The AI tools you use every day have a cost structure almost nobody talks about.

Infrastructure has been scaling fast, faster than most people could follow, and the industry has had little incentive to explain what's actually under the hood: the layers involved, the unit economics, the real cost of building and running AI at scale.

Billions flow into data centres every quarter. But where that capital actually goes has never really been part of the public conversation.

A few numbers worth knowing:
- Power and cooling alone can consume 30% of a facility budget before a single server is switched on
- A mid-size build runs around $10M
- A large-scale US facility can reach $250M to $500M or more

And that's before you factor in compute, networking, storage, recovery, and the software holding it all together, each carrying a price that shapes how AI gets built, and who gets to build it.

At AlphaTON Capital, building next-generation infrastructure and explaining how it works are part of the same mission. Not to overwhelm with numbers, but to help you make informed decisions about where your capital (and your data) actually goes.

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