It's not life-critical but it is financially-critical to the company. You aren't going to build a project on the scale of a data center that is capable of running 24/7 and not run it as much as possible.

Sorry, but that's wrong. You'll run it as much as is profitable. If electricity cost goes up, there is a point where you'll stop running it, since it becomes too expensive. Even more so considering that AI models don't have a set goal to reach - you train them as long as you want and can, but training a little bit extra will have diminishing returns after a while.

That equipment is expensive, and has a relatively short useful lifespan even if not running.

Not really, the limiting factors in AI training are mostly supply of cards. The cards already in use will stay in use until they fail, they won't be replaced with newer cards the second they get released.

This is why tire factories and refineries run three shifts, this isn't a phenomenon unique to data centers.

This is comparing apples and oranges, since tire factories:

• have long-term planning and production goals to reach

• have employees who must be planned

• have resource input costs that are higher than electricity

Of course you want the highest utilisation that you can economically reach, but a better comparison would be crypto mining - which also has expensive equipment that has a relatively short useful lifespan even if not running, and yet they stop mining when electricity is too expensive.

What are you trying to imply? That training Transformer models necessarily needs to be a continuous process? You know it's pretty easy to stop and continue training, right?

I don't know why people keep commenting in spaces they've never worked in.

Don’t need to, just down-blend from the available fuel used from weapons put out of commission as a result of disarmament treaties.

Now, about those materials used to construct solar panels…

I can't imagine they are. What would the training data of those models be? Why would you train the model when the user sent a request? Why would you wait responding to the request until the model is trained?