When Intelligence Becomes Capital

Something unusual happened this week.

OpenAI⁠ announced that an internal AI system had produced a solution to the Navier–Stokes existence and smoothness problem, one of mathematics’ celebrated Millennium Prize Problems.

The Economist rightly framed the development as raising “profound questions.”

I would go further.

The most profound question may not be whether AI can solve mathematics. It is what happens to capitalism when intelligence itself becomes scalable infrastructure.

For most of economic history, intelligence has been stubbornly scarce.

A brilliant mathematician cannot be copied 10,000 times. A great scientist cannot simultaneously pursue 10,000 hypotheses. A Nobel-level researcher still has 24 hours in a day.

Machines changed the productivity of human hands.

Computers changed the productivity of calculation.

The internet changed the cost of distributing information.

AI may now be beginning to change something much more fundamental:

the marginal cost of producing intellectual work.

And that could have consequences extending far beyond mathematics.

First, what actually happened?

The Navier–Stokes equations describe how fluids move. They underpin models used in fields ranging from aerodynamics and weather forecasting to blood flow.

The mathematical question that remained unresolved for roughly 90 years was deceptively simple: if a three-dimensional fluid starts in a perfectly smooth state, must its mathematical evolution remain smooth forever?

Or can the equations eventually produce a singularity — essentially a point at which the mathematical description breaks down?

OpenAI says its system has demonstrated the latter.

Its proposed solution constructs a fluid beginning smoothly at rest which, under a smooth external force, develops a singularity in finite time while maintaining finite energy. The company published both an analytical proof and a formalization using Lean, a proof-assistant system capable of mechanically checking mathematical reasoning.