文章背景与核心概要
本文由 Jeremy Avigad 撰写，探讨了人工智能在数学领域当前的现状及其未来潜力。尽管近期神经定理证明器（neural theorem provers）取得了令人瞩目的进展，但作者认为这些成就往往掩盖了 AI 在重塑数学研究与教育方面更深远、更广阔的愿景。
作者主张建立一种乐观且协作的新范式，呼吁数学家们积极主动地与人工智能展开互动。文章强调，AI 不应仅仅被视为一种自动化工具，而应成为推动数学发现和理解深化的核心伙伴，从而开启数学探索的新纪元。
当今数学是什么，未来又该走向何方？
摘要
What is mathematics now, and what should it be?
总结
Summary
In this essay, Jeremy Avigad examines the current landscape and future potential of artificial intelligence within mathematics. While recent advancements in neural theorem provers have been striking, they often overshadow a deeper and more expansive vision of how AI can transform mathematical research and education. The author advocates for an optimistic and collaborative paradigm where mathematicians actively engage with AI.
文档详情
Document Details
- arXiv Identifier: arXiv:2608.23218 [cs.AI]
- Subjects: Artificial Intelligence (
cs.AI); History and Overview (math.HO)- Author: Jeremy Avigad
- Submitted: August 24, 2026
- DOI: 10.48550/arXiv.2608.23218
摘要
Abstract
Advances in neural theorem provers have been impressive, but the successes obscure a broader vision of what AI can do for mathematics and how mathematicians can engage with AI. This essay advances a more expansive and optimistic point of view.
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