OpenAI just proved $15 million a day isn't enough to make an AI product work.

Sora got shut down last week. The technology worked. The economics didn't.

$15M a day in compute costs. No viable path to revenue. That's not a technology failure, it's an economics failure.

Two days later, ByteDance launched its own AI video tool globally. Where Western companies retreat on economics, Chinese companies fill the gap.

This is the actual AI race right now. Not who builds the best model. Who can run it at a cost the market will pay.

The companies positioning to win already understand this. Arm unveiled their first in-house chip in 35 years. Meta is building a full custom silicon stack. Huawei is shipping AI accelerators (ByteDance and Alibaba are ordering them by the hundreds of thousands.)

Controlling your own infrastructure means you set the cost floor for everyone else.

The capability gap between leading models is narrowing. The economics gap is widening.

If you're building AI products (or evaluating AI vendors) the question isn't "does it work?" anymore.

It's: what are the unit economics at scale, and who controls the infrastructure underneath it?

Full breakdown in this week's episode of The Human in the Loop.