The funniest part is beyond the typo, the complete lack of physical intuition from the analysts who circulated this. 500,000 tons is roughly the weight of 1.5 Empire State buildings. If your rack busbars weigh more than the structural steel of the facility housing them, you have a geotechnical engineering crisis on your hands. It is wild that we reached a point where financial modeling is so decoupled from physical reality that nobody paused to ask if the floor would collapse.
The world of financial analysis and modeling is broad. It’s common to give these tasks to juniors and expect them to grind through it when the output doesn’t really matter.
In this case the output wasn’t actually used for financial modeling. If it had been, it would have been caught immediately when someone put it into a table where they calculated the price or the supply constraints or anything else.
I wouldn't be surprised if that part was not really reviewed by an expert. They have the unit mass correct but maybe an editor is like ok but what does this look like for a gw project? It doesn't take more than 3rd grade math and a pocket calculator to do it correctly but journalist hasn't had to fumble that ball before. An expert knows its all too easy for any person to make that mistake and would second guess their own work.
With regards to the copper market: it keeps surprising me that some people seem to assume copper is a hard requirement for conducting electricity.
In reality copper is just convenient. We use it because it's easy to work with, a great conductor, and (until recently) quite affordable. But for most applications there's no reason we couldn't use something else!
For example, a 1.5mm2 copper conductor is 0.0134kg/m, which at current prices is $0.17 / meter. A 2.4mm2 aluminum conductor has the same resistance, weighs 0.0065kg/m, which at current prices is $0.0195 / meter!
Sure, aluminum is a pain to work with, but with a price premium like that there's a massive incentive to find a way to make it work.
Copper can't get too expensive simply due to power demands because people will just switch to aluminum. The power grid itself had been using it for decades, after all - some internal datacenter busbars should be doable as well.
I am not an electricity/wiring guy so maybe you can help me understand. I thought aluminum is dangerous to wire with because it is a fire hazard (I bought a home this year and this was a prominent warning in my reading). Is that because it needs to be done very carefully? I imagine most data centers would not mess with a fire risk on such a scale.
Residential aluminum is a Really Bad Idea because DIY Dave will inevitably do something wrong - which then leads to a fire hazard. Copper is a lot more forgiving.
But a large scale datacenter, solar farm, or battery storage installation? Those will be installed and maintained by trained electricians, which means they actually know what a "torque wrench" is, and how to deal with scary words like "corrosion" and "oxidation".
Like I said: it's what's used for most of the power grid. With the right training it really isn't a big deal.
Aluminum oxide has high resistance and if you mix aluminum wiring with copper outlets, etc the impedance mismatched is what causes fires. You need to either have special copper pigtails installed or use fixtures that are rated for aluminum wiring.
For commercial installs, it shouldn't be a problem as long as it's planned for.
Unless I'm mistaken, the risk with aluminum is that it can expand and contract if it gets too hot. Aluminum sized properly with the correct connectors torqued to spec would be fine, aluminum wires in a residence with a DIYer working on it can be riskier and is why inspectors will always note it.
Old aluminum wiring in your walls with cloth insulators, designed for a time where electricity consumption was a small fraction of today's electrified usage is dangerous because you're overloading an old, unprepared system.
Aluminum bus bars(solid, often exposed) would be designed for the required power levels and installation criteria.
It's because aluminium has a higher coefficient of thermal expansion. It expands and shrinks more as it heats, and as those cycles add up it tends to loosen electrical connections. Loose connections have higher resistance, heat up and can cause fires.
That said, there is no reason we can't design better connectors that can withstand the expansion and shrinkage cycles, like spring loaded or spring cage connectors.
Aluminum wires became brittle over time(tens of years), fluid which requires some maintenance for screw terminals and inducts galvanic corrosion when coupled with copper without special care. If wiring was properly done and maintained, it is okayish.
It’s a fire hazard in residential houses where people frequently do their own wiring, because it needs more expertise to wire correctly. Copper wiring is a lot more forgiving to being hooked up by amateurs.
The biggest reason is that aluminum oxidizes, and unlike copper, the oxide layer has high resistivity. In theory that shouldn’t be an issue in datacenters hiring expert technicians.
That's why my calculation example used a 1.5mm2 copper wire but a 2.4mm2 aluminum one.
Aluminum has a higher resistance, which means the same diameter will get hotter than copper. Make the cable thicker and its resistance drops, which means it gets less hot.
Want more amps at the same temperature? Ohm's law still applies: just use a thicker cable.
If the two wires are the same gauge, yes. If you size up the aluminum, at the same resistance/current would mean the same amount of power over the length of the conductor and same heat.
Thicker cables or higher voltage(lower current) is the answer which is why it's used in power distribution networks where they can control the voltage by planning what to transform to.
I would imagine most large-scale data center construction projects will include electrical engineers to design the electrical subsystem. A rack's floor footprint is a few square feet. You can put several million dollars of hardware into that rack. A data center will have at least a few racks. It's a very reasonable investment to bring someone in to do electrical design.
This sort of mistake is easy to make when you're mixing up your units; if they kept to one system of measure, it would've been trivial to catch, before or after release.
We need to standardize on using Earth circumferences as the unit of length. Or better, football fields! (the type of football of course being implied by the website's ccTLD)
We _have_ standardized on Earth circumferences for length, only we divide by 40 million to make the numbers more sane, and got the measurement slightly wrong!
You jest, but times around the Earth is the actual origin of the Meter. Kinda.
The history is quite interesting and well worth checking out.
I can't recommend a book on the subject, but I do heartily recommend "Longitude", which is about the challenges of inventing the first maritime chronometers for the purpose of accurately measuring longitude.
> If the "half a million tons" figure were accurate, a single 1 GW data center would consume 1.7% of the world's annual copper supply. If we built 30 GW of capacity—a reasonable projection for the AI build-out—that sector alone would theoretically absorb almost half of all the copper mined on Earth.
Quickly doing such "back of an envelope" calculations, and calling out things that seem outlandish, could be a useful function of an AI assistant.
Using your brain is so vastly more energy efficient, we might just only need half of that 30 GW capacity if fewer people had these leftpad-style knee-jerk reactions.
Each person uses about 100W (2000kcal/24h=96W). Running all of humanity takes about 775GW.
Sure, using or not using your brain is a negligible energy difference, so if you aren't using it you really should, for energy efficiency's sake. But I don't think the claim that our brains are more energy efficient is obviously true on its own. The issue is more about induced demand from having all this external "thinking" capacity on your fingertips
I did some math for this particular case by asking Google’s Gemini Pro 3 (via AI studio) to evaluate the press release. Nvidia has since edited the release to remove the “tons of copper” claim, but it evaluated the other numbers at a reported API cost of about 3.8 cents. If the stated pricing just recovers energy cost, that implies 1500kJ of energy as a maximum (less if other costs are recovered in the pricing). A human thinking for 10 minutes would use sbout 6kJ of direct energy.
I agree with your point about induced demand. The “win” wouldn’t be looking at a single press release with already-suspect numbers, but rather looking at essentially all press releases of note, a task not generally valuable enough to devote people towards.
That being said, we normally consider it progress when we can use mechanical or electrical energy to replace or augment human work.
Is there an AI system with functionality at or equal to a human brain that operates on less than 100W? Its currently the most efficient model we have. You compare all of humanity's energy expenditure, but to make the comparison, you need to consider the cost of replicating all that compute with AI (assuming we had an AGI at human level in all regards, or a set of AIs that when operated together could replace all human intelligence).
No one will ever agree on when AI systems have equivalent functionality to a human brain. But lots of jobs consist of things a computer can now do for less than 100W.
Also, while a body itself uses only 100W, a normal urban lifestyle uses a few thousand watts for heat, light, cooking, and transportation.
> Also, while a body itself uses only 100W, a normal urban lifestyle uses a few thousand watts for heat, light, cooking, and transportation.
Add to that the tier-n dependencies this urban lifestyle has—massive supply chains sprawling across the planet, for example involving thousands upon thousands of people and goods involved in making your morning coffee happen.
Wikipedia quoted global primary energy production at 19.6 TW, or about 2400W/person. Which is obviously not even close to equally distributed. Per-country it gets complicated quickly, but naively taking the total from [1] brings the US to 9kW per person.
And that's ignoring sources like food from agriculture, including the food we feed our food
Obviously we don't have AGI so we can't compare many tasks. But on tasks where AI does perform at comparable levels (certain subsets of writing, greenfield coding and art) it performs fairly well. They use more power but are also much faster, and that about cancels out. There are plenty of studies that try to put numbers on the exact tradeoff, usually focused more on CO2. Plenty that find AI better by some absurd degree (800 times more efficient at 3d modelling, 130 to 1500 times more efficient at writing, or 300 to 3000 times more efficient at illustrating [1]). The one I'd trust the most is [2] where GPT4 was 5-19 times less CO2 efficient than humans at solving coding challenges
A Gemini query uses about a kilojoule. The brain runs at 20 W (though the whole human costs 100 W). So, the human is less energy if you can get it done in under 50 seconds.
It's almost always the engineers, analysts and MBA spreadsheet pushers and other people removed from the physical consequences outputting these mistakes because it's way easier to not notice a misplaced decimal or incorrect value when you deal in pure numbers and know what they "should" be than you are the person actually figuring out how to make it happen the difference between needing 26666666.667 and 266666666.667 <units> of <widget> is pretty meaningful. Engineers don't output these mistakes as often as analysts or whatever because they work in organizations that invest more in catching them, not because they make them all that much less.
Whether talking weight or bulk a decimal place is approximately the difference between needing a wheelbarrow, a truck, a semi truck, a freight train and a ship.
Checking the arithmetic in every paper published seems like an good use case for LLMs. Has someone built a better version than uploading a PDF to ChatGPT and asking it to check the arithmetic?
Modern reasoning models are actually pretty good at arithmetic and almost certainly would have caught this error if asked.
Source: we benchmark this sort of stuff at my company and for the past year or so frontier models with a modest reasoning budget typically succeed at arithmetic problems (except for multiplication/division problems with many decimal places, which this isn't).
ChatGPT 5.2 has recently been churning through unsolved Erdös problems.
I think right now one is partially validated by a pro and the other one I know of is "ai-solved" but not verified. As in: we're the ones who can't quite keep up.
Yes, yes. We’ve all seen the same screenshots. Very funny.
Those of us who don’t base our technical understandings on memes are well aware of the tooling at the disposal of all modern reasoning models gives them the capability to do such things.
In this case the output wasn’t actually used for financial modeling. If it had been, it would have been caught immediately when someone put it into a table where they calculated the price or the supply constraints or anything else.
In reality copper is just convenient. We use it because it's easy to work with, a great conductor, and (until recently) quite affordable. But for most applications there's no reason we couldn't use something else!
For example, a 1.5mm2 copper conductor is 0.0134kg/m, which at current prices is $0.17 / meter. A 2.4mm2 aluminum conductor has the same resistance, weighs 0.0065kg/m, which at current prices is $0.0195 / meter!
Sure, aluminum is a pain to work with, but with a price premium like that there's a massive incentive to find a way to make it work.
Copper can't get too expensive simply due to power demands because people will just switch to aluminum. The power grid itself had been using it for decades, after all - some internal datacenter busbars should be doable as well.
Residential aluminum is a Really Bad Idea because DIY Dave will inevitably do something wrong - which then leads to a fire hazard. Copper is a lot more forgiving.
But a large scale datacenter, solar farm, or battery storage installation? Those will be installed and maintained by trained electricians, which means they actually know what a "torque wrench" is, and how to deal with scary words like "corrosion" and "oxidation".
Like I said: it's what's used for most of the power grid. With the right training it really isn't a big deal.
For commercial installs, it shouldn't be a problem as long as it's planned for.
Aluminum bus bars(solid, often exposed) would be designed for the required power levels and installation criteria.
That said, there is no reason we can't design better connectors that can withstand the expansion and shrinkage cycles, like spring loaded or spring cage connectors.
The biggest reason is that aluminum oxidizes, and unlike copper, the oxide layer has high resistivity. In theory that shouldn’t be an issue in datacenters hiring expert technicians.
Aluminum has a higher resistance, which means the same diameter will get hotter than copper. Make the cable thicker and its resistance drops, which means it gets less hot.
Want more amps at the same temperature? Ohm's law still applies: just use a thicker cable.
Look at the electrical fires of the 1950’s and 1960’s as an example, and that was at household levels of current.
Aluminum is used, but everything accounts for the insane coefficient of linear expansion and other annoying properties.
The history is quite interesting and well worth checking out.
I can't recommend a book on the subject, but I do heartily recommend "Longitude", which is about the challenges of inventing the first maritime chronometers for the purpose of accurately measuring longitude.
It's not the most aesthetic one, but it was at the time the most able to be measured.
Quickly doing such "back of an envelope" calculations, and calling out things that seem outlandish, could be a useful function of an AI assistant.
Sure, using or not using your brain is a negligible energy difference, so if you aren't using it you really should, for energy efficiency's sake. But I don't think the claim that our brains are more energy efficient is obviously true on its own. The issue is more about induced demand from having all this external "thinking" capacity on your fingertips
I agree with your point about induced demand. The “win” wouldn’t be looking at a single press release with already-suspect numbers, but rather looking at essentially all press releases of note, a task not generally valuable enough to devote people towards.
That being said, we normally consider it progress when we can use mechanical or electrical energy to replace or augment human work.
Also, while a body itself uses only 100W, a normal urban lifestyle uses a few thousand watts for heat, light, cooking, and transportation.
Add to that the tier-n dependencies this urban lifestyle has—massive supply chains sprawling across the planet, for example involving thousands upon thousands of people and goods involved in making your morning coffee happen.
And that's ignoring sources like food from agriculture, including the food we feed our food
https://www.eia.gov/energyexplained/us-energy-facts/
1: https://www.nature.com/articles/s41598-024-54271-x?fromPaywa...
2: https://www.nature.com/articles/s41598-025-24658-5
Whether talking weight or bulk a decimal place is approximately the difference between needing a wheelbarrow, a truck, a semi truck, a freight train and a ship.
https://developer.nvidia.com/blog/nvidia-800-v-hvdc-architec...
Source: we benchmark this sort of stuff at my company and for the past year or so frontier models with a modest reasoning budget typically succeed at arithmetic problems (except for multiplication/division problems with many decimal places, which this isn't).
ChatGPT 5.2 has recently been churning through unsolved Erdös problems.
I think right now one is partially validated by a pro and the other one I know of is "ai-solved" but not verified. As in: we're the ones who can't quite keep up.
https://arxiv.org/abs/2601.07421
And the only reason they can't count Rs is that we don't show them Rs due to a performance optimization.
Those of us who don’t base our technical understandings on memes are well aware of the tooling at the disposal of all modern reasoning models gives them the capability to do such things.
Please don’t bring the culture war here.