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          "note": "2024年研发投入4031亿欧元。"
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          "title": "美联储｜2024年均汇率",
          "date": "2025-01-06",
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          "date": "2026-06-30",
          "type": "公司产品披露",
          "url": "https://www.anthropic.com/news/claude-science-ai-workbench",
          "note": "连接科研数据、工具、代码与算力的专用工作环境。"
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          "title": "Thermo Fisher｜与NVIDIA推进AI科研仪器",
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          "url": "https://ir.thermofisher.com/investors/news-events/news/news-details/2026/Thermo-Fisher-Scientific-Announces-Strategic-Collaboration-With-NVIDIA-Leveraging-AI-to-Advance-Scientific-Instrumentation-and-Accelerate-Laboratory-Performance/default.aspx",
          "note": "仪器、实验自动化与AI计算协同。"
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          "url": "https://deepmind.google/blog/alphaevolve-impact/",
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          "title": "本报告研究｜AI科研全流程收入与创新价值模型",
          "date": "2026-09-24",
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          "note": "2026为研究估计，2027—2030为研究预测；分药物研发、非药科研及成果分成，排除芯片。"
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          "title": "西南证券｜AI制药专题：全流程赋能制药未来，成药验证未来可期",
          "date": "2026-09-22",
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          "note": "全球制药研发支出与AI赋能研发支出预测转引弗若斯特沙利文；研发流程、药物模态及产业链分析。"
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          "date": "2024-03-08",
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          "url": "https://www.nature.com/articles/s41587-024-02143-0"
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          "note": "71例、12周；首要终点为安全性；肺功能为探索性疗效观察。",
          "url": "https://www.nature.com/articles/s41591-025-03743-2"
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          "id": "SC24",
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          "date": "2026-09-10",
          "type": "公司临床及经营披露",
          "note": "Ⅲ期计划320例、47家中心、52周；上半年总收入约1.06亿美元，同比增长287%。",
          "url": "https://insilico.com/news/isn1009261-insilico-medicine-doses-first-patient-genesis-ipf-3"
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          "id": "SC25",
          "title": "IQVIA｜2026全球研发趋势中的AI项目临床表现",
          "date": "2026-05-14",
          "type": "行业队列研究",
          "note": "经核验的AI新兴生物药企队列，近三年窗口Ⅰ期成功率75%，Ⅱ期与同类企业相近。",
          "url": "https://www.iqvia.com/blogs/2026/05/iqvia-institutes-global-r-and-d-trends-2026-report-finds-credible-signal-on-ai-enabled-programs"
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          "title": "金斯瑞｜2026年中期业绩",
          "date": "2026-08-18",
          "type": "公司财务披露",
          "note": "AI赋能药物发现业务连续第三个半年实现收入翻倍；不是公司全部收入翻倍。",
          "url": "https://www.genscript.com/genscript-biotech-announces-2026-interim-results.html"
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          "type": "公司合作公告",
          "note": "为平台生物技术客户提供实验服务，连接计算预测与实物验证。",
          "url": "https://www.genscript.com/genscript-joins-lilly-tunelab-to-advance-ai-enabled-drug-discovery.html"
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          "id": "SC28",
          "title": "晶泰控股｜2026年中期业绩",
          "date": "2026-08-19",
          "type": "公司财务披露",
          "note": "智能解决方案收入1.935亿元、增长136.4%；剔除授权收入后整体基础业务增长73.8%。",
          "url": "https://www.prnewswire.com/news-releases/xtalpi-holdings-announces-2026-interim-results-302855288.html"
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          "title": "薛定谔｜2026年第二季度业绩及Bunsen",
          "date": "2026-08-05",
          "type": "公司SEC披露",
          "note": "软件收入3250万美元，药物发现收入2300万美元，其中Ajax里程碑1000万美元；Bunsen开始早期访问。",
          "url": "https://www.sec.gov/Archives/edgar/data/1490978/000149097826000067/sdgr-20260630x8kxexx991.htm"
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          "title": "英矽智能｜与礼来全球管线授权和研发合作",
          "date": "2026-03-29",
          "type": "公司交易所公告",
          "note": "首付款1.15亿美元，潜在总金额约27.5亿美元，另有阶梯式销售分成；潜在金额非当期收入。",
          "url": "https://www1.hkexnews.hk/listedco/listconews/sehk/2026/0329/2026032900717.pdf"
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          "id": "SC31",
          "title": "英矽智能｜与武田开展药物研发合作",
          "date": "2026-07-02",
          "type": "公司合作公告",
          "note": "约6000万美元为启动、近期与里程碑付款组合；总潜在金额6亿美元及销售分成。",
          "url": "https://insilico.com/news/4ifuiaal01-insilico-medicine-announces-collaboratio"
        },
        {
          "id": "SC32",
          "title": "OpenAI｜GPT-Rosalind科研能力与全球开放",
          "date": "2026-09-11",
          "type": "公司产品披露",
          "note": "4月16日发布，9月11日更新为面向符合条件的全球机构开放。",
          "url": "https://openai.com/index/introducing-gpt-rosalind/"
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          "id": "SC33",
          "title": "Microsoft与BHP｜AI筛选铜浸出试剂",
          "date": "2026-06-02",
          "type": "公司客户案例",
          "note": "筛选50多万种候选试剂，并将缩小后的候选送至实验室测试。",
          "url": "https://news.microsoft.com/signal/articles/microsoft-discovery-bhp-copper/"
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        {
          "id": "SC34",
          "title": "Microsoft Research｜MatterSim与实验材料发现",
          "date": "2026-05-12",
          "type": "公司原始研究",
          "note": "计算预测与实验验证连接，展示高导热四方TaP材料及更快的材料仿真。",
          "url": "https://www.microsoft.com/en-us/research/blog/advancing-ai-for-materials-with-mattersim-experimental-synthesis-faster-simulation-and-multi-task-models/"
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          "id": "SC35",
          "title": "Nature Communications｜TrialGPT患者与试验匹配",
          "date": "2024-11-18",
          "type": "原始论文",
          "note": "小规模模拟临床工作流用户研究，匹配筛选时间减少42.6%；不等于整个临床试验缩短42.6%。",
          "url": "https://www.nature.com/articles/s41467-024-53081-z"
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          "id": "SC36",
          "title": "Anthropic｜递归自我改进的进展与边界",
          "date": "2026-09-18",
          "type": "公司原始研究",
          "url": "https://www.anthropic.com/institute/recursive-self-improvement",
          "note": "9月18日更新。AI已参与研究执行、方法和工具改进；完整自主开发后继模型仍是未来路径。"
        },
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          "id": "SC37",
          "title": "Anthropic｜自动研究者改进模型后训练",
          "date": "2026-08-28",
          "type": "公司原始研究",
          "url": "https://www.anthropic.com/research/automated-researchers-mitigate-alignment-failures",
          "note": "Sonnet 5在60小时探索50余种方法，改善早期Opus 4.8检查点的对齐表现；研究另有未展示评测和较大模型迁移验证。"
        },
        {
          "id": "SC38",
          "title": "Google DeepMind｜科研智能体与验证瓶颈",
          "date": "2026-07",
          "type": "原始研究综述",
          "url": "https://deepmind.google/public-policy/conjecture-machines-ai-agents-and-the-new-validation-bottleneck-in-science/",
          "note": "公开日期为2026年7月。数学与代码可部分自动检验，材料与生物成果仍需独立实验，真实世界验证决定整轮提速。"
        },
        {
          "id": "SC40",
          "title": "VecAI知识库｜模型研发与递归改进进展",
          "date": "2026-09-18",
          "type": "专家访谈",
          "note": "讨论重复训练工作自动化与进一步提出假设、组织测试、复用研究知识的路径。"
        },
        {
          "id": "SC41",
          "title": "VecAI知识库｜模型迭代与科研反馈",
          "date": "2026-09-21",
          "type": "专家访谈",
          "note": "局部半自动递归迭代已经推进，研究流程、数据收集与模型能力共同决定进展。"
        },
        {
          "id": "SC43",
          "title": "本报告研究｜科研反馈与社会效益情景",
          "date": "2026-09-24",
          "type": "机制测算",
          "note": "单轮提速由计算和验证时间份额决定；健康增益和节能示意分别计算，不相加，也不形成AI供应商收入。"
        },
        {
          "id": "SC44",
          "title": "OpenAI｜Navier–Stokes问题的证明与多智能体研究",
          "date": "2026-09-08",
          "type": "公司原始研究",
          "url": "https://openai.com/index/navier-stokes-solution/",
          "note": "公司公布带光滑外力情形的证明及Lean形式化；成功组约1万并发智能体，88小时后得到解答，再用17小时形式化与验证。并发智能体数量不等于物理CPU数量。"
        },
        {
          "id": "SC45",
          "title": "Anthropic｜费马大定理的形式化验证",
          "date": "2026-09-04",
          "type": "公司原始研究",
          "url": "https://www.anthropic.com/research/formalizing-fermats-last-theorem",
          "note": "数十个智能体依靠共享定理依赖图，11天将已有证明形式化为Lean可检查证明；不是首次证明费马大定理。"
        },
        {
          "id": "SC46",
          "title": "Anthropic｜黎曼猜想相关数学问题的新进展",
          "date": "2026-08-10",
          "type": "公司原始研究",
          "url": "https://www.anthropic.com/research/riemann-zeta",
          "note": "临界线零点比例的已证下界由41.6%提高至67.2%；约60个子智能体参与探索和验证。该结果不是解决黎曼猜想本身。"
        },
        {
          "id": "SC47",
          "title": "OpenAI｜数学研究进展与独立顾问组",
          "date": "2026-09-21",
          "type": "公司研究进展披露",
          "url": "https://openai.com/index/advisory-group-on-mathematics-and-ai/",
          "note": "公司披露内部模型已解决100余个长期开放数学问题；数量为公司披露口径。"
        },
        {
          "id": "SC48",
          "title": "VecAI知识库｜科研智能体与沙盒执行架构",
          "date": "2026-09-13",
          "type": "产业研究",
          "note": "数学研究的并行探索带动代码执行、隔离环境与任务协调需求；与9月16日模型与Agent调研相互印证。"
        },
        {
          "id": "SC49",
          "title": "FDA｜临床Ⅰ、Ⅱ、Ⅲ期各自回答什么问题",
          "date": "2026-09-24",
          "type": "官方科普说明",
          "url": "https://www.fda.gov/patients/drug-development-process/step-3-clinical-research",
          "note": "查阅日。Ⅰ期聚焦安全性和剂量，Ⅱ期观察患者中的初步效果，Ⅲ期以更大规模试验确认治疗获益和不良反应。"
        },
        {
          "id": "SC51",
          "title": "本报告研究｜2035与2040年AI科研收入条件情景",
          "date": "2026-09-24",
          "type": "远期研究情景",
          "note": "在固定2030基准上，分科研预算、AI交付部署、外部收费与药物成果分成推演；含三条条件路径，不计芯片、药品销售额或社会价值。"
        },
        {
          "id": "SC52",
          "title": "BIO / Informa / QLS｜Clinical Development Success Rates and Contributing Factors 2011–2020",
          "date": "2021-02",
          "type": "原始行业队列研究",
          "url": "https://go.bio.org/rs/490-EHZ-999/images/ClinicalDevelopmentSuccessRates2011_2020.pdf",
          "note": "第6页图1：Ⅰ期至Ⅱ期通过率52.0%，4,414次阶段转移；样本为2011-01-01至2020-11-30企业资助、面向FDA注册的项目，覆盖全部疾病和药物模态。作为历史行业参照。"
        }
      ],
      "inputs": {
        "years": [
          2026,
          2027,
          2028,
          2029,
          2030
        ],
        "nominalGlobalRAndD2024": 2500,
        "nominalGlobalRAndDGrowth": 0.06,
        "drugRAndD": [
          316.8,
          335.7,
          354.9,
          374.4,
          394.3
        ],
        "drugStages": [
          {
            "id": "discovery",
            "name": "发现与分子优化",
            "budgetShare": 0.25,
            "adoption": [
              0.2,
              0.35,
              0.53,
              0.7,
              0.85
            ],
            "feeShare": [
              0.4,
              0.41,
              0.43,
              0.44,
              0.45
            ]
          },
          {
            "id": "preclinical",
            "name": "临床前验证与转化",
            "budgetShare": 0.15,
            "adoption": [
              0.15,
              0.27,
              0.43,
              0.6,
              0.75
            ],
            "feeShare": [
              0.3,
              0.32,
              0.35,
              0.38,
              0.4
            ]
          },
          {
            "id": "clinical",
            "name": "临床设计与运营",
            "budgetShare": 0.5,
            "adoption": [
              0.09,
              0.16,
              0.27,
              0.41,
              0.55
            ],
            "feeShare": [
              0.15,
              0.18,
              0.21,
              0.23,
              0.25
            ]
          },
          {
            "id": "development",
            "name": "制剂、工艺与注册研发",
            "budgetShare": 0.1,
            "adoption": [
              0.08,
              0.15,
              0.27,
              0.43,
              0.6
            ],
            "feeShare": [
              0.15,
              0.18,
              0.21,
              0.23,
              0.25
            ]
          }
        ],
        "nonDrugSegments": [
          {
            "id": "materials",
            "name": "材料、化学与能源研发",
            "workPool2026": 400,
            "growth": 0.08,
            "adoption": [
              0.08,
              0.17,
              0.32,
              0.51,
              0.7
            ],
            "feeShare": [
              0.18,
              0.21,
              0.24,
              0.27,
              0.3
            ]
          },
          {
            "id": "engineering",
            "name": "工业产品与多物理场研发",
            "workPool2026": 550,
            "growth": 0.08,
            "adoption": [
              0.07,
              0.16,
              0.32,
              0.54,
              0.75
            ],
            "feeShare": [
              0.18,
              0.21,
              0.24,
              0.27,
              0.3
            ]
          },
          {
            "id": "basic",
            "name": "基础生命、农业与环境科研",
            "workPool2026": 250,
            "growth": 0.08,
            "adoption": [
              0.08,
              0.16,
              0.29,
              0.44,
              0.6
            ],
            "feeShare": [
              0.16,
              0.18,
              0.21,
              0.23,
              0.25
            ]
          }
        ],
        "drugProductSales": [
          0.5,
          1.5,
          4,
          11,
          24
        ],
        "drugRoyaltyRate": 0.1,
        "scenarios": [
          {
            "id": "gradual",
            "label": "渐进扩散",
            "nonDrugGrowth": 0.06,
            "adoptionScale": 0.7,
            "feeScale": 0.8,
            "drugSalesScale": 0.5
          },
          {
            "id": "core",
            "label": "核心判断",
            "nonDrugGrowth": 0.08,
            "adoptionScale": 1,
            "feeScale": 1,
            "drugSalesScale": 1
          },
          {
            "id": "fast",
            "label": "加速扩散",
            "nonDrugGrowth": 0.1,
            "adoptionScale": 1.2,
            "feeScale": 1.15,
            "drugSalesScale": 2
          }
        ],
        "innovation": {
          "baselineProjects": 100,
          "costReduction": 0.3,
          "baselineSuccess": 0.1,
          "success": 0.15,
          "yearsEarlier": 2,
          "discountRate": 0.1
        },
        "scope": {
          "chipsIncluded": false,
          "drugSalesIncluded": false,
          "legacyNonAiServicesIncluded": false,
          "upstreamResaleIncluded": false,
          "integratedAiResearchDeliveryIncluded": true
        }
      },
      "chain": [
        {
          "stage": "选靶点",
          "question": "值得解决哪个生物问题？",
          "capability": "整合组学、文献与疾病证据，寻找并排序因果假设",
          "economic": "更早淘汰错误方向，减少无效立项",
          "deliverable": "可验证靶点与证据包"
        },
        {
          "stage": "造分子",
          "question": "什么分子既有效又能成药？",
          "capability": "联合优化结合能力、选择性、稳定性与可制造性",
          "economic": "少做低质量合成，把实验留给高价值候选",
          "deliverable": "候选分子与实验设计"
        },
        {
          "stage": "做验证",
          "question": "在真实生物系统中能否成立？",
          "capability": "自动化合成、细胞与动物验证，将失败结果反馈模型",
          "economic": "提高实验吞吐，形成可复用的专有数据",
          "deliverable": "候选药物与转化证据"
        },
        {
          "stage": "推临床",
          "question": "哪类患者、怎样试验能回答疗效？",
          "capability": "患者分层、试验设计、中心选择、匹配入组与数据整理",
          "economic": "减少等待和无效运营，提高单位试验的信息量",
          "deliverable": "临床方案与试验运营"
        },
        {
          "stage": "能交付",
          "question": "如何稳定生产、形成可授权资产？",
          "capability": "优化制剂、递送、合成路线、质量与注册资料",
          "economic": "扩大可开发药物范围，并分享上市后的成果收益",
          "deliverable": "工艺、申报与资产权益"
        }
      ],
      "companies": [
        {
          "name": "英矽智能",
          "model": "软件 + 候选药物授权",
          "proof": "2026上半年收入约1.06亿美元，增长287%；礼来合作首付款1.15亿美元",
          "reason": "将发现能力转为可开发资产，按研发推进获得付款",
          "sources": [
            "SC24",
            "SC30"
          ]
        },
        {
          "name": "金斯瑞",
          "model": "AI设计衔接合成与验证",
          "proof": "AI药物发现业务连续第三个半年翻倍；9月接入礼来TuneLab",
          "reason": "候选数量扩大后，客户为实验交付和数据反馈持续付费",
          "sources": [
            "SC26",
            "SC27"
          ]
        },
        {
          "name": "晶泰控股",
          "model": "计算平台 + 自动化实验",
          "proof": "上半年智能解决方案收入1.935亿元，增长136.4%",
          "reason": "从单次计算扩到持续研发项目与实验平台",
          "sources": [
            "SC28"
          ]
        },
        {
          "name": "薛定谔",
          "model": "科学软件 + 合作研发",
          "proof": "第二季度软件3250万美元、药物发现2300万美元",
          "reason": "既收工具费用，也按候选开发进度获得里程碑",
          "sources": [
            "SC29"
          ]
        },
        {
          "name": "百奥赛图",
          "model": "抗体库 + 药效验证 + 许可",
          "proof": "RenSuper连接抗体数据、AI筛选与自动验证",
          "reason": "真实生物反馈可反复复用，服务与资产权益互相支持",
          "sources": [
            "SC12",
            "SC13"
          ]
        },
        {
          "name": "Isomorphic Labs",
          "model": "药物设计与多靶点合作",
          "proof": "与强生合作向更多药物模态推进",
          "reason": "由模型能力进入大型药企的真实研发预算",
          "sources": [
            "SC15"
          ]
        }
      ],
      "sourceBaseInputs": {
        "drugBudget": {
          "sourceIds": [
            "SC21",
            "SC01"
          ],
          "status": "外部行业预测",
          "values": [
            316.8,
            335.7,
            354.9,
            374.4,
            394.3
          ]
        },
        "nominalGlobalBudget": {
          "sourceIds": [
            "SC02",
            "SC03",
            "SC04",
            "SC05",
            "SC06",
            "SC20"
          ],
          "status": "官方数据校验下的研究估计，非全球官方名义总额"
        },
        "nonDrugWorkPools": {
          "sourceIds": [
            "SC01",
            "SC11",
            "SC16",
            "SC17",
            "SC20",
            "SC33",
            "SC34"
          ],
          "status": "按完整科研交付范围构建的研究假设，不是外部统计"
        },
        "adoptionAndFees": {
          "sourceIds": [
            "SC20"
          ],
          "status": "研究假设；不将公司局部任务倍数当作全行业提效"
        },
        "drugProductRights": {
          "sourceIds": [
            "SC20",
            "SC30",
            "SC31"
          ],
          "status": "2030假设相关药物销售240亿美元、平均分成10%，只计24亿美元分成"
        }
      },
      "rsi": {
        "sourceIds": [
          "SC08",
          "SC17",
          "SC36",
          "SC37",
          "SC38",
          "SC40",
          "SC41",
          "SC43"
        ],
        "definition": "提升研究能力，并将可复用的改进用于下一轮研究；不等同于固定模型反复优化一个候选。",
        "cycleFormula": "1 / (computeShare / computeSpeedup + (1 - computeShare) / validationSpeedup)",
        "cycleExamples": [
          {
            "label": "计算主导的一轮",
            "computeShare": 0.7,
            "computeSpeedup": 4,
            "validationSpeedup": 1
          },
          {
            "label": "实验主导的一轮",
            "computeShare": 0.2,
            "computeSpeedup": 4,
            "validationSpeedup": 1
          }
        ],
        "levels": [
          {
            "title": "候选优化",
            "text": "固定研究方法，反复生成并筛选更好的答案。",
            "change": "候选变好"
          },
          {
            "title": "真实反馈",
            "text": "实验或独立评测检验结果，数据返回下一轮。",
            "change": "证据变多"
          },
          {
            "title": "工具与方法改进",
            "text": "优化科学软件、实验设计和搜索策略，并持续复用。",
            "change": "研究过程变强"
          },
          {
            "title": "研究模型改进",
            "text": "改进训练数据与方法，让模型承担更深的下一轮研究。",
            "change": "研究者能力增强"
          }
        ]
      },
      "societalScenarios": {
        "status": "独立应用情景示意，非临床预测或能源需求预测",
        "sourceIds": [
          "SC43"
        ],
        "healthUnit": "million healthy life-years for the beneficiary cohort; not an annual recurring flow",
        "energyUnit": "TWh saved per year; gross energy expenditure avoided in USD billion per year",
        "defaultId": "scale",
        "presets": [
          {
            "id": "limited",
            "label": "初步扩散",
            "patientsMillion": 2,
            "healthyYearsPerPatient": 0.05,
            "energyCoveredTwh": 500,
            "energySavingShare": 0.01,
            "electricityUsdPerKwh": 0.1
          },
          {
            "id": "scale",
            "label": "规模应用",
            "patientsMillion": 10,
            "healthyYearsPerPatient": 0.1,
            "energyCoveredTwh": 1000,
            "energySavingShare": 0.03,
            "electricityUsdPerKwh": 0.1
          },
          {
            "id": "broad",
            "label": "广泛应用",
            "patientsMillion": 20,
            "healthyYearsPerPatient": 0.2,
            "energyCoveredTwh": 2000,
            "energySavingShare": 0.05,
            "electricityUsdPerKwh": 0.1
          }
        ]
      },
      "asOf": "2026-09-24",
      "frontierMath": {
        "sourceIds": [
          "SC44",
          "SC45",
          "SC46",
          "SC47",
          "SC48"
        ],
        "cases": [
          {
            "name": "OpenAI · Navier–Stokes",
            "date": "2026-09-08",
            "metric": "约1万并发智能体",
            "result": "公布流体方程难题证明与Lean形式化",
            "detail": "88小时探索，随后17小时形式化验证",
            "sourceIds": [
              "SC44"
            ]
          },
          {
            "name": "Anthropic · 费马大定理",
            "date": "2026-09-04",
            "metric": "11天",
            "result": "将已有数学证明转成计算机可检查证明",
            "detail": "数十个智能体共享定理依赖图",
            "sourceIds": [
              "SC45"
            ]
          },
          {
            "name": "Anthropic · 黎曼相关问题",
            "date": "2026-08-10",
            "metric": "41.6% → 67.2%",
            "result": "提高临界线上零点比例的已证下界",
            "detail": "约60个子智能体探索、计算与交叉检验",
            "sourceIds": [
              "SC46"
            ]
          }
        ]
      },
      "clinicalInterpretation": {
        "sourceIds": [
          "SC23",
          "SC24",
          "SC25",
          "SC49",
          "SC52"
        ],
        "phaseOneSuccess": 0.75,
        "population": "IQVIA核验AI参与的新兴生物药企研发项目",
        "window": "最近三年统计窗口",
        "denominatorExplanation": "纳入该队列Ⅰ期阶段成功率评估的研发项目，统计单位是项目而非患者；不是从全部发现候选到上市的成功率。",
        "denominatorCount": null,
        "phaseTwoComparison": "与同类非AI项目相近",
        "drugStatus": "Rentosertib于2026-09-10进入Ⅲ期首例给药，仍在临床开发。",
        "historicalBaseline": {
          "phaseOneSuccess": 0.52,
          "phaseTransitions": 4414,
          "population": "企业资助、面向FDA注册的全部疾病与药物模态项目",
          "window": "2011-01-01—2020-11-30",
          "label": "历史行业基准",
          "sourceIds": [
            "SC52"
          ],
          "denominatorExplanation": "成功进入下一期和在该阶段终止的项目之和；未决项目不作为阶段结果。"
        },
        "comparisonNote": "时期、企业与药物构成不同；非随机队列比较，23个百分点差额不作AI因果增益。",
        "iqviaMatchedControlRate": null,
        "comparisonStatus": "AI队列与历史行业基准的跨队列参照；IQVIA公开说明未提供同规模非AI对照组的精确通过率。"
      },
      "longTerm": {
        "years": [
          2030,
          2035,
          2040
        ],
        "sourceIds": [
          "SC20",
          "SC21",
          "SC25",
          "SC36",
          "SC44",
          "SC51"
        ],
        "status": "2035/2040可观察条件下的研究情景；2030沿用固定基准",
        "unit": "USD billion per calendar year",
        "scope": {
          "chipsIncluded": false,
          "drugProductSalesIncluded": false,
          "socialValueIncluded": false,
          "upstreamResaleIncluded": false,
          "intermediateResearchProcurement": "最终科研客户的采购；如跨板块产品模型已包含某笔科研采购，汇总端只保留一次。"
        },
        "scenarioKeys": [
          "gradual",
          "core",
          "accelerated"
        ],
        "scenarios": [
          {
            "key": "gradual",
            "label": "渐进扩散",
            "drugBudgetGrowth": [
              0.04,
              0.04
            ],
            "nonDrugBudgetGrowth": [
              0.05,
              0.05
            ],
            "globalBudgetGrowth": [
              0.05,
              0.05
            ],
            "drugAdoption": [
              [
                0.9,
                0.82,
                0.65,
                0.7
              ],
              [
                0.95,
                0.9,
                0.78,
                0.85
              ]
            ],
            "drugFees": [
              [
                0.46,
                0.41,
                0.29,
                0.3
              ],
              [
                0.48,
                0.43,
                0.33,
                0.34
              ]
            ],
            "nonDrugAdoption": [
              [
                0.8,
                0.83,
                0.7
              ],
              [
                0.9,
                0.9,
                0.82
              ]
            ],
            "nonDrugFees": [
              [
                0.32,
                0.32,
                0.28
              ],
              [
                0.36,
                0.36,
                0.32
              ]
            ],
            "drugProductSales": [
              60,
              150
            ],
            "royaltyRates": [
              0.1,
              0.1
            ],
            "conditions": [
              "工具和局部实验交付率提升，跨机构连续执行仍以人工协调为主。",
              "AI项目阶段成功率保持优势，后期临床和跨领域复用逐步积累。",
              "研发预算温和增长，外部交付费用随工具采用提升。"
            ]
          },
          {
            "key": "core",
            "label": "核心路径",
            "drugBudgetGrowth": [
              0.06,
              0.05
            ],
            "nonDrugBudgetGrowth": [
              0.08,
              0.07
            ],
            "globalBudgetGrowth": [
              0.06,
              0.05
            ],
            "drugAdoption": [
              [
                0.95,
                0.9,
                0.75,
                0.8
              ],
              [
                0.98,
                0.95,
                0.9,
                0.92
              ]
            ],
            "drugFees": [
              [
                0.5,
                0.45,
                0.35,
                0.35
              ],
              [
                0.55,
                0.5,
                0.45,
                0.45
              ]
            ],
            "nonDrugAdoption": [
              [
                0.9,
                0.9,
                0.8
              ],
              [
                0.97,
                0.97,
                0.92
              ]
            ],
            "nonDrugFees": [
              [
                0.4,
                0.4,
                0.35
              ],
              [
                0.5,
                0.5,
                0.45
              ]
            ],
            "drugProductSales": [
              100,
              250
            ],
            "royaltyRates": [
              0.1,
              0.12
            ],
            "conditions": [
              "科研智能体稳定接通真实实验，自动执行与独立验证能够跨项目复用。",
              "到2035年临床设计与运营部署率达到75%，非药科研部署率达到80%—90%；到2040年进一步扩散。",
              "外部供应商承接更完整的设计、实验和运营任务，收费占部署预算比例达到35%—50%，随后继续加深。",
              "相关药物获得临床和商业验证，分成对应年销售2035年1000亿美元、2040年2500亿美元；科研预算按阶段增长。"
            ]
          },
          {
            "key": "accelerated",
            "label": "加速扩散",
            "drugBudgetGrowth": [
              0.08,
              0.07
            ],
            "nonDrugBudgetGrowth": [
              0.1,
              0.09
            ],
            "globalBudgetGrowth": [
              0.08,
              0.07
            ],
            "drugAdoption": [
              [
                0.98,
                0.95,
                0.85,
                0.9
              ],
              [
                0.99,
                0.98,
                0.95,
                0.97
              ]
            ],
            "drugFees": [
              [
                0.55,
                0.5,
                0.4,
                0.4
              ],
              [
                0.62,
                0.58,
                0.53,
                0.53
              ]
            ],
            "nonDrugAdoption": [
              [
                0.95,
                0.95,
                0.9
              ],
              [
                0.99,
                0.99,
                0.97
              ]
            ],
            "nonDrugFees": [
              [
                0.48,
                0.48,
                0.42
              ],
              [
                0.6,
                0.6,
                0.54
              ]
            ],
            "drugProductSales": [
              150,
              500
            ],
            "royaltyRates": [
              0.12,
              0.15
            ],
            "conditions": [
              "自动实验、可信验证与科研工具持续改进，降低更多领域的完整项目交付门槛。",
              "研发回报改善支持更快预算扩张，科研客户更多按完整成果采购。",
              "大规模临床验证与上市成果扩大分成池，部署率和交付深度共同上升。"
            ]
          }
        ]
      }
    },
    "chips": {
      "version": "chips-r5-20260924",
      "asOf": "2026-09-24",
      "unit": "USD billion / calendar year",
      "years": [
        2026,
        2027,
        2028,
        2029,
        2030
      ],
      "observed": {
        "q12026": {
          "cae": 2.0184,
          "physical": 0.7513,
          "pcbMcm": 0.4192,
          "ip": 2.3325,
          "services": 0.2264
        },
        "usRd2025": 76.8,
        "usRdShare2023": 0.62
      },
      "common": {
        "assumedUsRdShare2025": 0.6,
        "rdGrowth2026": 0.12,
        "annualRdGrowth": 0.1,
        "annualEdaGrowth": 0.1,
        "designLaborShare": 0.6
      },
      "scenarios": [
        {
          "key": "cautious",
          "name": "审慎",
          "attach": [
            0.15,
            0.25,
            0.35,
            0.45,
            0.55
          ],
          "premium": [
            0.1,
            0.14,
            0.18,
            0.22,
            0.25
          ],
          "adoption": [
            0.05,
            0.12,
            0.23,
            0.35,
            0.45
          ],
          "timeSaved": [
            0.2,
            0.25,
            0.3,
            0.35,
            0.35
          ],
          "valueCapture": [
            0.2,
            0.23,
            0.25,
            0.28,
            0.3
          ],
          "directComputeShare": [
            0.04,
            0.05,
            0.06,
            0.065,
            0.07
          ]
        },
        {
          "key": "base",
          "name": "基准",
          "attach": [
            0.2,
            0.35,
            0.5,
            0.65,
            0.8
          ],
          "premium": [
            0.15,
            0.2,
            0.25,
            0.3,
            0.35
          ],
          "adoption": [
            0.1,
            0.22,
            0.38,
            0.55,
            0.7
          ],
          "timeSaved": [
            0.25,
            0.32,
            0.4,
            0.45,
            0.5
          ],
          "valueCapture": [
            0.25,
            0.3,
            0.34,
            0.37,
            0.4
          ],
          "directComputeShare": [
            0.05,
            0.06,
            0.07,
            0.08,
            0.09
          ]
        },
        {
          "key": "upside",
          "name": "积极",
          "attach": [
            0.25,
            0.45,
            0.65,
            0.8,
            0.95
          ],
          "premium": [
            0.2,
            0.28,
            0.35,
            0.42,
            0.5
          ],
          "adoption": [
            0.15,
            0.3,
            0.5,
            0.7,
            0.85
          ],
          "timeSaved": [
            0.3,
            0.4,
            0.5,
            0.57,
            0.65
          ],
          "valueCapture": [
            0.3,
            0.35,
            0.4,
            0.45,
            0.5
          ],
          "directComputeShare": [
            0.06,
            0.07,
            0.08,
            0.09,
            0.1
          ]
        }
      ],
      "stages": [
        {
          "name": "产品需求",
          "deliverable": "需求规格、性能/功耗/成本目标",
          "mechanism": "把应用负载转成可测试约束，比较芯片、软件与封装的组合方案。",
          "effect": "减少需求遗漏和后期改规格；客户更早判断哪些定制值得做。",
          "budget": "架构与系统研发预算",
          "sources": [
            "CH09"
          ]
        },
        {
          "name": "芯片架构",
          "deliverable": "计算、存储、互连与IP分工",
          "mechanism": "并行探索模块组合、内存层次和带宽，调用仿真评估方案。",
          "effect": "同一团队比较更多架构，推动专用芯片、Chiplet和定制处理器。",
          "budget": "架构工具、IP与工程服务",
          "sources": [
            "CH07",
            "CH09"
          ]
        },
        {
          "name": "RTL / 验证",
          "deliverable": "硬件描述代码、测试平台、覆盖率",
          "mechanism": "阅读规格和旧代码，生成RTL与测试，运行仿真/形式验证，追踪失败并修改。",
          "effect": "最先释放可计量的工程人力；把等待人调试变成多轮自动执行。",
          "budget": "工程智能体、仿真许可与运行算力",
          "sources": [
            "CH05",
            "CH06",
            "CH07",
            "CH08"
          ]
        },
        {
          "name": "逻辑综合",
          "deliverable": "满足约束的逻辑门网表",
          "mechanism": "调用综合引擎，调整约束与脚本，比较面积、功耗和时序结果。",
          "effect": "更快搜索可行解，减少前端功能正确但后端难实现的返工。",
          "budget": "EDA功能升级与额外工具运行",
          "sources": [
            "CH09"
          ]
        },
        {
          "name": "布局布线",
          "deliverable": "器件位置、金属连线和物理版图",
          "mechanism": "搜索floorplan和实现参数；由专业引擎完成放置、布线与优化。",
          "effect": "扩大设计空间搜索，以更多计算换更好的性能、功耗和面积。",
          "budget": "物理实现软件、CPU/内存与GPU加速",
          "sources": [
            "CH06",
            "CH09",
            "CH12"
          ]
        },
        {
          "name": "签核",
          "deliverable": "时序、功耗、物理规则与电热检查",
          "mechanism": "归因违规、迭代修复，复用工艺认证的签核引擎检查每次修改。",
          "effect": "加快收敛并降低重新流片概率；签核质量决定成果是否可交付。",
          "budget": "签核工具、多物理场仿真和工程成果费",
          "sources": [
            "CH09",
            "CH20"
          ]
        },
        {
          "name": "流片",
          "deliverable": "最终版图交付、掩模数据与投片安排",
          "mechanism": "自动核对交付包，辅助光学邻近修正和掩模计算。",
          "effect": "减少交付错误与掩模计算等待；形成设计到制造的数据闭环。",
          "budget": "掩模计算、设计服务和工艺接口",
          "sources": [
            "CH09",
            "CH10"
          ]
        },
        {
          "name": "晶圆制造",
          "deliverable": "加工完成的晶圆与过程数据",
          "mechanism": "用于工艺仿真、缺陷识别、异常归因与设备/过程参数优化。",
          "effect": "提高工艺开发和良率爬坡效率；物理加工仍按工序完成。",
          "budget": "工艺研发、工厂软件和检测/计算资源",
          "sources": [
            "CH10",
            "CH15"
          ]
        },
        {
          "name": "封装测试",
          "deliverable": "互连、散热合格且通过测试的芯片",
          "mechanism": "协同优化多裸片、供电与散热，生成测试方案，回传失效分析。",
          "effect": "先进封装复杂度扩大系统级工具需求；测试数据反哺下一版设计。",
          "budget": "封装EDA、DFT、测试及良率软件",
          "sources": [
            "CH09",
            "CH11",
            "CH15"
          ]
        }
      ],
      "sources": [
        {
          "id": "CH01",
          "title": "SEMI｜2026Q1电子系统设计行业收入",
          "date": "2026-07-13",
          "type": "行业统计",
          "url": "https://www.semi.org/en/semi-press-release/esd-alliance-reports-electronic-system-design-industry-posts-5.7-billion-dollars-in-revenue-in-q1-2026",
          "note": "Q1 CAE 20.184亿、物理设计/验证7.513亿、PCB/MCM 4.192亿美元；三项合计31.889亿美元。全年参照按季度乘4，不是全年实绩。"
        },
        {
          "id": "CH02",
          "title": "SIA｜2026年美国半导体产业报告",
          "date": "2026-07-27",
          "type": "行业统计",
          "url": "https://www.semiconductors.org/2026-state-of-the-industry-report-historic-growth-amid-intensifying-global-competition/",
          "note": "美国总部企业2025年研发投入768亿美元；仅作为全球研发预算推算的观测锚。"
        },
        {
          "id": "CH03",
          "title": "TechInsights｜全球半导体研发地域结构",
          "date": "2024-06",
          "type": "行业原始研究",
          "url": "https://www.techinsights.com/blog/americas-chip-suppliers-continue-dominate-rd-spending",
          "note": "正文引用2024 McClean Report对2023年的研究：美洲约62%，其中基本为美国企业。网页更新日2026-08-20不是数据年份。"
        },
        {
          "id": "CH04",
          "title": "Cadence｜ChipStack前端设计与验证智能体",
          "date": "2026-02-10",
          "type": "公司公告",
          "url": "https://www.cadence.com/en_US/home/company/newsroom/press-releases/pr/2026/cadence-unleashes-chipstack-ai-super-agent-pioneering-a-new.html",
          "note": "前端设计/验证任务宣称最高10倍生产力提升；指指定任务。"
        },
        {
          "id": "CH05",
          "title": "Cadence与NVIDIA｜自主虚拟芯片工程师",
          "date": "2026-06-01",
          "type": "公司公告",
          "url": "https://www.cadence.com/en_US/home/company/newsroom/press-releases/pr/2026/cadence-unveils-industrys-first-fully-autonomous-virtual.html",
          "note": "特定RTL验证循环超过40倍提速、五周至一天以内；2026H2早期访问计划。"
        },
        {
          "id": "CH06",
          "title": "Synopsys、AMD与Microsoft｜自主调试与实现闭环",
          "date": "2026-07-27",
          "type": "公司及客户公告",
          "url": "https://news.synopsys.com/2026-07-27-Synopsys-Advances-Agentic-AI-Chip-Design-with-AMD-and-Microsoft",
          "note": "AMD评估中debug周期缩短25—40%；提供Microsoft Discovery评估访问。"
        },
        {
          "id": "CH07",
          "title": "ChipAgents与Andes｜定制处理器生产部署",
          "date": "2026-09-02",
          "type": "公司及客户案例",
          "url": "https://www.businesswire.com/news/home/20260902122134/en/ChipAgents-Helps-Andes-Technology-Dramatically-Accelerate-Custom-Processor-Design-and-Verification",
          "note": "LSU定制8.5周至6周；独立BIU验证2—3个月至约3周。"
        },
        {
          "id": "CH08",
          "title": "ChipAgents与eMemory｜非易失存储IP验证",
          "date": "2026-09-21",
          "type": "公司及客户案例",
          "url": "https://www.businesswire.com/news/home/20260921141786/en/ChipAgents-Helps-eMemory-Cut-NVM-IP-Functional-Model-Verification-Effort-by-80",
          "note": "手册分析与验证环境构建从估计4天至5小时；测试模式增加18%。"
        },
        {
          "id": "CH09",
          "title": "Siemens｜Fuse EDA AI Agent",
          "date": "2026-03-16",
          "type": "公司公告",
          "url": "https://news.siemens.com/en-us/siemens-fuse-eda-ai-agent/",
          "note": "编排架构、RTL、验证、布局布线、物理签核、DFT及OPC工具；专业工具输出提供验证闭环。"
        },
        {
          "id": "CH10",
          "title": "NVIDIA与TSMC｜AI进入晶圆制造流程",
          "date": "2026-05-31",
          "type": "公司及客户公告",
          "url": "https://nvidianews.nvidia.com/news/nvidia-and-tsmc-bring-ai-into-fabs-to-advance-semiconductor-design-and-manufacturing",
          "note": "涵盖计算光刻、器件/工艺仿真、过程控制和缺陷检测；计算光刻成本效率或周期改善20—50%。"
        },
        {
          "id": "CH11",
          "title": "Cadence｜AuraStack封装与PCB智能体",
          "date": "2026-07-16",
          "type": "公司公告",
          "url": "https://www.cadence.com/en_US/home/company/newsroom/press-releases/pr/2026/cadence-introduces-aurastack-ai-super-agent-the-worlds-first.html",
          "note": "拓展到先进封装和PCB；公告称2026年提供。"
        },
        {
          "id": "CH12",
          "title": "Google DeepMind｜AlphaChip芯片布局",
          "date": "2024-09-26",
          "type": "原始研究",
          "url": "https://deepmind.google/blog/how-alphachip-transformed-computer-chip-design/",
          "note": "强化学习已用于Google TPU的芯片布局；涉及floorplanning。"
        },
        {
          "id": "CH13",
          "title": "VecAI知识库 · 2026-07-29",
          "date": "2026-07-29",
          "type": "专家访谈",
          "note": "EDA与研发预算、设计方法学、工艺生态和客户流程相关；三维设计增加验证及电热耦合需求。"
        },
        {
          "id": "CH14",
          "title": "VecAI知识库 · 2026-08-10",
          "date": "2026-08-10",
          "type": "产业调研",
          "note": "前端代码、验证与脚本已可应用大模型；后端物理精度仍需专业EDA和工艺库。"
        },
        {
          "id": "CH15",
          "title": "VecAI知识库 · 2026-06-26",
          "date": "2026-06-26",
          "type": "公司交流",
          "note": "良率数据串联制造记录与测试；DFT服务和工具协同；硅光PDK与设计工具向光电共设计延伸。"
        },
        {
          "id": "CH16",
          "title": "Synopsys｜设计云与按用量计费",
          "date": "2026-09-24",
          "type": "官方产品说明",
          "url": "https://www.synopsys.com/cloud/design-in-the-cloud.html",
          "note": "FlexEDA提供按使用量付费；日期为查阅日，非新品发布日期。"
        },
        {
          "id": "CH17",
          "title": "本报告研究｜AI芯片研发收入与预算模型",
          "date": "2026-09-24",
          "type": "研究假设",
          "note": "以EDA工具底座和全球半导体企业研发预算推演新增采购。三情景参数、公式、归属与全量年度结果在本节方法说明。"
        },
        {
          "id": "CH18",
          "title": "合见工软｜2026年EDA创新矩阵",
          "date": "2026-09-01",
          "type": "公司发布",
          "url": "https://www.univista-isg.com/site/news_detail/549",
          "note": "验证、DFT、系统与三维物理设计工具；国内机会取决于工具接入客户生产流程。"
        },
        {
          "id": "CH19",
          "title": "广立微｜IDAS 2026良率分析与AI工具",
          "date": "2026-09-24",
          "type": "公司发布",
          "url": "https://en.semitronix.com/news/company-info/2228.html",
          "note": "良率、测试和AI数据分析方向；日期为查阅日。"
        },
        {
          "id": "CH20",
          "title": "Synopsys与Intel Foundry｜14A认证与硅到系统协同",
          "date": "2026-07-27",
          "type": "公司公告",
          "url": "https://news.synopsys.com/2026-07-27-Synopsys-and-Intel-Foundry-Fast-Track-Customer-Readiness-from-Silicon-to-Systems-on-Intel-14A",
          "note": "先进工艺PDK、签核与多物理场设计协同。"
        },
        {
          "id": "CH21",
          "title": "NVIDIA Dynamo｜预填充与解码分离部署",
          "date": "2026-09-24",
          "type": "官方工程文档",
          "url": "https://docs.dynamo.nvidia.com/dynamo/dev/kubernetes/disaggregated-serving/overview",
          "note": "查阅日。两阶段可以独立扩缩，也可以使用同种GPU；收益取决于输入、输出、并发与缓存传输成本。"
        },
        {
          "id": "CH22",
          "title": "AMD与Cerebras｜异构推理合作",
          "date": "2026-07-23",
          "type": "公司公告",
          "url": "https://ir.amd.com/news-events/press-releases/detail/1293/amd-and-cerebras-announce-industry-leading-ultra-low-latency-and-high-throughput-ai-inference-solution",
          "note": "公布Helios承担预填充、Cerebras晶圆级引擎承担低延迟解码的方案，计划2026年下半年提供云服务。"
        },
        {
          "id": "CH23",
          "title": "Apple｜第三代基础模型的端侧软硬件协同",
          "date": "2026-06-08",
          "type": "公司原始研究",
          "url": "https://machinelearning.apple.com/research/introducing-third-generation-of-apple-foundation-models",
          "note": "9月9日更新。端侧设计针对内存、权重读取与计算架构，展示延迟、能效和内存约束如何影响模型及芯片协同。"
        },
        {
          "id": "CH24",
          "title": "HeteroPanacea｜何时值得拆分推理工作负载",
          "date": "2026-08-04",
          "type": "原始预印本",
          "url": "https://arxiv.org/abs/2608.03741",
          "note": "模拟预填充、解码及细分算子的专门化；结果依赖硬件计算/带宽组合、模型、上下文和互连，不意味着所有负载都应使用不同芯片。"
        },
        {
          "id": "CH25",
          "title": "SPAD｜预填充与解码专用加速器研究",
          "date": "2025-10-09",
          "type": "原始预印本",
          "url": "https://arxiv.org/abs/2510.08544",
          "note": "研究模拟在相同性能下硬件成本下降19%—41%；不含一次性研发成本，不能直接当作完整商业回报。"
        },
        {
          "id": "CH26",
          "title": "本报告研究｜定制芯片的规模与成本门槛",
          "date": "2026-09-24",
          "type": "机制测算",
          "note": "相同工作负载和服务要求下，固定投入摊销加每单元全周期成本；AI只降低指定工程成本，不机械降低掩模、IP或制造成本。全部金额为示意假设。"
        },
        {
          "id": "CH27",
          "title": "NVIDIA｜年度AI基础设施路线图",
          "date": "2025-03-18",
          "type": "公司路线图",
          "note": "2025 Blackwell Ultra、2026 Rubin、2027 Rubin Ultra；平台年度发布不代表单个芯片研发只需一年。",
          "url": "https://blogs.nvidia.com/blog/nvidia-keynote-at-gtc-2025-ai-news-live-updates/"
        },
        {
          "id": "CH28",
          "title": "NVIDIA｜GTC 2026多代平台路线图",
          "date": "2026-03-16",
          "type": "公司路线图",
          "note": "图中列示Blackwell、Rubin和2028年Feynman；平台年度改进与多代芯片/系统协同，不等于单项目开发周期。",
          "url": "https://images.nvidia.com/nvimages/gtc/pdf/GTC26_SanJose_Highlights_Final.pdf"
        },
        {
          "id": "CH29",
          "title": "AMD｜Advancing AI 2026路线图与市场范围",
          "date": "2026-07-23",
          "type": "公司公告及预测",
          "note": "MI400/Helios进入生产、MI500于2027、MI600于2028；2030约2万亿美元TAM覆盖数据中心/PC/端侧等全产品，不是纯推理GPU收入。",
          "url": "https://ir.amd.com/news-events/press-releases/detail/1294/aai-2026-amd-delivers-full-stack-compute-for-the-agentic-ai-era"
        },
        {
          "id": "CH30",
          "title": "Qualcomm｜端侧智能体的Hexagon架构",
          "date": "2026-09-10",
          "type": "公司技术说明",
          "note": "片上共享内存扩大50%，减少DDR往返；面向低延迟、多任务、持续感知、模型路由和功耗约束。",
          "url": "https://www.qualcomm.com/news/onq/2026/09/hexagon-npu-agentic-ai-architecture"
        },
        {
          "id": "CH31",
          "title": "Cadence与Semidynamics｜芯片开发与模型迭代速度",
          "date": "2026-02-17",
          "type": "客户案例",
          "note": "客户案例介绍芯片设计约三年；用于说明多代研发项目与每年产品发布可以重叠，不是所有项目统一周期。",
          "url": "https://www.cadence.com/en_US/home/resources/videos/designed-with-cadence/semidynamics-designs-customizable-risc-v-technology-for-the-next.html"
        },
        {
          "id": "CH32",
          "title": "NVIDIA Dynamo｜条件化预填充与解码分离",
          "date": "读取于2026-09-24",
          "type": "官方工程文档",
          "note": "预填充计算并传KV给解码；短输入或高前缀命中可能本地一体执行更好。",
          "url": "https://docs.nvidia.com/dynamo/v-0-7-1/design-docs/disaggregated-serving"
        },
        {
          "id": "CH33",
          "title": "Batch-1解码｜内存受限不等于HBM带宽被吃满",
          "date": "2026-05-28",
          "type": "原始预印本",
          "note": "7–8B模型、四类GPU的单流测试，指出内核启动、调度及数据移动延迟影响；不能把所有Decode泛化为峰值内存带宽瓶颈。",
          "url": "https://arxiv.org/abs/2605.30571"
        },
        {
          "id": "CH34",
          "title": "VecAI知识库｜PD分离与国产卡适配",
          "date": "2026-09-21",
          "type": "专家访谈",
          "note": "讨论PD异构部署、KV缓存配置、国产卡算子适配与验证工程。"
        },
        {
          "id": "CH35",
          "title": "VecAI知识库｜精度、缓存与新型存储验证",
          "date": "2026-09-21",
          "type": "专家访谈",
          "note": "讨论存储容量、精度、PDK迁移及可靠性认证对产品交付的影响。"
        },
        {
          "id": "CH36",
          "title": "本报告研究｜2030推理加速器预算分配",
          "date": "2026-09-24",
          "type": "研究情景",
          "note": "以旧/更新AI基建投入为参照，分别乘设备采购占比、加速器产品价值份额和推理用途份额；硬件销售不再加回研发收入。"
        },
        {
          "id": "CH37",
          "title": "本报告研究｜芯片研发2035/2040远期情景",
          "date": "2026-09-24",
          "type": "研究情景",
          "note": "沿全球研发预算、设计工程人力、采用、时间释放与收费比例逐年计算；与芯片硬件销售分开，客户价值留存可核验。"
        },
        {
          "id": "CH38",
          "title": "NVIDIA｜Blackwell Ultra平台发布",
          "date": "2025-03-18",
          "type": "公司公告",
          "note": "2025年下半年伙伴产品；对照年度平台迭代。",
          "url": "https://nvidianews.nvidia.com/news/nvidia-blackwell-ultra-ai-factory-platform-paves-way-for-age-of-ai-reasoning"
        },
        {
          "id": "CH39",
          "title": "AMD｜MI350与Helios平台路径",
          "date": "2025-06-12",
          "type": "公司技术说明",
          "note": "MI350于2025、MI400 Helios于2026的公开平台路径。",
          "url": "https://www.amd.com/en/blogs/2025/amd-instinct-mi350-series-and-beyond-accelerating-the-future-of-ai-and-hpc.html"
        }
      ],
      "customEconomics": {
        "sourceIds": [
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          "CH22",
          "CH23",
          "CH24",
          "CH25",
          "CH26"
        ],
        "status": "机制示意，非厂商报价或硬件收入预测",
        "unit": "USD per equivalent deployment unit over the same three-year service period",
        "serviceYears": 3,
        "scaleUnits": [
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        "genericFixedUsd": 20000000,
        "customEngineeringUsd": 300000000,
        "customOtherFixedUsd": 200000000,
        "genericVariableUsd": 60000,
        "customVariableUsd": 40000,
        "engineeringReduction": 0.3,
        "fixedCostBoundary": "通用方案部署集成固定费；定制方案工程研发及掩模/IP等其他固定费。",
        "variableCostBoundary": "同等质量、延迟与吞吐需求下，每等效部署单元的采购、用电、运维等三年成本。",
        "formula": "averageCost = fixedCost / deploymentUnits + variableCost; breakEvenUnits = (customFixedCost - genericFixedCost) / (genericVariableCost - customVariableCost)",
        "assumption": "不计研发降本以外的性能改善；工作负载稳定、规模足够且部署约束满足，专用设计才可能更经济。"
      },
      "hardwareMarket": {
        "year": 2030,
        "unit": "USD billion / calendar year",
        "scope": "全球云端推理GPU/ASIC加速器产品的一次对外销售价值；含随封装/模组交付的HBM，不含整机、机柜、网络、独立存储和端侧SoC。自研ASIC只计实际外采芯片/模组，不虚构自用设计利润。",
        "boundary": "投入端采购的组成部分，不进入芯片研发客户新增收入或回报端再次相加。推理归属按购置设备的预期用途分配，非将现有训练设备存量再次出售。",
        "scenarios": [
          {
            "key": "cautious",
            "name": "较低分配",
            "equipmentShare": 0.45,
            "acceleratorShare": 0.55,
            "inferenceShare": 0.6
          },
          {
            "key": "base",
            "name": "基准分配",
            "equipmentShare": 0.55,
            "acceleratorShare": 0.65,
            "inferenceShare": 0.7
          },
          {
            "key": "upside",
            "name": "较高分配",
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            "acceleratorShare": 0.7,
            "inferenceShare": 0.8
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        "nicheShares": [
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        "status": "预算分配情景，比例均为研究假设，不是芯片厂商指引"
      },
      "iteration": {
        "roadmapYears": [
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          2026,
          2027,
          2028
        ],
        "platforms": [
          {
            "vendor": "NVIDIA",
            "items": [
              "Blackwell Ultra",
              "Vera Rubin",
              "Rubin Ultra（规划）",
              "Feynman（规划）"
            ],
            "sourceIds": [
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              "CH28"
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          },
          {
            "vendor": "AMD",
            "items": [
              "MI350",
              "MI400 / Helios",
              "MI500（规划）",
              "MI600（规划）"
            ],
            "sourceIds": [
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          }
        ],
        "examplePhases": [
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            "name": "架构 / 规格",
            "beforeMonths": 6,
            "afterMonths": 6
          },
          {
            "name": "设计 / 验证",
            "beforeMonths": 12,
            "afterMonths": 8
          },
          {
            "name": "物理实现 / 签核",
            "beforeMonths": 6,
            "afterMonths": 6
          },
          {
            "name": "首硅 / 验证",
            "beforeMonths": 6,
            "afterMonths": 6
          }
        ],
        "status": "路线图为公司披露；并行项目及30→26个月是机制示意，不是全芯片提速实绩"
      },
      "longHorizon": {
        "years": [
          2030,
          2035,
          2040
        ],
        "status": "独立远期客户研发支出情景；不含推理芯片销售，不改2026—2030基准",
        "scenarios": [
          {
            "key": "scale",
            "name": "工程自动化扩展",
            "rdGrowth2031to2035": 0.1,
            "rdGrowth2036to2040": 0.08,
            "edaGrowth2031to2035": 0.1,
            "edaGrowth2036to2040": 0.08,
            "adoption": [
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            ],
            "timeSaved": [
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            "valueCapture": [
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            "directComputeShare": [
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            "attach": [
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            ],
            "premium": [
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          },
          {
            "key": "breakthrough",
            "name": "完整工程交付突破",
            "rdGrowth2031to2035": 0.14,
            "rdGrowth2036to2040": 0.12,
            "edaGrowth2031to2035": 0.12,
            "edaGrowth2036to2040": 0.1,
            "adoption": [
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            "timeSaved": [
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            "valueCapture": [
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            "directComputeShare": [
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            "attach": [
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            "premium": [
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    },
    "physical": {
      "asOf": "2026-09-24",
      "version": "r4",
      "unit": "USD billion per calendar year unless explicitly specified",
      "inputs": {
        "years": [
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        "humanoid": {
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          "ownedPaidShare": [
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          "annualSoftwareFeeThousandUsd": [
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          "openingInstalledThousands": 300,
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          ],
          "retrofitPriceThousandUsd": [
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        },
        "consumerDriving": {
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          ],
          "aiHardwarePremiumUsd": [
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          ],
          "averagePaidVehiclesMillions": [
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          ],
          "annualFeeUsd": [
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        },
        "robotaxi": {
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          "openingFleet2026Thousands": 7,
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          "aiServiceShare": [
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        },
        "trucking": {
          "averageDriverlessFleetThousands": [
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          ],
          "annualMilesThousands": [
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          "driverFeeUsdPerMile": [
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          ],
          "totalFreightUsdPerMile": [
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        },
        "delivery": {
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          "annualAiServiceFeeThousandUsd": [
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        "factoryOperations": {
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          "annualAiFeeThousandUsd": [
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        "upstream": {
          "trainingInfrastructureBn": [
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          ],
          "simulationDataBn": [
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            2.4,
            3.5,
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          ],
          "consumerEdgeContentUsd": [
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          ],
          "humanoidEdgeContentUsd": [
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          ],
          "industrialEdgeContentUsd": [
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            1000
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        },
        "margins": {
          "hardware": 0.3,
          "raas": 0.5,
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          "driving": 0.65
        },
        "capabilityPricing": {
          "effectiveHours": [
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          "humanoidHourlyUsd": 6,
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          "sensitivityHours": [
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          "sensitivityHumanoidHourlyUsd": [
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          "key": "cautious",
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          "industrialScale": 0.65,
          "autonomyScale": 0.65,
          "servicePriceScale": 0.85
        },
        {
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          "key": "base",
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          "industrialScale": 1,
          "autonomyScale": 1,
          "servicePriceScale": 1
        },
        {
          "name": "积极",
          "key": "accelerated",
          "humanoid2030Thousands": 3000,
          "industrialScale": 1.5,
          "autonomyScale": 1.7,
          "servicePriceScale": 1.15
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      ],
      "sources": [
        {
          "id": "PH01",
          "title": "美银：Physical AI, part 2: Humanoid robots",
          "date": "2026-03-12",
          "type": "机构预测",
          "url": "https://institute.bankofamerica.com/content/dam/transformation/physical-ai-part-2.pdf",
          "note": "第2页全球人形年出货路径；第3、5页中国制造BOM与结构。"
        },
        {
          "id": "PH02",
          "title": "罗兰贝格：Humanoid Robots 2026",
          "date": "2026-04",
          "type": "机构预测",
          "url": "https://content.rolandberger.com/hubfs/07_presse/Roland_Berger_Humanoid_Robots_2026.pdf",
          "note": "第6页：2030年基准100万台/$40bn，积极300万台/$90bn，均为年销量/OEM收入。"
        },
        {
          "id": "PH03",
          "title": "高盛：人形机器人市场展望",
          "date": "2024-02-27",
          "type": "机构预测",
          "url": "https://www.goldmansachs.com/insights/articles/the-global-market-for-robots-could-reach-38-billion-by-2035",
          "note": "较早版本：2030年出货超25万台；2035年140万台/$38bn。"
        },
        {
          "id": "PH04",
          "title": "Interact Analysis：Humanoid robot revenue to reach $15bn by 2035",
          "date": "2026-05-21",
          "type": "机构预测",
          "url": "https://interact-analysis.prezly.com/humanoid-robot-revenue-to-reach-15bn-by-2035",
          "note": "2035年人形年出货超70万台、收入$15bn；保留其不同终点年份。"
        },
        {
          "id": "PH07",
          "title": "Figure：Helix 2.5 在30个未见家庭的泛化测试",
          "date": "2026-09-17",
          "type": "公司技术披露",
          "url": "https://www.figure.ai/news/helix-2-5-zero-shot-30-home-generalization",
          "note": "三类任务、30个家庭；Index预训练将完整任务成功率从9%提升至56%；任务本身在别处微调。"
        },
        {
          "id": "PH08",
          "title": "Figure：Index 人类行为数据管线",
          "date": "2026-08-25",
          "type": "公司技术披露",
          "url": "https://www.figure.ai/news/introducing-index",
          "note": "发布时累计1600万条视频；过滤、审查、去重、重采样与标注用于处理真实任务多样性。"
        },
        {
          "id": "PH09",
          "title": "Physical Intelligence：π0.7",
          "date": "2026-04-16",
          "type": "公司研究",
          "url": "https://www.pi.website/blog/pi07",
          "note": "跨本体、场景、任务的组合泛化；语言分步指导与视觉子目标提升新任务完成。"
        },
        {
          "id": "PH10",
          "title": "Physical Intelligence：真实客户场景合作",
          "date": "2026-02-24",
          "type": "公司与合作伙伴披露",
          "url": "https://www.pi.website/blog/partner",
          "note": "Ultra真实订单整班96.4%自主时间；Weave加入场景预训练数据后接管下降50%。"
        },
        {
          "id": "PH11",
          "title": "Google DeepMind：Gemini Robotics 2",
          "date": "2026-07-30",
          "type": "公司技术披露",
          "url": "https://deepmind.google/blog/gemini-robotics-2-brings-whole-body-intelligence-to-robots/",
          "note": "全身控制、灵巧操作、多机协作；新双臂本体通常少于200个示例适配。"
        },
        {
          "id": "PH12",
          "title": "Figure：Figure 03 产线爬坡",
          "date": "2026-04-29",
          "type": "公司披露",
          "url": "https://www.figure.ai/news/ramping-figure-03-production",
          "note": "披露已生产350台以上，节拍达到1台/小时，整机一次通过率超过80%；其中包含内部研发与数采用途。"
        },
        {
          "id": "PH13",
          "title": "Agility：Digit 5 商业部署与订单",
          "date": "2026-09-15",
          "type": "公司披露及规划",
          "url": "https://www.agilityrobotics.com/content/agility-unveils-digit-5-humanoid-robot-built-for-cooperatively-safe-work-at-scale",
          "note": "Digit 4累计6.5万运行小时；截至5月Digit 5多年订单超3亿美元，附合同里程碑；新产品预计2027年交付。"
        },
        {
          "id": "PH14",
          "title": "Boston Dynamics：制造现场训练中心启用",
          "date": "2026-09-21",
          "type": "公司披露及规划",
          "url": "https://bostondynamics.com/news/boston-dynamics-opens-robotics-metaplant-application-center-to-train-humanoid-robots-for-manufacturing-tasks/",
          "note": "Atlas在Hyundai现场训练；未来数年计划先部署2.5万台，并规划年产3万台设施。"
        },
        {
          "id": "PH17",
          "title": "VecAI知识库：机器人产线、任务迁移与数据访谈",
          "date": "2026-09-17",
          "type": "产业访谈",
          "note": "标准分拣与搬运的部署、产线节拍/良率、真实数据和训练机器人规划。"
        },
        {
          "id": "PH18",
          "title": "VecAI知识库：机器人本体与物流应用访谈",
          "date": "2026-09-15",
          "type": "产业访谈",
          "note": "双臂/轮式的任务适配、真实工厂数据、场景集成与商业模式。"
        },
        {
          "id": "PH19",
          "title": "VecAI知识库：关节感知与编码器访谈",
          "date": "2026-09-17",
          "type": "产业访谈",
          "note": "双编码器、抗干扰、可靠性与规模制造；编码器20%是关节模组口径，并非整机BOM。"
        },
        {
          "id": "PH20",
          "title": "绿的谐波：精密传动与执行器产品",
          "date": "截至2026-09-23",
          "type": "公司产品资料",
          "url": "https://www.leaderdrive.com/",
          "note": "谐波减速器、旋转执行器、无框电机；作为产业链代表，不指定客户订单。"
        },
        {
          "id": "PH21",
          "title": "拓普集团：机器人执行器业务",
          "date": "2024（2023年报）",
          "type": "公司年报",
          "url": "https://www.tuopu.com/wp-content/uploads/2024/07/%E6%8B%93%E6%99%AE%E9%9B%86%E5%9B%A22023%E5%B9%B4%E5%B9%B4%E5%BA%A6%E6%8A%A5%E5%91%8A.pdf",
          "note": "电驱与旋转执行器布局；仅用于确认产品方向，不据此认定2026客户份额。"
        },
        {
          "id": "PH22",
          "title": "恒立液压：线性传动产品",
          "date": "截至2026-09-23",
          "type": "公司产品资料",
          "url": "https://www.henglihydraulics.com/col1201/1226",
          "note": "滚珠丝杠产品；作为精密传动制造代表，不指定机器人客户。"
        },
        {
          "id": "PH24",
          "title": "高盛：Robotaxi市场展望",
          "date": "2026-04-30",
          "type": "机构预测",
          "url": "https://www.goldmansachs.com/insights/articles/robotaxis-to-become-a-400-billion-dollar-market-in-2035",
          "note": "全球商业Robotaxi车队2030约100万辆，2035约600万辆；2035市场约$415bn。"
        },
        {
          "id": "PH25",
          "title": "Hyundai：2026 AI机器人战略",
          "date": "2026-01-05",
          "type": "公司规划",
          "url": "https://www.hyundaimotorgroup.com/en/news/hyundai-motor-group-announces-ai-robotics-strategy--to-lead-human-centered-robotics-era-at-ces-2026",
          "note": "Hyundai Mobis开发执行器，集团制造/物流/售后协同，逐步拓展RaaS。"
        },
        {
          "id": "PH27",
          "title": "三花集团：机器人智能驱动与传感布局",
          "date": "2025-02-01",
          "type": "公司披露",
          "url": "https://www.sanhuagroup.com/newslist_526.html",
          "note": "集团研发方向；不推断具体客户的正式定点或份额。"
        },
        {
          "id": "PH28",
          "title": "Skild AI：商业部署十个月，ARR超过1亿美元",
          "date": "2026-09-10",
          "type": "公司披露",
          "note": "60多家付费客户，累计确认收入5000万美元；约90%收入来自操作任务。ARR与累计收入分别使用。",
          "url": "https://skild.ai/blogs/skild-crosses-100m-arr"
        },
        {
          "id": "PH29",
          "title": "Agility：2026年6月投资者演示材料",
          "date": "2026-06-24",
          "type": "公司情景与订单披露",
          "note": "第40、57—58页：RaaS五年约50万美元，为管理层示意；所有权模式另列；3亿美元多年订单附里程碑，不是当年收入。",
          "url": "https://www.sec.gov/Archives/edgar/data/2074973/000121390026071287/ea029548401ex99-2.htm"
        },
        {
          "id": "PH30",
          "title": "Aurora：2026投资者日与2030商业目标",
          "date": "2026-09-23",
          "type": "公司目标与商业模式",
          "note": "第41、43、45页：DaaS计划0.85美元以上/英里；2030年3万多辆、50亿美元以上收入，均为公司目标。",
          "url": "https://www.sec.gov/Archives/edgar/data/1828108/000182810826000082/auroraanalystinvestorday.htm"
        },
        {
          "id": "PH31",
          "title": "ARK：Big Ideas 2026，机器人与自动驾驶",
          "date": "2026-01",
          "type": "机构积极情景",
          "note": "第86页为长期自动化潜力；第99页2030自动驾驶技术商净收入1.9万亿美元；第104页自主配送4800亿美元，均非全行业共识。",
          "url": "https://research.ark-invest.com/hubfs/1_Download_Files_ARK-Invest/Big_Ideas/ARKInvest%20BigIdeas2026.pdf"
        },
        {
          "id": "PH32",
          "title": "McKinsey：自动驾驶的商业收入与零部件空间",
          "date": "2023-01-06",
          "type": "机构预测（历史版本）",
          "note": "2030年乘用车ADAS/AD零部件550亿—800亿美元；2035年乘用车ADAS/AD收入3000亿—4000亿美元。",
          "url": "https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/autonomous-drivings-future-convenient-and-connected"
        },
        {
          "id": "PH33",
          "title": "Waymo：新加坡布局及累计运营数据",
          "date": "2026-09-17",
          "type": "公司披露",
          "note": "累计超过2000万次全无人驾驶出行、3亿公里；新加坡商业服务计划2028年推出。",
          "url": "https://blog.waymo.com/blog/2026/09/waymo-in-singapore/"
        },
        {
          "id": "PH34",
          "title": "Tesla：FSD（Supervised）订阅价格",
          "date": "2026-09-24（查阅）",
          "type": "公司产品定价",
          "note": "美国官方订阅99美元/月，属于需驾驶员监督的辅助驾驶，不等同于全无人驾驶。",
          "url": "https://www.tesla.com/support/fsd"
        },
        {
          "id": "PH35",
          "title": "美国卡车运输协会：American Trucking Trends 2025",
          "date": "2025-08-28",
          "type": "行业统计",
          "note": "2024年美国卡车运输收入9060亿美元、职业司机358万人；用于存量预算参照，不直接归入AI收入。",
          "url": "https://www.trucking.org/news-insights/ata-american-trucking-trends-2025"
        },
        {
          "id": "PH36",
          "title": "IFR：World Robotics 2025服务机器人摘要",
          "date": "2025-10-07",
          "type": "行业统计",
          "note": "2024年专业服务机器人销售逾19.9万台；统计样本RaaS机队逾2.45万台、同比增长31%。",
          "url": "https://ifr.org/img/worldrobotics/Executive_Summary_WR_2025_Service_Robots.pdf"
        },
        {
          "id": "PH37",
          "title": "Amazon：百万机器人与DeepFleet",
          "date": "2025-06-30",
          "type": "公司披露",
          "note": "超过100万台机器人、300多个场所；DeepFleet以优化机器人行程为目标，公布约10%改善。自用节省不作为外部软件收入。",
          "url": "https://www.aboutamazon.com/news/operations/amazon-million-robots-ai-foundation-model"
        },
        {
          "id": "PH38",
          "title": "NVIDIA：2026年年度报告中的物理AI业务",
          "date": "2026-05-12",
          "type": "公司披露",
          "note": "披露FY2026物理AI收入60亿美元，涵盖训练与自动驾驶等，不是单独机器人终端销售额。",
          "url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581026000036/nvda-20260512.htm"
        },
        {
          "id": "PH39",
          "title": "Qualcomm：2026投资者日",
          "date": "2026-06-24",
          "type": "公司目标",
          "note": "汽车设计订单管线650亿美元；FY2029汽车收入目标100亿美元，含座舱、连接等，不能全部归为新增自动驾驶。",
          "url": "https://investor.qualcomm.com/news-events/press-releases/news-details/2026/Qualcomm-Accelerates-Diversification-with-Comprehensive-Strategy-for-Data-Center-and-Sees-Multiple-Inflection-Points-Over-the-Next-3-to-5-Years/default.aspx"
        },
        {
          "id": "PH40",
          "title": "Siemens与NVIDIA扩展工业AI合作",
          "date": "2026-01-06",
          "type": "公司合作规划",
          "note": "工业数字孪生、运行优化与自适应制造；Erlangen工厂拟作为2026年示范。",
          "url": "https://nvidianews.nvidia.com/news/siemens-and-nvidia-expand-partnership-industrial-ai-operating-system"
        },
        {
          "id": "PH41",
          "title": "Synopsys：Physical AI仿真与验证",
          "date": "2026-09-24（查阅）",
          "type": "公司产品资料",
          "note": "物理仿真、传感器仿真与部署前验证；不将传统仿真全部计为物理AI新增收入。",
          "url": "https://www.synopsys.com/ai/physical-ai.html"
        },
        {
          "id": "PH42",
          "title": "1X：NEO与世界模型发布",
          "date": "2026-01-12",
          "type": "公司定价与产品规划",
          "note": "公司公布2万美元Early Access购买方案和499美元/月订阅方案；价格为不同方案，不能相加。",
          "url": "https://www.globenewswire.com/fr/news-release/2026/01/12/3217155/0/en/1X-Unveils-Paradigm-Shift-In-Humanoid-AI-NEO-s-Starting-to-Learn-On-Its-Own.html"
        },
        {
          "id": "PH43",
          "title": "Formic：按使用付费的全服务自动化",
          "date": "2026-09-24（查阅）",
          "type": "公司商业模式",
          "note": "工厂可以按小时使用自动化服务，前期集成与维护由服务商承担；也有买断模式。",
          "url": "https://land.formic.co/automate"
        },
        {
          "id": "PH44",
          "title": "物理AI终端收入、服务机队与上游需求模型",
          "date": "2026-09-24",
          "type": "本报告研究情景",
          "note": "本报告物理AI年度终端收入、互斥收费机队、Token负载和2035/2040远期情景模型；假设、公式与敏感性见本章。"
        },
        {
          "id": "PH45",
          "title": "Anthropic：Claude Code成本管理文档",
          "date": "读取于2026-09-24",
          "type": "公司产品文档",
          "url": "https://code.claude.com/docs/en/costs",
          "note": "企业部署约13美元/开发者/活跃日，90%低于30美元；含输入、缓存、输出差异。"
        },
        {
          "id": "PH46",
          "title": "Anthropic：What a task costs on Opus 5.5",
          "date": "2026-09-22",
          "type": "公司成本示例",
          "url": "https://claude.com/blog/what-a-task-costs-on-opus-5-5",
          "note": "示例任务40轮、平均70k上下文，累计2.8M输入和60k输出；为官方说明示例，并非所有用户平均token。"
        },
        {
          "id": "PH47",
          "title": "Physical Intelligence：FAST动作编码",
          "date": "2025-01-16",
          "type": "公司研究",
          "url": "https://www.pi.website/research/fast",
          "note": "高频灵巧机器人以20–50个动作组成action chunk；动作压缩编码并非文本API token。"
        },
        {
          "id": "PH48",
          "title": "Google DeepMind：Gemini Robotics On-Device 2模型卡",
          "date": "2026-07-30",
          "type": "公司技术文档",
          "url": "https://deepmind.google/models/model-cards/gemini-robotics-on-device-2/",
          "note": "本地VLA输入图像、文字与本体感知，输出机器人连续动作数值；网络受限时仍可端侧运行。"
        },
        {
          "id": "PH49",
          "title": "Anthropic：模型与缓存价格",
          "date": "读取于2026-09-24",
          "type": "公司产品定价",
          "url": "https://platform.claude.com/docs/en/about-claude/pricing",
          "note": "Sonnet 5每百万token：输入2美元、缓存命中0.2美元、输出10美元；仅用于高层语言推理成本参照，不为VLA动作报价。"
        },
        {
          "id": "PH50",
          "title": "Physical Intelligence：π0通用机器人策略",
          "date": "2024-10-31",
          "type": "公司研究",
          "url": "https://www.pi.website/blog/pi0",
          "note": "3B视觉语言骨干，连续动作输出最高每秒50次；说明高频本地控制与高层语言推理的不同。"
        },
        {
          "id": "PH51",
          "title": "Anthropic：真实Claude Code使用研究",
          "date": "2026-06-16",
          "type": "公司实证研究",
          "note": "约40万会话；典型4次用户轮，每轮约10个模型动作、有时超过100；20小时/周。用户轮、模型调用与任务不同。",
          "url": "https://www.anthropic.com/research/claude-code-expertise"
        },
        {
          "id": "PH52",
          "title": "Anthropic：多智能体研究系统",
          "date": "2025-06-13",
          "type": "公司工程研究",
          "note": "样本中智能体约4倍普通对话、多智能体约15倍；多agent已有独立上下文，不再重复乘15。",
          "url": "https://www.anthropic.com/engineering/multi-agent-research-system"
        },
        {
          "id": "PH53",
          "title": "Anthropic：长任务上下文工程",
          "date": "2025-09-29",
          "type": "公司工程研究",
          "note": "压缩、结构化笔记和子智能体管理长任务；持久记忆按需检索，不是每次重读全部历史。",
          "url": "https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents"
        },
        {
          "id": "PH54",
          "title": "VecAI知识库：办公与编程Token使用强度访谈",
          "date": "2026-09-16",
          "type": "产业访谈",
          "note": "受访机构内部样本：编程员工约1.2亿Token/日，非编程约400多万；未分输入、缓存、输出，不等于全球平均。"
        },
        {
          "id": "PH55",
          "title": "VecAI知识库：企业Token额度与多智能体治理访谈",
          "date": "2026-09-17",
          "type": "产业访谈",
          "note": "受访者描述内部额度由2000美元扩至power-user4000美元，原文该段未说明周期；用于佐证重度应用而不据此月化。"
        },
        {
          "id": "PH56",
          "title": "Figure：Helix分层本地推理",
          "date": "2025-02-20",
          "type": "公司技术披露",
          "note": "7B S2以7–9Hz更新语义潜变量，80M S1以200Hz执行；两套嵌入式GPU，本地输出不是文本token。",
          "url": "https://www.figure.ai/news/helix"
        },
        {
          "id": "PH57",
          "title": "Figure：Helix 02全身控制",
          "date": "2026-01-27",
          "type": "公司技术披露",
          "note": "S1 200Hz、S0 1kHz；4分钟洗碗机任务包含61个动作，非每个动作一次云模型请求。",
          "url": "https://www.figure.ai/news/helix-02"
        },
        {
          "id": "PH58",
          "title": "Berg Insight：人形机器人远期出货与存量",
          "date": "2026-09",
          "type": "机构预测",
          "note": "机构分析师原帖、机构账号转发：2040年年出货2600万、在用接近8300万；原帖起点2025，二手资料写2026，未沿用起点CAGR。",
          "url": "https://www.linkedin.com/posts/juliawahl%C3%A9n_humanoidrobots-robotics-physicalai-activity-7502826405429243904-B5YA"
        },
        {
          "id": "PH59",
          "title": "Morgan Stanley：Humanoids—A $5 Trillion Market",
          "date": "2025-05-14",
          "type": "机构远期预测",
          "note": "2050年在用超10亿台，约90%工业/商业；5万亿美元覆盖更广价值链，不与本报告终端收入直接相加。",
          "url": "https://www.morganstanley.com/insights/articles/humanoid-robot-market-5-trillion-by-2050"
        },
        {
          "id": "PH60",
          "title": "Morgan Stanley：Robotaxi产业加速",
          "date": "2026-07-17",
          "type": "机构远期预测",
          "note": "2035年全球约250万辆，2040年约1万亿美元广义机会，包含服务、车辆、软件及相邻行业。",
          "url": "https://www.morganstanley.com/insights/articles/robotaxis-1-trillion-dollar-investor-opportunity"
        },
        {
          "id": "PH61",
          "title": "NVIDIA：Cosmos 3世界模型发布",
          "date": "2026-06-01",
          "type": "公司技术披露",
          "url": "https://investor.nvidia.com/news/press-release-details/2026/NVIDIA-Launches-Cosmos-3-the-Open-Frontier-Foundation-Model-for-Physical-AI/default.aspx",
          "note": "结合视觉推理、世界生成和动作预测；可用于合成数据、未来状态预测及机器人策略训练与评估。"
        },
        {
          "id": "PH62",
          "title": "NVIDIA：Cosmos 3 Edge开放与端侧部署",
          "date": "2026-07-20",
          "type": "公司技术披露",
          "url": "https://blogs.nvidia.com/blog/siggraph-news-2026/",
          "note": "40亿参数Edge模型开放；支持用机器人与传感器数据后训练，再在Jetson Thor部署操作或移动策略。文中机器人伙伴处于评估阶段。"
        }
      ],
      "institutionalForecasts": [
        {
          "institution": "高盛",
          "published": "2024-02",
          "year": 2030,
          "annualShipmentsThousands": 250,
          "qualifier": "超过",
          "sourceIds": [
            "PH03"
          ],
          "status": "历史版本"
        },
        {
          "institution": "罗兰贝格·基准",
          "published": "2026-04",
          "year": 2030,
          "annualShipmentsThousands": 1000,
          "qualifier": "",
          "sourceIds": [
            "PH02"
          ],
          "status": "机构预测"
        },
        {
          "institution": "美银",
          "published": "2026-03",
          "year": 2030,
          "annualShipmentsThousands": 1200,
          "qualifier": "",
          "sourceIds": [
            "PH01"
          ],
          "status": "机构预测"
        },
        {
          "institution": "罗兰贝格·积极",
          "published": "2026-04",
          "year": 2030,
          "annualShipmentsThousands": 3000,
          "qualifier": "",
          "sourceIds": [
            "PH02"
          ],
          "status": "机构情景"
        }
      ],
      "institutionsBroader": [
        {
          "name": "高盛",
          "date": "2026-04",
          "year": "2030",
          "metric": "全球Robotaxi年末车队",
          "value": "约100万辆",
          "sourceIds": [
            "PH24"
          ]
        },
        {
          "name": "高盛",
          "date": "2026-04",
          "year": "2035",
          "metric": "AV直接AI技术收入",
          "value": "约3000亿美元/年",
          "sourceIds": [
            "PH24"
          ]
        },
        {
          "name": "ARK",
          "date": "2026-01",
          "year": "2030",
          "metric": "自动驾驶技术商净收入（积极情景）",
          "value": "约1.9万亿美元/年",
          "sourceIds": [
            "PH31"
          ]
        },
        {
          "name": "ARK",
          "date": "2026-01",
          "year": "2030",
          "metric": "自主货运与末端配送完整服务收入",
          "value": "约4800亿美元/年",
          "sourceIds": [
            "PH31"
          ]
        },
        {
          "name": "McKinsey",
          "date": "2023-01",
          "year": "2030",
          "metric": "乘用车ADAS/AD零部件（历史预测）",
          "value": "550亿—800亿美元/年",
          "sourceIds": [
            "PH32"
          ]
        }
      ],
      "unitEconomics": {
        "effectiveHours": 3000,
        "hourlyLaborCostUsd": 25,
        "hourlyRaasPriceUsd": 15,
        "customerSiteCostUsd": 3000,
        "robotCostUsd": 30000,
        "lifeYears": 5,
        "deploymentCostUsd": 5000,
        "annualMaintenanceUsd": 4500,
        "annualRemoteSupportUsd": 4500,
        "annualComputeDataUsd": 6000
      },
      "boundary": {
        "terminal": "新能力驱动的AI机器人买断设备、独立改造、完整作业服务，以及驾驶AI硬件增量/订阅/技术服务。含硬件扩围，不能称为纯软件市场。",
        "ownedVsRaas": "每年新增机器人分到客户买断与服务商持有两类；服务商持有设备不进入终端硬件销售。两类存量分别留存，RaaS机队不另收独立软件。",
        "industrial": "非人形的双臂、移动操作、智能巡检/清洁、柔性生产作业；不含人形、公路驾驶和末端配送。只计新AI能力带来的销售，不使用传统机器人全市场。",
        "retrofit": "存量传统设备的新AI改造，排除当年新设备和已属服务机队的设备；无重复整机价。",
        "driving": "乘用车只计新增驾驶AI系统价值与独立付费，不计整车。Robotaxi只计票款中驾驶AI服务份额；卡车和末端配送计驾驶/调度技术费。完整运输账单另作扩围。",
        "factory": "生产运行期的独立现场优化、视觉质检与控制服务，排除设备已含功能、通用企业AI与研发/EDA/仿真。",
        "upstream": "训练基础设施、云端更新、仿真数据和端侧芯片为成本与供应商需求，不能再加到同一终端账单；研发仿真已在科研/芯片章节的部分不重复计入。",
        "legacyOverlap": "建议总量接入时：新AI机器人硬件与RaaS保留80%；独立机器人/工厂软件保留50%；驾驶AI硬件保留50%；新增驾驶订阅和技术服务保留70%。均为超过旧总量隐含采用的研究归因，不是精确客户去重。"
      },
      "image": {
        "src": "/images/industry/ai-returns-r3/physical-ai-payment-loop.png",
        "alt": "物理AI从模型与仿真，到工厂仓库道路部署、连续完成任务和客户持续付费；现场数据回流改进模型。设备、作业和驾驶分别收费，终端账单只计一次。",
        "generated": true
      },
      "claims": [
        {
          "text": "Skild的付费客户和操作任务收入说明物理AI能跨本体收费。",
          "sourceIds": [
            "PH28"
          ]
        },
        {
          "text": "RaaS把设备采购变成按作业能力持续付费，年账单不能只用薄软件订阅近似。",
          "sourceIds": [
            "PH29",
            "PH43"
          ]
        },
        {
          "text": "驾驶服务存在按英里收费和大规模车队目标。",
          "sourceIds": [
            "PH30"
          ]
        },
        {
          "text": "模型、真实作业数据和仿真互相提高任务迁移效率。",
          "sourceIds": [
            "PH07",
            "PH09",
            "PH17",
            "PH28"
          ]
        }
      ],
      "workload": {
        "daysPerYear": 250,
        "agentTasksPerDay": 4,
        "agentInputTokensPerTask": 2800000,
        "agentOutputTokensPerTask": 60000,
        "robotTasksPerHour": 60,
        "reasoningCallsPerTask": 4,
        "inputTokensPerCall": 12000,
        "outputTokensPerCall": 1000,
        "cloudRoutedShare": 0.2,
        "inputCacheShare": 0.5,
        "inputUsdPerMillion": 2,
        "cacheUsdPerMillion": 0.2,
        "outputUsdPerMillion": 10,
        "cameras": 2,
        "perceptionFramesPerSecond": 10,
        "visualTokensPerFrame": 256,
        "controlHz": 50,
        "actionDimensions": 24,
        "robotDailyHours": [
          8,
          16
        ],
        "status": "旧版兼容示例；当前正文与R4验收使用workloadR4。这里仅保留原始接口、旧示例和公开Token价格参数。"
      },
      "workloadR4": {
        "digitalObserved": [
          {
            "name": "一般办公（访谈样本）",
            "tokensMillions": 4,
            "status": "约数，下限参照，样本未分输入/缓存/输出"
          },
          {
            "name": "重度编程（访谈样本）",
            "tokensMillions": 120,
            "status": "受访机构内部员工人均单日，非行业平均"
          }
        ],
        "digitalScenarios": [
          {
            "name": "重度编程校准",
            "workers": 2,
            "activeHours": 8,
            "callsPerWorkerHour": 100,
            "averageInputTokens": 70000,
            "averageOutputTokens": 1500
          },
          {
            "name": "并行长程突破",
            "workers": 4,
            "activeHours": 16,
            "callsPerWorkerHour": 80,
            "averageInputTokens": 200000,
            "averageOutputTokens": 2000
          }
        ],
        "robotOrchestration": [
          {
            "name": "重复工位",
            "hours": 8,
            "tasksPerHour": 60,
            "callsPerTask": 4,
            "contextTokens": 12000,
            "outputTokens": 1000,
            "cloudShare": 0.2,
            "inputCacheShare": 0.5
          },
          {
            "name": "复杂现场",
            "hours": 16,
            "tasksPerHour": 30,
            "callsPerTask": 8,
            "contextTokens": 50000,
            "outputTokens": 1000,
            "cloudShare": 0.15,
            "inputCacheShare": 0.8
          }
        ],
        "onDevice": {
          "semanticHz": 8,
          "semanticHzRange": [
            7,
            9
          ],
          "controlHz": 200,
          "stabilizationHz": 1000,
          "hours": [
            8,
            16
          ]
        },
        "yearsDays": 250,
        "formula": "每日累计高层Token = 并行worker × 有效运行小时 × 每worker每小时调用 × (平均输入上下文 + 输出)。包含缓存读取，非新增内容或等价FLOPs。",
        "evidenceAsOf": "2026-09-24"
      },
      "longHorizon": {
        "years": [
          2030,
          2035,
          2040
        ],
        "retentionAfter2030": 0.97,
        "humanoid": {
          "shipmentsThousands": [
            1800,
            10000,
            30000
          ],
          "aspThousandUsd": [
            30,
            20,
            15
          ],
          "raasNewShare": [
            0.35,
            0.45,
            0.5
          ],
          "effectiveHours": [
            3000,
            3500,
            4000
          ],
          "capabilityHourlyUsd": [
            6,
            5,
            4
          ],
          "raasHourlyUsd": [
            15,
            12,
            10
          ],
          "ownedPaidShare": [
            0.7,
            0.8,
            0.85
          ]
        },
        "industrial": {
          "shipmentsThousands": [
            1000,
            3000,
            8000
          ],
          "aspThousandUsd": [
            30,
            24,
            18
          ],
          "raasNewShare": [
            0.35,
            0.45,
            0.5
          ],
          "effectiveHours": [
            3000,
            3500,
            4000
          ],
          "capabilityHourlyUsd": [
            4,
            3,
            2.5
          ],
          "raasHourlyUsd": [
            10,
            8,
            6
          ],
          "ownedPaidShare": [
            0.7,
            0.8,
            0.85
          ],
          "retrofitsThousands": [
            1500,
            5000,
            12000
          ],
          "retrofitPriceThousandUsd": [
            4,
            3,
            2
          ]
        },
        "factoryOperations": {
          "payingSitesThousands": [
            200,
            600,
            1500
          ],
          "annualAiFeeThousandUsd": [
            40,
            45,
            50
          ]
        },
        "mobility": {
          "newAiVehiclesMillions": [
            45,
            80,
            100
          ],
          "hardwareUsd": [
            800,
            650,
            500
          ],
          "averagePaidVehiclesMillions": [
            30,
            120,
            250
          ],
          "consumerAnnualUsd": [
            600,
            500,
            400
          ],
          "robotaxiAverageFleetThousands": [
            700,
            4000,
            10000
          ],
          "robotaxiFareThousandUsd": [
            60,
            50,
            45
          ],
          "robotaxiAiShare": [
            0.35,
            0.35,
            0.35
          ],
          "truckFleetThousands": [
            200,
            1000,
            3000
          ],
          "truckAnnualMilesThousands": [
            200,
            200,
            200
          ],
          "truckUsdPerMile": [
            0.5,
            0.4,
            0.3
          ],
          "deliveryFleetThousands": [
            1200,
            5000,
            15000
          ],
          "deliveryAnnualAiFeeThousandUsd": [
            5,
            4,
            3
          ]
        },
        "scenarios": [
          {
            "key": "scale",
            "name": "规模化延伸",
            "humanoid2035Thousands": 10000,
            "humanoid2040Thousands": 30000,
            "industrialScale2035": 1,
            "industrialScale2040": 1,
            "mobilityScale2035": 1,
            "mobilityScale2040": 1,
            "newAiVehicles2035Millions": 80,
            "newAiVehicles2040Millions": 100
          },
          {
            "key": "breakthrough",
            "name": "通用能力突破",
            "humanoid2035Thousands": 30000,
            "humanoid2040Thousands": 100000,
            "industrialScale2035": 1.5,
            "industrialScale2040": 1.8,
            "mobilityScale2035": 1.5,
            "mobilityScale2040": 2,
            "newAiVehicles2035Millions": 100,
            "newAiVehicles2040Millions": 120
          }
        ],
        "boundary": "2035/2040为独立远期情景，逐年出货与两类机队递推；不进入2026—2030基准或加到2030收入。每年硬件买断、RaaS、买断后能力服务仍互斥。",
        "maxServiceYears": 7,
        "retirementMethod": "2030年末按投放年份重建买断/RaaS批次；每年存活97%，到第7年退出；出货同时覆盖替换与新增，设备5年财务折旧与最长7年维护后服役分开。",
        "status": "2035与2040为独立研究情景；不改动2026—2030基准预测。"
      }
    },
    "personalAgents": {
      "version": "personal-agents-r6-20260924",
      "asOf": "2026-09-24",
      "unit": "USD billion per calendar year",
      "sources": [
        {
          "id": "PA01",
          "title": "Meta：Muse 个人智能体发布",
          "date": "2026-09-08",
          "type": "官方产品发布",
          "url": "https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/",
          "note": "Muse 产品、美国首发、Muse Spark 基座及官方演示视频。"
        },
        {
          "id": "PA02",
          "title": "Meta：How We Designed Muse",
          "date": "2026-09",
          "type": "官方产品设计",
          "url": "https://introducing.muse.ai/",
          "note": "持续任务、Goals、Artifacts、真实产品界面与设计负责人导览。"
        },
        {
          "id": "PA03",
          "title": "Meta：Muse 的执行与安全架构",
          "date": "2026-09-08",
          "type": "官方技术披露",
          "url": "https://research.meta.ai/blog/security-and-safety-for-ai-agents-our-approach-with-muse",
          "note": "每名用户独立 Linux 云电脑，含浏览器、存储、CPU 与内存；隔离运行单元支持工具、并发子智能体与定时任务，持久任务状态另存 Postgres，虚拟机数据持续备份。"
        },
        {
          "id": "PA04",
          "title": "Meta：Muse 订阅方案",
          "date": "2026-09-23（访问）",
          "type": "官方帮助中心",
          "url": "https://www.meta.com/en-gb/help/subscriptions/1021145227643680/",
          "note": "Power 20 美元/月、Max 100 美元/月；Muse tokens 是产品额度单位。"
        },
        {
          "id": "PA05",
          "title": "xAI：Grok Bot 扩大套餐覆盖",
          "date": "2026-08-26",
          "type": "官方产品发布",
          "url": "https://x.ai/news/grok-bot-more-plans",
          "note": "8 月 11 日开始测试，8 月 26 日扩至 SuperGrok、Cursor Pro 与 Teams 套餐。"
        },
        {
          "id": "PA06",
          "title": "xAI：Grok Bot 101",
          "date": "2026-09-11",
          "type": "官方使用演示",
          "url": "https://x.ai/bot/guides/grok-bot-101",
          "note": "持续云电脑、任务录制、计划任务、多智能体协作及实际工作流。"
        },
        {
          "id": "PA07",
          "title": "xAI：Grok Bot 产品文档",
          "date": "2026-09-21（更新）",
          "type": "官方产品文档",
          "url": "https://docs.x.ai/grok-bot/overview",
          "note": "同一账号多个 Bot 共享一台持久云电脑与文件、浏览器会话；跨账号隔离，关闭本机不停止后台任务；Bot 数不能等同用户数。"
        },
        {
          "id": "PA08",
          "title": "Stripe：Muse 接入 Link 智能体钱包",
          "date": "2026-09-08",
          "type": "官方合作披露",
          "url": "https://stripe.com/gb/newsroom/news/stripe-helps-meta-muse-shop-with-link",
          "note": "超过 100 万接受 Link 的商户与一次性虚拟卡；Link 同时支持 Grok Bot。"
        },
        {
          "id": "PA09",
          "title": "AWS：Meta 部署数千万 Graviton 核心",
          "date": "2026-04-24",
          "type": "官方合作披露",
          "url": "https://press.aboutamazon.com/aws/2026/4/meta-signs-agreement-with-aws-to-power-agentic-ai-on-amazons-graviton-chips",
          "note": "覆盖 Meta 智能体工作负载，并非全部为 Muse 专属采购。"
        },
        {
          "id": "PA10",
          "title": "AMD：智能体改变 CPU/GPU 需求结构",
          "date": "2026-05-07",
          "type": "官方产业分析",
          "url": "https://www.amd.com/en/blogs/2026/agentic-ai-changes-the-cpu-gpu-equation.html",
          "note": "工具执行、编排、验证带来独立 CPU 工作负载。"
        },
        {
          "id": "PA11",
          "title": "VecAI知识库 · 2026-09-22",
          "date": "2026-09-22",
          "type": "知识库研究",
          "note": "截至 9 月 21 日 Muse 累计下载约 250 万次；二手统计，非活跃用户。"
        },
        {
          "id": "PA12",
          "title": "VecAI知识库 · 2026-09-21",
          "date": "2026-09-21",
          "type": "知识库研究",
          "note": "工具调用、长任务与 CPU/HBM/NAND 需求；用于需求机制。"
        },
        {
          "id": "PA13",
          "title": "VecAI知识库 · 2026-09-22",
          "date": "2026-09-22",
          "type": "知识库调研",
          "note": "Co-Work 向持久主动执行演进；长上下文和并行智能体增加推理需求。"
        },
        {
          "id": "PA14",
          "title": "VecAI知识库 · 2026-09-21",
          "date": "2026-09-21",
          "type": "知识库研究",
          "note": "消费智能体 CPU 测算框架；按执行时长、占用核心及利用率复算。"
        },
        {
          "id": "PA15",
          "title": "本站个人智能体用户普及与收入模型",
          "date": "2026-09-24",
          "type": "研究假设",
          "note": "全球在线人数→可接入→实际执行→收费/交易。2026—2030年度研究预测；2035/2040独立远期普及情景。执行CPU为装机成本，不计应用收入。"
        },
        {
          "id": "PA16",
          "title": "Micron：智能体时代的内存层级",
          "date": "2026-09-23（访问）",
          "type": "官方技术分析",
          "url": "https://www.micron.com/about/blog/storage/ai/the-memory-wall-in-the-agentic-ai-era",
          "note": "HBM、DRAM、NAND 分层服务推理、运行状态及持久存储。"
        },
        {
          "id": "PA17",
          "title": "SK hynix：FMS 2026 内存架构",
          "date": "2026-08",
          "type": "官方技术披露",
          "url": "https://news.skhynix.com/en/fms-2026/",
          "note": "智能体推理对 HBM、服务器 DRAM、NAND 的协同需求。"
        },
        {
          "id": "PA18",
          "title": "CPU报告 · 陈明璋 V6",
          "date": "2026-09-24（查阅）",
          "type": "知识库研究",
          "note": "原PDF第17—19页；第18页页内编号12。GPU主机、强化学习环境、智能体运行容器三类CPU需求；曲线为定性机制，未标报告发布日期。"
        },
        {
          "id": "PA19",
          "title": "Spotify：2026年第二季度经营数据",
          "date": "2026-08-04",
          "type": "官方财报",
          "url": "https://newsroom.spotify.com/2026-08-04/spotify-q2-2026-earnings/",
          "note": "7.77亿MAU、3亿Premium用户；权益用户/MAU约38.6%，包含家庭计划成员，并非付款账户转化率。"
        },
        {
          "id": "PA20",
          "title": "RevenueCat：2026订阅应用报告",
          "date": "2026（2025样本）",
          "type": "平台统计",
          "url": "https://www.revenuecat.com/state-of-subscription-apps",
          "note": "AI应用下载35日内付费转化中位数2.4%；分母为新安装，不能用作成熟月活付费率。"
        },
        {
          "id": "PA21",
          "title": "Microsoft：消费套餐内的AI额度与功能",
          "date": "2026-07（页面更新）",
          "type": "官方产品文档",
          "url": "https://support.microsoft.com/en-US/Microsoft-365-Copilot/ai-credits-and-limits-for-microsoft-365-subscriptions",
          "note": "消费订阅套餐分配AI权益与使用限额，AI权益限订阅所有者；体现套餐收费与独立订阅的差别。"
        },
        {
          "id": "PA22",
          "title": "Cloudflare：智能体并发与CPU需求",
          "date": "2026-04-12",
          "type": "官方产业分析",
          "url": "https://blog.cloudflare.com/welcome-to-agents-week/",
          "note": "以约2400万并发、每CPU25—50会话测算50万—100万CPU；厂商情景，非实际装机统计。"
        },
        {
          "id": "PA23",
          "title": "AWS：Graviton5 M9g实例正式可用",
          "date": "2026-06-10",
          "type": "官方产品披露",
          "url": "https://aws.amazon.com/blogs/aws/now-available-amazon-ec2-m9g-and-m9gd-instances-powered-by-new-aws-graviton5-processors/",
          "note": "较Graviton4计算性能最多提升25%；实例规格到192 vCPU。供应商特定比较，不等于所有负载提升25%。"
        },
        {
          "id": "PA24",
          "title": "AWS：迁移至Graviton的兼容性要求",
          "date": "2026-09-24（访问）",
          "type": "官方技术文档",
          "url": "https://aws.github.io/graviton/transition-guide.html",
          "note": "Arm64需要匹配原生库、预编译依赖和镜像；移植范围取决于软件栈。"
        },
        {
          "id": "PA25",
          "title": "AMD：EPYC 9006的智能体工作负载分工",
          "date": "2026-07-23",
          "type": "官方技术分析",
          "url": "https://www.amd.com/en/blogs/2026/the-agentic-era-runs-on-a-cpu-foundation-and-it-s-called.html",
          "note": "高频主机与高密度执行CPU面向不同负载；内存带宽、I/O与每核性能共同影响部署。"
        },
        {
          "id": "PA26",
          "title": "Anthropic：Claude Code实际使用研究",
          "date": "2026-06-16",
          "type": "官方使用研究",
          "url": "https://www.anthropic.com/research/claude-code-expertise",
          "note": "典型会话约4个用户轮次，每轮平均约10次智能体动作；这是开发者样本，不能直接视作消费智能体负载。"
        },
        {
          "id": "PA27",
          "title": "DeepSeek：DSec生产沙箱系统",
          "date": "2026-09-19",
          "type": "原始论文 / 生产系统披露",
          "url": "https://arxiv.org/abs/2609.22978",
          "note": "单个生产规模单元约160节点、每日约300万沙箱；生产系统支持超过38万并发沙箱。针对训练/评估环境，不是消费用户实测。"
        },
        {
          "id": "PA28",
          "title": "AgentSysBench：智能体工作负载测量",
          "date": "2026-08-15",
          "type": "原始论文",
          "url": "https://arxiv.org/abs/2608.15127",
          "note": "10个应用中5个由非LLM环节主导延迟；会话工作集峰值28GB，生产会话状态在步骤间保留数分钟至数小时。"
        },
        {
          "id": "PA29",
          "title": "NVIDIA：Vera CPU与智能体执行效率",
          "date": "2026-07-07",
          "type": "官方技术分析",
          "url": "https://developer.nvidia.com/blog/nvidia-vera-cpu-boosts-ai-factory-throughput-to-accelerate-agentic-workloads/",
          "note": "CPU满载单核性能、工具调用尾延迟和环境反馈速度影响GPU有效吞吐；核数不是唯一指标。"
        },
        {
          "id": "PA30",
          "title": "ITU：2025年全球互联网用户",
          "date": "2025-11-17",
          "type": "国际组织统计",
          "url": "https://www.itu.int/en/mediacentre/Pages/PR-2025-11-17-Facts-and-Figures.aspx",
          "note": "2025年约60亿、74%世界人口使用互联网；2024修订为58亿。2030及以后在线人数为本报告情景。"
        },
        {
          "id": "PA31",
          "title": "Microsoft：2026年第二季度全球AI普及",
          "date": "2026-09-21",
          "type": "官方遥测研究",
          "url": "https://blogs.microsoft.com/on-the-issues/2026/09/21/the-continued-state-of-global-ai-diffusion-in-2026/",
          "note": "2026年6月15—64岁人口中18.8%使用生成式AI。这不是个人智能体执行或付费率。"
        },
        {
          "id": "PA32",
          "title": "世界银行：Global Findex 2025",
          "date": "2025-07-16",
          "type": "国际组织调查",
          "url": "https://www.worldbank.org/en/news/press-release/2025/07/16/mobile-phone-technology-powers-saving-surge-in-developing-economies",
          "note": "2024年全球68%成人有智能手机；中低收入经济体42%成人进行数字商户支付（含线下）。设备/支付成熟度参照。"
        },
        {
          "id": "PA33",
          "title": "Meta：2026年第二季度业绩",
          "date": "2026-07-29",
          "type": "官方财报",
          "url": "https://investor.atmeta.com/investor-news/press-release-details/2026/Meta-Reports-Second-Quarter-2026-Results/default.aspx",
          "note": "2026年6月Family日活36亿；仅作分发覆盖参照，不能等同Muse或AI执行用户。"
        },
        {
          "id": "PA34",
          "title": "Arm：AGI CPU生产硅与Meta合作",
          "date": "2026-03-24",
          "type": "官方产品发布",
          "url": "https://newsroom.arm.com/news/arm-agi-cpu-launch",
          "note": "Arm从IP/CSS拓展至生产硅，Meta为共同开发伙伴；最高136核心。授权/版税和自有芯片两种收入机会。"
        },
        {
          "id": "PA35",
          "title": "Intel：Xeon 6用于主机与行动执行",
          "date": "2026-04-08",
          "type": "官方产品合作",
          "url": "https://www.intel.com/content/www/us/en/newsroom/news/artificial-intelligence/intel-and-sambanova-advance-agentic-ai-with-xeon-6.html",
          "note": "与SambaNova披露GPU预填充、RDU解码、Xeon主机/行动CPU的异构方案，强调x86兼容性。"
        },
        {
          "id": "PA36",
          "title": "Qualcomm：Dragonfly智能体数据中心平台",
          "date": "2026-09-14",
          "type": "官方产品路线",
          "url": "https://www.qualcomm.com/news/onq/2026/09/qualcomm-dragonfly-ai-infra-summit-2026",
          "note": "CPU、推理加速、定制硅、连接四个产品方向；不将厂商性能估计当本模型系数。"
        },
        {
          "id": "PA37",
          "title": "Qualcomm：Dragonfly C1000 CPU",
          "date": "2026-09-24（查阅）",
          "type": "官方产品资料",
          "url": "https://www.qualcomm.com/data-center",
          "note": "C1000为250+核chiplet设计，面向智能体、通用和AI主机负载；新品部署规模取决于量产/客户落地。"
        },
        {
          "id": "PA38",
          "title": "Qualcomm：面向个人智能体的Snapdragon",
          "date": "2026-09-22",
          "type": "官方技术展望",
          "url": "https://www.qualcomm.com/news/onq/2026/09/snapdragon-for-agentic-age",
          "note": "个人智能体跨手机、PC、可穿戴及云协同；端侧芯片机会不作为云端CPU销售额加总。"
        },
        {
          "id": "PA39",
          "title": "VecAI知识库 · 2026-06-02",
          "date": "2026-06-02",
          "type": "知识库交流",
          "note": "高通交流涉及数据中心CPU、定制ASIC与加速器的分阶段收入机会。"
        },
        {
          "id": "PA40",
          "title": "Qualcomm：与Amazon开展多代产品合作",
          "date": "2026-09-08",
          "type": "官方合作发布",
          "url": "https://www.qualcomm.com/news/releases/2026/09/qualcomm-announces-multi-generational-product-collaboration-with",
          "note": "数据中心产品路线与客户合作；收入实现取决于实际交付。"
        },
        {
          "id": "PA41",
          "title": "xAI：Grok Bot 云电脑、应用与持久化工作区",
          "date": "2026-09-14（更新）",
          "type": "官方产品文档",
          "url": "https://docs.x.ai/grok-bot/computer-and-apps",
          "note": "浏览器、终端与文件提供实际执行能力；同账号共享云电脑，/workspace 保存长期工作文件，浏览器状态与支持的登录可跨正常更新保留。网站会话仍可能过期，临时目录与未保存状态不保证保留。"
        }
      ],
      "media": {
        "source": "https://introducing.muse.ai/",
        "newsroomSource": "https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/",
        "video": "https://about.fb.com/wp-content/uploads/2026/09/Muse_Shopping.mp4",
        "tour": "https://www.youtube.com/watch?v=wHn0hTjvFoo",
        "goals": "https://introducing.muse.ai/_next/static/immutable/media/goals.0afs6w3eczjsr.png",
        "checkout": "https://introducing.muse.ai/_next/static/immutable/media/checkout.0nx6hmfxq6ara.png",
        "verified": "2026-09-23：媒体链接 HEAD 200，PNG 与 video/mp4 类型核验。均为 2026 年 9 月 Muse 产品素材。",
        "rights": "Meta 官方产品说明与新闻素材，远程嵌入供研究展示并注明来源，不修改或重新分发素材，不宣称开放版权。"
      },
      "forecastInputs": [
        {
          "year": 2026,
          "usersMillion": 38.4375,
          "directShare": 0.08,
          "directMonthlyPrice": 12,
          "directIncrementalShare": 0.6,
          "bundleShare": 0.04,
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          "taskMonthlySpend": 2.5,
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          "annualGmv": 1900,
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        {
          "year": 2030,
          "usersMillion": 2550,
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          "taskMonthlySpend": 3,
          "transactionUsersMillion": 1020,
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      "scenarioInputs": [
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          "name": "审慎"
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          "name": "上行",
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          "usersMillion": 3867.5,
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        "coresPerCpu": 128,
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        "scenarios": [
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          {
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          {
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        ],
        "formula": "executionDauMillion × 1e6 × minutes × activeCores × peakAverageRatio ÷ (1440 × coresPerCpu × targetUtilization)",
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        "specificationNote": "128/192/256物理核是相同每核执行效率下的规模敏感性参数，不表示不同架构同核等速，也不是2030确定产品配置。192核可由当前Graviton5作为可实现的规格参照。"
      },
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        "paidDefinition": "直接订阅、仅通过付费套餐获得权益、仅按任务付款三组互斥，合计为用户显性付费覆盖。剩余用户免费使用或无增量价格的既有套餐捆绑；商户间接付费按交易额另计，不再加人数。",
        "directFormula": "用户百万数 × 直接订阅占比 × 月费 × 12 ÷ 1000 × 新增归因比例",
        "bundleFormula": "用户百万数 × 仅套餐付费占比 × 智能体引致月增量价差 × 12 ÷ 1000",
        "taskFormula": "用户百万数 × 仅按任务付费占比 × 每月实际服务支出 × 12 ÷ 1000",
        "transactionFormula": "年度交易用户百万数 × 每人年GMV ÷ 1000 × 智能体服务净费率 × 新增归因比例",
        "revenueFormula": "新增直接订阅 + 套餐增量 + 按任务收入 + 新增交易服务；USD billion。",
        "boundary": "仅消费/家庭个人智能体的终端应用服务收入，排除企业统一采购的办公/编码席位。直接订阅扣除原聊天等套餐迁移；套餐只计因智能体产生的实际涨价或付费升级价差，免费新增权益计零。按任务用户不与订阅/套餐重叠。交易服务是平台从商户/支付生态获得的额外服务净收入，扣除旧佣金迁移及已由订阅/按任务覆盖的同项收费。GMV不作收入。模型API、执行云、CPU、存储均为供应链成本，不再与终端收入相加。Muse广告增量为零。",
        "rationale": "成熟高频订阅服务证明权益渗透可以达到较高水平；个人智能体还具备可衡量省时价值与套餐分发优势。未来付费率不是当前事实。基准直接35%+套餐15%+按任务10%=60%；上行直接订阅50%，要求更高频、更可靠执行与价格适配。",
        "marginNote": "收入模型未设毛利率。CPU图仅计执行CPU装机，不代表包括推理、DRAM、存储、网络及服务成本的完整单位经济性；高强度付费产品需分档与额度约束。",
        "direct50Sensitivity": "固定2030基准用户路径与其他收费/交易参数，仅直接订阅占比由35%提高至50%。",
        "userPathFormula": "internetUsersMillion × accessShare × executionShare = usersMillion；usersMillion × paymentReadyShare × transactionAuthorizationShare = transactionUsersMillion",
        "userPathRationale": "ITU2025在线60亿为人口锚；2030在线68亿约隐含2.5%年增长。75%可接入综合语言、产品区域、设备、年龄与账户权限；基准假设其中50%每月实际跨应用委托。年度执行率假设为2026—2030年2.5%、10%、20%、35%、50%；2030审慎25%、上行65%。交易人数按稳定用户池40%=80%支付接入×50%年内至少一次授权估计。未来比例都是研究假设，Microsoft的AI使用率和Meta日活不直接替代这些比例。",
        "longTermBasis": "2035/2040是独立远期普及阶段情景：可接入人群的执行率分别65%/80%，均高于2030基准50%；人口、接入、付费价格与交易参数分别给定。以名义美元重新计算完整年度净新增服务收入，不是对2030作固定倍数外推。"
      },
      "longTermInputs": [
        {
          "year": 2035,
          "directShare": 0.4,
          "directMonthlyPrice": 18,
          "directIncrementalShare": 0.8,
          "bundleShare": 0.2,
          "bundleMonthlyUplift": 5,
          "taskOnlyShare": 0.1,
          "taskMonthlySpend": 5,
          "annualGmv": 3500,
          "takeRate": 0.01,
          "transactionIncrementalShare": 0.6,
          "usersMillion": 4446,
          "transactionUsersMillion": 2600.9100000000003
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        {
          "year": 2040,
          "directShare": 0.45,
          "directMonthlyPrice": 20,
          "directIncrementalShare": 0.85,
          "bundleShare": 0.22,
          "bundleMonthlyUplift": 6,
          "taskOnlyShare": 0.1,
          "taskMonthlySpend": 6,
          "annualGmv": 5000,
          "takeRate": 0.01,
          "transactionIncrementalShare": 0.7,
          "usersMillion": 6156,
          "transactionUsersMillion": 4678.56
        }
      ],
      "userPathInputs": [
        {
          "year": 2026,
          "internetUsersMillion": 6150,
          "accessShare": 0.25,
          "executionShare": 0.025,
          "paymentReadyShare": 0.5,
          "transactionAuthorizationShare": 0.15
        },
        {
          "year": 2027,
          "internetUsersMillion": 6300,
          "accessShare": 0.4,
          "executionShare": 0.1,
          "paymentReadyShare": 0.6,
          "transactionAuthorizationShare": 0.25
        },
        {
          "year": 2028,
          "internetUsersMillion": 6460,
          "accessShare": 0.55,
          "executionShare": 0.2,
          "paymentReadyShare": 0.7,
          "transactionAuthorizationShare": 0.35
        },
        {
          "year": 2029,
          "internetUsersMillion": 6630,
          "accessShare": 0.65,
          "executionShare": 0.35,
          "paymentReadyShare": 0.75,
          "transactionAuthorizationShare": 0.45
        },
        {
          "year": 2030,
          "internetUsersMillion": 6800,
          "accessShare": 0.75,
          "executionShare": 0.5,
          "paymentReadyShare": 0.8,
          "transactionAuthorizationShare": 0.5
        }
      ],
      "scenarioUserPathInputs": [
        {
          "year": 2030,
          "internetUsersMillion": 6800,
          "accessShare": 0.75,
          "executionShare": 0.25,
          "paymentReadyShare": 0.8,
          "transactionAuthorizationShare": 0.5,
          "name": "审慎"
        },
        {
          "year": 2030,
          "internetUsersMillion": 6800,
          "accessShare": 0.75,
          "executionShare": 0.5,
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          "transactionAuthorizationShare": 0.5,
          "name": "基准"
        },
        {
          "name": "上行",
          "year": 2030,
          "internetUsersMillion": 7000,
          "accessShare": 0.85,
          "executionShare": 0.65,
          "paymentReadyShare": 0.9,
          "transactionAuthorizationShare": 0.65
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      ],
      "longTermUserPathInputs": [
        {
          "year": 2035,
          "internetUsersMillion": 7600,
          "accessShare": 0.9,
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          "paymentReadyShare": 0.9,
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        },
        {
          "year": 2040,
          "internetUsersMillion": 8100,
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        {
          "key": "gradual",
          "label": "渐进扩散",
          "conditions": [
            "工具和局部实验交付率提升，跨机构连续执行仍以人工协调为主。",
            "AI项目阶段成功率保持优势，后期临床和跨领域复用逐步积累。",
            "研发预算温和增长，外部交付费用随工具采用提升。"
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        {
          "key": "core",
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          "conditions": [
            "科研智能体稳定接通真实实验，自动执行与独立验证能够跨项目复用。",
            "到2035年临床设计与运营部署率达到75%，非药科研部署率达到80%—90%；到2040年进一步扩散。",
            "外部供应商承接更完整的设计、实验和运营任务，收费占部署预算比例达到35%—50%，随后继续加深。",
            "相关药物获得临床和商业验证，分成对应年销售2035年1000亿美元、2040年2500亿美元；科研预算按阶段增长。"
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            "研发回报改善支持更快预算扩张，科研客户更多按完整成果采购。",
            "大规模临床验证与上市成果扩大分成池，部署率和交付深度共同上升。"
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              "industrialScale2035": 1,
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          "usersMillion": 38.4375,
          "directShare": 0.08,
          "directMonthlyPrice": 12,
          "directIncrementalShare": 0.6,
          "bundleShare": 0.04,
          "bundleMonthlyUplift": 2,
          "taskOnlyShare": 0.02,
          "taskMonthlySpend": 1,
          "transactionUsersMillion": 2.8828125,
          "annualGmv": 500,
          "takeRate": 0.006,
          "transactionIncrementalShare": 0.2,
          "paidShare": 0.13999999999999999,
          "freeShare": 0.86,
          "directGross": 0.4428000000000001,
          "direct": 0.26568,
          "bundle": 0.0369,
          "task": 0.009225,
          "subscription": 0.30258,
          "gmv": 1.44140625,
          "transaction": 0.0017296875,
          "total": 0.3135346875,
          "internetUsersMillion": 6150,
          "accessShare": 0.25,
          "executionShare": 0.025,
          "paymentReadyShare": 0.5,
          "transactionAuthorizationShare": 0.15,
          "reachableMillion": 1537.5,
          "paymentReadyMillion": 19.21875
        },
        {
          "year": 2027,
          "usersMillion": 252,
          "directShare": 0.15,
          "directMonthlyPrice": 13,
          "directIncrementalShare": 0.65,
          "bundleShare": 0.08,
          "bundleMonthlyUplift": 2.5,
          "taskOnlyShare": 0.04,
          "taskMonthlySpend": 1.5,
          "transactionUsersMillion": 37.8,
          "annualGmv": 900,
          "takeRate": 0.007,
          "transactionIncrementalShare": 0.25,
          "paidShare": 0.26999999999999996,
          "freeShare": 0.73,
          "directGross": 5.896799999999999,
          "direct": 3.832919999999999,
          "bundle": 0.6048,
          "task": 0.18144,
          "subscription": 4.437719999999999,
          "gmv": 34.02,
          "transaction": 0.059535000000000005,
          "total": 4.678694999999999,
          "internetUsersMillion": 6300,
          "accessShare": 0.4,
          "executionShare": 0.1,
          "paymentReadyShare": 0.6,
          "transactionAuthorizationShare": 0.25,
          "reachableMillion": 2520,
          "paymentReadyMillion": 151.2
        },
        {
          "year": 2028,
          "usersMillion": 710.6000000000001,
          "directShare": 0.23,
          "directMonthlyPrice": 14,
          "directIncrementalShare": 0.7,
          "bundleShare": 0.11,
          "bundleMonthlyUplift": 3,
          "taskOnlyShare": 0.06,
          "taskMonthlySpend": 2,
          "transactionUsersMillion": 174.097,
          "annualGmv": 1400,
          "takeRate": 0.008,
          "transactionIncrementalShare": 0.3,
          "paidShare": 0.4,
          "freeShare": 0.6,
          "directGross": 27.457584000000008,
          "direct": 19.220308800000005,
          "bundle": 2.8139760000000007,
          "task": 1.0232640000000002,
          "subscription": 22.034284800000005,
          "gmv": 243.7358,
          "transaction": 0.58496592,
          "total": 23.642514720000005,
          "internetUsersMillion": 6460,
          "accessShare": 0.55,
          "executionShare": 0.2,
          "paymentReadyShare": 0.7,
          "transactionAuthorizationShare": 0.35,
          "reachableMillion": 3553.0000000000005,
          "paymentReadyMillion": 497.4200000000001
        },
        {
          "year": 2029,
          "usersMillion": 1508.3249999999998,
          "directShare": 0.3,
          "directMonthlyPrice": 15,
          "directIncrementalShare": 0.7,
          "bundleShare": 0.13,
          "bundleMonthlyUplift": 3.5,
          "taskOnlyShare": 0.08,
          "taskMonthlySpend": 2.5,
          "transactionUsersMillion": 509.05968749999994,
          "annualGmv": 1900,
          "takeRate": 0.009,
          "transactionIncrementalShare": 0.35,
          "paidShare": 0.51,
          "freeShare": 0.49,
          "directGross": 81.44954999999999,
          "direct": 57.014684999999986,
          "bundle": 8.2354545,
          "task": 3.6199799999999995,
          "subscription": 65.25013949999999,
          "gmv": 967.2134062499999,
          "transaction": 3.046722229687499,
          "total": 71.91684172968749,
          "internetUsersMillion": 6630,
          "accessShare": 0.65,
          "executionShare": 0.35,
          "paymentReadyShare": 0.75,
          "transactionAuthorizationShare": 0.45,
          "reachableMillion": 4309.5,
          "paymentReadyMillion": 1131.2437499999999
        },
        {
          "year": 2030,
          "usersMillion": 2550,
          "directShare": 0.35,
          "directMonthlyPrice": 15,
          "directIncrementalShare": 0.7,
          "bundleShare": 0.15,
          "bundleMonthlyUplift": 4,
          "taskOnlyShare": 0.1,
          "taskMonthlySpend": 3,
          "transactionUsersMillion": 1020,
          "annualGmv": 2500,
          "takeRate": 0.01,
          "transactionIncrementalShare": 0.4,
          "paidShare": 0.6,
          "freeShare": 0.4,
          "directGross": 160.65,
          "direct": 112.455,
          "bundle": 18.36,
          "task": 9.18,
          "subscription": 130.815,
          "gmv": 2550,
          "transaction": 10.200000000000001,
          "total": 150.195,
          "internetUsersMillion": 6800,
          "accessShare": 0.75,
          "executionShare": 0.5,
          "paymentReadyShare": 0.8,
          "transactionAuthorizationShare": 0.5,
          "reachableMillion": 5100,
          "paymentReadyMillion": 2040
        }
      ]
    },
    "personal": [
      {
        "year": 2030,
        "usersMillion": 1275,
        "directShare": 0.35,
        "directMonthlyPrice": 15,
        "directIncrementalShare": 0.7,
        "bundleShare": 0.15,
        "bundleMonthlyUplift": 4,
        "taskOnlyShare": 0.1,
        "taskMonthlySpend": 3,
        "transactionUsersMillion": 510,
        "annualGmv": 2500,
        "takeRate": 0.01,
        "transactionIncrementalShare": 0.4,
        "name": "审慎",
        "paidShare": 0.6,
        "freeShare": 0.4,
        "directGross": 80.325,
        "direct": 56.2275,
        "bundle": 9.18,
        "task": 4.59,
        "subscription": 65.4075,
        "gmv": 1275,
        "transaction": 5.1000000000000005,
        "total": 75.0975,
        "internetUsersMillion": 6800,
        "accessShare": 0.75,
        "executionShare": 0.25,
        "paymentReadyShare": 0.8,
        "transactionAuthorizationShare": 0.5,
        "reachableMillion": 5100,
        "paymentReadyMillion": 1020
      },
      {
        "name": "基准",
        "year": 2030,
        "usersMillion": 2550,
        "directShare": 0.35,
        "directMonthlyPrice": 15,
        "directIncrementalShare": 0.7,
        "bundleShare": 0.15,
        "bundleMonthlyUplift": 4,
        "taskOnlyShare": 0.1,
        "taskMonthlySpend": 3,
        "transactionUsersMillion": 1020,
        "annualGmv": 2500,
        "takeRate": 0.01,
        "transactionIncrementalShare": 0.4,
        "paidShare": 0.6,
        "freeShare": 0.4,
        "directGross": 160.65,
        "direct": 112.455,
        "bundle": 18.36,
        "task": 9.18,
        "subscription": 130.815,
        "gmv": 2550,
        "transaction": 10.200000000000001,
        "total": 150.195,
        "internetUsersMillion": 6800,
        "accessShare": 0.75,
        "executionShare": 0.5,
        "paymentReadyShare": 0.8,
        "transactionAuthorizationShare": 0.5,
        "reachableMillion": 5100,
        "paymentReadyMillion": 2040
      },
      {
        "name": "上行",
        "year": 2030,
        "usersMillion": 3867.5,
        "directShare": 0.5,
        "directMonthlyPrice": 18,
        "directIncrementalShare": 0.75,
        "bundleShare": 0.15,
        "bundleMonthlyUplift": 5,
        "taskOnlyShare": 0.1,
        "taskMonthlySpend": 4,
        "transactionUsersMillion": 2262.4875,
        "annualGmv": 4000,
        "takeRate": 0.012,
        "transactionIncrementalShare": 0.5,
        "paidShare": 0.75,
        "freeShare": 0.25,
        "directGross": 417.69,
        "direct": 313.2675,
        "bundle": 34.8075,
        "task": 18.564,
        "subscription": 348.075,
        "gmv": 9049.95,
        "transaction": 54.29970000000001,
        "total": 420.93870000000004,
        "internetUsersMillion": 7000,
        "accessShare": 0.85,
        "executionShare": 0.65,
        "paymentReadyShare": 0.9,
        "transactionAuthorizationShare": 0.65,
        "reachableMillion": 5950,
        "paymentReadyMillion": 3480.75
      }
    ]
  },
  "historicalEvidence": {
    "anthropic": {
      "unit": "USD 100 million annualized",
      "points": [
        {
          "date": "2025-12-31",
          "dateLabel": "2025年末",
          "value": 90,
          "group": "披露/报道",
          "note": "2025年末ARR；后由公司公告及Reuters确认。",
          "source": "TL04"
        },
        {
          "date": "2026-02-12",
          "dateLabel": "2026年2月12日",
          "value": 140,
          "group": "披露/报道",
          "note": "Series G 公司公告。",
          "source": "TL02"
        },
        {
          "date": "2026-03-03",
          "dateLabel": "2026年3月3日",
          "value": 190,
          "group": "披露/报道",
          "note": "Bloomberg 报道；不是公司财报披露。",
          "source": "TL33"
        },
        {
          "date": "2026-04-06",
          "dateLabel": "2026年4月6日",
          "value": 300,
          "group": "披露/报道",
          "note": "公司 Google / Broadcom 合作公告。",
          "source": "TL32"
        },
        {
          "date": "2026-05-10",
          "dateLabel": "2026年5月上旬",
          "value": 470,
          "group": "披露/报道",
          "note": "5月28日 Series H 公告披露本月较早时达到470亿；横轴置于5月上旬。",
          "source": "TL03"
        },
        {
          "date": "2026-07-31",
          "dateLabel": "2026年7月末",
          "value": 650,
          "group": "披露/报道",
          "note": "8月17日 Reuters 转述的7月ARR；Bloomberg 首先报道。",
          "source": "TL04"
        },
        {
          "date": "2026-05-21",
          "dateLabel": "2026年5月21日",
          "value": 546,
          "group": "TickerTrends",
          "note": "独立跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-06-03",
          "dateLabel": "2026年6月3日",
          "value": 674,
          "group": "TickerTrends",
          "note": "独立跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-06-15",
          "dateLabel": "2026年6月15日",
          "value": 705,
          "group": "TickerTrends",
          "note": "独立跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-06-27",
          "dateLabel": "2026年6月27日",
          "value": 696,
          "group": "TickerTrends",
          "note": "独立跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-07-09",
          "dateLabel": "2026年7月9日",
          "value": 719,
          "group": "TickerTrends",
          "note": "独立跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-07-22",
          "dateLabel": "2026年7月22日",
          "value": 743,
          "group": "TickerTrends",
          "note": "独立跟踪估计；与公司/媒体口径分别展示。",
          "source": "TL34"
        },
        {
          "date": "2026-05-01",
          "dateLabel": "2026年5月初",
          "value": 440,
          "group": "其他机构",
          "note": "SemiAnalysis 跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-07-10",
          "dateLabel": "2026年7月10日",
          "value": 690,
          "group": "其他机构",
          "note": "Yipit Data 跟踪估计。",
          "source": "TL34"
        },
        {
          "date": "2026-12-31",
          "dateLabel": "2026年末预期 · 9月18日报道",
          "value": 1000,
          "group": "年末预期",
          "note": "NYT / Bloomberg：预计年末超过1000亿美元，非9月已实现值。",
          "source": "TL06"
        },
        {
          "date": "2026-12-31",
          "dateLabel": "2026年末预期 · 9月19日报道",
          "value": 1200,
          "group": "最新年末预期",
          "note": "FT：年末ARR预期超过1200亿美元；本报告采用1200亿研究基准。",
          "source": "TL08"
        }
      ]
    },
    "vercel": {
      "dates": [
        "2026-09-18",
        "2026-09-19",
        "2026-09-20",
        "2026-09-21",
        "2026-09-22"
      ],
      "unit": "percent of text inference spending on Vercel AI Gateway per day",
      "license": "CC-BY-4.0",
      "source": "https://vercel.com/ai-gateway/leaderboards/labs",
      "series": [
        {
          "label": "Kimi / Moonshot AI",
          "values": [
            10.1024,
            13.3644,
            14.0253,
            15.549,
            20.978
          ]
        },
        {
          "label": "DeepSeek",
          "values": [
            7.1441,
            6.2162,
            5.3734,
            5.2102,
            6.2536
          ]
        },
        {
          "label": "智谱 / Z.ai",
          "values": [
            6.7515,
            3.4758,
            2.7831,
            4.3422,
            4.5568
          ]
        },
        {
          "label": "OpenAI",
          "values": [
            22.2393,
            25.1086,
            21.0894,
            30.5846,
            24.9619
          ]
        }
      ]
    }
  },
  "bridgeAssumptions": {
    "enterpriseWorkflowIncluded": false,
    "incrementalShare": {
      "science": 0.5,
      "chips": 0.5,
      "personal": 0.75,
      "robotHardware": 0.8,
      "drivingHardware": 0.5,
      "raas": 0.8,
      "software": 0.5,
      "driving": 0.7
    },
    "marginalGrossMargin": {
      "science": 0.55,
      "chips": 0.65,
      "personal": 0.65,
      "robotHardware": 0.3,
      "drivingHardware": 0.3,
      "raas": 0.5,
      "software": 0.6,
      "driving": 0.65
    }
  },
  "investmentUpdate": {
    "capacityGW": [
      2.3,
      12,
      20,
      26,
      32
    ],
    "newCapacityGW": [
      1,
      9.7,
      8,
      6,
      6
    ],
    "unitCostBnPerGW": 55,
    "unitCostRangeBnPerGW": [
      50,
      60
    ],
    "recognizedIncrementShare": 0.8,
    "incremental2026": 33
  },
  "chinaInvestmentUpdate": {
    "years": [
      2026,
      2027
    ],
    "byteDanceCompanyCapexBn": [
      70,
      100
    ],
    "oldCompanyCapex2026Bn": 28.169014084507044,
    "aiAssetShare": 0.95,
    "domesticOwnerShare": 0.65,
    "sourceIds": [
      "TL40",
      "TL41"
    ],
    "status": "9月积极研究情景；公司全球预算按原模型比例折算中国境内AI资产",
    "outputs": [
      {
        "year": 2026,
        "base": 77.46478873239437,
        "oldByteDanceProxy": 17.3943661971831,
        "revisedByteDance": 43.225,
        "increment": 25.8306338028169,
        "updated": 103.29542253521127,
        "updatedGrowth": 0.589160346695558
      },
      {
        "year": 2027,
        "base": 214.74744038759823,
        "oldByteDanceProxy": 48.22056161430615,
        "revisedByteDance": 61.75,
        "increment": 13.529438385693851,
        "updated": 228.27687877329208,
        "updatedGrowth": 1.2099418654827345
      },
      {
        "year": 2028,
        "base": 350.8510420446346,
        "oldByteDanceProxy": 78.78200671365886,
        "revisedByteDance": 78.78200671365886,
        "increment": 0,
        "updated": 350.8510420446346,
        "updatedGrowth": 0.536953912853672
      },
      {
        "year": 2029,
        "base": 465.25773859977124,
        "oldByteDanceProxy": 104.47151039467592,
        "revisedByteDance": 104.47151039467592,
        "increment": 0,
        "updated": 465.25773859977124,
        "updatedGrowth": 0.3260833882334089
      },
      {
        "year": 2030,
        "base": 569.8493308781607,
        "oldByteDanceProxy": 127.95707702445972,
        "revisedByteDance": 127.95707702445972,
        "increment": 0,
        "updated": 569.8493308781607,
        "updatedGrowth": 0.22480355209816794
      }
    ]
  },
  "longTerm": {
    "assumptions": {
      "years": [
        2030,
        2035,
        2040
      ],
      "matureDigitalGrowth2031To2035": 0.15,
      "matureDigitalGrowth2036To2040": 0.1,
      "lowerDigitalGrowth2031To2035": 0.1,
      "lowerDigitalGrowth2036To2040": 0.07,
      "componentBasis": "AI科研、AI芯片研发和物理AI为各章年度收入；个人智能体为扣原套餐及旧佣金迁移后的年度新增服务收入。既有消费AI套餐包含在数字业务中，非AI旧佣金不加入。",
      "sourceIds": [
        "TL45"
      ],
      "status": "条件化远期研究情景，非公司指引；2030年与近端模型一致"
    },
    "sectors": {
      "science": [
        424.53097994000007,
        1012.3355258196783,
        1914.975130661279
      ],
      "chips": [
        26.827161099200012,
        74.49023439752855,
        151.17758612310027
      ],
      "personal": [
        150.195,
        441.95463000000007,
        870.70464
      ],
      "physical": [
        255.76986889975,
        1255.1678072517198,
        3880.2978677044466
      ],
      "physicalBreakthrough": [
        255.76986889975,
        2377.247719620062,
        10723.884409906917
      ]
    },
    "outputs": [
      {
        "year": 2030,
        "matureDigital": 4164.213377766765,
        "matureDigitalLower": 4164.213377766765,
        "science": 424.53097994000007,
        "chips": 26.827161099200012,
        "personal": 150.195,
        "physical": 255.76986889975,
        "newFields": 857.32300993895,
        "total": 5021.536387705715,
        "newFieldsShare": 0.17072922383634292,
        "physicalBreakthrough": 255.76986889975,
        "totalPhysicalBreakthrough": 5021.536387705715,
        "totalLowerDigital": 5021.536387705715
      },
      {
        "year": 2035,
        "matureDigital": 8375.720507654833,
        "matureDigitalLower": 6706.507287027155,
        "science": 1012.3355258196783,
        "chips": 74.49023439752855,
        "personal": 441.95463000000007,
        "physical": 1255.1678072517198,
        "newFields": 2783.9481974689265,
        "total": 11159.668705123759,
        "newFieldsShare": 0.24946512938961418,
        "physicalBreakthrough": 2377.247719620062,
        "totalPhysicalBreakthrough": 12281.7486174921,
        "totalLowerDigital": 9490.455484496082
      },
      {
        "year": 2040,
        "matureDigital": 13489.181634783188,
        "matureDigitalLower": 9406.223402372101,
        "science": 1914.975130661279,
        "chips": 151.17758612310027,
        "personal": 870.70464,
        "physical": 3880.2978677044466,
        "newFields": 6817.155224488826,
        "total": 20306.336859272014,
        "newFieldsShare": 0.33571565722234464,
        "physicalBreakthrough": 10723.884409906917,
        "totalPhysicalBreakthrough": 27149.923401474487,
        "totalLowerDigital": 16223.378626860927
      }
    ]
  },
  "outputs": [
    {
      "year": 2026,
      "oldXaiProxy": 30.799999999999997,
      "companyDelta": 0,
      "scienceDelta": 13.46648,
      "chipsDelta": 0.5138940000000001,
      "personalDelta": 0.23515101562500001,
      "physicalDelta": 18.1513675,
      "physicalComponents": {
        "robotHardware": 7.464,
        "drivingHardware": 6,
        "raas": 2.0712,
        "software": 0.58083,
        "driving": 2.0353375
      },
      "physicalGrossDelta": 6.746267375,
      "delta": 32.366892515625,
      "terminal": 344.24361451703203,
      "investment": 969.8204225352113,
      "incrementalInvestment": 58.830633802816905,
      "xaiIncrementalInvestment": 33,
      "chinaIncrementalInvestment": 25.8306338028169,
      "grossProfit": 170.57807163585977,
      "grossCoverage": 0.1758862441666788,
      "coverage": 0.3549560377550552,
      "internalEfficiency": 83.4972
    },
    {
      "year": 2027,
      "oldXaiProxy": 48.443172160726,
      "companyDelta": 0,
      "scienceDelta": 32.72058975,
      "chipsDelta": 1.6900848272000002,
      "personalDelta": 3.5090212499999995,
      "physicalDelta": 35.2938088,
      "physicalComponents": {
        "robotHardware": 15.93424,
        "drivingHardware": 8.55,
        "raas": 4.41772,
        "software": 1.6423488000000002,
        "driving": 4.749499999999999
      },
      "physicalGrossDelta": 13.62671628,
      "delta": 73.2135046272,
      "terminal": 832.219005402487,
      "investment": 1923.1015504599804,
      "incrementalInvestment": 401.57490065711306,
      "xaiIncrementalInvestment": 388.0454622714192,
      "chinaIncrementalInvestment": 13.529438385693851,
      "grossProfit": 444.17981547086106,
      "grossCoverage": 0.23097054618078755,
      "coverage": 0.4327483409305303,
      "internalEfficiency": 142.10703468
    },
    {
      "year": 2028,
      "oldXaiProxy": 58.94761223017116,
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