AI SOLVES MATH PROBLEMS FASTER THAN EXPERTS

OpenAI's refutation of the Unit Distance Conjecture marks a turning point in mathematics. GPT 5.6 Pro has solved problems on its first attempt that human mathematicians spent considerable time pursuing, demonstrating AI's capacity for high-level mathematical reasoning. Fields Medal winner Timothy Gowers confirmed that the system solved two problems he had personally worked on, raising questions about the future of mathematical practice. Gowers expressed concern about what he calls the "possible destruction of mathematical culture," warning that if mathematicians rely primarily on AI to solve problems, the field risks losing the deep expertise required to understand and build upon such results. The divide among mathematicians reflects broader uncertainty about AI's role in academic research. Some view these breakthroughs as tools that accelerate discovery and free researchers to pursue higher-order questions. Others worry that outsourcing problem-solving to AI could hollow out mathematical training and intuition. The practical implications are significant. If AI can reliably solve conjecture-level problems, the incentive structure of mathematics changes. Problems that once motivated years of research could be resolved in seconds. This raises questions about what mathematicians should focus on and how the field should adapt to maintain its intellectual rigor. The debate also touches on reproducibility and understanding. Mathematicians traditionally value not just solutions but the reasoning behind them. AI-generated proofs sometimes lack the intuitive explanations that help advance mathematical thinking. For now, the field is observing cautiously. While AI's problem-solving capacity is undeniable, the long-term effects on mathematical culture remain an open question. The challenge for mathematicians is to integrate these tools productively while preserving the intellectual foundations that have sustained the discipline.