Researchers are getting tired of OpenAI gatekeeping its breakthroughs

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Researchers are getting tired of OpenAI gatekeeping its breakthroughs. Expert ‘shepherds’ will decide how best to share the latest breakthroughs in computer science and physics.

研究人员对 OpenAI 把控其技术突破的行为感到厌倦。专家“引导者”将决定如何以最佳方式分享计算机科学和物理学领域的最新突破。

On Monday, OpenAI announced impressive breakthroughs in mathematics, computer science, and physics, along with what the company says is an evolving approach to communicating its findings. But despite its apparent course correction, researchers who spoke to The Verge are growing increasingly tired of the company’s antics.

周一，OpenAI 宣布在数学、计算机科学和物理学领域取得了令人瞩目的突破，并表示公司正在改进其发布研究成果的方式。然而，尽管 OpenAI 似乎做出了调整，但接受《The Verge》采访的研究人员对该公司的种种行为感到愈发厌倦。

It has been a turbulent few months between OpenAI and mathematicians, who are still grappling with the hundreds of preprints unceremoniously dumped on them at the start of October. This time, OpenAI says it is working with expert “shepherds” to decide how best to share its latest breakthroughs.

过去几个月，OpenAI 与数学界的关系一直动荡不安，数学家们仍在努力应对 10 月初被粗暴抛给他们的数百篇预印本论文。这一次，OpenAI 表示正在与专家“引导者”合作，以决定如何以最佳方式分享其最新突破。

All three results concern some of the most consequential unsolved problems in mathematics, computer science, and physics. Some extend OpenAI’s previous work and others break new ground. Following advice from OpenAI’s “shepherds,” each has a different release strategy.

这三项成果均涉及数学、计算机科学和物理学领域中一些最重大的未解难题。其中一些是对 OpenAI 此前工作的延伸，另一些则开辟了新的领域。根据 OpenAI“引导者”的建议，每项成果都采用了不同的发布策略。

For the mathematics result, OpenAI released the AI-generated output, “leaving researchers free to organize their own efforts to explain the result.” For its computer science finding, OpenAI will also assemble an external group of researchers “to explain the result.” Physics, meanwhile, has not been released at all, and OpenAI said it will “defer” to an external group of experts about how to release the materials.

对于数学成果，OpenAI 发布了人工智能生成的输出结果，“让研究人员可以自由组织力量来解释该结果”。对于计算机科学发现，OpenAI 也将组建一个外部研究小组“来解释该结果”。与此同时，物理学成果尚未发布，OpenAI 表示将“听从”外部专家小组关于如何发布这些材料的建议。

The mathematics result appears striking. It purports to resolve the Kakeya conjecture in all dimensions. Roughly speaking, the problem asks how little space is needed to rotate a needle or pencil in every direction. A proof of the three-dimensional version was among the achievements for which NYU mathematician Hong Wang was awarded a prestigious Fields Medal earlier this year.

这项数学成果令人瞩目。它声称解决了所有维度下的 Kakeya 猜想。粗略地说，这个问题探讨的是在各个方向旋转一根针或一支铅笔所需的最小空间。纽约大学数学家王宏（Hong Wang）今年早些时候获得著名的菲尔兹奖，其成就之一便是证明了该猜想的三维版本。

Brown University mathematics professor Brendan Hassett told The Verge OpenAI’s claim “looks well supported,” though he stressed he had not yet checked the Lean formalization, a means of computationally verifying results.

布朗大学数学教授 Brendan Hassett 告诉《The Verge》，OpenAI 的主张“看起来有充分的依据”，但他强调自己尚未检查 Lean 形式化验证，这是一种对结果进行计算验证的方法。

The physics result explores the Standard Model, the most successful and complete theoretical framework in physics. It concerns quantum chromodynamics, which describes the strong nuclear force, one of nature’s four fundamental forces (alongside gravitational force, electromagnetic force, and weak nuclear force) and its relationship to Yang-Mills theory, a cornerstone of modern particle physics.

物理学成果探讨了标准模型，这是物理学中最成功、最完整的理论框架。它涉及量子色动力学，该理论描述了强核力——自然界四种基本力之一（另外三种是引力、电磁力和弱核力）——及其与现代粒子物理学基石杨-米尔斯理论（Yang-Mills theory）的关系。

Yang-Mills theory is also at the heart of one of the seven Millennium Prize problems in mathematics, though OpenAI’s work does not address the unresolved “mass gap.”

杨-米尔斯理论也是数学界七大“千禧年大奖难题”之一的核心，尽管 OpenAI 的工作并未涉及尚未解决的“质量间隙”问题。

The final result claims to disprove the exponential time hypothesis, a widely held assumption in theoretical computer science that certain problems cannot be solved substantially faster than brute-force approaches. It is closely related to P versus NP, another Millennium Prize problem and one of the field’s biggest unsolved problems, which asks whether problems whose solutions can be easily checked are also easy to solve.

最后一项成果声称推翻了指数时间假设，这是理论计算机科学中一个被广泛接受的假设，即某些问题无法比暴力破解法快得多地解决。它与 P 对 NP 问题密切相关，后者是另一个千禧年大奖难题，也是该领域最大的未解之谜之一，探讨的是那些解可以被轻易验证的问题是否也容易被求解。

Given the varying levels of disclosure and the complexity of evaluating such work, it is difficult for researchers to fully judge the company’s findings. Even with all of the information, doing so would take time. But experts who spoke to The Verge said there are good reasons to take the results seriously, variously describing them as “huge,” “major breakthroughs,” and “significant.”

鉴于披露程度各异以及评估此类工作的复杂性，研究人员很难全面评判该公司的研究结果。即使拥有所有信息，评估也需要时间。但接受《The Verge》采访的专家表示，有充分的理由认真对待这些结果，他们分别将其描述为“巨大的”、“重大的突破”和“意义深远的”。

“It doesn’t make any sense that first only a few distinguished scientists can look at them.” But researchers’ excitement about the science was tempered by exasperation with OpenAI’s conduct, a familiar feeling after months of what they describe as an exhausting barrage of AI-generated findings.

“首先只有少数杰出科学家能看到这些结果，这毫无道理。”但研究人员对科学本身的兴奋感被对 OpenAI 行为的愤怒所冲淡，在经历了数月被他们形容为令人筋疲力尽的 AI 生成成果轰炸后，这种感觉已变得司空见惯。

Many were eager for the wider community to get on with the arduous task of scrutinizing the AI lab’s findings and questioned why OpenAI was putting up additional barriers by handpicking experts to oversee the process.

许多人渴望更广泛的学术界能够着手进行审查该 AI 实验室研究成果的艰巨任务，并质疑为什么 OpenAI 要通过挑选专家来监督这一过程，从而设置额外的障碍。

Most experts The Verge spoke to welcomed OpenAI’s decision to consult outside researchers, but argued that publicly announcing results should also mean making that work available for anyone to scrutinize. “I am fine with them releasing the problems as they did today,” said Constantin Kogler, a researcher at the Institute for Advanced Study, welcoming the more manageable batch of three results compared with the hundreds released previously.

大多数接受《The Verge》采访的专家对 OpenAI 咨询外部研究人员的决定表示欢迎，但认为公开宣布研究结果也意味着应让任何人都能审查这些工作。“我同意他们像今天这样发布问题，”普林斯顿高等研究院的研究员 Constantin Kogler 表示，他欢迎这种相比之前一次性发布数百个结果而言更易于管理的三个成果的批次。

But he questioned the decision to restrict access to experts of OpenAI’s choosing. “It doesn’t make any sense that first only a few distinguished scientists can look at them,” he said.

但他质疑限制只有 OpenAI 选择的专家才能查看这些成果的决定。“首先只有少数杰出科学家能看到这些结果，这毫无道理，”他说。

“The fact that they handpick the group is a disaster,” Andreas Karch, a physics professor at the University of Texas at Austin, told The Verge. “The large labs have enough power as it is. They should not be picking winners and losers.”

“他们挑选小组的事实是一场灾难，”德克萨斯大学奥斯汀分校的物理学教授 Andreas Karch 告诉《The Verge》。“大型实验室本身已经拥有足够的权力了。他们不应该去挑选赢家和输家。”

Karch initially suggested selecting researchers through a “competitive process,” though he acknowledged it would likely produce a similar group, which he described as “first rate.” Later, he questioned why OpenAI “can’t release the proof now,” in addition to appointing its team of experts. “This would democratize access while still showing that they care about making the results meaningful and understandable,” he said.

Karch 最初建议通过“竞争性程序”来选择研究人员，尽管他承认这很可能会产生一个类似的小组，他将其描述为“一流的”。后来，他质疑为什么 OpenAI 在任命专家团队的同时“不能现在就发布证明”。“这既能实现获取渠道的民主化，又能表明他们关心如何让结果变得有意义且易于理解，”他说。