BUSINESS REFLECTION: Crossed Wires: Farewell Nobel prizes — is AI disrupting scientific discovery and ownership?

Beyond the drama surrounding OpenAI’s claim to the Navier‑Stokes solution and a whistleblower’s subsequent dispute over data use is the question of what AI‑driven breakthroughs mean for scientific prizes and academic credit.

At the beginning of last week I wrote a story about the diminishing value of a university degree as artificial intelligence seeps into education, leaving institutions unsure about the soundness of their pedagogical promise.

Then it got worse. The new story has many thrilling plotlines – please stay with me.

It turns out that the motion of fluids (like water or oil) has been historically thorny for scientists to understand. But in the 19th century, Claude-Louis Navier and George Gabriel Stokes worked out a set of equations that describe how fluids move. They are in your weather forecast, tidal charts, sea current charts, in the shape of an aircraft wing, in the model of blood moving through an artery. They work beautifully, every day, everywhere.

But there has always been a niggling concern that the equations may not work under all conditions. So much of a concern that the problem of proving (or disproving) this entered the hallowed halls of the Clay Mathematics Institute’s Millennium Prize Problems – seven of the world’s most difficult mathematical and physics conjectures, of which six remain unsolved. For the past 90 years thousands of scientists have devoted part (or all) of their careers to solving the Navier-Stokes problem. No one had done so until last week.

On 8 September, OpenAI announced that one of their unreleased models had solved it. It took the model all of 88 hours. The Navier-Stokes conjecture seemed to have fallen to AI (peer review still pending) – this was big news, obviously, but perhaps not that surprising to some given what we now know about the exponentially increasing capabilities of AI. More of the great problems will fall – in maths, chemistry, physics, microbiology, medicine. It will become unsurprising and commonplace, starting now and accelerating into the future. It is predicted that another Millennium Prize problem (something called Yang-Mills theory in physics) will fall within months.

Surprisingly, this is only the surface story, because even before the announcement was made trouble started brewing, and that is where all the meat lies. What happened was that a New York University mathematics professor, Tristan Buckmaster, softly blew the whistle on OpenAI and said: I think you guys have stolen my homework.

In 2023, long before OpenAI claimed the Navier-Stokes scalp, two Spanish mathematicians, Luis Martínez-Zoroa and Diego Córdoba, had been chipping away at the problem, but had not been able to carry their approach through to a general solution that would satisfy the terms set out by the Millennium Prize. Science being what it is, their work was public, if rather obscure. The technique that they were using was picked up by Buckmaster and his colleague Levent Alpöge, who is an Anthropic employee. They recruited AI tools into their efforts to solve the problem.