OpenAI未发布前沿模型产出722篇数学成果
🔮 What is left to do
未发布模型展现出的数学能力具有里程碑意义，直接冲击基础科学范式，值得从业者关注大模型在科研领域的边界拓展。
Also from Exponential View: Could falling compute costs make persistent personal agents commercially feasible by 2028?, in our AI Investment Brief
同样来自 Exponential View：计算成本下降是否会使持久化个人代理在 2028 年前具备商业可行性？，见我们的 AI 投资简报
Yesterday, OpenAI released a range of mathematical results produced by an unreleased frontier model. It’s a remarkable range: 722 manuscripts in 372 families, across number theory, complexity theory, and mathematical physics. The average result took the equivalent of three hours of ChatGPT Pro thinking.
昨天，OpenAI 发布了一系列由未公开的前沿模型产生的数学成果。这是一组令人瞩目的成果：涵盖数论、复杂性理论和数学物理领域，共 372 个家族中的 722 篇手稿。每项成果平均相当于 ChatGPT Pro 思考三小时的工作量。
As scientist Derya Unutmaz points out, it comprises 81% of the major math discoveries in the past three years.
正如科学家 Derya Unutmaz 所指出的，这占到了过去三年主要数学发现的 81%。
Many of the results have been verified in Lean, but not all. Even if the real number is half of that, it’s staggering. Problems that have stumped the best human minds for decades fell to one afternoon of compute.
许多结果已在 Lean 中验证，但并非全部。即使实际数字只有这一半，也令人震惊。困扰人类最优秀头脑数十年的问题，仅用一下午的计算力便迎刃而解。
How should we think about this?
我们该如何看待这一点？
suggests:
表明：
Imagine millions of superhuman research agents at work. Formal systems may verify the proofs, but humans won’t have enough context to understand the underlying web of machine-invented concepts.
想象一下数百万个超人研究代理正在工作。形式系统可以验证证明，但人类将没有足够的上下文来理解机器发明概念背后的复杂网络。
Mathematics could split into two layers:
数学可能会分裂为两个层次：
Machine mathematics: vast, verified, mostly consumed by AIs.
机器数学：庞大、已验证，主要由 AI 消费。
Human mathematics: a compressed “effective theory” of the machine frontier—the small subset of ideas we can understand.
人类数学：对机器前沿的压缩“有效理论”——即我们能够理解的那小部分思想。
A turning point
一个转折点
It might be an intriguing turning point in how we, as humans, understand the world.
这可能是一个有趣的转折点，关乎我们人类如何理解世界。
We’ve only had three hundred years of making sense of the world through natural rather than supernatural explanations. The Enlightenment gave us that – a way to use reason and empiricism to understand what had previously been inexplicable.
我们只有通过自然而非超自然的解释来理解世界的时间仅有三百年。启蒙运动赋予了我们要义——一种运用理性和经验主义去理解此前无法解释之事物的方法。
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