Google TPU vs Nvidia Ecosystem Infographic
Creates a Chinese futuristic industry-chain infographic comparing the Google TPU supply ecosystem with the Nvidia GPU ecosystem for investment or technology analysis.

Prompt
{"type":"中國科技產業鏈資訊圖表海報","theme":"未來TPU產業鏈對比,谷歌生態系統對抗輝達生態系統","canvas":"16:9寬螢幕,深海軍藍未來主義資料中心背景,發光的藍色電路線,高對比度,精緻企業科技展示風格","headline":"{argument name=\"headline text\" default=\"圍繞 TPU 的未來產業鏈:谷歌生態 vs 輝達生態\"}","subheadline":"{argument name=\"subheadline text\" default=\"谷歌自研 TPU + 博通/聯發科 + 台積電 + 中際旭創,打造超越輝達的技術未來\"}","top_row":{"description":"五張圓角卡片從左到右連接,由白色箭頭連接,代表谷歌TPU供應鏈。","count":5,"cards":[{"position":"最左","title":"Google(谷歌)","subtitle":"生態核心/需求方","visual":"Google標誌,藍色圖標,白色卡片帶藍色發光","bullets":["自研晶片架構:TPU","專為AI訓練/推論優化","高效能低功耗大規模叢集","AI雲端&模型驅動","Gemini / Search / YouTube / Cloud","算力需求爆發的核心驅動力"]},{"position":"左中","title":"BROADCOM","subtitle":"高端定制晶片設計","visual":"Broadcom標誌和黑色ASIC晶片渲染","bullets":["負責 TPU 核心 ASIC 設計(訓練晶片為主)","高效能計算架構","高速 SerDes / 網路晶片","先進封裝設計能力"]},{"position":"中央","title":"MEDIATEK 聯發科","subtitle":"晶片設計(協同+補充)","visual":"MediaTek標誌和小型黑色晶片渲染","bullets":["負責 TPU I/O、外圍、推論晶片(成本優化 + 多樣化)","I/O 晶片 / 介面","推論晶片 / 邊緣AI","成本優化專家"]},{"position":"右中","title":"tsmc 台積電","subtitle":"全球最先進晶片製造","visual":"TSMC標誌在橙色矽晶圓上","bullets":["製造所有 TPU 晶片(3nm / 2nm 領先)","全球最先進製程","最強產能 & 良率","AI時代的“水電煤”"]},{"position":"最右","title":"中際旭創","subtitle":"高速光模組供應","visual":"藍色光收發模組","bullets":["提供 800G / 1.6T 高速光模組","連接 TPU 叢集","光通信龍頭","AI算力的“高速公路”","數據傳輸的核心保障"]}]},"centerpiece":{"title":"谷歌 TPU 叢集(訓練 & 推論)","visual":"大型發光TPU晶片在中央前景,兩側各有一排黑色伺服器機架,藍色霓虹平台,從頂部供應商卡片的箭頭匯聚向TPU叢集","labels":["TPU"]},"side_boxes":{"count":2,"boxes":[{"position":"中左","title":"效益筆記","style":"藍色半透明圓角矩形,帶有火箭、葉子和硬幣圖標","items":["更高效能:專為AI優化,效率更高","更低功耗:TPU 架構天然節能","更低成本:自研+協同設計,成本可控"]},{"position":"中右","title":"核心優勢","style":"藍色半透明圓角矩形,帶有獎盃圖標和綠色勾選標記","items":["自研架構,擺脫對手技術限制","多方協同,成本更低,迭代更快","完整生態,雲端-晶片-網路-光模組閉環","規模效應,長期超越輝達生態"]}]},"bottom_row":{"description":"對標輝達生態系統的比較條帶,由五張綠色卡片從左到右連接,加一張紅色劣勢卡片。","comparison_label":"對標:輝達生態系統","count":6,"cards":[{"position":"最左","title":"輝達(NVIDIA)","subtitle":"GPU 架構設計","visual":"NVIDIA標誌和GPU卡","notes":["通用GPU","CUDA生態系統"]},{"position":"左中","title":"台積電(TSMC)","subtitle":"晶片製造","visual":"矽晶圓","notes":["同樣依賴台積電"]},{"position":"中央左","title":"台積電封裝 / 代工夥伴","subtitle":"封裝","visual":"先進封裝基板與晶片","notes":["封裝產能受限"]},{"position":"中央右","title":"光模組供應商(多家)","subtitle":"光通信連接","visual":"光模組線纜","notes":["需求旺盛","供不應求"]},{"position":"右中","title":"客戶/雲端廠","subtitle":"","visual":"Microsoft, Meta 和 AWS 標誌","notes":["依賴輝達GPU","成本高,供應緊張"]},{"position":"最右","title":"Nvidia 生態系統劣勢","style":"紅色輪廓卡片,帶有紅色X圖標","items":["通用架構,效率不如專用","功耗高,成本高","供應鏈單一,受限多","生態封閉,客戶依賴強"]}]},"footer_banner":"{argument name=\"footer slogan\" default=\"未來格局:谷歌 TPU 生態 = 更高效 + 更低成本 + 更可控 → 有望超越輝達,成為AI時代新王者!\"}","style_details":"使用清晰的中文排版,粗體白色標題,TPU用橙色,谷歌生態系統文字用藍色,輝達生態系統文字用綠色,圓角光澤卡片,小型說明圖標,真實3D晶片渲染,發光箭頭,深藍色賽博金融美學,簡潔資訊圖表層次,清晰文字,無人物。"}
機器翻譯 — 實際產出作品的是原文 prompt。
原文 Prompt
{"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":"{argument name=\"headline text\" default=\"围绕 TPU 的未来产业链:谷歌生态 vs 英伟达生态\"}","subheadline":"{argument name=\"subheadline text\" default=\"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":"{argument name=\"footer slogan\" default=\"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":"Use crisp Chinese typography, bold white title with TPU in orange, Google ecosystem text in blue and Nvidia ecosystem text in green, rounded glossy cards, small explanatory icons, realistic 3D chip renders, glowing arrows, dark blue cyber-finance aesthetic, clean infographic hierarchy, legible text, no people."}