อินโฟกราฟิกระบบนิเวศ Google TPU เทียบกับ Nvidia

{
  "type": "Chinese technology industry-chain infographic poster",
  "theme": "future TPU industry chain comparison, Google ecosystem versus Nvidia ecosystem",
  "canvas": "16:9 widescreen, dark navy futuristic data-center background, glowing blue circuit lines, high contrast, polished corporate tech presentation style",
  "headline": "[围绕 TPU 的未来产业链：谷歌生态 vs 英伟达生态]",
  "subheadline": "[谷歌自研 TPU + 博通/联发科 + 台积电 + 中际旭创，打造超越英伟达的技术未来]",
  "top_row": {
    "description": "Five rounded cards connected left-to-right with white arrows, representing the Google TPU supply chain.",
    "count": 5,
    "cards": [
      {
        "position": "far left",
        "title": "Google（谷歌）",
        "subtitle": "生态核心/需求方",
        "visual": "Google logo, blue icons, white card with blue glow",
        "bullets": [
          "自研芯片架构：TPU",
          "专为AI训练/推理优化",
          "高性能 低功耗 大规模集群",
          "AI 云 & 模型驱动",
          "Gemini / Search / YouTube / Cloud",
          "算力需求爆发的核心驱动力"
        ]
      },
      {
        "position": "left center",
        "title": "BROADCOM",
        "subtitle": "高端定制芯片设计",
        "visual": "Broadcom logo and black ASIC chip render",
        "bullets": [
          "负责 TPU 核心 ASIC 设计（训练芯片为主）",
          "高性能计算架构",
          "高速 SerDes / 网络芯片",
          "先进封装设计能力"
        ]
      },
      {
        "position": "center",
        "title": "MEDIATEK 联发科",
        "subtitle": "芯片设计（协同+补充）",
        "visual": "MediaTek logo and small black chip render",
        "bullets": [
          "负责 TPU I/O、外围、推理芯片（成本优化 + 多样化）",
          "I/O 芯片 / 接口",
          "推理芯片 / 边缘AI",
          "成本优化专家"
        ]
      },
      {
        "position": "right center",
        "title": "tsmc 台积电",
        "subtitle": "全球最先进芯片制造",
        "visual": "TSMC logo over orange silicon wafer",
        "bullets": [
          "制造所有 TPU 芯片（3nm / 2nm 领先）",
          "全球最先进制程",
          "最强产能 & 良率",
          "AI时代的“水电煤”"
        ]
      },
      {
        "position": "far right",
        "title": "中际旭创",
        "subtitle": "高速光模块供应",
        "visual": "blue optical transceiver module",
        "bullets": [
          "提供 800G / 1.6T 高速光模块",
          "连接 TPU 集群",
          "光通信龙头",
          "AI算力的“高速公路”",
          "数据传输的核心保障"
        ]
      }
    ]
  },
  "centerpiece": {
    "title": "谷歌 TPU 集群（训练 & 推理）",
    "visual": "large glowing TPU chip in the middle foreground, flanked by two rows of black server racks, blue neon platform, arrows from the top-row supplier cards converging toward the TPU cluster",
    "labels": [
      "TPU"
    ]
  },
  "side_boxes": {
    "count": 2,
    "boxes": [
      {
        "position": "middle left",
        "title": "benefit notes",
        "style": "blue translucent rounded rectangle with rocket, leaf and coin icons",
        "items": [
          "更高性能：专为AI优化，效率更高",
          "更低功耗：TPU 架构天然节能",
          "更低成本：自研+协同设计，成本可控"
        ]
      },
      {
        "position": "middle right",
        "title": "核心优势",
        "style": "blue translucent rounded rectangle with trophy icon and green check marks",
        "items": [
          "自研架构，摆脱对手技术限制",
          "多方协同，成本更低，迭代更快",
          "完整生态，云-芯片-网络-光模块闭环",
          "规模效应，长期超越英伟达生态"
        ]
      }
    ]
  },
  "bottom_row": {
    "description": "Comparison strip labeled against Nvidia ecosystem, with five green cards connected left-to-right by arrows, plus one red disadvantage card.",
    "comparison_label": "对标：英伟达生态",
    "count": 6,
    "cards": [
      {
        "position": "far left",
        "title": "英伟达（NVIDIA）",
        "subtitle": "GPU 架构设计",
        "visual": "NVIDIA logo and GPU card",
        "notes": [
          "通用GPU",
          "CUDA生态"
        ]
      },
      {
        "position": "left center",
        "title": "台积电（TSMC）",
        "subtitle": "芯片制造",
        "visual": "silicon wafer",
        "notes": [
          "同样依赖台积电"
        ]
      },
      {
        "position": "center left",
        "title": "台积电封装 / 代工伙伴",
        "subtitle": "封装",
        "visual": "advanced package substrate with chips",
        "notes": [
          "封装产能受限"
        ]
      },
      {
        "position": "center right",
        "title": "光模块供应商（多家）",
        "subtitle": "光通信连接",
        "visual": "optical module cable",
        "notes": [
          "需求旺盛",
          "供不应求"
        ]
      },
      {
        "position": "right center",
        "title": "客户/云厂",
        "subtitle": "",
        "visual": "Microsoft, Meta and AWS logos",
        "notes": [
          "依赖英伟达GPU",
          "成本高，供应紧张"
        ]
      },
      {
        "position": "far right",
        "title": "Nvidia ecosystem disadvantages",
        "style": "red outlined card with red X icons",
        "items": [
          "通用架构，效率不如专用",
          "功耗高，成本高",
          "供应链单一，受限多",
          "生态封闭，客户依赖强"
        ]
      }
    ]
  },
  "footer_banner": "[未来格局：谷歌 TPU 生态 = 更高效 + 更低成本 + 更可控 → 有望超越英伟达，成为AI时代新王者！]",
  "style_details": "Crisp Chinese typography, bold white title with TPU in orange, Google ecosystem text in blue and Nvidia ecosystem text in green, rounded glossy cards, 3D chip renders, glowing connecting lines, dark blue cyber-tech aesthetic, legible text, no people."
}