Yup, because they're still losing hundreds of dollars for every dollar spent. Their economics still rely on a delusion that the hardware outlay is a fixed cost that can be recovered after model training by selling cheaper compute. Instead, models continue to be released not only to match competition, but because models still do not do a fraction of what they are promised and being sold to do. So capital costs are not fixed.

So AI hyperscalers have a lose/lose/lose/lose choice of either growing at a rate that requires unsustainable subsidies, stopping growth and admitting models can't do what they and a thousand other startups have been selling them for, charging actual costs, or any combination of the three.

If people were charged anything near the actual costs, much less with a profit margin, demand would implode fast enough to create a sonic boom.

"we lose money on every sale but we make it up in volume!"