this is super overblown. what their executive said was that eventually the scale of compute required is so large, that it requires not only investing in new DCs, but new fabs, power plants, etc, which can only happen if there is implicit government support to guarantee 10+ year investment horizons required for the lower level of capital investment. that is not controversial at all and has nothing to do with OpenAI specifically being too big to fail.
We're barely scratching the surface of the utility of LLMs with today's models. They aren't more pervasive because of their costs today, but what happens if they drop another order of magnitude with the current capabilities?
What does that even mean?
If OpenAI crashes, for example funding stops, they go broke, fall behind, nobody buys anything, then all the money they invested for data centers or demand they created for NVIDIA chips and compute collapses. That creates surplus of hardware, causes lots of construction/buildout / stockup orders to get cancelled, and the whole thing ripples as suppliers and construction and data center providers etc etc suddenly lose a ton of anticipated profits.
Share prices drop as people dump to protect their portfolios, anticipating dips in the prices because share prices will drop as people dump to protect their portfolios (I'm not kidding).
Given that the big 7 AI companies are basically _all_ of the market growth lately, it doesn't even take a serious panic / paranoia episode to see the market itself stagnate or significantly regress, as people pull from anything AI related, and then pull from the market itself anticipating the market will fall.
It's a fairly standard playbook at this point.
But what you're describing is about keeping the AI bubble from popping. Can a bubble really be too big too fail?
And, because AI is currently what prevents the US economy from being in a recession (at least that what some people speculate), the US economy will stumble, which means that everyone else will to.