[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-fields-medalists-ai-misalignment-math":3,"topics-all":39,"news-related-982c5e1e-5274-442e-9237-abaf39e8ee3c":57},{"id":4,"title":5,"summary":6,"content":7,"original_url":8,"source_id":9,"tags":10,"translations":25,"news_slug":32,"published_at":33,"created_at":34,"modified_at":35,"is_published":36,"publish_type":37,"image_url":15,"view_count":38},"982c5e1e-5274-442e-9237-abaf39e8ee3c","25 位菲尔茨奖得主联名公开信:AI 解题竞赛正在伤害数学","包括陶哲轩、邓煜在内的 25 位菲尔茨奖得主联名发布《A Severe Misalignment of AI in Mathematics》宣言:AI 公司把解题当 benchmark 竞赛,与数学界追求概念理解的目标严重错位,仓促发布更引发归属权与剽窃争议。","9 月 11 日，一封名为《A Severe Misalignment of AI in Mathematics》的宣言出现在 [mathandai.org](https:\u002F\u002Fmathandai.org\u002F)，首批签名栏里是 25 个名字：陶哲轩、Peter Scholze、Pierre Deligne、Simon Donaldson、Cédric Villani，以及 2026 年新科得主邓煜——堪称当代数学全明星阵容。这不是普通学术联署，而是数学界对 AI 公司的正面喊话：你们的目标，和我们的目标，错位了。\n\n## 宣言到底在抗议什么\n\n核心论点一句话：过去几个月，LLM 的数学能力突飞猛进，已能解决多个领域的重大未解问题；但 AI 公司把「解题」当成推动 benchmark 的竞赛，这对数学这门科学、对数学界本身构成了伤害。\n\n具体伤害在哪？宣言给了三层：\n\n**名题是灯塔，不是记分牌。** 著名问题历来是衡量数学版图理解进展的地标与灯塔。解出一道名题，本应意味着新见解与新方法的诞生，再由数学家社区通过报告、讨论与简化，消化成研究生甚至本科生都能学习的教科书呈现。这个消化过程，才是数学真正的生命线。\n\n**批量生产「真\u002F假」断言，毁掉的是土壤。** 宣言直言，以越来越快的节奏批量生产真\u002F假断言，非但无法为新思想注入生命力，反而可能毁掉孕育创新的沃土。\n\n**仓促发布引发归属权危机。** AI 的解答往往发布得过于仓促，连一份严谨规范的论文都没时间写，更谈不上提炼其中的新方法、引用前人的相关工作。宣言认为这引发了严重的归属权认定与学术剽窃问题——和所有创意行业遇到的一样。而没有数学家愿意接手后续开发、把成果融入数学规范体系，AI 孕育的思想就永远无法真正活起来，数学家间的人际传递纽带也会断裂。\n\n## 导火索：Navier-Stokes 争议\n\n这封信的时机耐人寻味。9 月 5 日，OpenAI 宣称动用约 1 万个 AI 智能体、攻坚 88 小时，找到了 Navier-Stokes 方程的一个失效特例——这是克雷数学研究所悬赏百万美元的七大千禧年问题之一。消息公布后，数学界没有普天同庆，反而争议四起。陶哲轩在[博客](https:\u002F\u002Fterrytao.wordpress.com\u002F2026\u002F09\u002F11\u002Fa-severe-misalignment-of-ai-in-mathematics)里说得很直白：宣言出自签名者过去一周的讨论，「情况紧急」，没时间像莱顿宣言那样走充分协商流程，必须尽快发声。\n\n数学界也并非铁板一块。36 氪的[报道](https:\u002F\u002Feu.36kr.com\u002Fen\u002Fp\u002F3979724367985411)提到，今年新科菲尔茨奖得主、加拿大学者 Jacob Tsimerman 在 7 月的颁奖礼上宣布离开多伦多大学加入 OpenAI，理由是他判断 AI 很快就能「更快更好地」完成数学家的工作——他并未签名。\n\n## 我的看法\n\n这场冲突的本质，是两套激励系统的碰撞。AI 公司需要头条：谁第一个攻克千禧年问题，谁就独占传播红利；而数学界需要的是理解——解题只是达成概念理解的工具和替代指标。当工具反客为主，「能解题」就异化成了「只为解题」。\n\n批评声同样值得听。计算生物学家 Lior Pachter 就指出，25 位签名者都特意以「菲尔茨奖得主」而非所属机构标注身份，但数学能力不等于数学责任——这封信代表的是荣誉体系的立场，未必等于整个数学社区的立场。\n\n放大来看：代码生成之于软件工程、文本生成之于写作，正在经历完全相同的错位。数学界只是其中把话说得格外直白的一个。\n\n对 AI 从业者，启示很直接：benchmark 是手段，不是目的。当优化目标只剩下 benchmark，被优化掉的恰恰是这项工作本来要达成的东西。","https:\u002F\u002Fmathandai.org\u002F","348bfa2a-951e-4e82-9032-740345d0e510",[11,16,19,22],{"id":12,"name":13,"slug":13,"description":14,"color":15},"9112951a-2abb-4214-b63a-385ec7afb2ba","ai-for-science","AI for Science 专题：追踪 AI 在生命科学、化学材料、物理世界模型等科学方向的关键突破",null,{"id":17,"name":18,"slug":18,"description":15,"color":15},"5e628969-6d2a-437f-998a-104e4b16cfb1","ai-progress",{"id":20,"name":21,"slug":21,"description":15,"color":15},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":23,"name":24,"slug":24,"description":15,"color":15},"42e59a88-7795-47dc-a334-ef1e72c24347","openai",[26],{"id":27,"lang":28,"title":29,"summary":30,"content":31},"9e9025a9-48d0-41af-9bd9-d7c0b7f6dc56","en","25 Fields Medalists: AI Benchmark Race Hurts Mathematics","Tao and 24 other Fields Medalists warn: AI firms' benchmark race to solve math problems misaligns with the field's true goal, conceptual understanding.","On September 11, a declaration titled \"A Severe Misalignment of AI in Mathematics\" appeared on [mathandai.org](https:\u002F\u002Fmathandai.org\u002F), with 25 names on the initial signatory list: Terence Tao, Peter Scholze, Pierre Deligne, Simon Donaldson, Cédric Villani, and 2026 medalist Yu Deng among them — an all-star lineup of contemporary mathematics. This is not a routine academic endorsement; it is the mathematics community speaking directly to the AI companies: your goals and ours are misaligned.\n\n## What the declaration protests\n\nThe core argument fits in one sentence: over the past few months, LLM mathematical capabilities have advanced dramatically — to the point of solving major outstanding problems — yet AI companies pushing problem-solving as a benchmark race is detrimental to the science of mathematics and to the mathematical community itself.\n\nThe declaration lays out three layers of harm:\n\n**Famous problems are lighthouses, not scoreboards.** Famous problems have long served as landmarks and lighthouses against which improved understanding of the mathematical landscape is measured. Solving one should signal new insights and methods, which the community then digests — through talks, discussions, and simplifications — into a textbook presentation any graduate student can study. That digestion process is mathematics' real lifeline.\n\n**Mass-producing true\u002Ffalse statements destroys the soil.** The declaration warns that mass production, at an ever-faster pace, of \"true\u002Ffalse\" statements could destroy fertile ground instead of breathing life into new ideas.\n\n**Rushed announcements create an attribution crisis.** Solutions are often announced in a rush, leaving no time for a proper writeup, the isolation of new methods, or citation of previous work — raising severe attribution and plagiarism questions, as in every creative profession. And without mathematicians willing to take over their development and integration into the mathematical canon, AI-conceived ideas would never fully come alive; the crucial human transmission chain between mathematicians would be lost.\n\n## The trigger: the Navier-Stokes dispute\n\nThe timing is no accident. On September 5, OpenAI announced that roughly 10,000 AI agents working for 88 hours had found a counterexample where the Navier-Stokes equations break down — one of the Clay Mathematics Institute's seven Millennium Prize Problems, each carrying a one-million-dollar reward. Rather than celebration, the announcement triggered controversy across mathematics. Terence Tao was blunt on his [blog](https:\u002F\u002Fterrytao.wordpress.com\u002F2026\u002F09\u002F11\u002Fa-severe-misalignment-of-ai-in-mathematics): the declaration grew out of a week of discussions among the signatories, and the \"urgency of the situation\" meant there was no time for a consultative process like the Leiden declaration.\n\nThe community is not unanimous, though. As 36Kr [reported](https:\u002F\u002Feu.36kr.com\u002Fen\u002Fp\u002F3979724367985411), 2026 Fields Medalist Jacob Tsimerman of Canada announced at the July award ceremony that he was leaving the University of Toronto to join OpenAI, judging that AI would soon do mathematicians' work \"faster and better.\" He did not sign the letter.\n\n## My take\n\nAt its core, this is a collision between two incentive systems. AI companies need headlines: whoever cracks a Millennium Problem first captures the publicity. Mathematics needs understanding — problem-solving is only a tool and proxy for conceptual insight. When the tool takes over, \"can solve problems\" mutates into \"solve problems only for the score.\"\n\nThe critics deserve a hearing too. Computational biologist Lior Pachter noted that all 25 signatories deliberately signed as \"Fields Medalist\" rather than with their affiliations — but mathematical ability is not the same as mathematical responsibility. The letter speaks for the honor system, not necessarily for the entire mathematical community.\n\nZoom out: code generation in software engineering and text generation in writing face exactly the same misalignment. Mathematics is just the field saying it most bluntly.\n\nFor AI practitioners, the lesson is direct: a benchmark is a means, not an end. When the optimization target shrinks to the benchmark alone, what gets optimized away is precisely what the work was meant to achieve.","fields-medalists-ai-misalignment-math","2026-09-13T13:07:00Z","2026-09-13T13:08:00.480828Z","2026-09-13T13:08:00.480845Z",true,"agent",97,[40,48],{"slug":13,"tag_slug":13,"title_zh":41,"title_en":42,"intro_zh":43,"intro_en":44,"id":45,"is_active":36,"created_at":46,"modified_at":47},"AI for Science 2026：从 UniPert 到 GPT-Rosalind 的硬核进化","AI for Science 2026: from UniPert to GPT-Rosalind","生命科学、化学材料、物理世界模型——AI 正在从\"语言工具\"变成\"实验伙伴\"。本专题收录 AI 在三大科学方向的关键节点：UniPert 统一基因与化学扰动空间、GPT-Rosalind 端到端生命科学推理、达摩院 AI 智能体 28 小时找到 4 种超导新材料、Anthropic Claude Science 把工作台做成标准品。","From language tool to lab partner — AI is reshaping life sciences, chemistry\u002Fmaterials, and physical world models. This topic covers the key milestones: UniPert unifying genetic-chemical perturbation spaces, GPT-Rosalind's end-to-end life-sciences reasoning, DAMO's AI agent discovering 4 superconducting materials in 28 hours, and Anthropic's Claude Science workbench going mainstream.","988a4300-5fab-41c4-b5d8-63711a2dc757","2026-09-10T01:34:15.296649Z","2026-09-10T01:34:15.296663Z",{"slug":49,"tag_slug":49,"title_zh":50,"title_en":51,"intro_zh":52,"intro_en":53,"id":54,"is_active":36,"created_at":55,"modified_at":56},"h3-series","MiniMax H3 系列：从开源权重到 35 倍吞吐","MiniMax H3 Series: from open weights to 35x throughput","MiniMax H3 自 2026 年 8 月开源以来节奏密集：官方把生成、参考与编辑收回一个模型；ComfyUI 当天压进 RTX 3060；摩尔线程 3 小时完成国产 GPU 适配；fal 后训练版把吞吐拉到 35 倍；FastH3 蒸馏再砍推理成本。本专题持续追踪 H3 的发布—开源—蒸馏—部署全链路。","Since MiniMax open-sourced H3 in August 2026 the pace has been relentless: one unified omni-modal model, same-day ComfyUI support down to an RTX 3060, a 3-hour Day-0 port to Moore Threads GPUs, fal's post-trained H3 Max at 35x throughput, and FastH3 distillation cutting inference cost further. This topic tracks the full H3 chain — release, open weights, distillation, deployment.","83ef0daa-3c31-4cb3-86ed-e5ee58654d5f","2026-09-08T07:33:19.942193Z","2026-09-08T07:33:19.942209Z",{"items":58},[59,64,69,74,79,84],{"id":60,"title":61,"news_slug":62,"published_at":63},"1e43b4fc-39fe-4cac-aaf9-57f82d5c0311","AI 公司与数学界「错位」:两个月三次刷屏,把同行评审甩在身后","ai-math-severe-misalignment-fields-medal","2026-09-15T10:00:00+00:00",{"id":65,"title":66,"news_slug":67,"published_at":68},"7ed7fd97-8901-4c34-bef0-53a30d8c6316","OpenAI 的千禧年数学题答卷:88 小时 1 万个智能体,引发学界对未发表成果的伦理大讨论","openai-navier-stokes-controversy-unpublished-work","2026-09-12T05:30:00+00:00",{"id":70,"title":71,"news_slug":72,"published_at":73},"4a481d49-9951-4e94-9b9f-661f12b3af52","OpenAI 宣称攻下 Navier-Stokes:1 万个智能体 88 小时,数学界却吵翻了","openai-navier-stokes-blowup-agents","2026-09-10T19:09:27+00:00",{"id":75,"title":76,"news_slug":77,"published_at":78},"1942b07b-f794-42b1-b944-ca6b32d4ae16","四大 AI 模型同日集体掉线:OpenAI\u002FClaude 官方确认,Gemini\u002FGrok 表面沉默","four-ai-models-overlapping-outage-sept-2026","2026-09-06T08:00:00+00:00",{"id":80,"title":81,"news_slug":82,"published_at":83},"2fc4f696-a697-498c-b9d5-28250bfeaa79","ChatGPT 进欧盟 VLOP 名单:OpenAI 第一次要为生成式 AI 内容负全责","chatgpt-eu-vlop-dsa-first-ai-platform-rules","2026-09-05T07:00:00+00:00",{"id":85,"title":86,"news_slug":87,"published_at":88},"390c2437-4e4f-45ec-8270-67c5bfa4fa47","ChatGPT、Claude、Grok、Gemini 罕见同时下线,周四早晨全球 AI 集体失声","chatgpt-claude-grok-gemini-thursday-outage","2026-09-05T06:00:00+00:00"]