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A.I.’s Latest Challenge: the Math Olympics

WorldA.I.’s Latest Challenge: the Math Olympics

For four years, the computer scientist Trieu Trinh has been consumed with something of a meta-math problem: how to build an A.I. model that solves geometry problems from the International Mathematical Olympiad, the annual competition for the world’s most mathematically attuned high-school students.

Last week Dr. Trinh successfully defended his doctoral dissertation on this topic at New York University; this week, he described the result of his labors in the journal Nature. Named AlphaGeometry, the system solves Olympiad geometry problems at nearly the level of a human gold medalist.

While developing the project, Dr. Trinh pitched it to two research scientists at Google, and they brought him on as a resident from 2021 to 2023. AlphaGeometry joins Google DeepMind’s fleet of A.I. systems, which have become known for tackling grand challenges. Perhaps most famously, AlphaZero, a deep-learning algorithm, conquered chess in 2017. Math is a harder problem, as the number of possible paths toward a solution is sometimes infinite; chess is always finite.

“I kept running into dead ends, going down the wrong path,” said Dr. Trinh, the lead author and driving force of the project.

The paper’s co-authors are Dr. Trinh’s doctoral adviser, He He, at New York University; Yuhuai Wu, known as Tony, a co-founder of xAI (formerly at Google) who in 2019 had independently started exploring a similar idea; Thang Luong, the principal investigator, and Quoc Le, both from Google DeepMind.

Dr. Trinh’s perseverance paid off. “We’re not making incremental improvement,” he said. “We’re making a big jump, a big breakthrough in terms of the result.”

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