My guess would be it's all about electricity.

Texas has a .... unique energy market (literally! They don't connect to the national grid so they can avoid US Government regulations- that way it's not interstate commerce). Because of that spot prices fluctuate very wildly up and down, depending on the weather, demand, and their large quantity of renewables (Texas is good for solar and wind energy). When the weather is good for renewables they have very cheap electricity (lots of production and can't sell to anyone outside the state), when the weather is bad they can have incredibly expensive electricity (less production, can't buy from anyone outside the state). Larger markets, able to pull from larger pools of producers and consumers, just fluctuate less.

I know some bitcoin miners liked to be in Texas and basically worked as energy speculators: when electricity was cheap they would mine bitcoin, when it was expensive they shut down their plant- sometimes they even got paid by producers to shut-down their plant! I would bet that you could do a lot of that with AI training as well, given good checkpointing.

You wouldn't want to do inference there (which needs to be responsive and doesn't like 'oh this plant is going to shut down in one minute because a storm just came up') but for training it should be fine?