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> I’ve heard from sources I trust that both Google Gemini and Amazon Nova charge less than their energy costs for running inference...

Then, several headings later:

> I have it on good authority that neither Google Gemini nor Amazon Nova (two of the least expensive model providers) are running prompts at a loss.

So...which is it?



Oh whoops! That's an embarrassing mistake, and I didn't realize I had that point twice.

They're not running at a loss. I'll fix that.


If they are subsidised they can make a profit while still not making enough money to cover energy costs.


The tip I got about both Gemini and Nova is that the low prices they are charging still cover their energy costs.


OK!


Subsidised by whom?


E.g. tax payers.


Are tax payers subsiding that particular activity of Google or Amazon? If they do, “they make enough money” to cover costs. If they don’t, how does it become profitable if it doesn’t even cover the cost of one of the inputs?


Where I live corporations like those get to build data centers and energy subsidies from the state, i.e. tax payers pay a part of their energy bills. This isn't money they're making, it's money other people made and gave to them.

This means that they could make a profit off inference models without the revenue being large enough to pay the energy costs.

If it's the case I don't know. I'm more concerned with getting rid of those corporations altogether since interacting with them is generally forbidden due to the lack of data protection regulations in the US.


Subsidies are often in the form of tax credits - they cannot be really used to pay for things. I'm not sure if "energy subsidies" may be about providing energy below the cost of production but it's true that the "true" cost of production is not clear when a political decision to close nuclear plants, for example, introduces a distortion on their useful life and their amortised cost.




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