Turns out their wind "opercapacity" maybe isn't. Maybe they are trading chip efficiency for raw power.

Something I’ve been sort of wondering about—LLM training seems like it ought to be the most dispatchable possible workload (easy to pause the thing when you don’t have enough wind power, say). But, when I’ve brought this up before people have pointed out that, basically, top-tier GPU time is just so valuable that they always want to be training full speed ahead.

But, hypothetically if they had a ton of previous gen GPUs (so, less efficient) and a ton of intermittent energy (from solar or wind) maybe it could be a good tradeoff to run them intermittently?

Ultimately a workload that can profitably consumer “free” watts (and therefore flops) from renewable overprovisioning would be good for society I guess.

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WJW 6 hours ago | parent | next [-]

First: Almost anything can be profitable if you have free inputs.

Second: Even solar and wind are not really "free" as the capital costs still depreciate over the lifetime of the plant. You might be getting the power for near-zero or even negative cost for a short while, but the power cost advantage will very quickly be competed away since it's so easy to spend a lot of energy. Even remelting recycled metals would need much less capital investment than even a previous-gen datacentre.

That leaves the GPUs. Even previous gen GPUs will still cost money if you want to buy them at scale, and those too depreciate over time even if you don't use them. So to get the maximum value out of them, you'd want to run them as much as possible, but that contradicts the business idea of utilizing low cost energy from intermittent sources.

Long story short: in might work in very specific circumstances if you can make the numbers work. But the odds are heavily stacked against you because typically energy costs are relatively minor compared to capital costs, especially if you intend to run only a small fraction of the time when electricity is cheap. Do your own math for your own situation of course. If you live in Iceland things might be completely different.

	▲	nebula8804 6 minutes ago \| parent [-]
		They are amazing at making batteries as well. How does adding batteries to the mix change the calculation?

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zozbot234 8 hours ago | parent | prev | next [-]

> top-tier GPU time is just so valuable that they always want to be training full speed ahead.

I don't think this makes much sense because the "waste" of hardware infrastructure by going from 99.999% duty cycle to 99% is still only ~1%. It's linear in the fraction of forgone capacity, while the fraction of power costs you save from simply shaving off the costliest peaks and shifting that demand to the lows is superlinear.

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actionfromafar 8 hours ago | parent | prev [-]

I think as such intermittent power comes on the grid in the coming decades, people will find creative uses for it.