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| Title: | AI晶片設計產業之動態競爭分析 —— 以Nvidia和AMD為例
An Analysis of Competitive Dynamics in the AI Chip Design Industry: Case Studies of Nvidia and AMD |
| Authors: | 姜蘊玲
Chiang, Yun-Ling |
| Contributors: | 楊宗翰
Yang, Tsung-Han
姜蘊玲
Chiang, Yun-Ling |
| Keywords: | AI晶片產業
GPU
Nvidia
AMD
動態競爭
AMC分析
外部環境
AI Chip Industry
GPU
Nvidia
AMD
Competitive Dynamics
AMC Model
External Environment |
| Date: | 2025 |
| Issue Date: | 2025-09-01 16:05:30 (UTC+8) |
| Abstract: | 隨著人工智慧AI(Artificial Intelligence)與高效能運算(High-Performance Computing)應用的崛起，AI晶片產業已成為全球半導體平台競爭的核心。自2000年代以來，GPU(Graphics Processing Unit)從圖形處理器逐步轉型為AI運算的基礎設施，推動AI模型規模與算力成長，帶動產業進入新競爭時代。Nvidia憑藉「軟硬體協同」加「生態鎖定」的競爭策略，使Nvidia在AI訓練市場市占率長期維持在80%以上，成為產業技術標準與生態規則的制定者。 AMD(Advanced Micro Devices, Inc.)則推動「開放」加「異質」策略使AMD在推 論市場、邊緣運算與部分資料中心場景取得突破，市占率逐步提升，成為AI產業格局中具威脅性的挑戰者。
本研究採用動態競爭理論之市場共同性與資源相似性指標與AMC（察覺-Awareness、動機-Motivation、能力-Capability）分析架構，針對Nvidia與AMD於AI晶片產業的競爭行動與回應進行個案剖析。本研究主要結論如下：
結論一：AI晶片設計產業中，具有市場領先優勢的先進廠商相較於挑戰者，其在產品佈局上為更完整，技術迭代上具有較深遠且連貫的升級，且投入更多資源在高附加價值的高階產品市場，挑戰者多僅以片段式技術升級與回應，並投注資源在中低階產品市場。
結論二：AI晶片設計產業中，挑戰者需善用生態系統、供應鏈協同或技術路線調整，並結合策略模仿與差異化，並針對產業技術轉換或外部環境變動的關鍵時機，尋求切入與突破的機會，才能有效降低進入障礙，提升市場地位。
結論三：AI晶片設計產業中，具有市場及技術優勢的領導者廠商可透過態壁壘強化、技術迭代加速與供應鏈韌性反制挑戰者發起的攻擊，提升競爭障礙，維持領導者地位。
本研究理論貢獻在於驗證動態競爭理論與AMC模型於AI晶片產業的適用性。未來可進一步探討AI晶片產業地緣政治、產業政策與新興應用之競爭影響。
Driven by the growth of Artificial Intelligence (AI) and High-Performance Computing (HPC), AI chips have become central to global semiconductor competition. Since the 2000s, GPUs have transitioned from graphics accelerators to essential AI computing infrastructure, enabling larger AI models and greater computational power. Nvidia, through a “hardware-software co-optimization” and “ecosystem lock-in” strategy, has sustained over 80% market share in AI training and set prevailing industry standards. In contrast, Advanced Micro Devices (AMD) leverages an “open” and “heterogeneous” approach to achieve gains in inference, edge computing, and select data center markets, positioning itself as a significant competitor in the AI chip sector.
This study adopts the dynamic competition theory’s indicators of market commonality and resource similarity, along with the AMC (Awareness–Motivation–Capability) analysis framework, to conduct a case analysis of the dynamic competitive actions and responses between Nvidia and AMD within the AI chip industry. The fianl conclusions of this study are as follows:
1. In the AI chip design industry, advanced firms with market leadership have more comprehensive product portfolios, deeper and more consistent technical iterations, and invest more resources in the high value-added, high-end product market. Challengers, on the other hand, mostly respond with fragmented technological upgrades and allocate resources to the mid- and low-end product markets.
2. In the AI chip design industry, challengers must fully leverage ecosystems, supply chain collaboration, or adjust their technology paths. By combining strategic imitation and differentiation, and seizing critical opportunities stemming from technological shifts or changes in the external environment, challengers can effectively lower entry barriers and enhance their market positions.
3. In the AI chip design industry, leading firms with market and technological advantages can fortify entry barriers, accelerate technical iteration, and reinforce supply chain resilience to counteract challengers’ initiatives, thereby raising competitors’ hurdles and maintaining their leadership positions.
The theoretical contribution of this study lies in validating the applicability of dynamic competition theory and the AMC model to the AI chip industry. Future research may further explore the impact of geopolitics, industrial policy, and emerging applications on competition within the AI chip sector. |
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| Description: | 碩士
國立政治大學
科技管理與智慧財產研究所
111364116 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111364116 |
| Data Type: | thesis |
| Appears in Collections: | [科技管理與智慧財產研究所] 學位論文
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