'Why would you ruin your career?': OpenAI claims to have cracked one of math's greatest unsolved problems, but mathematicians allege it played dirty
Tristan Buckmaster , a mathematician at New York University, had just spent months working on what he believed could be a life-defining mathematical proof.
Then, during a Sept.
6 meeting with OpenAI employees, he claims that he was issued a stark warning: "Why would you ruin your career?" That exchange, which Buckmaster described in a detailed public statement this week, sits at the heart of a ballooning controversy around a famous set of mathematical equations called Navier-Stokes.
OpenAI says its artificial intelligence (AI) model has solved an outstanding problem tied to this 200-year-old set of fluid dynamics equations.
The set of equations appears on the list of one of the seven Millennium Prize Problems posed by the Clay Mathematics Institute, and its solution comes with a $1 million reward.
Buckmaster had been working on the same problem.
And he has questions about how the company got there so fast.
The OpenAI breakthrough The Navier-Stokes equations were formulated in the early 1800s by Claude-Louis Navier and George Gabriel Stokes.
They're basically Newton's second law of motion for fluids, describing how any fluid moves: Push air with a fan blade, and the equations predict how that air will flow; or heat the atmosphere with sunlight, and they help forecast tomorrow's weather.
They describe how planes fly and how blood moves through your arteries.
The problem is that nobody has proved whether the equations always produce finite answers.
Could there be rare conditions that make the equations go haywire? This is called a "blowup," or singularity, which happens when a quantity that should represent something physical (like fluid speed or pressure) spirals toward impossible infinities at certain points in space and time.
Imagine the swirl of water circling a bathtub drain.
The Navier-Stokes equations describe how it spins faster as it tightens toward the center.
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