VC Talks: Shao-Yu Jheng (Harvard) | Why Reindustrialization Won't Work Without Global Supply Networks

As reshoring and industrial policy return to the center of U.S. economic strategy, supply chains are increasingly framed as matters of national security and sovereignty. But history tells a more complicated story. In this episode of VC Talks, Uly revisits Left for Dead, a 1997 study on the revival of U.S. electronics, to question whether bringing manufacturing back home was ever the true driver of America’s industrial recovery.

Joined by Shao-Yu Jheng, a postdoctoral researcher in Economics at Harvard University, the conversation reframes the 1980s–90s comeback as a story of network leadership rather than national production. The episode examines why the Japanese manufacturing model ran into structural limits, how Taiwan and overseas Chinese (OC) production networks enabled coordination at scale, and why control over global supply networks—rather than factory location alone—proved decisive. Looking ahead, the discussion challenges today’s reshoring debate by asking what industrial policy can realistically change, and where its influence fundamentally ends.

在美國近年大力推動再工業化與製造回流的政策背景下，供應鏈被重新視為國家競爭力的核心資產。然而，歷史是否真的支持「把工廠搬回國內」就能重建產業實力？本集《VC Talks》回到一篇 1997 年探討美國電子產業復甦的研究〈Left for Dead〉，試圖從產業史的角度，重新檢視當前對 reshoring 的普遍想像。

主持人 Uly 與哈佛大學經濟學博士後研究員鄭紹鈺深入對談，指出美國在 1980 至 1990 年代的產業反彈，並非來自製造回流，而是成功主導橫跨多國的生產網絡。節目聚焦日本製造模式的結構性限制，以及臺灣與海外華人（OC）產業網絡如何在關鍵時刻提供彈性、效率與協調能力，成為美國科技體系得以延續競爭優勢的隱形支柱。本集不只回顧歷史，也直指一個當代問題：在高度全球化的供應鏈體系中，真正的產業力量，究竟掌握在國家邊界，還是網絡控制之中？

Robotics and AI are becoming core foundational capabilities of the physical economy. As AI extends from cloud-based models into hospitals, logistics centers, and a wide range of service environments, robots increasingly carry functions of perception, reasoning, and decision-making, directly translating into measurable gains in productivity, system reliability, and operational safety. Together, they are emerging as critical infrastructure supporting the operation of modern society.

Taiwan has established “Robotics + AI” as a key direction in its future industrial布局, responding to the long-term challenge of a highly concentrated industrial structure. While semiconductors remain a central pillar, their capital-intensive nature and limited spillover effects mean that the next phase of growth must come from a new industrial curve. The National Development Council has therefore been tasked with identifying scalable, repeatable, and extensible industry models—channeling Taiwan’s deep strengths in hardware, engineering, and systems integration into professional, service-oriented robotics, with priority deployment in healthcare, long-term care, logistics, and facility management where demand is clear.

Along this trajectory, the government’s role is evolving into that of an industry accelerator. By integrating R&D outputs and supporting the formation of new robotics companies, it is laying the groundwork for private capital and startups to enter, scale, and participate sustainably. This episode approaches the topic through the lens of industrial structure and policy logic, explaining why Taiwan has positioned Robotics + AI at the core of its next industrial phase, and how this strategy may shape the country’s economic future.

機器人與 AI 正成為實體經濟運作的核心底層能力。隨著 AI 從雲端模型延伸至醫院、物流中心與各類服務場域，機器人逐步承載感知、判斷與決策功能，並直接轉化為可量化的生產力、系統穩定度與營運安全，成為支撐現代社會運作的重要基礎設施。

臺灣已將「機器人＋AI」確立為未來產業布局的關鍵方向，回應產業結構高度集中的長期挑戰。半導體仍是核心支柱，但其資本密集與產業外溢有限，使得下一階段成長動能必須來自新的產業曲線。國發會因此被賦予尋找可延展、可複製、可擴散產業模式的任務，將臺灣深厚的硬體、工程與系統整合能力，導入專業用、服務型機器人領域，並優先落地於醫療、長照、物流與場域管理等需求明確的應用場景。

在這個方向上，政府的角色將成為產業成形的推進器。透過整合研發成果整合、成立新的機器人企業，將可為民間資本與新創團隊鋪設可進場、可放大的基礎。本集從產業結構與政策邏輯切入，解析臺灣以機器人與 AI 作為下一階段產業核心的理由，以及這項布局對臺灣經濟可能帶來的深層影響。

In this episode, Uly examines five defining technology signals emerging from Taiwan in 2025—and explains why they matter far beyond local headlines. Rather than viewing Taiwan solely as a semiconductor manufacturing center, this conversation reframes it as a critical capability hub shaping how artificial intelligence systems scale, deploy, and sustain over the next decade.

The discussion covers TSMC’s USD 100 billion expansion in the United States, NVIDIA’s decision to establish its major R&D headquarters in Taipei, and AMD’s continued expansion of its R&D footprint in Taiwan. Uly also breaks down the strategic implications of Taiwan’s AI Basic Law, as well as the accelerating commercialization of silicon photonics and co-packaged optics (CPO) by leading Taiwanese technology companies.

Together, these developments point to a deeper shift: AI’s future growth is increasingly constrained not by models alone, but by infrastructure, hardware integration, regulation, and long-term system design. This episode offers investors, founders, and technology leaders a clearer framework for understanding why Taiwan plays a central role in the global AI roadmap—and why the AI era cannot scale without it.

本集深入解析 2025 年來自臺灣的五項關鍵科技訊號，說明這些發展為何不只是區域新聞，而是正在影響全球 AI 擴展路徑的重要因素。本集重新定位臺灣的角色，從單一的半導體製造重鎮，轉向支撐 AI 長期發展的核心能力基地。

內容涵蓋台積電在美國規模達 1,000 億美元的投資布局、NVIDIA 將重要研發總部設於台北、AMD 持續擴大在臺灣的研發投入，同時也討論《AI 基本法》對產業與技術治理的影響，以及臺灣大型科技公司加速推動矽光子與 CPO 商業化的進展。

這些訊號共同指向一個更深層的轉變：AI 的成長瓶頸，已不再只是模型能力，而是來自硬體整合、基礎設施、制度設計與長期系統規劃。本集提供投資人、創辦人與產業決策者一個清楚視角，理解為何臺灣在全球 AI 發展中占據關鍵位置，以及 AI 時代為何無法在沒有臺灣的情況下持續擴展。



📍 About Host: Uly Su
General Partner, Addins Venture
#CrossBorderMentor #StartupExpansion #TaiwanToSiliconValley
🌏 A cross-border mentor who supports startups in entering global markets, with deep experience in fundraising, talent strategy, and international operations across the U.S. and Taiwan.
🔗 LinkedIn: https://www.linkedin.com/in/ulysu/

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