In the interview, Karina Hong, CEO of Axiom Math, discusses their AI system, Axiom Prover, which achieves superhuman mathematical reasoning to solve complex proofs and verify code, demonstrating both theoretical breakthroughs and practical applications. She highlights the AI’s potential to accelerate scientific discovery, improve software reliability, and foster collaboration between human mathematicians and machines, positioning Axiom Math as a leader in bridging foundational AI research with commercial impact.
In this interview, Katherine Schwab of Forbes speaks with Karina Hong, CEO and co-founder of Axiom Math, about their groundbreaking work in building an AI mathematician. Karina explains that their AI, called Axiom Prover, is designed to achieve superhuman mathematical intelligence, enabling it to solve complex theoretical math proofs and generate new conjectures autonomously. This capability could accelerate breakthroughs in mathematics and foster unexpected connections across various scientific fields such as physics, neuroscience, and economics. Axiom Math’s approach leverages synthetic data generation and self-verification, allowing the AI to improve itself continuously without human labeling.
Karina highlights the commercial applications of their AI, particularly in code verification for both hardware and software. Axiom Prover can formally verify that computer programs behave exactly as intended, which is crucial in high-stakes industries where errors can be costly or dangerous. The system has demonstrated impressive performance, scoring a perfect 12 out of 12 on the hardest college math test in the US and achieving state-of-the-art results on a respected code verification benchmark. This blend of advanced mathematical reasoning and practical application positions Axiom Math as a unique player bridging research and industry.
Karina’s diverse academic background in mathematics, neuroscience, and law has deeply influenced her vision for Axiom Math. She shares how her experiences in math competitions and interdisciplinary studies shaped her understanding of abstract reasoning and transfer learning. This foundation inspired her to build an AI system capable of both theoretical breakthroughs and real-world impact. She also discusses the importance of resilience and collaboration in entrepreneurship, emphasizing the challenges and excitement of growing a high-talent team focused on verified knowledge generation.
The conversation touches on the broader AI research landscape, including the rise of “new labs” that focus on foundational AI research with significant venture capital backing. Karina distinguishes Axiom Math by its strong customer focus and commercial orientation, aiming to translate technical advances into practical solutions. She expresses enthusiasm for AI’s potential in both digital and physical domains, particularly in verified AI that can not only eliminate errors but also improve code quality. This vision underscores the transformative potential of combining formal mathematics with AI-driven software verification.
Finally, Karina reflects on the future role of human mathematicians in an era of AI-generated proofs. She believes mathematicians will continue to play a vital role by guiding the AI’s problem selection and interpreting proofs, maintaining a collaborative relationship with machines. The AI’s ability to produce proofs quickly will free humans to focus on deeper understanding and new conjectures, amplifying their impact. Karina concludes by emphasizing the mission-driven culture at Axiom Math and the excitement of pioneering a paradigm shift in both mathematics and AI.
