AI vs Human Intelligence: What Olympiad Gold Medals Reveal About the Future of Math and Machines
Artificial Intelligence is no longer just about chatbots and writing essays—it’s now winning gold medals at the world’s most prestigious mathematics competition, the International Math Olympiad (IMO). In a historic breakthrough, AI models built by OpenAI and Google DeepMind scored 35 out of 42 points—enough to win gold—marking the first time in history that machines have reached this level in mathematical problem solving.
This isn’t just a technological flex. It raises deep questions about the nature of intelligence, human creativity, and the role of AI in shaping future research and learning.
🧠 What Happened at the IMO 2025?
Since 1959, the IMO has been the ultimate test of mathematical genius for high school students worldwide. Participants solve six extremely challenging problems over two sessions, each lasting 4.5 hours. The problems are not just about formulas—they test deep reasoning, creativity, and out-of-the-box thinking in fields like algebra, combinatorics, number theory, and geometry.
This year, AI stepped into the competition—not to assist students, but to compete.
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OpenAI’s experimental reasoning model scored 35/42, the cutoff for gold.
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Google DeepMind’s Gemini Deep Think, also scored 35/42, with its results officially certified by IMO judges.
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Both AI systems solved five of the six problems under the same time and test conditions as humans.
India also had a proud showing, bagging three golds, two silvers, and one bronze. Among them, Kanav Talwar from DPS Faridabad even outscored the AI models by two points.
🤖 How Did the AI Models Work?
These weren’t ordinary large language models (LLMs) like ChatGPT. The AI systems used here were specially designed for mathematical reasoning. Unlike standard LLMs that often guess answers or hallucinate facts, these models worked through each step logically, mimicking how a top student might think.
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Google’s Gemini Deep Think introduced a new technique called parallel thinking, where it explores many solution paths at once before selecting the best.
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It also worked end-to-end in natural language—reading the problem in plain English and outputting the full proof in the same format.
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OpenAI, although not part of the official competition, had its model’s answers graded by former IMO medallists.
While both AI systems performed impressively, only Google’s results were officially verified by IMO judges.
🏁 The Race Between OpenAI and Google DeepMind
This gold-medal performance highlights a growing rivalry. Both companies are investing heavily in AI reasoning models, aiming to leap beyond just language understanding.
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Last year, Google’s AlphaProof and AlphaGeometry only reached silver-equivalent scores. They needed human help to translate problems into formal logic.
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This year’s models needed no human intervention, completed the work within the 4.5-hour time limit, and used natural language throughout.
For now, Google plans to release Deep Think to a limited group of AI Ultra subscribers. OpenAI says its math-capable model won’t be available to the public for several more months.
🧩 What Does This Mean for Human Mathematicians?
Despite the buzz, even the brightest students believe AI has limits.
“AI can’t experience the emotions or creative thrill of solving a tough problem,” said Kanav Talwar.
“It may struggle with problems that require genuinely new ideas,” added Archit Manas.
Even so, AI can still play a powerful role—as a math assistant, not a replacement:
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Brainstorming ideas during tough problems
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Checking proofs for mistakes
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Suggesting creative angles, just like AI has revolutionized chess strategy
As Talwar rightly said, this could be the beginning of a new era where AI becomes a collaborator in solving some of the world’s hardest unsolved mathematical problems.
🚀 Where Does AI Go From Here?
This milestone isn’t just a win for AI—it’s a glimpse into what’s coming next. If AI can win gold at IMO, what else can it do?
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Cryptography: Solving math-based security problems
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Physics & Space: Cracking equations that power space exploration
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Education: Helping students prepare for exams like the IMO
But we must be cautious. These systems still make simple errors—like comparing decimal numbers incorrectly—and their success relies heavily on training data and pattern recognition.
As AI pioneer Andrej Karpathy puts it, today’s AI has “jagged intelligence”—brilliant in some tasks, bafflingly bad in others.
📝 Final Thoughts
The fact that AI can now stand on the IMO stage alongside the world’s brightest students is astonishing. But it also serves as a reminder: while AI can replicate logic, it can’t (yet) replicate human intuition, imagination, or the joy of problem-solving.
So for now, it’s not a battle between humans and machines. It’s a collaboration.
Gold medals or not, the real winners are those who learn to work with AI—whether in math, science, or beyond.
Reference from:-https://indianexpress.com/article/explained/explained-sci-tech/math-olympiad-gold-medals-ai-race-10144794/?ref=latestnews_hp