When Open AI announced earlier this month that its artificial intelligence agents had solved one of mathematics’ most vexing formulas, the scientific world took notice.
And many cried foul.
At issue is what’s known as the Navier-Stokes equation, a formula that explains how liquids and gases react, particularly when outside factors such as velocity, pressure, temperature and density of a moving fluid are taken into account.
Solving the formula, based in part on Newton’s second law of motion, has been so elusive for generations that the Clay Mathematics Institute has offered a $1 million grand prize to anyone who can prove it.
Fast forward to Sept. 8, when Open AI announced it solved the Navier Stokes question in an 88-hour period, using 10,000 autonomous AI agents.
THE ripples throughout the scientific community were immediate.
Savonburg’s Jesse Hart counts himself among those most skeptical that Open AI has solved the famed Navier-Stokes equation.
Hart bases the rationale behind his skepticism for one reason—he solved it first, and says he has the receipts to prove it.
The 40-year-old Hart has no formal training in science or mathematics, but with an aptitude for science and computer coding, will offer to anyone willing to look through what he says is proof that he solved the formula first.
“I was ahead of it,” he said. “I just want Open AI to stop lying. Even the public is wary about how they got it.”
Hart says the Open AI “solution” carries several markers in its complex set of formulas that mirror ones Hart had published, starting back in May.
HART is anything but your typical mathematician.
After losing his job because of a traffic accident, he began reading about Navier Stokes in his spare time at home.
His theory: The formula is centered on a toroidal field formulation mathematical technique that splits fluid movement into specific parts—an attractor, and a void.
“Everything is connected by a singular inevitable flow,” he said.
In layman’s terms, Navier Stokes is based on the assumption that the laws of physics are better understood if the universe is considered a large donut, rather than a flat plane.
