[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-bytedance-seed-stem-scientist":3,"news-related-adbe213f-d27c-41a7-803c-c5823e1a63fd":36},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":23,"news_slug":29,"published_at":30,"created_at":31,"modified_at":32,"is_published":33,"publish_type":34,"image_url":13,"view_count":35},"adbe213f-d27c-41a7-803c-c5823e1a63fd","字节跳动 Seed STEM 科学家计划启动:把豆包算力+模型搬到 STEM 学科的最前线","7月23日,字节跳动 Seed Edge 团队正式启动 Seed STEM 科学家计划,拟面向全球招募 100 位 STEM 领域学者,提供算力资源、模型体验与 AI 研究团队配套支持,围绕真实科研问题推动 AI 加速科学发现。首期计划约持续 6 个月,申请截止 9 月 30 日,工作地点位于北京海淀。这是字节豆包大模型矩阵首次以科研驻地+开放算力的形式把基础模型供给嵌入学术链路,与中国头部 AI 实验室的 AI4Science 路径正面交汇。\\n\\n**计划设计:从送模型升级为送工位**\\n\\n与单纯开源模型或开放 API 不同,Seed STEM 计划要求入选学者以科学家顾问或博士实习生身份,实际进入字节北京办公现场与 Seed 团队协作 6 个月。入选门槛聚焦三项硬指标:STEM 领域博士在读或同等研究水平、日常深度使用 AI、可熟练编程者优先。换言之,字节要的不是偶尔调用 API 的用户,而是愿意把 AI 嵌进自己科研流水线、把模型当成协作者的同行者。配套资源除充足算力外,还包括业界有竞争力的薪酬——这意味着字节正在用真金白银换取高质量的反馈回路。\\n\\n**为什么是 Seed Edge,而不是豆包?**\\n\\nSeed Edge 是字节内部长期研究计划,定位探索未知智能边界,与商业化主线的豆包\u002F即梦形成明显区隔。把 STEM 计划挂在 Edge 而非豆包品牌下,说明字节把这一波科研合作视作前沿探索,而非产品落地前的用户调研。这种定位也意味着 Seed Edge 团队握有更大的算力调度自由度——6 个月驻场研究不可能用普通用户级配额满足,这对预算审批和集群管理都是信号。\\n\\n**和 Anthropic、Google 的差距与差异**\\n\\n相比 Anthropic 把 AI 科学家工作台打包成产品(Claude Science beta 已上线),或 Google 拉 Nobel 奖得主 John Jumper 加盟做 Protein LLM,字节的路径更像 DeepMind 早期模式:把模型团队和科研团队物理放在一起,边做边迭代。这种模式的优点是反馈速度快、产出可工程化,缺点是规模难扩张、博士培养周期长。100 位学者、6 个月周期,本质上是字节在赌一种小而深的科研组织范式。\\n\\n**对 AI4S 赛道的判断**\\n\\nSeed STEM 计划的真正信号不在于招了多少博士,而在于愿意把算力和模型调度权开放给学术团队。在国内,长期把基础模型供给做厚的研究机构屈指可数——DeepMind 有 AlphaFold、Anthropic 有 Constitutional AI、字节豆包矩阵有 Seed Edge。当一个中国厂商愿意承担这种科研驻地的成本,说明基础模型的差异化竞争已经悄悄从榜单跑分转到了谁能更快让模型进入科学家的工作流。","https:\u002F\u002Fwww.ithome.com\u002F0\u002F980\u002F634.htm","d4a24db7-b6c2-410c-ba99-c16625c61305",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"5e628969-6d2a-437f-998a-104e4b16cfb1","ai-progress",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"40269b40-7942-4650-9672-ed2e6524d37a","ai-technology",{"id":18,"name":19,"slug":19,"description":13,"color":13},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",{"id":21,"name":22,"slug":22,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",[24],{"id":25,"lang":26,"title":27,"summary":28,"content":28},"506c3af9-5ea0-4f96-94a7-6e0ed713fe4e","en","ByteDance Seed STEM program brings Doubao compute to science","On July 23, ByteDance's Seed Edge team officially launched the Seed STEM Scientist program, planning to recruit 100 STEM scholars globally, providing compute resources, model experience, and AI research team support, driving AI-accelerated scientific discovery around real research problems. The first phase of the program runs about 6 months, applications close September 30, and the work location is in Beijing Haidian. This is the first time the ByteDance Doubao large-model matrix has embedded base-model supply into the academic chain in the form of a research residency + open compute, intersecting head-on with the AI4Science path of China's top AI labs. **Program design: from giving models to giving desks** Unlike simply open-sourcing models or opening APIs, the Seed STEM program requires selected scholars to enter ByteDance's Beijing offices as scientist advisors or PhD interns, collaborating with the Seed team for 6 months. The selection threshold focuses on three hard criteria: a PhD in a STEM field or equivalent research level, daily deep use of AI, and a preference for those who can program fluently. In other words, ByteDance isn't looking for occasional API users, but for peers willing to embed AI into their own research pipeline and treat the model as a collaborator. Beyond ample compute, the package also includes an industry-competitive salary — meaning ByteDance is using real money to buy a high-quality feedback loop. **Why Seed Edge, not Doubao?** Seed Edge is ByteDance's long-term internal research program, positioned to explore the unknown boundaries of intelligence, clearly differentiated from the commercial main line of Doubao\u002FJimeng. Putting the STEM program under Edge rather than the Doubao brand means ByteDance sees this round of research collaboration as frontier exploration, not pre-launch user research. This positioning also means the Seed Edge team has more freedom in compute scheduling — 6-month on-site research can't be satisfied with ordinary user-level quotas, which is a signal to both budget approval and cluster management. **Gap and difference with Anthropic, Google** Compared with Anthropic packaging its AI scientist workbench as a product (Claude Science beta is already online), or Google bringing Nobel laureate John Jumper on board to do Protein LLM, ByteDance's path is closer to DeepMind's early model: put the model team and the research team in the same room physically, iterate as you go. This model's strengths are fast feedback and engineering-ready output; its weakness is hard-to-scale and long PhD-training cycles. 100 scholars, 6-month cycle — ByteDance is essentially betting on a small-and-deep research organization paradigm. **A judgment on the AI4S track** The real signal of the Seed STEM program isn't how many PhDs it hired, but that it's willing to open up compute and model scheduling power to academic teams. In China, the research institutions that have consistently built up base-model supply are few — DeepMind has AlphaFold, Anthropic has Constitutional AI, and the ByteDance Doubao matrix has Seed Edge. When a Chinese vendor is willing to bear the cost of a research residency, it means the differentiated competition of base models has quietly shifted from leaderboard scores to who can get the model into scientists' workflows faster.","bytedance-seed-stem-scientist","2026-07-23T08:00:00Z","2026-07-23T08:11:34.625834Z","2026-08-19T02:08:40.142862Z",true,"agent",173,{"items":37},[38,43,48,53,58,63],{"id":39,"title":40,"news_slug":41,"published_at":42},"49d19ba1-8f45-475c-bed1-a69dc353523e","字节跳动用 10 万亿参数下注：规模赛跑与张一鸣的「不蒸馏」表态","bytedance-10t-mythos-zhangyiming-no-distill-2026-08","2026-08-08T00:00:00+00:00",{"id":44,"title":45,"news_slug":46,"published_at":47},"5f5bd5f2-9a02-470b-aa25-3f27fb9bb093","字节跳动正训练 10 万亿参数模型，规模对标 Anthropic Mythos 5","bytedance-10t-parameter-model-ft","2026-08-07T09:30:00+00:00",{"id":49,"title":50,"news_slug":51,"published_at":52},"59a18390-a856-4251-8407-96e641cf74bc","\"辰光一号\"把大模型搬上天:国内首次航天垂直大模型在轨训练开启","chenguang-1-satellite-llm","2026-07-25T00:00:00+00:00",{"id":54,"title":55,"news_slug":56,"published_at":57},"86c258f4-5fd5-45fa-9fe5-60dbb585bfff","DeepSeek 梁文锋路线图:持续学习才是 Agent 之后的真瓶颈","deepseek-liang-wenfeng-roadmap","2026-07-24T08:30:00+00:00",{"id":59,"title":60,"news_slug":61,"published_at":62},"8492350c-74ff-4ce3-bda5-c17b95b9e385","清华 CausalMix 把 LLM 数据混合从回归问题改成因果推断：换数据池不再重跑 proxy","tsinghua-causalmix-data-mix","2026-07-07T18:00:00+00:00",{"id":64,"title":65,"news_slug":66,"published_at":67},"0d8fdf45-4585-47c0-9e78-3652e318b156","Apple Intelligence 中国版落地:通义千问接管语言 AI,百度负责视觉搜索","apple-intelligence-china-qwen-baidu-2026","2026-08-25T12:00:00+00:00"]