-data/ https://www.bloomberg.com/graphics/2025-ai-impacts-data-cent...
- jeffbee 1y ago
  Your water use estimate is high by a large factor. Order of magnitude. Your claim: 50-100 liters per second to cool a 26MW workload. Actual water consumption, according to Google annual report: 730 liters per second, globally, for an average 3GW load.
energywut 1y ago
An average US home uses ~10,000 KWh over a year, resulting in about 1 kilowatt average power use. Figures I can find suggest that a 737 uses approximately 7MW to stay aloft. So a couple things I learned -- I think it's still a notable amount of power, enough to power ~6,000 homes for a year just to train a single model. But also, I learned that planes use a whole lot more power than I thought! Training a single model is essentially consuming one plane-year's worth of power, or 3-4 flights continuously while it trains. I had no idea planes used so much energy. But also, I bet most of these companies aren't training one model and calling it done. There's probably 1s or 10s of models being trained per year per company. That's a material amount of energy use. If we could power tens or hundreds of thousands of homes, that isn't 'trivial' energy input. I think it's useful to put it into context next to other things we take for granted, but I don't think it's fair to diminish it as nothing either.

r0m4n0 1y ago

What is the alternative though? I think it’s fair to question a decision but if people put their foot down when they don’t see the answer as good or clear enough then you end up with the status quo. This is the same thing that happened with housing (and building projects in general) in many larger cities. If all the housing projects are squashed for some decent alternative reason, you end up with the alternate reality which is potentially worse. City’s that have massive sprawl, people relying on cars for travel, unaffordable housing, etc. In the energy case, we will be more reliant on non nuclear power: coal, fossil fuel, etc. I’m not sure you can scale “clean energy” at the rate we are moving.

bryanlarsen 1y ago
The world added 600GW of solar last year, and is adding at a 1TW annualized rate. We do not have the capacity to add any other power source at that rate.
epistasis 1y ago
Clean energy is scaling far faster than gas. Coal is dead. Nuclear takes 10+ years, and the US industry is so small that it can not scale to meet future needs. Look at what was deployed last year, in GW terms: https://www.eia.gov/todayinenergy/detail.php?id=64586#:~:text=Solar%2C%20battery%20storage%20to%20lead%20new%20U.S.%20generating%20capacity%20additions%20in%202025,-Data%20source%3A%20U.S.&text=We%20expect%2063%20gigawatts%20(GW,Monthly%20Electric%20Generator%20Inventory%20report. https://www.eia.gov/todayinenergy/detail.php?id=64586#:~:tex... but note that gas produces at a capacity factor of ~50%, and solar at 25%, so scale solar down by half to better compare gas to solar. Batteries are also here in great force. The average cost of battery-backed solar is cheaper is comparable to gas, and cheaper than new nuclear. The main barrier to new solar and batteries are grid expansion to ship the electricity places. Putting a datacenter next to a proposed site for building solar + batteries that's waiting for its turn to get connected to the grid would probably be the fastest way to scale, if fiber can go there.
- mmmBacon 1y ago
  The main problem with renewables is their capacity factor (amount of time they can produce their max capacity). In the US this is ~24%, in Germany I think it's ~12% (can be wrong here). The reason for nuclear here is that it has the highest capacity factor of any form of energy (see EIA.gov).