The reasons are:

- Running billions of dollars worth of GPUs only 30-50% of the time insanely wasteful. Everyone else is running them at 99% duty cycle or close to it.

- Solar is big and generally has to be built far from where the data centres are. Transmission is already a bottleneck in many states. Adding tens of gigawatts requires non-trivial large scale infrastructure investment by… the utility companies, not SpaceX. Not to mention regulatory hurdles, etc.

- Battery production is already mostly maxed out, so obtaining tens of gigawatt hours of capacity on short notice is a decent percentage of global production.

Gas and other fossil fuel power plants can be deployed adjacent to the data centres for effectively zero transmission loss and no long powerlines that upset the NIMBY types.

They can work 24/7 and are largely available right now, but as others have pointed out the turbine blades are a limiting factor with these too.

»Don't understand why.«

Because you cannot turn a large datacenter with thousands of aggregates, power supplies and so on off and on like a toaster.

It’s an industrial supply bottleneck and rollout timeline incompatibility rather than a Dr Doom Evil Genius Complex that prevents everyone from deploying solar. The race dynamics make the discount rate on GPU deployments very high.

Solar is preferable when you have a ton of unproductive land and longer timelines to set it up - it’s certainly going to be cheaper than gas when everyone goes sets up NG plants as option 1 for new energy capacity.

The other confound is that China is the primary supplier of battery and solar tech, I’m sure that supply chain risk becomes part of the calculus when setting up so much infrastructure.

For scale, the current DC is about 8k acres, and the solar to run 7.6GW is almost 40k acres.

I would assume that training pales in comparison to inference when it comes to energy use, taking into account the number of inference users

The problem is that the grid can’t get built out fast enough. You’ll probably see most AI data centers switch to grid power in the coming years using mostly wind and solar because it’s simply cheaper as well

and would be cheaper in the long run? or maybe they could even do solar + storage.

i guess even at this stage “gas is easier” is still winning…

You’re talking about one of the most hated person on hearth with one of the worst reputation. The literal Nazi salute guy. I don’t think he cares much about positive PR like that

Elon has aligned with the hard-right. He'd rather own the libs and hurt the global south than do that.

It's not possible, the system can't work w/o fossil fuels.

I agree, America should finally build more nuclear power plants.

China is currently building 37 reactors simultaneously [1].

> [1] https://www.statista.com/statistics/513671/number-of-under-c...

Not if the benefits of automating basically all forms of labor reach them.

> Is Amazon too broke to buy the necessary land to build out wind/solar/battery?

It's more capital intensive, and interest rates are 8%, because our elected officials are completely incompetent.

sometime in the energy sector once told me "the solution to pollution is dilution"

Natural gas is basically a waste product that gets flared off in many oil-producing parts of Texas. If this private power plant can use that gas for something productive then I guess at least we're no worse off. But it's not clear that is what is happening.

Trees are wonderful for a number of reasons, and the need for them for local climate, which includes shading and their contribution to local humidity, is important as well.

They are not, though, a significant sequestration for CO₂.

A helpful way to think about this is to consider coal. To produce coal the energy input comes from time, pressure, etc over tens to thousands of millions of years.

The significance of trees is for the local climate, or global if you are considering one of handful of rainforests.