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title: 'AI逐字稿:蘇姿丰台大演講'

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AI逐字稿:蘇姿丰台大演講
https://www.youtube.com/live/wYcJDEsawGM?si=_aC_5ZNyaQ_Ad0s4

AI逐字稿:蘇姿丰台大演講
請和我一起歡迎今天的東道主——國立臺灣大學校長陳文章教授，上台為我們介紹今天的演講嘉宾。

Please join me in welcoming the hosts today. Professor Chen Wen Zhang, the president of National Taiwan University, as we take the stage to give us an introduction about our speaker today.

各位老師、同學，早上好！很榮幸能在此介紹我們今天的講者，這是我的榮幸與責任。今天我們有幸邀請到一位傑出的學者與行業領袖，來為我們進行APU（Advanced Processing Unit）榮譽講座。

Good morning, faculty and students. It’s my great pleasure and honor to welcome such a distinguished scholar and leader to give the APU honor lectures today.

我們的講座旨在邀請具有全球影響力的領袖與學者，例如諾貝爾獎得主或業界先驅。國立臺灣大學作為一所享有盛譽的大學，長期致力於連結學術與產業。去年12月，我們曾邀請台積電（TSMC）創辦人張忠謀先生蒞臨演講，相信大家記憶猶新。

The lecture series aims to invite globally influential leaders and scholars, such as Nobel laureates or industry pioneers. As a prestigious university, National Taiwan University has long been committed to bridging academia and industry. As you may recall, we invited TSMC founder Morris Chang to give a lecture last December.

首先，讓我介紹今天的講者及其卓越的背景與成就。她畢業於麻省理工學院（MIT），獲得學士、碩士以及博士學位。隨後，她在德州儀器（Texas Instruments）、IBM、飛思卡爾半導體（Freescale Semiconductors）等公司擔任工程師與管理職位。

First of all, let me introduce our speaker, her background, and remarkable achievements. She received her bachelor’s, master’s, and PhD degrees from MIT. She then worked at Texas Instruments, IBM, Freescale Semiconductors, and other companies as an engineer or in managerial positions.

在這些公司任職期間，她帶領團隊開發了多項先進技術，例如絕緣體上矽（Silicon on Insulator, SOI）技術及其他關鍵技術，幫助這些企業成為全球半導體行業的領跑者。

During her tenure, she led teams to develop advanced technologies, such as Silicon on Insulator (SOI) and other key technologies, enabling these companies to become frontrunners in the global semiconductor industry.

目前，她擔任公司總裁、首席執行官（CEO）以及董事會主席，多年來被公認為業界的領袖人物。她在追求卓越的過程中獲得了無數榮譽，包括被《時代雜誌》（TIME）評選為年度最佳首席執行官，以及入選人工智能（AI）領域最具影響力的百大人物。

Today, she serves as president, CEO, and chair of the board, and has been recognized as an industry leader for many years. Her remarkable achievements have earned her numerous honors, including TIME’s CEO of the Year and inclusion among the hundred most influential people in AI.

除此之外，她還獲得了多項商業領袖獎項，並在經濟發展委員會中擔任重要職位。她是首位榮獲IEEE（國際電機電子學會）羅伯特·諾伊斯獎章（Robert Noyce Medal）的女性，並當選為美國國家工程院（National Academy of Engineering）院士。她也曾擔任美國總統的科學技術顧問。

In addition, she has received multiple awards for business leadership and holds a key position in the Committee on Economic Development. She is the first woman to receive the IEEE Robert Noyce Medal and was elected to the National Academy of Engineering. She also served as a science and technology adviser to the President of the United States.

坦白說，我們的APU榮譽講座至今已舉辦了12場，而她是首位女性講者。當我審閱她的履歷時，發現她的成就中有太多「第一」與「最具影響力」的紀錄。她的創新思維與領導力令人敬佩，今天我們有幸聆聽她分享AMD（Advanced Micro Devices）如何轉型成為AI時代的領軍者。

Frankly, we have held 12 APU honor lectures so far, and she is the first female speaker. When I reviewed her CV, I found too many “firsts” and “most influential” records. Her innovative thinking and leadership are inspiring, and we have the privilege today to hear her speak on AMD’s transformation into a leader in the AI era.

我相信，在接下來的一小時中，她將為我們深入剖析如何將電機工程（Electrical Engineering）、計算機科學（Computer Science）與人工智能（AI）相結合，推動技術與產業的革新，讓世界變得更美好。我們期待這場精彩的講座！

I believe that in the next hour, she will share insights on how to integrate electrical engineering, computer science, and AI to drive technological and industrial innovation, making the world a better place. We look forward to an inspiring lecture!

最後，我想特別感謝講座的贊助單位、親切的組織團隊，以及吳瑞教授的協助，促成了這場講座。我也要感謝Lisa Su博士蒞臨，與我們分享她在AI與AMD轉型方面的真知灼見。

Finally, I would like to express my gratitude to our sponsors, the dedicated organizing team, and Professor Rui-Wu for their efforts in making this lecture possible. I also thank Dr. Lisa Su for joining us to share her insights on AI and AMD’s transformation.

今天的講座吸引了極大的關注。當我們宣布Lisa Su博士的演講時，500個講座席位在一分鐘內就全數註冊一空！由於報名踴躍，我們在三樓另外開設了一間視訊轉播室，讓更多人能參與這場盛會。

Today’s lecture has generated tremendous interest. When we announced Dr. Lisa Su’s speech, the 500 seats in this lecture hall were fully registered within one minute! Due to the overwhelming response, we have set up an additional video streaming room on the third floor to accommodate more attendees.

為了讓講座更具互動性，我們將採用類似爐邊對談（Fireside Chat）的形式，讓Lisa Su博士能回答部分學生的提問。講座中場休息時，我們將挑選大約十個問題請她回答。其餘問題則可能在講座後的交流環節中回應。

To make the lecture more interactive, we will adopt a fireside chat format, allowing Dr. Lisa Su to answer some student questions. During the break, we will select about ten questions for her to address. Additional questions may be answered during the post-lecture interaction session.

Lisa Su博士非常親切且平易近人。講座結束後，她願意與學生交流、回答問題，甚至合影留念。希望大家珍惜這次難得的機會，與她進行深入的對話。

Dr. Lisa Su is very approachable and easygoing. After the lecture, she is open to engaging with students, answering questions, and taking photos. I hope everyone seizes this rare opportunity to have meaningful conversations with her.

再次感謝大家參與今天的講座！請以熱烈的掌聲歡迎Lisa Su博士上台演講！

Thank you all again for joining us today! Please give a warm round of applause to welcome Dr. Lisa Su to the stage!

大家早上好！希望今天能與各位共同度過一場充滿啟發的講座！

How’s everyone this morning? I hope we can share an inspiring lecture together today!

首先，陳校長，非常感謝您的邀請。您多次邀請我來國立臺灣大學（NTU），每次我都感到非常榮幸。然而，每次來臺灣時，行程總是非常繁忙，尤其是在複雜的時間安排下更是如此。這次能來訪是一個絕佳的時機。感謝您熱情的邀請與接待，讓我倍感溫暖。能站在這裡與各位才華洋溢的學生見面，我感到非常高興，雖然你們的青春活力讓我覺得自己有點「老」了！希望我能分享一些故事與經驗，對你們的職業生涯有所啟發。接下來，我會先回答十個預設問題，之後再開放給現場學生提問，好吗？

First of all, President Chen, thank you so much for inviting me. You’ve invited me to NTU several times, and I’ve been honored each time. However, whenever I come to Taiwan, my schedule is often very busy, especially with complicated timing. This is a great opportunity for me to visit. Thank you for the warm invitation and hospitality, which I deeply appreciate. It’s truly my pleasure to be here to meet all of you talented students, though your energy makes me feel a bit old! Hopefully, I can share some stories and insights to inspire your careers. I’ll start by addressing the ten initial questions, and after that, we’ll open the floor to questions from the students. Okay?

第一個問題是關於AMD（Advanced Micro Devices）如何從一家專注於CPU（Central Processing Unit）的公司，轉型成為跨越CPU與GPU（Graphics Processing Unit）的強大技術領袖。推動這一轉型的關鍵階段或轉折點是什麼？在回答之前，我想先問問在場的學生：有多少人是電機工程（Electrical Engineering）或計算機科學（Computer Science）相關科系的？請舉手！

The first question is about how AMD evolved from a CPU-focused company into a powerhouse across CPUs and GPUs. What were the key phases or turning points that drove this transformation? Before I answer, I’d like to ask the students: How many of you are studying electrical engineering or computer science? Please raise your hands!

好的，看來人數不少！那麼，醫學相關科系的學生呢？似乎不多。讓我先分享一下我的背景：我在麻省理工學院（MIT）主修電機工程與計算機科學，獲得學士、碩士和博士學位，我的專業是半導體器件（Semiconductor Devices）。那時我還是個年輕學生，這就是我研究的領域。如今，我在半導體行業已有超過30年的經驗。你會發現，這個行業的技術進步非常迅速。我從2012年加入AMD，並於2014年成為首席執行官（CEO）。對任何公司來說，最重要的事情之一就是決定自己的定位與方向。

Great, quite a few of you! How about students in medical fields? Not too many. Let me share my background: I studied electrical engineering and computer science at MIT, earning my bachelor’s, master’s, and PhD degrees, with a specialty in semiconductor devices. When I was a young student, that’s what I focused on. Now, I’ve been in the semiconductor industry for over 30 years. You’ll find that technology moves incredibly fast in this field. I joined AMD in 2012 and became CEO in 2014. One of the most important things for any company is deciding its direction and identity.

那麼，AMD的定位是什麼？我們相信，AMD的專長在於高性能計算（High-Performance Computing, HPC）。高性能計算是我們生活核心的一部分。今天，AMD的技術每天影響著數十億人，無論是雲端數據中心（Cloud Data Centers）、網路邊緣（Edge of the Network）、個人電腦（PCs）、汽車（Automotive）還是工業應用（Industrial Applications），你幾乎都能接觸到AMD的技術。作為一家科技公司，制定長期的策略與路線圖至關重要。我們的策略聚焦於三個方面：首先是高性能計算；其次是建立卓越的合作夥伴關係，例如與台積電（TSMC）的緊密合作；第三，適應半導體行業的變革。你們可能聽說過摩爾定律（Moore’s Law）正在放緩，我們因此大力投資於三維晶片技術（Chiplet Technology），作為未來的關鍵領域。這些策略對AMD的轉型至關重要。今天，我很高興地說，全球十大超級計算機（Supercomputers）中，有五台採用了AMD的技術。這證明了高性能計算在未來的重要性。

So, what is AMD’s direction? We believe our specialty lies in high-performance computing (HPC). HPC is at the core of our lives. Today, AMD’s technology touches billions of people every day, whether in cloud data centers, at the edge of the network, in PCs, automotive, or industrial applications—you can likely encounter AMD’s technology. For a technology company, having a long-term strategy and roadmap is critical. Our strategy focuses on three areas: first, high-performance computing; second, building excellent partnerships, such as our close collaboration with TSMC; and third, adapting to changes in the semiconductor industry. Many of you have heard that Moore’s Law is slowing down, so we made a significant bet on chiplet technology as a key area for the future. These strategies have been vital to AMD’s transformation. Today, I’m thrilled to say that five of the top ten supercomputers in the world are powered by AMD’s technology. This underscores the importance of high-performance computing moving forward.

第二個問題是：您認為當今晶片設計（Chip Design）中最令人興奮的前沿是什麼？我聽說許多學生認為晶片設計是最具吸引力的領域。我認為，這個行業總是在變動——有時硬件更引人注目，有時軟件更具吸引力。從我的角度來看，最令人興奮的部分在於整體設計（Holistic Design）。在設計人工智能（AI）相關技術時，硬件、軟件和系統必須一體化設計。你不能單獨設計每個部分，而是需要考慮整體系統應用（System Application），特別是演算法（Algorithms）與應用場景（Applications）。只有在這樣的框架下，你才能決定如何設計晶片。

The second question is: Where do you see the most exciting frontiers in chip design today? I’ve heard that many students still view chip design as the most exciting field. I’d say there’s always movement in this industry—sometimes hardware is more exciting, sometimes software takes the spotlight. From my perspective, the most exciting part is holistic design. When designing AI-related technologies, hardware, software, and systems must be integrated. You can’t design each piece separately; instead, you need to consider the overall system application, especially the algorithms and applications. Only within this framework can you decide how to design your chips.

接下來，我希望聽聽你們的問題！請提出有趣且有深度的問題，讓我們一起探索更多可能性！

Now, I’d love to hear your questions! Please ask interesting and thought-provoking questions so we can explore more possibilities together!

今年一月，業界發布了一項重要聲明，據我所知，這似乎對人工智能（AI）產業產生了一些影響。您對此有何看法？這項聲明如何影響AI產業？我想說的是，AI產業的特點之一就是幾乎每週都有新的技術與創新問世。DeepSeek（深尋）就是其中之一。當它在一月亮相時，確實讓人感到有些意外。仔細觀察他們的成果，你會發現這是一項相當聰明的技術，特別是通過整合多種創新，例如專家模型混合（Mixture of Expert Models）等方式。他們的核心貢獻在於找到了一種方法，讓AI技術更易於普及且成本更低。這意味著AI的應用場景與使用率將大幅提升。DeepSeek真正加速了AI的應用，這是一項技術上的突破，而非市場宣傳。

In January, an announcement was made that, as I recall, seemed to have some impact on the AI industry. What are your thoughts on this, and how does it affect AI? The one thing I can say about the AI industry is that almost every week, there’s a new technology or innovation emerging. DeepSeek is one of those. When it came out in January, it caught many by surprise. When you look at what they’ve done, it’s actually quite clever technology, integrating various innovations like Mixture of Expert Models and so forth. The key thing we saw with DeepSeek is that when you make AI more accessible and affordable, you significantly increase its usage and applications. DeepSeek has truly accelerated AI adoption, and that’s a technology statement, not a market statement.

我聽說美國計劃投資約5000億美元用於AI基礎設施（AI Infrastructure）。這樣的投資規模令人震驚，您對此有何看法？在我看來，AI的關鍵在於計算生態系統（Computing Ecosystem）並非「一體適用」。有些公司專注於超大規模的前沿模型（Frontier Models），他們投入數千億美元，力求以最快速度打造頂尖模型，這需要極高的資本門檻，只有少數玩家能參與。但這只是AI應用的一個面向。與此同時，我們也看到許多中型模型（Medium-Sized Models）與小型模型（Smaller Models）在不同場景中蓬勃發展，這些模型依賴不同的演算法（Algorithms）來實現目標。因此，我預期未來AI領域將持續吸引巨額投資，包括大規模的資金投入，同時也會有更多成本可控的投資，滿足多樣化的需求。

I’ve heard that the United States plans to invest around 500 billion dollars in AI infrastructure. That’s a staggering amount—what’s your take on this? From my perspective, the key point about AI is that there’s no one-size-fits-all solution for the computing ecosystem. Some focus on massive frontier models, investing hundreds of billions to build the best models as quickly as possible—a level of investment only a few can afford. But that’s just one application of AI. At the same time, we’re seeing many medium-sized and smaller models thriving in different scenarios, relying on varied algorithms to achieve their goals. My expectation is that AI will continue to attract significant investment, including massive capital commitments, alongside more affordable investments to meet diverse needs moving forward.

下一個問題是：AMD在AI策略（AI Strategy）上與其他競爭者有何不同？您認為開放生態系統（Open Ecosystem）與合作夥伴關係（Partnerships）在推動AI普及（AI Adoption）中扮演什麼角色？或者更直接一點，您如何看待AMD與其他競爭者，例如NVIDIA（英偉達），的競爭？

The next question is: How does AMD’s AI strategy differ from others in the space? What role do you see for the open ecosystem and partnerships in driving AI adoption? Or, more directly, how do you plan to compete with others, like NVIDIA?

這個問題真是令人興奮！我想聽聽您對AMD如何打造AI解決方案（AI Solutions）的看法。在我看來，關於人工智能（AI）最重要的一點是市場潛力巨大。我們預計未來三到四年，AI市場規模將達到5000億美元。在這樣的市場中，需要各種不同的計算技術。沒有一家公司能獨自提供所有解決方案。我認為，市場需要多種類型的計算技術，包括中央處理器（CPUs）、圖形處理器（GPUs）、特定應用積體電路（ASICs）以及現場可程式化邏輯閘陣列（FPGAs）。在這個框架下，AMD的AI策略有兩個核心：第一，提供全面的解決方案（Complete Solutions），涵蓋硬件（Hardware）、軟件（Software）與系統整合（Systems）；第二，建立開放的生態系統（Open Ecosystem）。開放生態系統能促進合作，讓不同參與者相互學習，這一點至關重要。例如，DeepSeek（深尋）採用開放模型（Open Model），因此吸引了許多人在其基礎上進行創新。總結來說，AI市場龐大，AMD的AI策略貫穿我們業務的每個層面，從大型數據中心（Data Centers）到個人電腦（PCs），我們相信AI將無處不在。這為所有參與者提供了廣闊的市場機會。

I think this question is very exciting! I’d love to hear your thoughts on how AMD is building AI solutions. In my opinion, the most important thing about AI is that the market is enormous. We expect the market to reach 500 billion dollars over the next three to four years. In a market like this, you need all kinds of computing technologies. No single company has all the solutions. My view is that the market requires a variety of computing technologies, including CPUs, GPUs, ASICs, and FPGAs. Within this framework, AMD’s AI strategy has two core pillars: first, delivering complete solutions that include hardware, software, and systems; second, fostering an open ecosystem. An open ecosystem is critical because it encourages collaboration and allows participants to learn from one another. For example, DeepSeek’s open model enabled many to innovate on top of it. In summary, the AI market is vast, and AMD’s AI strategy permeates every aspect of our business, from the largest data centers to PCs. We believe AI will be ubiquitous, creating ample market opportunities for everyone.

關於引導AMD進行AI轉型（AI Transformation）的核心原則，我已經在前面有所提及，因此我想提出另一個問題：您對臺灣有什麼建議？

I’ve already addressed the core principles guiding AMD through its AI transformation, so I’d like to ask another question: What’s your advice for Taiwan?

您提到未來的人工智能（AI）技術競爭，臺灣在半導體製造（Semiconductor Manufacturing）、AI伺服器（AI Servers）等方面表現出色，但AI將改變許多產業。對此，您對臺灣有什麼建議？我們如何在全球競爭中維持現有優勢？我認為，臺灣的生態系統（Ecosystem）非常獨特。以台積電（TSMC）為核心，臺灣打造了無與倫比的製造能力，涵蓋原始設計製造（ODM）、原始設備製造（OEM）、製造生態系統（Manufacturing Ecosystem）以及設計生態系統（Design Ecosystem）。從AMD的角度來看，未來應在軟件與系統（Software and Systems）領域投入更多資源。我們在臺灣的團隊是AMD全球研發（R&D）的重要組成部分，對此我們感到非常驕傲。此外，當今世界的生態系統高度互聯。從美國的視角來看，我們高度依賴臺灣的製造生態系統，因此強化這個生態系統的韌性（Resilience）至關重要。

To compete in future AI technology, Taiwan excels in semiconductor manufacturing, AI servers, and more. But AI will transform many things. What’s your advice for Taiwan to compete globally and maintain its current advantage? I think Taiwan’s ecosystem is very special. Starting with TSMC, it has built an incredible manufacturing capability, encompassing ODM, OEM, manufacturing, and design ecosystems. From AMD’s perspective, more investment in software and systems is needed. We’re very proud of our Taiwan team, a critical part of our global R&D. Additionally, today’s ecosystems are highly interconnected. From a U.S. perspective, we rely heavily on Taiwan’s manufacturing ecosystem, and building resilience into that ecosystem is crucial.

接下來，我想問一個關於您個人經歷的問題。家庭與教育（Family and Education）對您的早期生活和職業生涯影響深遠，能否分享一些相關經驗？此外，這是否與您帶領AMD成為世界領先公司的艱難時期有關？順便一提，您覺得陳校長是否應該從大學校長轉行做脫口秀主持人？或許這樣他能賺更多錢！回到正題，我很高興分享我的背景。我出生於海南，父母移民到美國，這對他們來說是一次巨大的轉變。到了美國後，父母一直強調教育的重要性，這對我影響深遠。我記得在麻省理工學院（MIT）求學時，我迫不及待想完成學業。拿到學士學位後，我曾想直接工作，但父母堅決反對，他們強烈建議我繼續攻讀博士學位（PhD）。當時，我對學校感到不耐煩，覺得學業「夠了」，相信在場有些同學也有類似感受。但事實證明，父母是對的。大學與研究所的經歷不僅讓我學到多方面的知識，還培養了我解決未來問題的信心。雖然當時我對父母的堅持有些不滿，但現在我認為他們完全正確。擔任AMD首席執行官（CEO）是我夢寐以求的工作，從半導體工程師（Semiconductor Engineer）到商務人士，再到行業領袖，這條路並不容易，尤其是在早期階段。我的父母與家人始終給予我無比的支持，這讓我感到非常幸運。

The next question is about your personal journey. Family and education were crucial to your early life and career—could you share more about that? Also, does this connect to the challenging period of leading AMD to become a world-leading company? By the way, do you think President Chen should go from university president to talk show host? He might make more money that way! Back to the topic, I’m happy to share my background. I was born in Hainan, and my parents immigrated to the United States—a significant move for them. Once in the U.S., my parents always emphasized the importance of education, which deeply shaped me. I remember being at MIT, eager to finish school. After my bachelor’s degree, I thought I should start working, but my parents said, “No, Lisa, you can’t do that.” They strongly urged me to pursue a PhD. At the time, I was impatient, thinking school was “enough.” Some of you might feel the same way. But the truth is, my parents were right. University and graduate school gave me the opportunity to learn diverse skills and build confidence to tackle future challenges. Though I wasn’t thrilled with my parents then, I now know they were absolutely right. Being CEO of AMD is my dream job, transitioning from a semiconductor engineer to a business leader and then an industry leader. It wasn’t easy, especially in the early years. My parents and family have always been incredibly supportive, and I’m very lucky for that.

我很好奇，您提到教育的重要性，但像比爾·蓋茨（Bill Gates）、史蒂夫·賈伯斯（Steve Jobs）或早期的業界領袖並未完成大學教育，卻成為領袖。如今，像您或黃仁勳（Jensen Huang）這樣的領袖都完成了學位。您對此有何看法？我認為，領袖有許多不同的類型，我們對各種領袖都懷有敬意。但我堅信，大學教育（University Education）非常有價值。在大學的這段時光是你最佳的學習機會，讓你探索自己的興趣，找到最適合的職業方向。這段經歷能幫助你為未來的職業生涯做好準備。

I’m curious about your take on education. Earlier industry leaders like Bill Gates or Steve Jobs didn’t finish university yet became leaders. Now, new leaders like you or Jensen Huang completed degrees. What’s your comment on this? There are many types of leaders, and we have great respect for all of them. But I truly believe university education is invaluable. These years at university are the best time to learn and discover what you enjoy most, helping you decide the next steps in your career.

或許我該反問您，您怎麼看呢？

Maybe I should ask you, what do you think?

我想談談教育的重要性。在臺灣，完成大學教育（University Education）幾乎是必須的，這與美國的情況有些不同。在臺灣的教育系統（Education System）與就業系統（Job System）中，學位是一道門檻。許多父母，特別是受中華文化影響的父母，會強烈要求孩子完成學位。我想問一個稍微私人的問題：您和黃仁勳（Jensen Huang）是親戚嗎？

I’d like to talk about the importance of education. In Taiwan, completing university education is almost a must, which might differ from the U.S. now. In Taiwan’s education and job systems, a degree is a prerequisite. Many parents, especially those influenced by Chinese culture, insist their children finish their degrees. I have another question, a bit personal: Are you and Jensen Huang relatives?

您是否與黃仁勳交換過經營人工智能公司（AI Company）的想法，或者你們是各自獨立運營？首先，我對黃仁勳有著極大的尊重。作為英偉達（NVIDIA）的創始人，他打造了一家卓越的公司。但我要說的是，我們各自經營獨立的公司。在半導體行業（Semiconductor Industry）中，我們通過美國的半導體行業協會（Semiconductor Industry Association）進行交流，所有半導體公司都在這個平台上分享一些想法。

Do you exchange ideas with Jensen Huang about running an AI company, or do you operate independently? First of all, I have tremendous respect for Jensen. As the founder of NVIDIA, he has built an amazing company. That said, we run independent companies. In the semiconductor industry, we connect through the Semiconductor Industry Association in the U.S., where all semiconductor companies come together to exchange some ideas.

接下來，我想問一個針對學生的問題。對於希望在技術領域（Technology Field）產生影響的學生，您會給予什麼建議，特別是在承擔風險（Taking Risks）、選擇方向（Choosing a Path）或培養韌性（Building Resilience）方面？根據我的經驗，我從一位導師那裡得到的最佳建議是：無論你做什麼，選擇最具挑戰性的問題（Hardest Problems）。他告訴我，要勇於直面問題。這是我能給學生最好的建議。世界上有許多有趣的事情可以做，選擇一個能讓你產生重大影響的項目、問題或公司，你將學到很多，並能貢獻更多。我可以肯定地說，我從犯下的最大錯誤中學到了最多。錯誤並不可怕，相反，它們是寶貴的學習機會，因為你能從中吸取教訓，讓自己在未來做得更好。

Next, I’d like to ask a question for students who want to make an impact in the technology field. What advice would you give about taking risks, choosing a path, or building resilience? In my experience, the best advice I received from a mentor was to pick the hardest problems, no matter what you do. He told me to run toward problems. That’s the best advice I can give students. There are so many interesting things to do in the world. By choosing a project, problem, or company where you can make a big impact, you’ll learn a lot and contribute significantly. I can say for sure that I learned the most from my biggest mistakes. Mistakes aren’t bad—they’re actually good because you can learn from those lessons and improve in the future.

這真是很棒的建議！我記得當我在《自然》（Nature）期刊提交第一篇論文時，被拒稿了。我仔細閱讀審稿意見後，發現自己沒有認真檢視實驗數據（Experimental Data）。於是我修改了論文，重新提交到另一本更優質的期刊，最終被接受。有時候，我們確實從錯誤中學習。現在，讓我們開放提問給學生，只有學生可以舉手，好嗎？

That’s great advice. I remember when I submitted my first paper to Nature, it was rejected. After reviewing the comments, I realized I hadn’t carefully examined the experimental data. So, I revised the manuscript and submitted it to a better journal, where it was accepted. Sometimes, we learn from mistakes. Now, let’s open the floor to questions from students. Only students can raise their hands, okay?

學生提問：早上好，Su博士與陳校長。我是吉成玲，來自政治學系（Department of Political Science）。2023年9月，哥倫比亞大學法學院（Columbia University Law School）出版了一本名為《數位帝國》（Digital Empires）的書，描述了網際網路世界的三種基本模式：歐盟的權利空間（Rights Space）、美國的市場空間（Market Space）以及中國的國家空間（State Space）。從2023年到2025年，我們看到人工智能（AI）領域的快速發展。我有兩個問題：第一，關於歐盟的權利空間模式，其監管措施眾多，您認為目前的《歐盟人工智能法案》（EU AI Act）會否阻礙歐洲的創新？第二，您如何評價當前美國的政治環境（Political Environment），特別是拜登（Biden）與川普（Trump）第二任期在AI政策（AI Policy）上的差異？謝謝！

Student: Good morning, Dr. Su and President Chen. My name is Ji Cheng-Ling, and I’m from the Department of Political Science. In September 2023, a book from Columbia University Law School, Digital Empires, described three basic models of the internet world: the rights space from the EU, the market space in the United States, and the state space from China. From 2023 to 2025, we’re seeing significant developments in AI. I have two questions. The first is regarding the EU’s rights space model, with its many regulations. Do you think the regulations currently published will hinder innovation in Europe? The second question is, what’s your evaluation of the United States’ political environment right now, especially the AI policy differences between the Biden and Trump administrations in Trump’s second term? Thank you!

回答：謝謝你的提問！政治學的問題確實不簡單，相比之下，技術問題可能更直接一些。我不會針對特定國家逐一評論，而是想分享我對人工智能（AI）的一些看法。AI是一項新興技術（Emerging Technology），過去幾年，我們所有人——包括國家、企業與個人——都在學習如何應對它。最初的共識是，如果沒有完善的護欄（Guardrails），AI可能帶來風險。然而，過多的監管可能會扼殺創新（Innovation）。以歐盟為例，《歐盟人工智能法案》（EU AI Act）於2024年夏天成為法律，採取風險為基礎的監管框架（Risk-Based Framework），對高風險AI系統（如面部辨識軟件）施加嚴格要求。一些美國科技公司，如亞馬遜（Amazon）、谷歌（Google）與Meta，認為這些規定過於嚴格，可能限制創新，尤其是在通用人工智能模型（General-Purpose AI, GPAI）的開發上。 我的觀點是，AI需要快速創新，但也需要適度監管以確保安全，關鍵在於找到平衡點。

在美國，政治環境對AI政策的影響顯著。拜登政府於2023年10月發布的行政命令（Executive Order 14110）強調安全、公平與風險管理，要求高風險AI系統的開發者在公開發布前提交安全測試結果。 然而，川普於2025年1月20日就職首日廢除了這項命令，改推《消除美國人工智能領導障礙》（Removing Barriers to American Leadership in Artificial Intelligence）行政命令，優先促進創新與市場競爭，減少聯邦監管。 這種轉向反映了川普政府希望通過放寬限制來加速美國在全球AI競賽中的領先地位，特別是在與中國的競爭中。

總的來說，我認為擁抱技術的國家將從AI中受益匪淺。全球各國正在制定自己的AI政策，這是一個充滿變化的時期——有時甚至每天都有新進展。監管與創新的平衡是核心挑戰，過嚴或過鬆都不利於長期發展。還有其他問題嗎？

Response: Thank you for your questions! Political science questions are not the easiest—technology is a bit simpler in comparison. I won’t talk about individual countries specifically but will share my thoughts on AI. AI is a new technology, and over the past few years, we’ve all been learning together—countries, companies, and individuals. Initially, there was concern that AI could be dangerous without proper guardrails. However, excessive regulation risks stifling innovation. For example, the EU’s AI Act, which became law in the summer of 2024, adopts a risk-based framework, imposing strict requirements on high-risk AI systems like facial recognition software. Some U.S. tech companies, such as Amazon, Google, and Meta, argue these rules are too stringent and may hinder innovation, particularly for general-purpose AI models. My view is that AI requires rapid innovation but also moderate regulation to ensure safety, and the key is finding a balance.

In the U.S., the political environment significantly shapes AI policy. The Biden administration’s 2023 Executive Order 14110 emphasized safety, equity, and risk management, requiring developers of high-risk AI systems to share safety test results before public release. However, on January 20, 2025, Trump revoked this order on his first day in office, issuing a new Executive Order, Removing Barriers to American Leadership in Artificial Intelligence, prioritizing innovation and market competition over federal oversight. This shift reflects the Trump administration’s aim to accelerate U.S. leadership in the global AI race, particularly against China.

Generally, countries that embrace technology will benefit greatly from AI. Nations worldwide are crafting their AI policies during this dynamic time—sometimes changes happen daily. Balancing regulation and innovation is the core challenge; too much or too little regulation can harm long-term progress. Any more questions?

學生提問：好的，請讓女性同學提問！這位同學，請。早上好，Su博士，感謝您的精彩演講。我的一位親戚提到，臺灣人在半導體（Semiconductors）與人工智能（AI）領域特別有成就。我有兩個問題：第一，非工程學院（School of Engineering）的學生如何參與這些領域？例如，我是語言與文學系（Department of Languages and Literature）的大一新生。第二，台裔美國人（Taiwanese Americans）是美國受教育程度最高、收入最高的族群之一，您認為這對臺灣未來的地位有何影響？謝謝！

Student: We need a female student to ask a question! Here’s the microphone. Good morning, Dr. Su, and thank you for your inspiring presentation. One of my relatives said Taiwanese people are most likely to excel in semiconductors and artificial intelligence. I have two questions. First, how can students not from the School of Engineering play a role in these fields? For example, I’m a freshman in the Department of Languages and Literature. Second, Taiwanese Americans are among the most highly educated and highest-earning ethnic groups in the U.S. How do you think this will affect Taiwan’s status in the future? Thank you!

回答：謝謝你的問題！關於第一個問題，我認為每個人都應該學習人工智能（AI），無論你來自哪個學系。AI的應用範圍非常廣泛，不限於工程領域。例如，你在語言與文學系（Department of Languages and Literature），AI可以應用於自然語言處理（Natural Language Processing, NLP）、文本分析（Text Analysis）或文學研究，幫助你探索語言模式或創作新的研究方法。目前，AI的發展仍處於早期階段，各領域都在探索其應用潛力。除了AI技術的開發，AI應用（AI Applications）也是一個重要的領域。我鼓勵所有學生，不論背景如何，都去了解AI如何融入自己的專業，這將為你開啟新的可能性。

關於第二個問題，台裔美國人（Taiwanese Americans）在美國的高教育水平與經濟成就確實令人矚目，這對臺灣的全球地位有積極影響。他們在科技、學術與商業界的成功，增強了臺灣的國際影響力與軟實力（Soft Power）。此外，這些人才往往成為連結臺灣與美國的橋樑，促進技術交流、投資與合作，進一步鞏固臺灣在全球供應鏈（Global Supply Chain），特別是半導體與AI領域的關鍵地位。這種跨國網絡將有助於提升臺灣的國際能見度與競爭力。你能再重複一下第二個問題的細節嗎？

Response: Thank you for your questions! For the first question, I believe everyone should learn about AI, regardless of their department. AI has broad applications beyond engineering. For example, as a student in the Department of Languages and Literature, you can use AI in natural language processing, text analysis, or literary studies to explore language patterns or develop new research methods. We’re still in the early stages of AI development, and every field is discovering its potential. Beyond AI development, the application of AI is a significant area. I encourage all students, no matter their background, to explore how AI can enhance their field—it will open new possibilities.

For the second question, the high educational attainment and economic success of Taiwanese Americans are remarkable and positively impact Taiwan’s global status. Their achievements in technology, academia, and business enhance Taiwan’s international influence and soft power. Moreover, these individuals often serve as bridges between Taiwan and the U.S., fostering technical exchanges, investments, and collaborations that strengthen Taiwan’s critical role in the global supply chain, especially in semiconductors and AI. This transnational network will boost Taiwan’s visibility and competitiveness. Could you repeat the details of your second question?


回答（續接前述問題）：關於台裔美國人（Taiwanese Americans）作為美國受教育程度最高、收入最高的族群之一，這對臺灣未來地位的影響，我不確定能否給出確切答案。但我要說的是，無論是台裔美國人還是臺灣人，他們都以極度勤奮（Hard-Working）與對專業領域的貢獻而聞名，這是我們引以為傲的特質。雖然有人說我更像美國人而非臺灣人，但我認為自己是台裔美國人（Taiwanese American）。這種跨文化的身份讓我能從多重視角看待問題。如果你有興趣，歡迎在演講後找我簽名！

Response: Regarding Taiwanese Americans being among the most highly educated and highest-earning ethnic groups in the U.S. and how this affects Taiwan’s future status, I’m not sure I can say definitively. But I will say that Taiwanese Americans and Taiwanese people in general are extremely hard-working and dedicated to contributing to their fields and professions. That’s something we can be very proud of. Though some say I’m more American than Taiwanese, I like to think of myself as Taiwanese American. This cross-cultural identity allows me to see issues from multiple perspectives. If you’re interested, come check out my signature outside after the talk!

補充：你提到我的中文簽名比英文簽名寫得好，這真是令人驚訝！因為我在三歲時就離開了臺灣，中文對我來說並不容易。能保留這份文化連結，我感到非常榮幸。還有其他問題嗎？

Addition: You mentioned that my Chinese signature is better than my English one, which is incredible! Since I left Taiwan at the age of three, Chinese hasn’t been easy for me. I’m honored to maintain this cultural connection. Any more questions?

學生提問：早上好，Lisa博士與陳校長。我知道AMD經歷過許多高潮與低谷，我想特別了解在低谷（Lows）時，您是如何保持自信（Confidence）的？謝謝！

Student: Good morning, Dr. Lisa and President Chen. As I understand, AMD has experienced many highs and lows, and I’d like to know, especially during the lows, how you maintained your confidence? Thank you!

回答：這是一個很棒的問題。對AMD來說，最困難的時期大概是2014年我剛成為首席執行官（CEO）時。當時，公司的產品路線圖（Product Roadmap）缺乏競爭力（Competitive）。在科技公司，產品是核心，這是第一要務。我們的目標是重新規劃產品路線圖，當時我設定了三個優先事項：第一，打造卓越的產品（Great Products）；第二，建立深厚的客戶關係（Customer Relationships），因為正如我之前提到的，沒有一家公司能獨自擁有所有好點子，合作至關重要；第三，保持敏捷（Agile），快速行動。當時最大的挑戰是爭取時間來打造這個路線圖。如今，我們的中央處理器（CPU）路線圖基於禪宗技術（Zen Technology），已經發展到第五代。從當時的不具競爭力，到現在我認為我們擁有世界上最好的CPU技術，並且未來還有更廣闊的路線圖。關鍵在於困難時期要清楚自己的目標。對科技公司來說，打造卓越產品永遠是基礎。

Response: That’s a great question. The most difficult time for AMD was probably around 2014 when I became CEO. At that time, the company’s product roadmap wasn’t competitive. In a technology company, your product is the most important thing—that’s number one. Our goal was to reframe our product roadmap, and I set three priorities: first, build great products; second, foster deep customer relationships, because, as I mentioned earlier, no single company has all the good ideas, and collaboration is key; third, be agile and move quickly. Our biggest challenge was buying time to build this roadmap. Today, our CPU roadmap, based on Zen Technology, is in its fifth generation. We went from being uncompetitive to, I believe, having the best CPU technology in the world, with an even broader roadmap ahead. The key during tough times is to be clear about what you’re trying to achieve. For a technology company, building great products is always the foundation.

學生提問：早上好，Su博士與陳校長。感謝您的啟發性演講。我是電機工程（Electrical Engineering）專業的學生，對半導體產業（Semiconductor Industry）的發展趨勢（Development Trends）感到好奇。您認為在未來5到10年，特別是在人工智能（AI）時代，這個產業將如何演變？

Student: Good morning, Dr. Su and President Chen. Thank you for your inspiring lecture. As a student majoring in electrical engineering, I’m curious about development trends in the semiconductor industry. How do you see the industry evolving in the next 5 to 10 years, especially in this era of AI?

回答：這是一個很重要的問題。在人工智能（AI）時代，半導體產業（Semiconductor Industry）正處於快速變革的階段。未來5到10年，我認為有幾個關鍵趨勢。首先，高性能計算（High-Performance Computing, HPC）將繼續推動需求，特別是針對AI工作負載（AI Workloads）的中央處理器（CPUs）、圖形處理器（GPUs）與特定應用積體電路（ASICs）。隨著摩爾定律（Moore’s Law）放緩，三維晶片技術（Chiplet Technology）與先進封裝（Advanced Packaging）將成為突破瓶頸的關鍵，實現更高效率與靈活性。其次，AI的普及將帶動邊緣計算（Edge Computing）與物聯網（Internet of Things, IoT）的成長，對低功耗、高效率的半導體需求將激增。第三，軟件與硬件的整合（Software-Hardware Integration）將更加重要，特別是在AI應用中，開發者需要客製化的解決方案（Customized Solutions）。最後，全球供應鏈（Global Supply Chain）的韌性與在地化（Localization）將是重點，臺灣的半導體生態系統（Semiconductor Ecosystem），特別是以台積電（TSMC）為核心的製造能力，將在這波浪潮中扮演關鍵角色。對電機工程學生來說，這是一個充滿機會的時代，建議你們深入學習AI與半導體設計（Semiconductor Design），並關注跨領域的應用。還有其他問題嗎？

Response: This is an important question. In the era of AI, the semiconductor industry is undergoing rapid transformation. Over the next 5 to 10 years, I see several key trends. First, high-performance computing will continue to drive demand, especially for CPUs, GPUs, and ASICs tailored to AI workloads. As Moore’s Law slows, chiplet technology and advanced packaging will be critical to overcoming bottlenecks, enabling greater efficiency and flexibility. Second, the proliferation of AI will fuel growth in edge computing and the Internet of Things, increasing demand for low-power, high-efficiency semiconductors. Third, software-hardware integration will become even more vital, particularly for AI applications, where developers need customized solutions. Finally, the resilience and localization of the global supply chain will be a priority, and Taiwan’s semiconductor ecosystem, centered around TSMC’s manufacturing prowess, will play a pivotal role in this wave. For electrical engineering students, this is an era full of opportunities. I recommend diving deep into AI and semiconductor design while staying attuned to cross-disciplinary applications. Any more questions?

回答（續接半導體趨勢問題）：關於半導體產業（Semiconductor Industry）的發展趨勢，我認為有幾個關鍵方向。首先，我們需要一個全面的設計環境（Holistic Design Environment），將硬件（Hardware）、軟件（Software）與系統（Systems）整合優化。這是AI時代的核心需求之一。AI目前仍處於早期階段（Early Innings），未來10年將迎來顯著的創新（Significant Innovation）。在應用層面（Application Space），AI正從提升企業與個人生產力（Productivity）轉向更深遠的變革。例如，在醫療保健（Healthcare）與生命科學（Life Sciences）領域，AI能幫助診斷疾病（Diagnose Diseases）、開發新藥（Drug Therapeutics）並提前預測健康問題（Health Problems）。這只是AI潛力的一個例子。我知道這裡有醫學院（Medical School），AI與醫學的結合將帶來革命性的改變。未來，AI的應用將滲透各行各業，改變我們的生活方式。

Response: Regarding semiconductor trends, I see a few key directions. First, we need a holistic design environment where hardware, software, and systems are optimized together. This is a core requirement in the AI era. AI is still in its early innings, and we likely have a decade of significant innovation ahead. In the application space, AI is moving beyond making businesses and people more productive to enabling larger changes. For example, in healthcare and life sciences, AI can help diagnose diseases, develop new drug therapeutics, and predict health issues earlier. This is just one example of what AI can do. I know there’s a medical school here, and the integration of AI with medicine will bring revolutionary changes. In the future, AI applications will permeate every industry, transforming how we live.

學生提問：謝謝Su博士、陳校長及所有來賓。我是Yvonne。我們大多數是臺灣人，擁有相似的教育與文化背景。您提到不同領導風格（Leadership Styles），如果我們想成為國際舞台的未來領袖（Future Leaders），有什麼建議或提醒？謝謝！

Student: Thank you, Dr. Su, President Chen, and all the guests here today. I’m Yvonne. Most of us here are Taiwanese, with similar educational and cultural backgrounds. You mentioned different leadership styles. Is there anything you’d like to remind us of if we want to become future leaders on the international stage? Thank you!

回答：這是一個很深刻的問題。我想給的建議是：要懷抱遠大的抱負（Ambitious Goals）。對年輕學生或剛踏入職場的人來說，最重要的是相信自己無所不能。設定遠大的夢想（Big Dreams），並勇敢與同事、主管或未來導師（Mentors）分享你的目標。他們會幫助你實現這些機會。我觀察到，臺灣或亞洲文化中有時會有些許內斂（Shy），但我鼓勵你們勇敢表達自己的願景。國際領袖需要自信與開放的心態，積極尋求合作與支持，這將幫助你們在全球舞台上脫穎而出。

Response: That’s a deep question. My advice is to be very ambitious in what you want to achieve. For young students or those early in their careers, the most important thing is to believe you can do anything. Have big dreams and share them with colleagues, managers, or future mentors—they will help you seize those opportunities. Sometimes, Taiwanese or Asian individuals can be a bit shy, but I encourage you to boldly express your vision. International leaders need confidence and an open mindset, actively seeking collaboration and support to stand out on the global stage.

陳校長提問：基於她的問題，我想反問您一些事。當張忠謀（Morris Chang）創辦台積電（TSMC）時，他曾告訴員工，總有一天我們會超越英特爾（Intel）。當時沒人相信，大約是1990年代到2000年左右。但最終，台積電成為全球最重要的半導體公司（Semiconductor Company）。您提到讓學生或員工挑戰最困難的問題（Most Difficult Problems），我很好奇您是如何激勵員工追求這樣的目標？例如，若您希望AMD成為世界第一（Number One），您如何激發員工的動力？我發現要推動學生與教師讓我們的大學成為世界頂尖（Top University）非常困難，您有什麼經驗分享？

President Chen’s Question: Based on her question, I have a follow-up for you. When Morris Chang founded TSMC, he told his employees that one day they would surpass Intel. Back then, around the 1990s to 2000, nobody believed him. Yet, TSMC became the most important semiconductor company in the world. You mentioned challenging students or employees with the most difficult problems. I’m curious—how do you motivate your employees to pursue such goals? For example, if you want AMD to be number one in the world, how do you inspire that drive? I find it very difficult to push our students and faculty to make our university the top in the world. What’s your experience?

回答：這是一個很重要的問題。激勵團隊的關鍵在於找到合適的人才（Right People），因為每個人的動機不同。有些人為項目（Projects）而努力，有些人想創業（Start a Company），有些人則有其他動力。在AMD，我們專注於組建一支有共同目標的團隊。當我們開始時，我們的抱負是打造最好的產品（Best Products）。但我們也保持現實，知道無法一夜之間從缺乏競爭力（Not Competitive）變成行業領袖。因此，我們制定了明確的計畫（Plan），逐步實現目標。工程師天生愛解決問題（Solve Problems），我們的角色是給他們有價值的問題（Good Problems）、清晰的目標（Clear Objectives）以及支持性的環境（Supportive Environment）。例如，我們的禪宗技術（Zen Technology）路線圖花了數年打造，但最終讓我們在CPU領域成為領導者。提到激勵，我記得黃仁勳（Jensen Huang）曾公開說英偉達（NVIDIA）的股價會大幅成長，當時聽起來像天方夜譚，但最終實現了。激勵需要遠見（Vision）與實際行動（Action）的結合，讓員工相信他們的努力能改變現狀。對大學來說，設定明確的里程碑（Milestones）並培養挑戰文化的氛圍（Culture of Challenge）或許是關鍵。

Response: This is an important question. The key to motivating a team is finding the right people, as not everyone has the same motivation. Some are driven by projects, others by starting a company, and some by other reasons. At AMD, we focus on building a team with shared goals. When we started, our ambition was to build the best products. But we were realistic—you can’t go from uncompetitive to the best overnight. So, we created a clear plan to achieve that. Engineers love to solve problems, and our role is to give them valuable problems, clear objectives, and a supportive environment. For example, our Zen Technology roadmap took years to build, but it ultimately made us leaders in the CPU space. On motivation, I recall Jensen Huang publicly saying NVIDIA’s stock price would soar, which sounded far-fetched at the time but came true. Motivation requires a blend of vision and actionable steps, convincing employees their efforts can change the status quo. For universities, setting clear milestones and fostering a culture of challenge might be key.

陳校長提問（續）：您提到激勵員工挑戰困難目標，您是否有類似的激勵機制（Incentive Motivation）來驅動員工？我認為，成功的不同形式都能激發動力。成功來自產品的認可（Product Recognition）、優秀人才加入公司（Talent Acquisition），以及收入成長（Revenue Growth），進而帶動市場份額（Market Share）與股價（Stock Price）的提升。我不會去預測股價，因為這非常困難且不確定。但另一種重要的激勵是讓員工為自己的公司感到驕傲（Proud of the Company）。當員工認同公司的願景（Vision）與成就（Achievements），他們會更有動力為共同目標努力，這對建立團隊凝聚力（Team Cohesion）至關重要。

President Chen’s Question (Continued): You mentioned motivating employees to tackle tough goals. Do you have specific incentive motivations when talking with your employees? I think we’re all motivated by seeing success, which comes in different ways. Success comes from product recognition, great people wanting to join the company, and revenue growth, which leads to market share growth and stock price growth. I don’t predict stock prices—it’s very difficult. But another kind of motivation is making employees proud of their company. When employees identify with the company’s vision and achievements, they’re more driven to work toward shared goals, which is crucial for building team cohesion.

學生提問：謝謝您的演講。我是政治學（Political Science）的博士生（PhD Student）。上次張忠謀博士（Dr. Morris Chang）來此演講時，提到博士學位（PhD Degree）並非那麼重要。但您擁有博士學位，我想聽聽您對博士學位對您職業生涯（Career）影響的看法。謝謝！

Student: Thank you for your speech. I’m a PhD student in political science. Last time, Dr. Morris Chang came here and mentioned that a PhD degree isn’t that important. However, you hold a PhD, so I’d like to hear your view on the impact of a PhD on your career. Thank you!

回答：這是一個很棒的問題。首先，我要說我們都非常敬仰張忠謀博士（Dr. Morris Chang），他是半導體產業（Semiconductor Industry）的標誌性人物，我無法反駁他的觀點！但就我個人而言，我認為博士學位（PhD）非常有價值。在博士論文（PhD Thesis）研究中，你有機會專注於一個全球獨一無二的問題（Unique Problem），這讓你能深入探索，並培養廣泛的思考能力（Broad Thinking）。相較之下，企業中的工作往往更聚焦於特定目標（Focused Goals）。博士學位的訓練讓我學會如何解決複雜問題（Complex Problems），這對我的職業生涯至關重要。當然，每個人的路徑不同，博士學位並非成功的唯一途徑，但它確實為我提供了堅實的基礎（Solid Foundation）。

Response: That’s a great question. First, we all love Dr. Morris Chang—he’s an icon in the semiconductor industry, and I can’t contradict him. But personally, I believe a PhD is quite useful. During your PhD thesis, you work on a problem that’s often unique globally, giving you the chance to explore broadly and develop critical thinking skills. In contrast, company work tends to be more focused. The PhD training taught me how to tackle complex problems, which was invaluable for my career. Of course, everyone’s path is different, and a PhD isn’t the only route to success, but it provided me with a solid foundation.

學生提問：抱歉，可能我選錯位置了！我是陳校長的女兒，您提到研究生院（Graduate School）的訓練與本科（Undergraduate）不同。我是電機工程（Electrical Engineering）專業的學生，想知道您認為研究生應該學習的前三大技能（Top Three Skills），是軟技能（Soft Skills）還是硬技能（Hard Skills）？另外，當您面臨挫折（Setbacks）或低谷（Rock Bottom）時，是什麼心態（Mindset）讓您堅持下去？謝謝！

Student: Sorry, I might be in the wrong spot! I’m President Chen’s daughter. You mentioned that graduate school training differs from undergraduate education. As an electrical engineering student, I’m curious about the top three skills you think engineering students should learn in graduate school—soft skills or hard skills? Also, what’s your mindset when facing setbacks or rock bottom? What keeps you going? Thank you!

回答：謝謝你的問題！首先，關於研究生院（Graduate School）應該學習的技能，我認為硬技能（Hard Skills）與軟技能（Soft Skills）同等重要。以下是我認為的前三大技能：第一，深入的技術專長（Technical Expertise），例如半導體設計（Semiconductor Design）或AI演算法（AI Algorithms），這是工程師的核心競爭力；第二，問題解決能力（Problem-Solving Skills），研究生訓練讓你學會拆解複雜問題並找到創新解法（Innovative Solutions）；第三，溝通與團隊合作（Communication and Teamwork），這是軟技能，因為無論技術多強，你都需要與團隊、客戶或跨領域專家合作，將想法轉化為實際成果（Actionable Outcomes）。這三者相輔相成，讓你成為全面的專業人士。

關於面對挫折（Setbacks）的心態，我想說的是，堅持（Perseverance）來自於對目標的清晰信念（Clear Belief in Goals）。在AMD的低谷時期，例如2014年我們的產品路線圖（Product Roadmap）不具競爭力時，我專注於三件事：打造卓越產品（Great Products）、建立深厚客戶關係（Customer Relationships）以及保持敏捷（Agility）。這些目標讓我保持動力，即使面對失敗，我也視之為學習機會（Learning Opportunities）。我記得有次產品開發失敗，但分析錯誤後，我們調整策略，最終推出了成功的禪宗技術（Zen Technology）。我的建議是：將挫折視為成長的墊腳石（Stepping Stones），並始終專注於長期願景（Long-Term Vision）。

Response: Thank you for your questions! First, regarding skills in graduate school, I believe hard skills and soft skills are equally important. Here are my top three: First, deep technical expertise, like semiconductor design or AI algorithms, which is the core of an engineer’s competitiveness. Second, problem-solving skills—graduate training teaches you to break down complex problems and find innovative solutions. Third, communication and teamwork, a soft skill, because no matter how strong your technical skills are, you need to collaborate with teams, clients, or cross-disciplinary experts to turn ideas into actionable outcomes. These three complement each other, making you a well-rounded professional.

On the mindset for setbacks, I’d say perseverance comes from a clear belief in your goals. During AMD’s tough times, like in 2014 when our product roadmap wasn’t competitive, I focused on three things: building great products, fostering deep customer relationships, and staying agile. These goals kept me motivated. Even when facing failures, I saw them as learning opportunities. I recall a product development failure, but after analyzing the mistakes, we adjusted our strategy and launched the successful Zen Technology. My advice is to view setbacks as stepping stones for growth and always focus on your long-term vision.

回答（續接研究生技能與挫折心態）：不僅僅是在公司中，生活中也一樣，無論遇到什麼挑戰，軟技能（Soft Skills）都至關重要。我想強調幾點：第一，世界變化很快（Fast-Changing World），因此保持思維敏捷（Agile Thinking）非常重要。今天你認為正確的道路，明天可能需要調整。我的哲學是持續學習（Continuous Learning），每天吸收新知識，並根據新資訊調整你的路徑（Path）。這是我經常運用的方法，也是我認為最重要的軟技能之一。持續學習讓你能適應變化，並在職業與生活中找到新的機會。

關於挫折（Setbacks），我之前提到，你從失敗（Failure）中學到的東西最多。我可以分享無數自己的挫折案例，但我的建議是：允許自己短暫地感到難過（Feel Sad for a Short Time），因為我們都是人，會有情緒。但這段時間要很短！然後，快速學習（Learn Quickly）並專注於下一步（Next Step）。這是應對挫折的關鍵。讓我們進入最後兩個問題，好吗？

Response (Continued): This applies not just in companies but in life—everything that happens to you. Soft skills are crucial. I’d highlight a few things: First, the world changes very fast, so it’s important to be agile in your thinking. What seems like the right path today might need adjustment tomorrow. My philosophy is continuous learning—every day, you learn something new and can decide how to tweak your path. That’s something I use a lot and consider a vital soft skill. Continuous learning helps you adapt to change and find new opportunities in your career and life.

On setbacks, as I said earlier, you learn the most from failures. I could share countless examples of my own setbacks, but my advice is to allow yourself to be sad for just a short time—we’re all human, after all. But keep it brief! Then, learn quickly and focus on the next step. That’s the key to handling setbacks. Let’s move to the final two questions, okay?

學生提問：謝謝您的演講。我想問，當您還是學生時，您認為自己是天賦型學生（Gifted Student）還是努力型學生（Hard-Working Student）？在您看來，天賦（Talent）與努力（Effort）哪個更重要？謝謝！

Student: Thank you for your speech. I’d like to ask, when you were a student, did you consider yourself a gifted student or a hard-working one? In your opinion, which is more important—talent or effort? Thank you!

回答：這是一個有趣的問題！我可以肯定地說，我只是個「還可以」的學生（Okay Student），不是頂尖（A++），有時甚至是A-的那種！每個人都不同（Everyone is Different），天賦與努力都很重要，但最關鍵的是如何將所學應用於現實世界（Real World）。以我為例，設備物理（Device Physics）課程對我來說非常困難，書面問題（Written Problems）讓我頭痛。但在實驗室做項目（Lab Projects）時，我表現得很出色。每個人都有自己的專長（Specialty）。我的經驗是，努力讓你走得更遠，因為它幫助你將天賦轉化為實際成果（Tangible Results）。

Response: That’s an interesting question! I can say for sure I was just an okay student—not A++, maybe sometimes A-. Everyone is different, and both talent and effort matter, but the most important thing is applying what you learn to the real world. For me, device physics was a very hard class, and written problems were tough. But working on lab projects, I excelled. Everyone has their specialty. My experience is that effort takes you further because it helps turn talent into tangible results.

學生提問：謝謝Su博士與陳校長。AMD的員工數量（Number of Employees）僅約為英特爾（Intel）的三分之一，與英偉達（NVIDIA）相當。在快速變化的半導體產業（Semiconductor Industry）與AI時代，您有3到5個策略或原則（Strategies or Principles）來保持競爭力（Competitiveness）、創新（Innovation）、敏捷（Agility），同時確保盈利能力（Profitability）與可持續性（Sustainability）嗎？第二個問題是，AMD是否總是與其他公司正面競爭（Head-to-Head Competition），還是會尋找新的藍海（Blue Ocean）來創造更大的商機（Business Opportunities）與利潤（Profits）？謝謝！

Student: Thank you, Dr. Su and President Chen. Given that AMD has about one-third the number of employees compared to Intel and a similar number to NVIDIA, in the fast-changing semiconductor industry and AI era, do you have 3 to 5 strategies or principles to stay competitive, innovative, and agile while maintaining profitability and sustainability? My second question is, does AMD always compete head-to-head with other companies in the same industry, or do you identify new blue oceans for AMD to create better business opportunities and larger profits? Thank you!

回答：這是一個很長但很棒的問題！關於第一個問題，員工數量（Number of Employees）並非成功的決定因素，關鍵在於是否擁有合適的人才（Right People）。在AMD，我們的策略與原則可以歸納為以下幾點：第一，打造卓越產品（Great Products），這是科技公司的核心，例如我們的禪宗技術（Zen Technology）在CPU領域的領先地位；第二，深耕客戶關係（Deep Customer Relationships），與台積電（TSMC）等合作夥伴緊密協作以實現創新；第三，保持敏捷（Agility），快速適應AI等新興趨勢；第四，投資長期路線圖（Long-Term Roadmap），例如三維晶片技術（Chiplet Technology）以突破摩爾定律（Moore’s Law）限制；第五，平衡盈利與可持續性（Profitability and Sustainability），通過高效運營（Efficient Operations）與環境責任（Environmental Responsibility）實現長期價值（Long-Term Value）。

關於第二個問題，AMD並不總是正面競爭（Head-to-Head Competition）。我們確實與英特爾（Intel）、英偉達（NVIDIA）在CPU與GPU市場競爭，但也積極尋找藍海（Blue Ocean）。例如，我們專注於高性能計算（High-Performance Computing, HPC）與AI邊緣應用（Edge AI Applications），這些領域的需求快速成長，且競爭相對較少。通過差異化產品（Differentiated Products）與開放生態系統（Open Ecosystem），我們創造新的商機（Business Opportunities），例如與雲端數據中心（Cloud Data Centers）與遊戲產業（Gaming Industry）的合作。這讓AMD在競爭中保持靈活性（Flexibility）並實現更高的利潤（Profits）。

Response: That’s a long but great question! For the first question, the number of employees isn’t what determines success—it’s about having the right people. At AMD, our strategies and principles include: First, building great products, the core of any tech company, like our leading Zen Technology in CPUs. Second, cultivating deep customer relationships, collaborating closely with partners like TSMC to drive innovation. Third, staying agile to adapt quickly to trends like AI. Fourth, investing in a long-term roadmap, such as chiplet technology to overcome Moore’s Law limitations. Fifth, balancing profitability and sustainability through efficient operations and environmental responsibility to create long-term value.

For the second question, AMD doesn’t always compete head-to-head. We do compete with Intel and NVIDIA in CPU and GPU markets, but we also seek blue oceans. For instance, we focus on high-performance computing and edge AI applications, areas with rapidly growing demand and less competition. Through differentiated products and an open ecosystem, we create new business opportunities, such as partnerships with cloud data centers and the gaming industry. This approach keeps AMD flexible in competition and drives higher profits.

回答（續接員工數量與競爭策略）：當我2014年加入AMD時，公司只有8000名員工（Employees）。當時人們常說，與英特爾（Intel）相比，AMD規模太小，英特爾的員工人數可能是我們的十倍。他們說：「Lisa，你瘋了！這不可能贏！」但我並不這麼認為。我問：「為什麼這麼說？」我認為，成功的關鍵不在於人數（Number of People），而是擁有合適的人才（Right People）、正確的項目（Right Projects）、專注的方向（Right Focus）與清晰的願景（Right Vision）。每家公司的路徑（Path）不同，對AMD來說，我們專注於高性能計算（High-Performance Computing, HPC），這是我們的強項。我認為我們非常幸運能從事科技領域（Technology Field），因為我們的技術每天影響數十億人（Billions of People）。這些技術讓企業更高效（More Efficient）、生活更美好（Better Lives）、醫療保健更先進（Advanced Healthcare）、環境更永續（Sustainable Future）。在AMD，我們選擇專注於能對人類生活產生深遠影響（Profound Impact）的領域，這是我們的使命（Mission）。

Response (Continued): When I started at AMD in 2014, we had 8,000 people. People used to say, “My goodness, you’re so small compared to Intel!” At the time, Intel probably had ten times the employees of AMD. They said, “Lisa, you’re crazy. Why are you doing this? You can’t possibly win.” But I didn’t see it that way. I asked, “Why do you say that?” I don’t believe it’s about the number of people—it’s about having the right people, the right projects, the right focus, and the right vision. Every company’s path is different. For AMD, we focus on high-performance computing, our strength. We’re incredibly lucky to be in the technology field. Our technology touches billions of people every day, making companies more efficient, lives better, healthcare more advanced, and the future more sustainable. At AMD, we choose to focus on areas that have a profound impact on people’s lives—that’s our mission.

結尾致謝與贈禮：（陳校長）從這場爐邊對談（Fireside Chat）中，我覺得您比我更適合做國立臺灣大學（NTU）的校長！您真是個了不起的領袖（Great Leader），我只是個普通人（Okay Person）。由於時間限制（Time Limitation），我要代表大家感謝Su博士（Dr. Su）蒞臨分享。我們非常享受這場演講！現在，請允許我為您頒發獎章（Medal）以表彰您的貢獻。（主持人）感謝Su博士與陳校長帶來的精彩討論！我們邀請陳校長為我們尊敬的講者Su博士頒發獎盃（Trophy）。此外，我們為Su博士準備了一份特別禮物（Special Gift）——國立臺灣大學限量版棒球外套（NTU Special Edition Baseball Jacket）！（Su博士）謝謝Jack，謝謝大家，這真的很有趣！（主持人）感謝Su博士與陳校長，您真是個出色的領袖！

Closing Remarks and Gift Presentation: (President Chen) From this fireside chat, I think you’re better suited to be the president of NTU than me! You’re a great leader, while I’m just an okay person. Due to time limitations, on behalf of everyone, I’d like to thank Dr. Su for being here. We all enjoyed her talk immensely! Now, allow me to present a medal to honor your contributions. (Host) Thank you, Dr. Su and President Chen, for the wonderful discussion. We’d like to invite President Chen to present a trophy to our esteemed speaker, Dr. Su. We also have a special gift for Dr. Su—an NTU special edition baseball jacket! (Dr. Su) Thank you, Jack, and thank you all—this is really fun! (Host) Thank you, Dr. Su and President Chen—you’re an outstanding leader!

合影環節：（主持人）感謝大家參與！請再次以熱烈的掌聲感謝我們的講者Lisa Su博士（Dr. Lisa Su）分享她的寶貴見解（Valuable Insights）。現在，若您想與Su博士合影（Take a Picture），請耐心在舞台中間左側排隊（Line Up at the Middle-Left Side of the Stage）。為確保離場通道暢通（Ensure Exits Are Available），請配合引導。請大家靠近講廳中央（Middle of the Lecture Hall），我們的攝影師（Photographer）將在舞台上拍攝。請面向鏡頭（Look at the Camera），我們數到三：一、二、三！再拍一張，請展現您燦爛的笑容（Brilliant Smile），再五秒：一、二、三！再來一次，五秒鐘的燦爛笑容：一、二、三！好了嗎？謝謝大家！

Photo Session: (Host) Thank you all for participating! Please give another round of applause to our esteemed speaker, Dr. Lisa Su, for sharing her valuable insights. Now, if you wish to take a picture with Dr. Su, please wait patiently and line up at the middle-left side of the stage. To ensure exits are available, please follow the guidance. Everyone, move closer to the middle of the lecture hall. Our photographer will be on stage. Please look at the camera—we’ll count to three: one, two, three! Let’s take another one. Show us your brilliant smile for five seconds: one, two, three! One more time, five seconds of brilliant smiles: one, two, three! Are we good? Thank you all!
